Influence of College Students’ MP3-Player Motives on Their Social Interaction
A dissertation submitted to the College of Communication and Information of Kent State
University in partial fulfillment of the requirements for the degree of
Doctor of Philosophy
by
Peter Nello Miraldi
December, 2010
Dissertation written by
Peter Nello Miraldi
B.A., Cleveland State University, 1997
M.A.C.T.M., Cleveland State University, 1998
Ph.D., Kent State University, 2010
Approved by
_________________________________
Paul Haridakis, Ph.D., Chair, Doctoral Dissertation Committee
_________________________________
Danielle Coombs, Member, Ph.D., Doctoral Dissertation Committee
_________________________________
Janet R. Meyer, Member, Ph.D., Doctoral Dissertation Committee
_________________________________
Stanley T. Wearden, Member, Ph.D., Doctoral Dissertation Committee
Accepted by
_________________________________
Paul Haridakis, Ph.D., Interim Director, School of Communication Studies
_________________________________
Stanley T. Wearden, Ph.D., Dean, College of Communication and Information
Table of Contents
Page
TABLE OF CONTENTS………….…………………………………………………………..
iii
LIST OF FIGURES...………...………………….……………………….……………..….…
v
LIST OF TABLES.……………………………….…………………………………….….….
vi
ACKNOWLEDGEMENTS………………………………………………………...…………. viii
CHAPTER
I. INTRODUCTION………………………………….……………….…………….......
Problem Statement…………………….……...…………………...……………
Rationale and Objectives……………………………………………..………...
Uses and Gratifications……………………………………………......………..
Background Characteristics………………………………………..……..…….
Motives…………………………………………………………………………
Exposure……………………………………………………….……………….
Audience Activity…………………...………………..…...……………………
Social Interaction…………………………………..……..………….…………
Summary…………………………………………………..…….……………...
Research Questions and Hypotheses…………………….………….………….
II. METHODOLOGY………………………………………………….……………..…
Sampling Procedure………………………………...………….………….……
Measures……………………………………………..…………………………
Statistical Analysis………………………………...……………………………
III. RESULTS……………………………………………...……………………………
Hypotheses………………………………………...……………………………
Research Questions……………………………...………………...……………
Summary of Results…………………………………………………………….
IV. DISCUSSION……………………………………………...……………………......
Influence of Antecedent Variables on Social Interaction…………..………..…
Relationships among Some of the Antecedent Variables…………...………….
Limitations and Future Directions………………………………...………...….
1
2
5
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29
33
37
46
48
58
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60
86
91
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125
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APPENDICES
A. Kent State University Consent Form……………………………..………………….
B. Demographics…………………………………………………………………..……
C. The Revised UCLA Loneliness Scale…………...………………………...…………
D. MP3 Motive Scale……………...……………………………………………………
E. Time Spent Listening……………………………………………..………………….
F. Listening Attention…………………….……………...…………..………………….
G. Listening Elaboration Scale...…………………………………….………….………
135
137
139
141
145
146
147
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H. Sociability Questions…………...……………...……….…………..………………
I. Social Participation……...……………………………………………..……………
J. Post-Listening Discussion of Music………………...………………………………
K. Music File-Sharing…………………………...………………….…………………
L. Regression Analysis Tables for Research Question 7…………..….………………
M. Regression Analysis Tables for Research Question 8…………………….……….
148
149
150
151
152
170
REFERENCES…………………………………………………………………………….… 188
iv
List of Figures
Figure
1.
2.
Page
Loneliness, Motives to Listen to MP3-Player Music, Exposure to MP3-Player Music,
and Audience Activity with MP3-Player Music as Predictors of Social Interaction…..
11
Proposed Relationships Regarding Loneliness, Motives to Listen to MP3-Player
Music, Exposure to MP3-Player Music, and Audience Activity with MP3-Player
Music as Predictors of Social Interaction.……………..…………………………....…
88
v
List of Tables
Table
Page
1.
Revised UCLA Loneliness Scale: Item Means and Standard Deviations…….………. 63
2.
Factor Loadings for the MP3-Player Motive Items……………..…………….…….
3.
MP3-Player Motive and Item Means and Standard Deviations………………....……. 71
4.
Listening Attention Scale: Item Means and Standard Deviations………………….…. 76
5.
Listening Elaboration Scale: Item Means and Standard Deviations…….…………….
78
6.
Social Participation Scale: Item Means and Standard Deviations……...……...……...
82
7.
Post-Listening Discussion of Music Scale: Item Means and Standard Deviations...…. 84
8.
Music File-Sharing Scale: Item Means and Standard Deviations…….………………. 87
9.
Partial Correlations between MP3-Player-Use Motives and Social Interaction…...….
95
10.
Summary of Regression Analysis for Variables Predicting Overall Time Spent
Socializing with Others………………………………………………………………..
152
Summary of Regression Analysis for Variables Predicting Time Spent Socializing
with Family Members…………...…………………………………………………….
154
11.
68
12.
Summary of Regression Analysis for Variables Predicting Time Spent Socializing
with Friends…………………………………………………………………………… 156
13.
Summary of Regression Analysis for Variables Predicting Time Spent Socializing
with Acquaintances……………………………………………………………………
158
Summary of Regression Analysis for Variables Predicting Participation in Social
Activities…………………………………………………...………………….………
160
Summary of Regression Analysis for Variables Predicting Post-Listening
Discussion......................................................................................................................
162
14.
15.
16.
Summary of Regression Analysis for Variables Predicting Overall File-Sharing…..... 164
17.
Summary of Regression Analysis for Variables Predicting File-Sharing Using an
Online Music Service……………………………………………………………….....
166
Summary of Regression Analysis for Variables Predicting File-Sharing Using an
MP3 Player……………………………………………………………............…….....
168
18.
vi
19.
Summary of Regression Analysis for Variables (Excluding Loneliness) Predicting
Time Spent Socializing with Others Overall………………………………………….. 170
20.
Summary of Regression Analysis for Variables (Excluding Loneliness) Predicting
Time Spent Socializing with Family Members……………………………………….. 172
21.
Summary of Regression Analysis for Variables (Excluding Loneliness) Predicting
Time Spent Socializing with Friends………...………………………………………..
174
22.
Summary of Regression Analysis for Variables (Excluding Loneliness) Predicting
Time Spent Socializing with Acquaintances………………………………………….. 176
23.
Summary of Regression Analysis for Variables (Excluding Loneliness) Predicting
Participation in Social Activities……………..……………………………………….. 178
24.
Summary of Regression Analysis for Variables (Excluding Loneliness) Predicting
Post-Listening Discussion……………………………………………………………..
180
25.
Summary of Regression Analysis for Variables (Excluding Loneliness) Predicting
Overall File-Sharing…………………………………………………………….…….. 182
26.
Summary of Regression Analysis for Variables (Excluding Loneliness) Predicting
File-Sharing Using an Online Music Service………………………………………..... 184
27.
Summary of Regression Analysis for Variables (Excluding Loneliness) Predicting
File-Sharing Using an MP3 Player……………………………………...…………….. 186
vii
Acknowledgements
I appreciate the patience and encouragement of my family and friends, the guidance and support
of my advisor, and the comments and suggestions of my committee members.
viii
1
Chapter I
INTRODUCTION
Music media are more portable than ever (Bassoli, Moore, & Agamanolis, 2006; Duncan
& Fox, 2005). Technologies such as transistors, lightweight headphones, and compact discs have
helped make music a ubiquitous part of many people’s lives (Hargreaves, Ita, & North, 1999).
Newer technologies such as digital file compression and high-speed Internet connections have
allowed consumers even more interfacing with portable music media than had been possible
previously.
Portable MP3 players, so-named for their common use of the MPEG-1 Audio Layer 3
(MP3) digitized file-format, are one of the most popular portable devices for listening to music,
especially among teens and young adults (Arensman, 2005; Ferguson, Greer, & Reardon, 2007;
Harrigan, 2007; IFPI, 2007, 2008; Madden & Rainie, 2005; Norris & Lee, 2006; Pew Internet &
American Life Project, 2005; Rose & Lenski, 2008; Wheeler, 2006). In 2006, Wheeler reported
that over 50% of households in the U.S. owned an iPod, the most popular brand of MP3 players.
According to the International Federation of the Phonographic Industry (IFPI, 2008), consumers
had bought over 120 million iPods by 2007. Rose and Lenski reported that, by 2008, half of 18
to 34 year olds owned an iPod or other portable MP3 player. Also, they reported that overall
MP3-player ownership among people in the United States rose from 14% in 2005 to 37% in
2008.
Furthermore, companies, such as Apple, have integrated portable MP3 players with
cellular phones (e.g., the iPhone). Nokia had sold about 220 million music-capable cellular
phones in 2007 alone, almost twice the total number of iPods that had sold at that time (IFPI,
2
2008). Albarran et al. (2007) noted that the convergence of MP3 players with other portable
technologies, such as cell phones, ensures a promising future for these portable music players.
One reason for portable MP3 players’ popularity and widespread diffusion may be their
ability to store and play hundreds to thousands of music files on a relatively small, personalized
device. Users can transfer digital music files via the Internet, categorize them into playlists, and
upload them to a portable MP3 player that can fit in their pocket (Bull, 2005; Norris & Lee,
2006). With the aid of earphones, users can enjoy a personalized media experience wherever
they go, without disturbing others (Diva, 2004; Hosokawa, 1984; Levy, 2006).
In addition to not disturbing others, Bull (2000) suggested that wearing headphones
allows users to cocoon themselves in their own virtual space and convey the message that they
do not want to be disturbed. Bull (2005) stated that “iPods can be used as a form of
conversational preserve, delimiting who the user wishes to converse with” (p. 353). For example,
he found that some iPod users reported listening to music to avoid communication. One iPod
user noted that MP3 players can serve as a social shield, protecting users from unwanted
conversations (Kadden, 2004). One of Bull’s (2000) interviewees exemplified this sentiment in
her observation of personal stereo use stating, “If you want to switch off and be in a room of
your own you put that on and you close your eyes and shut your ears and it’s a way of not being
bothered” (p. 52). Also, Diva (2004) wrote about her use of an iPod to avoid contact with others
in public: “When I am listening to my iPod, with the white earbuds in my ears being so
noticeable, I am able to thwart some unwanted social contact” (para. 14).
Problem Statement
In regard to the privatized experience portable MP3 players can provide, some critics
have raised concerns that people’s growing use of MP3 players is displacing their social
3
interaction with others and causing loneliness among users (Armour, 2006; Copeland, 2006;
Doherty & Baker, 2005; Harris, 2005; Kadden, 2004; Rose, 2006; Rothman, 2006; Stapp, 2007;
White, 2006; Yzer & Southwell, 2008). For example, Copeland claimed that “as a result of
devices such as the iPod, conversation and human interaction are suffering” (para. 8). The
principal of International Grammar School in Sydney, Australia even banned students from using
iPods because, she claimed, they breed social isolation (Doherty & Baker, 2005). Also, some
employers have claimed that MP3 players are socially limiting and disruptive to collaboration in
the workplace (Armour, 2006; Rose, 2006). James Katz, Director of the Center for Mobile
Communication Studies at Rutgers University, stated that consumers may be using iPods to
withdraw “from the public sphere or the public culture into one’s private space” (quoted in
Kadden, 2004, p. 14). White also argued that this type of use displaces social interaction and is
detrimental to our society. Ferguson et al. (2007) noted that “the use of MP3 players potentially
might decrease interpersonal connections while isolating the user from his or her environment”
(p. 117).
Researchers have addressed similar concerns that the use of other media may be related
negatively to consumers’ psychological well-being and social interaction (Bickham & Rich,
2006; Flanders, 1982; Humphreys, 2005; Jeffres, Neuendorf, & Atkin, 2003; JohnssonSmaragdi, 1983; Katz & Rice, 2002; Kraut et al., 1998, 2002; Walker & Bellamy, 1991). For
example, Kraut et al. (1998) suggested that Internet use “may represent a privatization of
entertainment” (p. 1029) and that this personal use could lead to decreases in users’ social
interaction. However, Katz and Rice found that Internet use did not necessarily have such
negative consequences. Rather, they found that people may have used the Internet to increase
their involvement and friendships. Similarly, Kraut et al. (2002) conducted a replication of Kraut
4
et al.’s (1998) study and found that, overall, people who used the Internet often tended to spend a
lot of time interacting with others, had large social circles, and were involved in community
activities.
However, some scholars have contended that listening to music on a personal music
player may be more isolating and less social than using media such as the Internet (Bull, 2000,
2005; Ferguson et al., 2007; Kadden, 2004). Music listening devices, themselves, do not have the
capability to connect users together or provide them with a means of two-way communication
(Kestnbaum, Robinson, Neustadtl, & Alvarez, 2002). Bull (2000) stated that “the personal-stereo
user is communicating with the products of the culture industry, not individual persons” (p. 98).
Putnam (1995b) suggested that personal music players provide users with an isolated
entertainment experience that limits their ability to form and maintain social networks.
Researchers have not empirically examined the influence of people’s MP3-player-music
listening on their social interaction. Therefore, the degree to which people’s MP3-player use
influences their social interaction is unclear and needs to be studied (Albarran et al., 2007;
Ferguson et al., 2007).
Unfortunately, personal stereo research is lacking and, thus, our understanding of
people’s use of this device to listen to music is limited (Albarran et al., 2007; Bull, 2004, 2005;
Ferguson et al., 2007; Madden & Rainie, 2005). Bull (2004) stated that people’s use of portable
stereos “has gone relatively unnoticed in academic literature” (p. 244). Ferguson et al. observed
that “scholarly research focused on MP3 players is scarce” (p. 103). They suggested that
researchers need to study people’s reasons for using MP3 players further and need to examine
the relationships among users’ background characteristics and MP3-player use. Also, Albarran et
5
al. claimed that an understanding of young adults’ motives to use MP3 players and uses of MP3
players requires additional research.
Rationale and Objectives
Based on the growing popularity of MP3 players, especially among college students
(Arensman, 2005; Harrigan, 2007; IFPI, 2007, 2008; Madden & Rainie, 2005; Pew Internet &
American Life Project, 2005; Rose & Lenski, 2008; Wheeler, 2006), the unique capabilities of
MP3 players (Bull, 2005; Norris & Lee, 2006), concerns about the potentially negative effects of
MP3-player use on consumers’ social interaction (Copeland, 2006; Doherty & Baker, 2005;
Harris, 2005; Kadden, 2004; Rose, 2006; Rothman, 2006; Stapp, 2007; White, 2006), the general
need to research MP3-player motives and use further (Albarran et al., 2007; Ferguson et al.,
2007; Ferguson, personal communication, March 12, 2008) and extant literature, I propose to
study the relationships among college students’ loneliness, motives to listen to music on an MP3
player, time spent listening to MP3-player music, MP3-player activity (i.e., attention to songs
and elaboration on songs), and social interaction (i.e., time spent socializing with others,
frequency of participation in social activities, frequency of post-listening discussion of music,
and frequency of music file-sharing).
As previously stated, some scholars and reporters have claimed that listening to music on
an MP3 player decreases social interaction (Cole & Robinson, 2002; Lee & Zhu, 2002; Mikami,
2002; Nordlund, 1978; Russell, Peplau, & Curtona, 1980). Some researchers and journalists have
indicated that people’s time spent socializing with others, participation in social activities,
discussions with others about music after listening, and music file-sharing are types of social
interaction that are relevant to the study of people’s music listening (Bull, 2005; Copeland, 2006;
Horrigan, 2008; Putnam, 2000; Stapp, 2007). Typically, college students listen to music on MP3
6
players (Arensman, 2005; Ferguson et al., 2007). Therefore, the types of social interaction
mentioned above may be important outcomes of college students’ MP3-player use.
A better understanding of the process and outcomes of college students’ MP3-playermusic listening may reduce critics’ speculation about the effects of MP3-player use. However,
researchers have not examined how college students’ loneliness, motives to listen to music on an
MP3 player, time spent listening to music on an MP3 player, and activity with MP3-player music
work together to influence their social interaction. Therefore, based on the above discussion, my
objectives are to examine some of these relationships to bolster our understanding of college
students’ MP3-player-music listening and its effects.
First, some critics have expressed concern that consumers’ use of MP3 players to avoid
interaction with others is decreasing users’ overall social interaction (Armour, 2006; Doherty &
Baker, 2005; Kadden, 2004; Rose, 2006). As previously discussed, there are reports that some
people use MP3 players to avoid social interaction with others (Bull, 2005, 2006; Diva, 2004).
However, there are also reports that some people listen to MP3 players to bolster their social
interaction (Doherty & Baker, 2005; Evangelista, 2005; Rose, 2006; Wheeler, 2006). For
example, a student at the Sydney school where iPods have been banned claimed that users can
share one of their earphones with someone else (Doherty & Baker, 2005).
In addition to avoiding and bolstering social interaction, researchers have identified some
basic reasons why people listen to music on MP3 players (e.g., Albarran et al., 2007; Bull, 2005,
2006; Ferguson et al., 2007; Yaksich, 2007). For example, Ferguson et al. found that college
students used iPods to relax/escape, for entertainment, and to avoid loneliness. However,
researchers have examined only some of the reasons college students use MP3 players and have
called for further examination of other reasons (Albarran et al., 2007; Ferguson et al., 2007).
7
Explaining people’s reasons for using media is essential to understanding their media use
and effects (Katz, Blumler, & Gurevitch, 1974; Perse & Dunn, 1998; Rubin, 1993).
Unfortunately, researchers have not examined the relationships among college students’ motives
to listen to MP3-player music to bolster social interaction or to avoid social interaction, among
other reasons, and their social interaction. Also, there is a need for further examination of the
relationships among college students’ motives to listen to music on an MP3 player, their
exposure to MP3-player music, and activity with MP3-player music (Albarran et al., 2007;
Ferguson et al., 2007). Therefore, my first objective is to examine some reasons for listening to
music on an MP3 player and their influence on college students’ exposure to MP3-player music,
activity with MP3-player music, and social interaction.
Second, based on concerns that people who listen to music on MP3 players may be
lonely, listeners’ loneliness should be a relevant characteristic to consider in my study (Doherty
& Baker, 2005; Ferguson et al., 2007; Kadden, 2004; Rothman, 2006). Researchers have
identified loneliness as a background characteristic that influences people’s motives to use media
(Finn & Gorr, 1988; Perloff & Krevans, 1987), media use (Caplan, 2003), and social interaction
(Bell & Daly, 1985; Rubin, Perse, & Powell, 1985). For example, research suggests that people
who are lonely tend to use media for social compensation (Finn & Gorr, 1988; Perloff &
Krevans, 1987; Perse & Rubin, 1990).
Based on the findings mentioned above, researchers should examine the influence of
loneliness on college students’ MP3-player-music listening before assuming that these
characteristics are caused by MP3-player use. College students who are high in loneliness may
use MP3 players to listen to music differently than those who are low in this background
characteristic. In addition to college students’ MP3-player motives and music listening,
8
loneliness may influence their social interaction. Therefore, my second objective is to examine
the influence of college students’ loneliness on their motives to listen to music on an MP3
player, music listening, and social interaction.
Third, people may differ in the degree of their media exposure and activity from low to
high levels of exposure to media content and activity with media content (Blumler, 1979;
Hawkins et al., 2001; Patwardhan, 2004; Rubin & Step, 2000). Exposure refers to people’s
encounters with media and media content (Slater, 2004). Activity represents people’s
participation, both cognitively and behaviorally, with media content (Levy & Windahl, 1984;
Perse, 1990). Variations in people’s degree of media exposure and activity influence certain
media effects, such as Internet affinity (Papacharissi & Rubin, 2000), issue knowledge and
opinion strength (Drew & Weaver, 1990), media satisfaction (Perse & Rubin, 1988), social
attitudes (Rubin, Haridakis, Hullman et al., 2003), social support (Leung & Lee, 2005); and
discussion with others (Godlewski & Perse, 2007).
For example, Rubin, Haridakis, Hullman et al. (2003) found that people who did not pay
close attention to media coverage of terrorist activities tended to have a great deal of faith in
other people. Drew and Weaver (1990) found that people who paid close attention to televised
news programs tended to have more knowledge and stronger opinions about the issues than did
viewers who paid little attention to news programs. Godlewski and Perse (2007) found that
people who paid a lot of attention to reality television shows and elaborated a lot on the content
while watching were more likely to participate in online discussions about the content than were
those who demonstrated low levels of attention and elaboration regarding the programs. Leung
and Lee (2005) found that people who spent a lot of time listening to an MP3 player tended to
have more people to rely on for social interaction than did those who did not spend a lot of time
9
listening. The findings mentioned above suggest that media effects are more pronounced for
those who spend a lot of time consuming media content, pay a lot of attention to the content, and
think a lot about the content.
Researchers have suggested that people’s time spent listening to music and their activity,
including attention to songs and elaboration on songs, are especially important to consider
regarding music listening (Christenson, 1994; Hansen & Hansen, 1991; Larson & Kubey, 1983;
Lin, 2006; Lull, 1985). In addition, these types of music listening are important to consider
regarding MP3 players (Bull, 2005; Ferguson et al., 2007). Based on the above discussion,
college students’ MP3-player exposure and activity should influence media effects. Specifically,
the amount of time that college students spend listening to music, their attention to songs, and
elaboration on songs should influence their social interaction. However, researchers have not
examined the relationships among college students’ exposure to MP3-player music, activity with
MP3-player music, and social interaction, thus, these relationships remain unclear. Therefore, my
third objective is to examine the influence of college students’ time spent listening to music,
attention to songs, and elaboration on songs on their social interaction.
Uses and gratifications theory is an ideal guide for the focus of my study because it
explains how users’ background characteristics, reasons for using media, media exposure, and
activity, or engagement, with media content work together to influence users’ subsequent
behavior (Blumler, 1979; Katz et al., 1974; Levy, 1987; Rouner, 1984; Rubin, 1993; Rubin &
Windahl, 1986; Slater, 2004). Uses and gratifications researchers have elucidated relationships
among people’s background characteristics, motives to use media, exposure, activity, and media
effects (Armstrong & Rubin, 1989; Charney & Greenberg, 2002; Finn, 1997; Greene & Krcmar,
2005; Lin, 2006; Papacharissi & Rubin, 2000; Weaver, Walker, McCord, & Bellamy, 1996).
10
Thus, a uses and gratifications approach may help explain the influence of college students’
MP3-player-music listening on their social interaction. Therefore, my fourth objective is to
examine the combined influence of college students’ loneliness, motives for listening to music
on an MP3 player, time spent listening to MP3-player music, and activity with MP3-player
music (i.e., attention to songs and elaboration on songs) on some specific types of social
interaction, including time spent socializing with others, frequency of participation in social
activities, frequency of post-listening discussion of music, and frequency of music file-sharing.
The objectives discussed above are important goals that need to be examined.
Researchers can gain a more comprehensive understanding of MP3-player use if they examine
the relationships among college students’ loneliness, motives to listen to music on an MP3
player, time spent listening to MP3-player music, activity with MP3-player music (i.e., attention
to songs and elaboration on songs), and social interaction. Also, if researchers examine the
above-mentioned relationships, they can address better the concerns of those who feel that MP3player use may be decreasing users’ social interaction.
Based on the above discussion, uses and gratifications theory, research, and my rationale
and objectives, I have developed a model of college students’ MP3-player-music listening to
illustrate some possible relationships among loneliness, MP3-player motives, exposure to MP3player music, activity with MP3-player music, and social interaction (see Figure 1). The first
component in the model identifies the background characteristic, loneliness, that is relevant to
critics’ concerns about MP3-player users (Copeland, 2006; Doherty & Baker, 2005; Kadden,
2004; White, 2006). Also, researchers have found that loneliness influences motives to use
media, exposure to media content, and social interaction (e.g., Caplan, 2003; Finn & Gorr, 1988;
Perse & Rubin, 1990). Loneliness may influence college students’ reasons for listening to music
11
Loneliness
MP3-Player-Music-Listening Motives
(relaxation/escape, stimulation,
entertainment, loneliness, boredom,
social utility, social avoidance,
atmosphere creation/mood control,
attention to lyrics, fashion/status)
Exposure
Audience Activity
(time spent listening to music)
(attention to songs, elaboration on songs)
Social Interaction
(time spent socializing with others, frequency of participation in
social activities, frequency of post-listening discussion of music,
frequency of music file-sharing)
Figure 1. Loneliness, Motives to Listen to MP3-Player Music, Exposure to MP3-Player Music,
and Audience Activity with MP3-Player Music as Predictors of Social Interaction.
12
on MP3 players, time spent listening to music on an MP3 player, and social interaction,
including time spent socializing with others, frequency of participation in social activities,
frequency of post-listening discussion of music, and frequency of music file-sharing.
Furthermore, college students’ MP3-player motives, the second component in the model, may
influence their time spent listening to music, attention to songs, elaboration on songs, and social
interaction. Also, college students’ MP3-player exposure and activity, the third and fourth
components in the model, respectively, may influence their social interaction, the fifth
component in the model.
I will expound upon and develop the components of my model (see Figure 1) further in
the following literature review. First, I will review briefly some of the assumptions of uses and
gratifications theory that guide my study. Second, I will examine literature regarding loneliness
as a background characteristic that may influence college students’ motives to listen to music on
an MP3 player, time spent listening to music on an MP3 player, attention to songs, elaboration
on songs, and social interaction. Third, I will review and discuss literature about people’s
reasons, or motives, for listening to music on an MP3 player that may influence their exposure,
activity, and social interaction. Fourth, I will examine extant literature regarding some types of
exposure to music and activity with music (i.e., attention to songs and elaboration on songs) that
may influence MP3-player listeners’ social interaction with others. Fifth, I will identify research
that suggests the role of some types of social interaction (i.e., spending time socializing with
others, participating in social activities, discussing music after listening, and sharing music files)
as possible outcomes of college students’ loneliness, motives to listen to music on an MP3
player, time spent listening to music on an MP3 player, and activity with MP3-player music.
13
Based on the following literature review, I will develop research questions and hypotheses to test
the relationships illustrated in my model (see Figure 1).
Critics seem to assume that MP3 players are causing users to be less social, regardless of
their individual differences (Doherty & Baker, 2005; Kadden, 2004; Rose, 2006; Rothman,
2006). However, Katz (1959) suggested that concerns about what “the media do to people” (p. 2)
may be misdirected. Instead, he advocated an audience-centered approach, uses and
gratifications, to identify and explore what “people do with the media” (Katz, 1959, p. 2).
Uses and Gratifications
Uses and gratifications focuses on what consumers do with the media rather than what
the media do to consumers (Katz, 1959; Katz & Foulkes, 1962; Rubin, 1993). This audiencecentered approach marked a shift from an earlier perspective (i.e., a hypodermic needle theory)
that held that media had a universal effect on their audience because, it was assumed, people
shared a similar disposition, or temperament (Lowery & De Fleur, 1988). Hirsch (1971) noted
that some analysts and observers adopted a hypodermic needle perspective regarding the
influence of popular song lyrics on their “undifferentiated target audience” (p. 367). Rather, uses
and gratifications researchers have recognized that “significant differences exist within the
viewing audience” (Hawkins et al., 2001, p. 239).
Uses and gratifications theory that claims consumers play an active role in their media
consumption and that their background characteristics, reasons for using media, media exposure,
and activity with media content work in concert to influence media effects (Blumler, 1979; Katz
et al., 1974; Rubin, 2002; Rubin & Windahl, 1986). These relationships are exemplified in an
early uses and gratifications framework that focused on “(a) the social and psychological origins
of (b) needs, which generate (c) expectations of (d) the mass media or other sources, which lead
14
to (e) differential patterns of media exposure (or engagement in other activities), resulting in (f)
need gratifications and (g) other consequences, perhaps mostly unintended ones” (Katz et al.,
1974, p. 20).
First, uses and gratifications theory assumes that people’s background characteristics
influence their motives to use media, exposure to media content, activity with media content, and
media effects (Katz et al., 1974; Rosengren, 1974; Rubin, 1993, 2002; Rubin & Windahl, 1986).
Indeed, researchers have found that background characteristics influence motives to use media,
media use, and effects (Armstrong & Rubin, 1989; Charney & Greenberg, 2002; Conway &
Rubin, 1991; Katz & Rice, 2002; Kraut et al., 1998; Papacharissi & Rubin, 2000; Rubin,
Haridakis, & Eyal, 2003; Weaver et al., 1996; Whitty & McLaughlin, 2007). For example,
Moore and Schultz (1983) found that most adolescents agreed that, when they were lonely, they
watched television or listened to music. Whitty and McLaughlin found that lonely people tended
to listen to music on the Internet frequently. Similarly, college students’ loneliness should
influence their motives to listen to music on an MP3 player, time spent listening to music on an
MP3 player, activity with MP3-player music, and social interaction.
Second, uses and gratifications theory claims that people’s reasons, or motives, for using
media influence their exposure to media, activity with media, and media effects (Blumler &
Katz, 1974; Hall, 2007; Leung, 2001). Motives are people’s reasons for acting or behaving in a
certain way that, they believe, will lead to a desired outcome (Atkinson, 1965; Rubin & Martin,
1998). Understanding people’s differing motives to use media helps explain their different uses
of media and outcomes.
Some of people’s motives for using media may be similar to their reasons for
communicating with others face-to-face and, therefore, people may use media as a functional
15
alternative to interpersonal communication (Armstrong & Rubin, 1989; Ebersole, 2000; Rubin,
2002; Rubin & Martin, 1998; Rubin & Rubin, 1985, 2001). In other words, people may use
media to substitute for interpersonal communication needs. For example, although Flaherty,
Pearce, and Rubin (1998) concluded that many of people’s motives to use the Internet were
different from their motives to communicate interpersonally (i.e., not functional alternatives),
they found that pleasure and time-shifting were functional alternatives. Overall, researchers have
found that people who perceive themselves as being deficient in their relationships and
interpersonal communication are especially likely to use media for social compensation
(Armstrong & Rubin, 1989; Finn & Gorr, 1988; Papacharissi & Rubin, 2000; Perloff & Krevans,
1987; Perse & Rubin, 1990; Rubin, Haridakis, & Eyal, 2003).
Also, researchers have found evidence supporting the influence of people’s motives on
their media exposure, activity, and effects (Greene & Krcmar, 2005; Hawkins et al., 2001;
Papacharissi & Rubin, 2000; Patwardhan, 2004; Sun, Rubin, & Haridakis, 2008). For example,
researchers have found that people who use media to escape tend to spend a lot of time
consuming media content (McClung et al., 2007; Sherry et al., 2006). Hawkins et al. found that
people who watched television programs to see specific shows tended to pay close attention to
dramas and sitcoms. Sun et al. found that people’s motives to use the Internet influenced their
dependency on the Internet. They found that people who used the Internet to reduce
boredom/relax, to acquire information, to interact with others, and to control others’ behaviors
tended to depend on the Internet to achieve goals such as seeking information and making
interpersonal connections.
Specifically, researchers have found that people’s motives to use media influence their
social interaction. For example, Rubin and Perse (1987a) found that college students who
16
watched soap operas to be with others and to talk with others about the programs (i.e., for social
utility) tended to discuss the programs with others after watching (i.e., post-viewing discussion).
Rubin and Step (2000) found that people who listened to talk radio programs for entertainment
tended to talk to others about politics.
There are reports that some people listen to MP3 players to avoid interacting with other
people (Bull, 2005, 2006; Chen, 1998; Diva, 2004). Other reports indicate that some people
listen to music on an MP3 player to bolster their social interaction (Doherty & Baker, 2005;
Evangelista, 2005; Rose, 2006; Wheeler, 2006; Yaksich, 2007). Unfortunately, uses and
gratifications researchers have not examined the relationships among college students’ motives
for listening to music on an MP3 player and their social interaction. In accordance with uses and
gratifications theory, college students’ reasons for listening to music on MP3 players should
influence their time spent listening, attention to songs, and social interaction.
Third, in addition to the influence of motives, uses and gratifications theory claims that
media effects are influenced by people’s exposure to media content and activity with media
content. Researchers have found evidence of relationships among exposure, activity, and
outcomes of people’s media use (Katz et al., 1974; Kim & Rubin, 1997; Larson & Kubey, 1983;
Roe, 1985; Rubin, 1993, 2002; Selnow, 1987). For example, Larson and Kubey found that high
school students who watched a lot of television content (i.e., heavy viewers) tended to spend
more time with their friends than did light viewers. Unfortunately, uses and gratifications
researchers have not examined the influence of college students’ time spent listening to MP3player music or their activity with MP3-player music on their social interaction.
Overall, many researchers have incorporated the uses and gratifications approach to guide
their examinations of people’s media use and media effects (e.g., Charney & Greenberg, 2002;
17
Greene & Krcmar, 2005; Katz et al, 1974; Leung & Wei, 2000; Lewis, 1981; Palmgreen &
Rayburn, 1979; Rubin, 1983; Sherry, Lucas, Greenberg, & Lachlan, 2006). Uses and
gratifications researchers have helped explain relationships among people’s background
characteristics, reasons for using media, media exposure, activity with media, and how they
relate to outcomes of media use. These explanations provide insight into people’s pattern of
media use and media effects that may be valuable to those who wish to understand the process
and outcomes better.
In accordance with uses and gratifications theory and research such as that referred to
above, college students’ loneliness, motives to listen to MP3-player music, time spent listening,
attention to songs, and elaboration on songs should work in concert to influence their social
interaction. Unfortunately, despite the uses and gratifications research discussed above, there is a
gap in our understanding of college students’ MP3-player-music listening and effects.
Researchers need to identify and examine important factors suggested in the uses and
gratifications model that are relevant to college students’ MP3-player use because they can help
bolster our understanding of the uses and effects of this pervasive medium. Therefore, I will rely
on uses and gratifications theory to guide my study of some social impacts of college students’
MP3-player-music listening.
Background Characteristics
As referenced above, the influence of people’s background characteristics on media use
and effects has been an integral part of uses and gratifications theory and research (Conway &
Rubin, 1991; McGuire, 1974; Rubin, 2002). Uses and gratifications researchers have claimed
that people’s background characteristics help influence their motives to use media and
consumption of media (Finn, 1997; Katz et al., 1974; Rosengren, 1974; Rubin, 2002).
18
Furthermore, Rubin suggested that researchers must understand audience members’
characteristics before they can explain any media effects. Daly and Bippus (1998) noted that
people’s background characteristics “account for significant variations in communication
behavior” (p. 22). This is important because it suggests that college students may use MP3
players in different ways based on their individual background characteristics. In other words,
college students’ background characteristics and MP3-player-music listening may influence their
social interaction more than would their MP3-player-music listening, alone.
Some scholars, journalists, and other members of the public have claimed that people
who listen to MP3 players are inadvertently forgoing social interaction with others and are
typically lonely as a result (Copeland, 2006; Doherty & Baker, 2005; Ferguson et al., 2007;
Kadden, 2004; Rothman, 2006; White, 2006). However, their accusation assumes that listeners
are affected indiscriminately and negatively by their media use. Rather, in accordance with uses
and gratifications theory, differences in people’s background characteristics lead to differences in
media consumption and effects. In other words, college students’ loneliness may be an
underlying factor that influences their music listening on MP3 players and their social
interaction.
However, researchers have not examined the probability that background characteristics,
such as loneliness, influence MP3 listeners’ social interaction with others. Research has shown
that people who are lonely are less likely to interact socially with others than are those who are
less-lonely (Bell & Daly, 1985; Caplan, 2003; Perse & Rubin, 1990; Pornsakulvanich, Haridakis,
& Rubin, 2008). It follows, from above, then, that MP3-player-music listeners’ social interaction
is influenced, in part, by their degree of loneliness.
19
Loneliness is a person’s perception that the quality of his or her social relationships is
less than desired (Peplau & Perlman, 1982; Peplau, Russell, & Heim, 1979; Weiss, 1974; Young,
1982). Gibson (2000) suggested that loneliness is “an experience and a feeling or emotion” (pp.
1-2). Feelings of loneliness are a common occurrence for many Americans and, typically, are
stressful (Curtona, 1982; Gibson, 2000; Peplau & Perlman, 1982; Stivers, 2004; Weiss, 1974;
Young, 1982).
For some people, feelings of loneliness are temporary or fleeting. For others, these
feelings may persist for weeks, months, or years (Lynch, 2000). If people’s relational
dissatisfaction persists for a long period of time, researchers classify them as chronically lonely,
suggesting an enduring characteristic rather than a situational disposition (Canary & Spitzberg,
1993; Young, 1982). On the contrary, less-lonely people are generally satisfied with the quality
of their social relationships and although they may experience brief episodes of feeling lonely,
these instances are rare and mild (Canary & Spitzberg, 1993).
College students, especially freshmen, may be susceptible to loneliness because moving
away from friends and family members can be a difficult period of adjustment (Cutrona, 1982;
Koenig & Abrams, 1999; Peplau & Perlman, 1982). Many college students are able to adjust to
their new environment. However, students who are unable to adjust may experience temporary
or even chronic loneliness. Cutrona (1982) noted that college students’ loneliness may be related
to drop out rates, alcohol abuse, and even suicide.
Researchers have found that people’s loneliness influences their motives for using media
(Austin, 1984; Finn & Gorr, 1988; Kraut et al., 1998; Leung, 2001; Perloff & Krevans, 1987;
Perse & Rubin, 1990). For example, Moore and Schultz (1983) found that most adolescents
reported listening to music when they felt lonely. Finn and Gorr found that lonely people were
20
more likely to watch television for companionship than were less-lonely people. Perse and Rubin
found that chronically lonely people were more likely than were less-lonely people to use the
radio, movies, and television when they felt lonely. Perloff and Krevans found that lonely adults
tended to watch television programs for companionship. Rubin et al. (1985) suggested that
lonely people may tend to use media for social compensation because they are not satisfied with
their interpersonal relationships.
Also, some evidence suggests that loneliness is relevant to people’s motives to listen to
music on MP3 players. Specifically, lonely people may listen to music on an MP3 player for
social compensation (Chen, 1998; Ferguson et al., 2007). For example, Chen found that listening
to music on a Walkman provided some students with companionship. Ferguson et al. found that
some people listened to an MP3 player to reduce their feelings of loneliness. The authors
suggested that MP3 players may function as a substitute for interpersonal communication.
In addition to people’s motives to use media, loneliness is related to people’s exposure to
media content (Caplan, 2003; Moore & Schultz, 1983; Perloff, Quarles, & Drutz, 1983; Rubin et
al., 1985). For example, Rubin et al. found that lonely people tended to watch more television
than did less-lonely people. Caplan found that loneliness was related to excessive use of the
Internet. Moore and Schultz found that most of their respondents claimed to watch television or
listen to music when they were lonely. Overall, research suggests that people who are lonely
spend more time consuming media content than do less-lonely people.
Also, researchers have found that people’s loneliness influences their social interaction
(Bell & Daly, 1985; Caplan, 2003; Moore & Schultz, 1983; Morahan-Martin & Schumacher,
2003; Perse & Rubin, 1990; Rubin et al., 1985; Solano, Batten, & Parish, 1982). Specifically,
loneliness is related to decreased social interaction. For example, Perse and Rubin found that
21
chronic loneliness related to reduced social interaction with others and low levels of participation
in social activities. Bell and Daly found that lonely people were less likely than were less-lonely
people to be highly involved in their conversations with others. Morahan-Martin and
Schumacher found that lonely Internet users were more likely than were less-lonely users to
claim that their Internet use affected their social activities negatively, keeping them from social
engagements. Moore and Schultz found that lonely adolescents were more likely to watch
television or listen to music than they were to talk with someone.
Based on the above discussion, people’s loneliness can be an important influence on their
motives to use media, MP3-player-music listening, and social interaction. Unfortunately,
researchers have not examined the above-mentioned relationships and, thus, we do not know the
degree to which loneliness influences MP3-player users’ motives, music listening, or social
interaction, if at all. Therefore, it is necessary to examine differences among college students’
loneliness because they may account for some differences among their motives to listen to music
on an MP3 player, music listening, and their social interaction.
Uses and gratifications theory claims that people’s background characteristics work in
concert with their motives to influence media effects (Katz et al. 1974; Rubin, 2002). Therefore,
people’s motives for listening to music on an MP3 player, which may include listening to music
for social interaction and to avoid social interaction, among other motives, are important because
they may influence consumers’ MP3-player-music listening and social interaction. However,
researchers have not examined fully college students’ motives to listen to music on MP3 players
(Albarran et al., 2007; Fergusson et al, 2007). Therefore, in the following section, I will review
literature pertaining to people’s motives to use media and, specifically, their motives for listening
to music on an MP3 player.
22
Motives
There is a general consensus across disciplines, including education (Pintrich & Schunk,
2002), neurobiology (Stellar & Stellar, 1985), psychology (Atkinson, 1965; Hogan, 1998;
Maslow, 1954), and communication (Rubin & Martin, 1998), that motives influence behavior.
“The word motivate means to cause to move” (Hogan, 1998, p. 164). Rubin and Martin defined
motives as “reasons for action” (p. 288) and “potentials for behavior” (p. 290). Pintrich and
Schunk suggested that motivation is an intentional and goal-directed process. Atkinson defined a
motive as “a relatively general disposition which will influence actions that are expected to lead
to a particular kind of consequence or goal” (p. 14). Stellar and Stellar stated that “motivated
behavior is goal-directed behavior and is thought by most theorists to be dependent upon specific
arousal or drive of the organism” (p. 29).
Researchers have found relationships between people’s media-use motives and their
media consumption, including their exposure to media and activity with media such as television
(Perse, 1990; Rouner, 1984; Hawkins et al., 2001), VCRs (Levy, 1983, 1987; Lin, 1990), video
games (Sherry et al., 2006), the Internet (Johnson & Kaye, 2003; Patwardhan, 2004), and radio
(Lin, 2006; McDowell & Dick, 2003). For example, Sherry et al. found that college students who
played video games for social interaction, diversion, and arousal tended to spend a lot of time
playing video games. Also, Hawkins et al. found that people who watched drama and situation
comedy television programs to change or maintain their mood tended to think about the
programs they watched. It follows from above that college students’ motives to listen to music
on MP3 players should influence their time spent listening to MP3-player music and activity
with MP3-player music.
23
In addition to exposure and activity, uses and gratifications researchers have suggested
that people’s motives to use media influence outcomes of their media use (e.g., Abelman &
Atkin, 2000; Perse & Butler, 2005; Rubin, 1983, 2002). For example, Rubin (1983) noted that,
according to uses and gratifications theory, people’s motives to watch television explain or
predict patterns in people’s behavior and attitudes. Uses and gratifications researchers have
found that peoples motives to use media such as television (Lee & Lee, 1995; Lull, 1980;
Palmgreen & Rayburn, 1979; Rubin, 1979), video games (Sherry et al., 2006), radio (Perse &
Butler, 2005; Towers, 1985, 1987) and the Internet (Charney & Greenberg, 2002; Haridakis &
Hanson, 2009; Johnson & Kaye, 2003; Kaye, 2005; Papacharissi & Rubin, 2000) influence
media effects. For example, Haridakis and Hanson found that college students who watched
videos on YouTube, a video-oriented website, for social interaction, co-viewing, and
entertainment tended to share videos with others online.
Critics’ main concern is that people’s MP3-player use is reducing their social interaction
(Copeland, 2006; Doherty & Baker, 2005; Harris, 2005; Kadden, 2004; Rose, 2006; Rothman,
2006; Stapp, 2007; White, 2006). However, based on uses and gratifications theory and the
findings discussed above, the influence of college students’ motives to listen to music on an MP3
player should be accounted for as well. For example, some college students may listen to music
on an MP3 player to avoid others and may experience decreased social interaction as a result.
However, some college students may listen for social utility, resulting in increased social
interaction. Unfortunately, researchers have not examined the influence of college students’
MP3-player motives on their social interaction. Therefore, to respond to the assertions that critics
have made and to bolster our understanding of college students’ MP3-player-music listening and
24
effects, researchers need to examine college students’ motives to listen to music on an MP3
player and how they influence their social interaction.
Researchers have identified some motives for listening to music that should be relevant to
college students’ use of MP3 players to listen to music (Christenson, 1994; Hakanen, 1995;
Lamont, Hargreaves, Marshall, & Tarrant, 2003; Lichtenstein & Rosenfeld, 1983; Roe, 1985;
Tarrant, North, & Hargreaves, 2000). For example, Lichtenstein and Rosenfeld found that
college students used recorded music as a means for escape, to get away from usual cares and
problems. Christenson found that first- through sixth-graders’ most frequent reason for listening
to music was for general entertainment. Tarrant et al. found that adolescents listened to music to
alleviate boredom. Roe found that Swedish adolescents listened to music because it created a
good atmosphere when they were with others and it helped them get into the right mood.
Furthermore, researchers have found that some people listen to music for social utility, or
to bolster their social interaction with others (Hall, 2005; Hansen & Hansen, 2000; HoughtonLarsen, 1982; McClung, Pompper, & Kinnally, 2007; Tarrant et al., 2000; Towers, 1985, 1987).
For example, Towers (1985, 1987) found that some people listened to the radio for
surveillance/interaction. This motive includes listening to get information that you can pass to
others and finding interesting stories to tell other people. Hansen and Hansen suggested that
young people may listen to pop, or mainstream, music because it is a common referent that they
can discuss with others.
Other researchers have found that some people listen to music for the song lyrics and
lyrical themes (Christenson, 1994; Gantz, Gartenberg, Pearson, & Schiller, 1978; Lewis, 1981;
Roe, 1985). For example, Christenson found that children claimed that they liked to listen to
music because it had a good message and because they liked the words. Roe found that 11- to
25
15-year-olds listened to music so that they could listen to the words and because the words
expressed how they felt.
The above-mentioned motives to listen to music are important to consider in my study of
college students’ MP3-player use. As previously stated, people who use MP3 players commonly
use them to listen to music (Arensman, 2005; IFPI, 2006; Pew Internet & American Life Project,
2005). Therefore, it makes sense that college students’ motives to listen to music may be similar
to their motives for listening to music on an MP3 player.
Furthermore, Tarrant et al. (2000) suggested that researchers should study the media that
people use to deliver and receive music because users may report distinctive motives for, and
benefits from, using these devices. Ruggiero (2000) noted that understanding people’s motives
for using new media technologies is especially important because these devices offer consumers
a plethora of choices and interactivity. Researchers have identified reasons why consumers use
new media such as electronic bulletin boards (Garramone, Harris, & Anderson, 1986), pagers
(Leung & Wei, 1998), cell phones (DeBaillon & Rockwell, 2005; Katz & Sugiyama, 2005;
Leung & Wei, 2000), personal digital assistants (Trepte, Ranné, & Becker, 2003), video games
(Lucas & Sherry, 2004; Sherry et al., 2006), and the Internet (Charney & Greenberg, 2002;
Ebersole, 2000; Papacharissi & Rubin, 2000). Unfortunately, only a few researchers have
empirically examined college students’ motives for using MP3 players (Albarran et al., 2007;
Ferguson et al., 2007).
Albarran et al. (2007) surveyed college students about their motives for listening to
AM/FM radio, satellite radio, Internet streaming radio, and MP3 players. They found that college
students’ reasons for using an MP3 player were similar to their reasons for listening to AM/FM
radio. Specifically, respondents indicated that they used MP3 players to relax and to forget about
26
their daily cares, among other reasons. In fact, respondents indicated that MP3 players were
more helpful than was terrestrial radio for all of the reasons examined, except for gaining access
to news and information. Albarran et al. suggested that college students may prefer to listen to
terrestrial radio for local news, weather, and traffic information that is not as readily available on
satellite radio, Internet radio, or MP3 players.
Also, Ferguson et al. (2007) examined college students’ reasons for using iPods. They
found that some college students used their iPod to relax/escape, for stimulation, for
entertainment, to avoid loneliness, and to reduce boredom. In addition to the above-mentioned
MP3-player motives identified by Albarran et al. (2007) and Ferguson et al. (2007), scholars
have speculated that some users may have other reasons for using an MP3 player, including
social utility, social avoidance, atmosphere creation or mood control, lyrical content, and
fashion/status (Bull, 2000; Christenson, 1994; Kahney, 2004; McClung et al., 2007; Roe, 1985;
Tarrant et al., 2000).
First, scholars and journalists have reported that some people listen to music on portable
personal stereos, such as a Walkman or iPod, to avoid others (Bull, 2000, 2005, 2006; Chen,
1998; Diva, 2004; Kadden, 2004; Rothman, 2006; White, 2006). For example, Chen reported
that some people listened to a Walkman to intentionally segregate themselves from others. Some
of the people she interviewed indicated that they listened to avoid talking with others, to be left
alone by other people, and to block out another person. Bull (2000) noted that some Walkman
listeners avoided conversations by absorbing themselves in their music and, thus, preventing
interruptions from others. Bull (2006) reported that some people also used iPods to avoid talking
with others. Diva suggested that listening to an iPod prevented unwanted conversations. One of
Kadden’s interviewees suggested that people who want to avoid interacting with others can use
27
an MP3 player to shield themselves from social interaction. Based on the above reports, avoiding
social interaction should be an important motive for some college students to listen to music on
an MP3 player.
Second, however, it is possible that some people may listen to music on an MP3 player
for social utility (Doherty & Baker, 2005; Evangelista, 2005; Rose, 2006; Wheeler, 2006;
Yaksich, 2007). Hall (2005) suggested that consumers’ use of music to interact with others “may
be increasing as music storage formats switch to digital, allowing audiences to share music over
the Internet or through personalized mixed tapes or CDs” (p. 393). For example, Yaksich found
that some college students enjoyed sharing their music with others because their iPod allowed
them to access a lot of their music easily.
Third, as mentioned above, music can create a good atmosphere and help listeners control
their mood (Roe, 1985). Christenson, DeBenedittis, and Lindlof (1985) claimed that the
personalization and portability of audio media make them ideal tools for controlling moods, even
better than television. MP3 players allow users to create playlists of specific songs for
maximized familiarity (Duncan & Fox, 2005). Bull (2005) noted that iPod users may create a
variety of playlists to evoke different moods. Starkman (2007) reported that a person he
interviewed claimed that listening to music on an iPod can change one’s mood. Therefore, based
on the above discussion, atmosphere creation/mood control should be an important motive for
listening to music on an MP3 player.
Fourth, as previously discussed, some people listen to music because they like the lyrics
or want to hear lyrical themes (Christenson, 1994; Gantz et al., 1978; Lewis, 1981; Roe, 1985).
Chen (1998) interviewed Walkman listeners and found that some people listened to music on
their portable cassette player for the lyrics. One of the college students that she interviewed
28
claimed that he would listen to his Walkman at full volume and sing along to the lyrics. Schedl,
Knees, Pohle, and Widmer (2006) noted that some digital music players provide users with
information about their music, including song lyrics. Purushotma (2005) indicated that
synchronized lyrics can be downloaded from the Internet and embedded into MP3 files. This
allows users to read the lyrics as they follow the song. Therefore, it follows from above, then,
that some college students may listen to music on an MP3 player to hear the lyrics.
Fifth, some people may use MP3 players to be fashionable or to gain status (Kahney,
2004; Levy, 2004; Wheeler, 2006; Yaksich, 2007). Katz and Sugiyama (2005) suggested that
fashion should be considered as a motive for using newer technologies because devices such as
mobile phones have become part of users’ social identity. Katz (2007) noted that MP3 players
have become portable displays of status like the Walkman before them. Other scholars have
argued that iPod is the most popular brand of MP3 player because of its status as a fashion icon
(Levy, 2004; Wheeler, 2006). Teenagers consider status to be an important value, but adults also
may desire to use an iPod as a sign of their youthfulness (Wheeler, 2006). Furthermore, iPods are
especially recognizable due their trademark white earphone cords that can be seen even when the
iPod itself is out of view (Wheeler, 2006). Professor Michael Bull stated that iPods “will appeal
to those who want an artifact for style” (quoted in Kahney, 2004). Therefore, some college
students may listen to music on MP3 players for fashion and status.
The aforementioned research suggests that the following motives may be important
reasons for listening to music on an MP3 player: (a) relaxation/escape, (b) stimulation, (c)
entertainment, (d) loneliness, (e) boredom alleviation, (f) social utility, (g) social avoidance, (h)
atmosphere creation/mood control, (i) attention to lyrics, and (j) fashion/status. In accordance
with uses and gratifications theory, users’ motives for listening to music on MP3 players should
29
influence media use and effects (see Katz et al., 1974; Rubin, 2002). Therefore, based on the
above discussion, researchers need to examine college students’ reasons for listening to music on
MP3 players and the degree to which these motives influence their MP3-player-music listening
and social interaction.
In addition to college students’ motives to listen to music on an MP3 player, their
exposure to media content is especially important to consider in my study because it is at the
center of the controversy surrounding MP3-player use. Some critics seem to argue that people
are spending too much time listening to MP3-player music and, as a result, not enough time
interacting socially with others (Copeland, 2006; Doherty & Baker, 2005; White, 2006).
Although time spent listening to MP3-player music is typically spent alone (Bull, 2005, 2006),
listeners are not necessarily forgoing social interaction because they spend time listening to
music on an MP3 player. Overall, researchers have found that people’s time spent using media
content does not tend to displace their social interaction (Kraut et al., 2002; Mares & Woodard,
2005). In some cases, researches have even found that media exposure related positively to social
interaction (Bickham & Rich, 2006; Jeffres et al., 2003; Katz & Rice, 2002). In other words,
some people who spent a lot of time consuming media content were more likely to interact with
others than were those who did not spend a lot of time consuming media content.
Exposure
Gunter (2000) stated that “one of the fundamental questions asked about the media by
researchers is to what extent are they used?” (p. 93). Exposure is “the extent to which audience
members have encountered specific messages or classes of messages/media content” (Slater,
2004, p. 168). Gunter noted that if people do not experience media, then, media cannot have any
impact on them.
30
Some researchers have conceptualized and measured exposure as the frequency of media
use including the number of days per week, month, or year that they rented pre-recorded tapes
(Van den Bulck, 1999) or how often they left messages on a computer bulletin board (Garramone
et al., 1986), for example. Other researchers have conceptualized exposure as the time people
spend with various types of media (Drew & Weaver, 1990; Patwardhan, 2004; Slater, 2004). For
example, some researchers have examined the number of hours that consumers spent watching
television (Rubin, 1984; Van den Bulck, 1999) or listening to an MP3 player (Albarran et al.,
2007; Ferguson et al., 2007) on a particular day.
The amount of time that people spend consuming media content is an important variable
to consider in my study of college students’ MP3-player-music listening. The long battery life,
music storage capacity, and earbuds of MP3 players provide users with an opportunity to spend
more time listening to music on these devices than on traditional portable music players
(“Earbuds: Hip or Harmful?,” 2006). Also, Levy (2004) suggested that the interface functions of
iPods may allow users to listen to more music than traditional music delivery devices. Indeed,
Rose and Lenski (2008) found that most of their respondents reported that they listened to less
over-the-air radio in the car due to time spent listening to their iPod or other portable MP3
player. Similarly, Ferguson et al. (2007) found that iPod use served as a substitute for radio
listening. They reported that, on average, college students listened to their MP3 players about 2.5
hours per day, or almost 18 hours per week.
Most of people’s time spent listening to music on an MP3 player is likely spent alone,
without other people (Bull, 2005, 2006; Diva, 2004). For example, Bull (2005) reported that iPod
users tended to listen to music by themselves and did not interact with others while listening. His
observation coincides with evidence that most of the time people spend listening to music is
31
alone, or by themselves (Christenson, 1994; Larson & Kubey, 1983; Lull, 1985). For example,
Larson and Kubey (1983) used diaries to record how people spent their time. They found that
adolescents spent more than twice the amount of time listening to music by themselves as they
did listening to music with family members and friends, combined. Christenson (1994) found
that children were more likely to spend their time listening to music alone than they were to
spend time with their family members. Older children were even more likely to spend their time
listening to music alone than were younger children.
Some critics have raised concerns that people’s time spent listening to music on their
MP3 player is displacing time they spend interacting with others (Copeland, 2006; Doherty &
Baker, 2005; Stapp, 2007; White, 2006). For example, Stapp argued that people who use iPods
are depriving themselves, as well as others, of social interaction because, he claimed, iPod use
limits opportunities for social interaction. Copeland claimed that it is more common to see
college students listening to their own iPod than having a conversation with each other. Other
critics have raised similar concerns regarding people’s use of media such as the Internet,
television, and VCRs (Kraut et al., 1998; Putnam, 1995b).
However, researchers have found that, overall, media use does not displace time spent
interacting with others and that some people’s time spent using media is related to increased
social interaction (Bickham & Rich, 2006; Jeffres et al., 2003; Katz & Rice, 2002; Kraut et al.,
2002; Mares & Woodard, 2005). For example, Katz and Rice found that long-term Internet users
had met with friends more often than had new users or nonusers. Jeffres et al. found that people’s
time spent using media such as film and videos was related to increased participation in leisure
activities, including visiting an outdoor entertainment district and attending a concert.
32
Similarly, college students’ time spent listening to music on an MP3 player may be
related to social interaction. For example, Leung and Lee (2005) found that MP3-player listening
related positively to social support, a person’s perception of his or her social network’s ability to
provide him or her with emotional, informational, social, and affectionate assistance.
Specifically, they found that people who spent a lot of time listening to music on an MP3 player
were more likely to have someone to socialize with than were those who did not spend much
time listening to MP3-player music. Although having someone to socialize with is not the same
as actually socializing with someone, Leung and Lee’s finding suggests that heavy listeners of
MP3-player music had a greater potential to interact socially than did light listeners. Mizerski,
Pucely, Perrewe, and Baldwin (1988) found that people who spent a lot of time listening to
music on the radio, television, or a record/tape were more likely to have attended a musical
concert in the past six months than were those who did not spend a lot of time listening to music.
Similarly, Dixon (1979, 1980) found that people who spent a lot of time listening to music
tended to be concert-goers.
Based on the above discussion, college students who spend a lot of time listening to
music on an MP3 player may be more likely to interact socially with others than would those
who do not spend a lot of time listening to MP3-player music. However, researchers have not
examined the relationship between time spent listening to MP3-player music and social
interaction. Researchers need to examine the previously mentioned relationship because
differences in college students’ time spent listening to MP3-player music may be related to
variations in their social interaction.
In addition to consumers’ exposure to media content, their activity with media content is
an important component of their media consumption (Charney & Greenberg, 2002; Dittmar,
33
1994; Katz et al., 1974; Leung, 2007; Minnebo, 2006; Palmgreen & Rayburn, 1982; Perse, 1990;
Rubin, 1984; Wober & Gunter, 1982) and an especially important part of their music listening
(Christenson, 1994; Christenson & Peterson, 1988; Gantz et al., 1978; Hansen & Hansen, 1991;
Knobloch & Zillmann, 2002; Lin, 2006; Roe, 1985). Uses and gratifications theory claims that
people may be more or less active with media during their exposure (Kim & Rubin, 1997;
Metzger & Flanagin, 2002; Rubin, 1993). Chaffee and Schleuder (1986) noted that people can
spend time consuming media but they may not be paying much attention to the media content or
thinking about it deeply. College students’ activity with MP3-player music may be an important
influence on their social interaction.
Audience Activity
An active audience is a core assumption of uses and gratifications theory and represents
behavioral and cognitive engagement with media and media content (Katz et al., 1974; Kim &
Rubin, 1997; Lin, 2006; Rubin, 2002). Audience activity is especially important to the study of
newer media (Heeter & Greenberg, 1988; Metzger & Flanagin, 2002; Patwardhan, 2004; Perse,
1990; Walker, Bellamy, & Traudt, 1993). Perse claimed that newer technologies may increase
the potential for users to be active. Specifically, music researchers have suggested that delivery
devices such as the Walkman (Bull, 2000; Chen, 1998) and iPod (Bull, 2005) may allow users a
more active listening experience. Chen noted that people who listen to Walkmans pay a lot of
attention to the rhythm and beat of their music. Bull (2000) noted that portable personal stereos
like the Walkman allow users to immerse themselves in their own world of sound wherever they
go. Unfortunately, little is known about college students’ different types of activities with music
on an MP3 player or the relationship between their activity and social interaction. Attention and
elaboration represent two types of audience activity that are especially relevant to college
34
students’ music listening because researchers have found that people’s attention and elaboration
vary when listening to music and these variations should influence media effects (Christenson,
1994; Christenson & Peterson, 1988; Gantz et al., 1978; Hansen & Hansen, 1991; Knobloch &
Zillmann, 2002; Roe, 1985).
Attention and elaboration are two different types of audience activity that typically occur
during people’s exposure to media (Levy & Windahl, 1984). Attention is increased and focused
sensory effort directed toward media content or messages (Chaffee & Schleuder, 1986; Perse,
1990). Elaboration on media content while consuming it, involves the cognitive processing of
media messages (Hawkins et al., 2001; Levy & Windahl, 1984; Perse, 1990). Perse noted that
elaboration entails thinking about media content and “relating it to prior knowledge” (p. 679).
Attention and elaboration are activities that are especially relevant to music listening
(Christenson, 1994; Christenson & Peterson, 1988; DeNora, 2003; Dixon, 1979, 1980; Gantz et
al., 1978; Hansen & Hansen, 1991; Knobloch & Zillmann, 2002; Kubey & Larson, 1990; Lacher
& Mizerski, 1994; Lewis, 1980, 1981; Lin, 2006; Meyer, 1956; Mizerski et al., 1988; Roe, 1985;
Yingling, 1962). For example, Lewis (1980) asked eleventh graders about their attention to
music. He found that, although some people tended to listen carefully and some people tended to
listen to music as a background to other activities, most respondents’ attention level tended to be
between these two extremes. Lewis (1980) also found that males were slightly more likely to
listen to music as a background to other activities than were females.
Meyer (1956) noted that “music may give rise to images and trains of thought” (p. 256).
DeNora (2003) claimed that listeners often relate music to other things, including their past
experiences, and their elaboration on songs influences music listening effects. Yingling (1962)
found that college students associated songs with past events and mental images. Gatewood
35
(1927) noted that music often reminds listeners of their past or invites imagination, even if the
music selection is novel. Lacher and Mizerski (1994) found that college students’ imaginal
response to songs related to their intention to purchase songs. The imaginal response refers to the
images and memories that people associate with the songs to which they listen (Ortmann, 1927).
Knobloch and Zillmann (2002) suggested that consumers who listen to their personal
catalog of pre-recorded music tend to be more active in their music listening than those who
listen to the radio because pre-recorded music requires more physical interaction than does the
radio. Other scholars have warned that people who listen to music on portable devices with
headphones at loud volumes may be so focused on their music that they may not pay much
attention to surrounding dangers (Catalano & Levin, 1985; Long, 2008; Vogel, Brug, Hosli, van
der Ploeg, & Ratt, 2008). For example, Vogel et al. found that some people listened to music on
their MP3 players at maximum volume to focus their attention on the songs, thereby minimizing
outside noises. However, some people reported that they listened to music on their MP3 player
as a background to other activities such as homework.
Researchers have found that people’s activity with music is related to their social
interaction with others (Dixon, 1979, 1980; Mizerski et al., 1988). For example, Dixon (1979,
1980) found that people who listened intently to music were more likely to have attended a
musical concert in the past year than were people who did not listen intently. Also, Mizerski et
al. found that listeners who were highly involved with a particular song during listening were
more likely to have attended musical concerts than were those who did not report a lot of
involvement with a song. Ouellet (2007) found that college students’ imaginal response to songs
was related to their file-sharing of digital music files. Gantz et al. found that some high school
students elaborated on songs by contemplating the meaning of the lyrics when they listened to
36
music. Elaborating on song lyrics may be especially important for those who want to discuss
their music listening with others (Hansen & Hansen, 1991; Roe, 1985).
It follows, then, from the above discussion, that college students’ attention and
elaboration are likely to vary from low to high levels of activity during their MP3-player-music
listening. Differences among college students’ attention to songs on an MP3 player and
elaboration on songs should be related to variations in their social interaction. Unfortunately,
little is known about college students’ attention to music and elaboration on music on an MP3
player and their relationship with social interaction. Researchers need to examine college
students’ attention to songs and the degree to which they think about the songs they listen to on
an MP3 player because high levels of attention and elaboration may be related to pronounced
media effects (Katz, 1959; Kim & Rubin, 1997; Levy, 1987).
Specifically, college students’ social interaction is an important outcome on which I am
focusing in my study of MP3-player use because some journalists and scholars have expressed
concern that MP3-player use is decreasing users’ social interaction (Copeland, 2006; Doherty &
Baker, 2005; Harris, 2005; Kadden, 2004; Rose, 2006; Rothman, 2006; Stapp, 2007; White,
2006). In accordance with uses and gratifications theory and research discussed above, college
students’ loneliness, motives to listen to music on an MP3 player, exposure to MP3-player
music, and activity with MP3-player music should influence their social interaction (Levy, 1987;
Levy & Windahl, 1984; Perse & Rubin, 1988; Rubin & Perse, 1987a). Unfortunately, researchers
have not examined these relationships. Therefore, to address the concerns that critics have raised
and to better our understanding of college students’ MP3-player-music listening and effects,
researchers need to examine the influence of college students’ loneliness, motives to listen to
37
music on an MP3 player, time spent listening to music on an MP3 player, and activity with MP3player music (i.e., attention to songs and elaboration on songs) on their social interaction.
Social Interaction
Social interaction, or engagement with others, is necessary to develop and maintain
personal relationships (Cutrona, 1982; Johnsson-Smaragdi, 1983; Meeuwesen, 2006; Schachter,
1974; Weiss, 1974). Morrill and Snow (2005) noted that these “personal relationships are at the
core of human existence” (p. 3). Social interaction is so important that some people can
experience uneasiness and mental anguish when deprived even for a short period of time
(Schachter, 1974).
Weiss (1974) noted that people fulfill their social needs by interacting with a variety of
social contacts. Cutrona, Russell, and Rose (1986) suggested that, typically, people interact with
a spouse or lover for emotional closeness, friends for a sense of social integration, and family
members for notions of dependability. They stated that although interacting with one person may
satisfy several of the previously mentioned needs, people typically interact with a variety of
others (e.g., family members and friends) to fulfill these needs. People who rely on a small
network of others with which to interact socially are more vulnerable to disruptions in their need
fulfillment than those who have a greater number of social contacts (Meeuwesen, 2006).
Therefore, a robust, or varied, amount of social contact is an important indicator of healthy social
interaction (Cole & Robinson, 2002; Lee & Zhu. 2002; Mikami, 2002; Nordlund, 1978; Russell
et al., 1980).
Scholars have been concerned with the impact that consumers’ media use has on their
social interaction (e.g., Flanders, 1982; Hennion, 2001; Kraut et al., 1998; Nie, Hillygus, &
Erbring, 2002; Putnam, 1995a, 1995b; Robinson & Godbey, 1997, Yzer & Southwell, 2008). For
38
example, Kraut et al. argued that increased Internet use may be related to decreased social
interaction with others. Nie et al. claimed that the Internet can be more isolating than television
because “computers are in more private spaces where interruptions are less likely to occur” (p.
231). Putnam (1995a, 1995b) claimed that people’s use of media technologies such as personal
cassette and compact disc players to listen to music exemplify a privatization or an
individualization of people’s leisure time, diminishing opportunities for social interaction and
participation in social activities.
For the most part, research findings on the relationships between people’s media use and
their social interaction suggest that people’s media use does not seem to displace their social
interaction and, in some cases, people’s use of media is related to increased social interaction
(Cole et al., 2004; Cole & Robinson, 2002; DeBaillon & Rockwell, 2005; DiMaggio, Hargittai,
Neuman, & Robinson, 2001; Hampton & Wellman, 2003; Johnsson-Smaragdi, 1983; Katz &
Rice, 2002; Larson & Kubey, 1983; Mikami, 2002; Rubin, 1979; Shah et al., 2002). For
example, in response to criticisms that television use detracts from viewers’ social relationships,
isolating them from others, Johnsson-Smaragdi examined the impact that television had on
adolescents’ social interaction. Based on his findings, he concluded that “TV certainly plays a
role in social interaction – both positively and negatively – but it cannot prevent interaction
entirely” (p. 199). In a meta-analysis of children’s television use, Mares and Woodard (2005)
found that “television has the potential to foster positive social interactions” (p. 316). Hampton
and Wellman found that people who had an in-home Internet connection were more likely to
communicate with others and visit others than were those who did not have in-home Internet
access. Shah et al. found that people who spent a lot of time using the Internet tended to
39
participate in more social events, such as attending a pop rock concert, than did those who spent
little time online.
As previously mentioned, journalists and scholars have raised concerns about MP3player-music listening and its potential to decrease users’ social interaction with others
(Copeland, 2006; Doherty & Baker, 2005; Ferguson et al., 2007; Harris, 2005; Kadden, 2004;
Rothman, 2006; Stapp, 2007; White, 2006). For example, in an article entitled iPods Destroying
Social Interaction, White warned that “people are so in touch with their iPods that they are
losing touch with the world around them” (para. 4). Furthermore, listening to pre-recorded music
tends to be performed without other people (Bull, 2005; Hennion, 2001; Putnam, 2000). Hennion
suggested that listening to music on compact discs tends to be a solitary experience. With the aid
of lightweight, tiny earphones, MP3 players are designed to allow users a private listening
experience wherever they go. Bull noted that people tend to use iPods by themselves.
However, although people may tend to listen to MP3-player music by themselves, their
music listening may benefit their future social interactions with others. For example, users have
reported sharing their iPod with friends to exchange music (Wheeler, 2006). Rose (2006)
reported that some workers share their playlists of songs with other employees to expand their
musical repertoire and learn about their colleagues’ music preferences. Evangelista (2005) found
that some people even flirt with others by exchanging playlists and music libraries. Leung and
Lee (2005) found that MP3-player listeners tended to have a lot of opportunities to participate in
social activities with others. The different types of social interaction mentioned above should be
important outcomes to consider in my study of people’s MP3-player-music listening.
40
Time Spent Socializing with Others
The amount of time that people spend socializing with others is an indicator of people’s
social interaction that is especially important to my study of people’s use of MP3 players to
listen to music. Stapp (2007) suggested that people’s time spent using an iPod decreases their
time spent interacting with other people. Copeland (2006) claimed that iPod use reduces time for
conversations among friends. Similarly, Harris (2005) argued that listening to music on an iPod
has the potential to decrease conversations with others. Yzer and Southwell (2008) alleged that it
is common for college students to walk around “plugged into their iPod or other portable music
device rather than talking with other people” (p. 10). The above-mentioned concerns suggest that
people’s time spent listening to MP3-player music is displacing their time for social interaction
with others.
However, Cole and Robinson (2002) found that Internet users and non-users spent the
same amount of time socializing with others. Mikami (2002) found that heavy Internet users in
Japan spent more time socializing with others than did light Internet users. Katz and Rice (2002)
documented research findings on the social consequences of Internet use and concluded that
“rather than a technology of isolation and loneliness, the Internet is a technology through which
social capital can be created” (p. 337).
Unfortunately, researchers have not examined the relationship between college students’
MP3-player use and the time they spend interacting with others. Specifically, differences in
college students’ loneliness, motives to listen to MP3-player music, time spent listening,
attention to songs, and elaboration on songs may explain differences, if any, in their time spent
interacting with others. Researchers need to examine the impact of college students’ individual
41
differences on their time spent interacting with others to reduce speculation about this
relationship.
Frequency of Participation in Social Activities
In addition to the overall amount of time spent with others, the frequency with which
MP3-player users participate in specific social activities is an important indicator of their social
interaction. Bagozzi, Dholakia, and Pearo (2007) suggested that media researchers need to
examine people’s participation in social activities that are more descriptive than their social
interaction with others. Specifically, they considered activities such as participation in
neighborhood activities and hobby groups. Shklovski, Kraut, and Rainie (2004) suggested that
participation in social groups, such as going out to dinner with others and doing volunteer work,
represents fulfilling and healthy personal relationships.
Researchers have found that people’s use of media is related to their participation in
social activities (Bagozzi et al., 2007; Murray & Kippax, 1978; Mutz, Roberts, & van Vuuren,
1993; Putnam, 1995c). For example, researchers have examined the impact of people’s Internet
use on their participation in social activities such as eating out with others, going to a bar or
tavern, attending parties, or calling friends just to talk (Anderson, 2008; Gershuny, 2002; Mesch,
2001; Neustadtl & Robinson, 2002; Qiu, Pudrovska, & Bianchi, 2002). Anderson found that
users who switched from narrow to broadband Internet access did not experience any declines in
the frequency of their social activities such as meeting with friends and going to a concert,
among others.
Also, Qiu et al. (2002) found that families that used the Internet or a home computer were
just as likely to participate in religious and organizational activities as were families who did not
have Internet or computer access at home. Gershuny (2002) found that new users of home
42
computers were more likely to eat out at a restaurant, go to the cinema, and visit family members
and friends than they were before they started using the Internet. He suggested that people may
use the Internet and e-mail to gain information about social activities and to make arrangements
for social interaction. Overall, researchers have found that Internet use does not tend to reduce
people’s participation in social activities, and in some cases, is related to increased social
interaction.
As previously discussed, some scholars have noted that listening to music on an MP3
player has the potential to be isolating and unsocial (Bull, 2005; Ferguson et al., 2007; Kadden,
2004). Putnam (2000) suggested that heavy consumption of entertainment media is related to
privatized leisure time. He noted that music listening has become a more individualized
experience than it had been in the past because of personalized stereos such as the Walkman and
portable CD players. However, as mentioned above, Leung and Lee (2005) found that listening
to music on CD and MP3 players related positively to social support. Specifically, they found
that people who spent a lot of time listening to music on CD and MP3 players were more likely
to have someone with whom to get together and do something enjoyable than were light
listeners. Although Leung and Lee did not specify the types of potential activities in which
listeners could engage, their finding suggests that heavy music listeners may have more
opportunities to participate in social activities than those who don’t spend a lot of time listening
to music on an MP3 player.
Understanding the relationship between MP3-player listening and participation in social
activities is important because it may help explain the specific types of social activities in which
listeners participate, if any. Also, differences among college students’ loneliness, motives to
listen to music on an MP3 player, exposure to MP3-player music and activity with MP3-player
43
music may account for differences in their social activities. Unfortunately, there is little research
on how frequently MP3-player music listeners are participating in specific types of social
activities. Therefore, researchers need to examine the impact of college students’ MP3-player use
on their participation in social activities.
Frequency of Post-Listening Discussion of Music
Levy (1987) noted that individuals may utilize media after exposure by discussing
content with others. For example, he found that most VCR users discussed movies they had seen.
MacDonald, Miell, and Wilson (2005) claimed that talking about music can serve an important
social function for people as well. They noted that musicians who play together often socialize
by discussing music. “During a tour, for example, bands are likely to spend more time in
conversation about music than actually playing together” (p. 321). MacDonald et al. suggested
that players are not that different from some listeners of music because fans are often very
knowledgeable and conversant about their music listening.
As previously mentioned, researchers have found that some people listen to music to
interact with others (Christenson & Peterson, 1988; Hall, 2005; Houghton-Larsen, 1982;
McClung et al., 2007; Roe, 1985; Tarrant et al., 2000). Also, scholars have found that some
people engage in social interaction by discussing music with others (Clarke, 1973; Hansen &
Hansen, 2000; Horrigan, 2008; Katz, 2006; Lin, 2006; Madden & Rainie, 2005; McClung et al.,
2007). For example, Lin found that some adults shared and discussed things that they had heard
on the radio, including music programs. Also, Roe found that some adolescents listened to the
lyrics of songs so that they would have something to discuss with their peers. Horrigan found
that most people who purchased music discussed the music with family members and friends
after their purchase. Katz noted that people may interact with others who appreciate their musical
44
tastes. Therefore, based on the above findings, it makes sense that some people may interact with
others by discussing the music that they listened to on their MP3 player. Researchers need to
examine college students' post-listening discussion to see if certain antecedents influence the
frequency with which they talk with others about the music to which they listen.
Frequency of Music File-Sharing
In addition to discussing music with others after listening, college students may share
media fare with others as a form of social interaction. Levy (1987) suggested that VCR users
may exchange video tapes with others to bolster their interpersonal relationships. He found that
about half of VCR users shared video tapes with their family members and friends often or some
of the time. Haridakis and Hanson (2009) noted that people can use the Internet to share video
files with others. Haythornthwaite (2005) suggested that people may be more likely to adopt and
use new media to exchange information with strong ties, including close friends, than weak ties,
including acquaintances and casual contacts.
Some people may engage in social interaction with others by sharing music files (Bakker,
2004; Chiang & Assane, 2008; Evangelista, 2005; Madden & Rainie, 2005; Rainie, Madden,
Hess, & Mudd, 2004; Rose, 2006). For example, researchers have found that some people shared
music files with others via e-mail, instant messaging services, peer to peer online networks, or by
borrowing each other’s MP3 player (Madden & Rainie, 2005; Rainie et al., 2004). Also, some
people used their MP3 player to share files, in person, with others (Evangelista, 2005; Rose,
2006).
Hall (2005) noted that people’s use of music to interact socially with others “may be
increasing as music storage formats switch to digital, allowing audiences to share music over the
Internet” (p. 393). Bakker (2004) noted that most online file-sharing involves trading music files
45
with others. Bull (University of Sussex, 2004, Online) suggested that sharing digital music files
with other iPod users is similar to people’s use of mobile phones to exchange sounds and
pictures and this may help to create a social community of iPod users.
Based on the above discussion, people’s time spent with others, participation in social
activities, post-listening discussion of music, and music file-sharing are important types of social
interaction to consider in my study of college students’ MP3-player-music listening. Specifically,
differences among college students’ loneliness, motives to listen to MP3-player music, time
spent listening, and activity with songs (i.e., attention and elaboration) may account for
differences in their time spent interacting socially with others, participation in social activities,
discussion of music, and music file-sharing. Unfortunately, researchers have not examined the
relationships among these variables and, thus, the influences of MP3-player-music listeners’
social interaction are unclear. Therefore, researchers need to examine college students’ time
spent socializing with others, participation in social activities, post-listening discussion of music,
and music file-sharing as potential outcomes of their background characteristics, motives to
listen to MP3-player music, time spent listening, and activity with MP3-player music.
Overall, some critics have argued that MP3-player use causes decreased social interaction
(Copeland, 2006; Doherty & Baker, 2005; Harris, 2005; Kadden, 2004; Rose, 2006; Rothman,
2006; Stapp, 2007; White, 2006). According to uses and gratifications theory, people’s
background characteristics, their motives to use media, their media exposure, and their media
activity work in concert to influence such outcomes (Blumler, 1979; Katz et al., 1974; Rubin,
2002). Therefore, researchers need to examine these relationships, as well as bivariate
relationships of interest, and add to our understanding of college students’ MP3-player-music
listening and social interaction.
46
Summary
MP3 players have become popular, especially among college students (Harrigan, 2007;
IFPI, 2006; Madden & Rainie, 2005; Pew Internet & American Life Project, 2005). However,
critics have raised concerns that people may be using MP3 players to withdraw from others,
reducing their social interaction (Copeland, 2006; Kadden, 2004; Harris, 2005; Stapp, 2007;
White, 2006). Researchers have addressed similar concerns about people’s use of television and
the Internet, among other media (e.g., Johnsson-Smaragdi, 1983; Katz & Rice, 2002; Kraut et al.,
2002; Mares & Woodard, 2005). Their findings suggest that although people’s media use has the
potential to increase or decrease their social interaction, individual differences among users
contribute to media effects.
Uses and gratifications is a promising approach for examining the relationship between
college students’ MP3-player use and their social interaction because it focuses on users’
characteristics, motives to use media, and media behaviors as predictive of their outcomes (e.g.,
Armstrong & Rubin, 1989; Charney & Greenberg, 2002 ; Greene & Krcmar, 2005; Lin, 2006;
Papacharissi & Rubin, 2000; Weaver et al., 1996). This focus on individual differences allows
uses and gratifications researchers to predict media effects based on users’ background
characteristics and how they use media, rather than on the types of media they use, alone. In
other words, differences among users’ background characteristics, motives to use media,
exposure to media content, and activity with media content should help explain different
outcomes among users of the same medium. If researchers adopt a uses and gratifications
approach to study MP3-player uses and effects, they should be able to address speculation about
the impact of college students’ MP3-player-music listening on their social interaction, add to our
47
knowledge of the uses and gratifications of music delivery devices, and enlighten future
investigations and policies relevant to college students’ use of MP3 players to listen to music.
Some critics have argued that MP3-player music listeners have decreased social
interaction with others and are lonely as a result (Copeland, 2006; Doherty & Baker, 2005;
Kadden, 2004; Stapp, 2007; White, 2006). However, before assuming that all people who listen
to MP3 players have a deficiency in their social interaction and are lonely, researchers need to
consider individual differences that may explain differences in their social interaction.
Specifically, loneliness is an important background characteristic to consider in my study
because it is related to decreased social interaction (Perse & Rubin, 1990) and may influence the
social interaction of those who listen to MP3-player music. Therefore, researchers need to
examine loneliness, and its relationships with college students’ MP3-player use and social
interaction.
Also, extant literature suggests that college students’ motives to listen to music on an
MP3 player should influence their time spent listening to MP3-player music, activity with MP3player music, and social interaction. A few researchers have identified some reasons that college
students listen use MP3 players, including relaxation/escape, to avoid loneliness, and to reduce
boredom (Albarran et al., 2007; Ferguson et al., 2007). However, scholars have suggested that
there are other motives that should be important reasons for listening to music and for listening
to music on an MP3 player, including social utility, social avoidance, and fashion/status, among
others (Bull, 2000; Christenson, 1994; Kahney, 2004; Roe, 1985; Yaksich, 2007). Researchers
need to examine college students’ motives to listen to MP3-player music further and their
relationships with time spent listening, attention to songs, elaboration on songs, and social
48
interaction to see if differences among college students' motives account for any differences in
their exposure, activity, and social interaction.
Extant literature also suggests that people’s time spent listening to music and activity
with music (i.e., attention to songs and elaboration on songs) should influence their social
interaction (Christenson, 1994; Hansen & Hansen, 1991; Kim & Rubin, 1997; Larson & Kubey,
1983; Lull, 1985; Roe, 1985). Therefore, college students’ time spent listening to music on an
MP3 player and their activity with MP3-player music should influence their social interaction.
Scholars have indicated that spending time socializing with others, participating in social
activities, discussing music after listening, and sharing music files are types of social interaction
that are especially relevant to people’s MP3-player-music listening. It is important that
researchers examine the previously-mentioned types of social interaction to see if they are
influenced by college students’ loneliness, motives to listen to MP3-player music, time spent
listening to MP3-player music, and activity with MP3-player music. Therefore, in the following
section, I will develop research questions and hypotheses to test the above-mentioned
relationships.
Research Questions and Hypotheses
Only a few researchers have examined college students’ motives for using MP3 players
(Albarran et al., 2007; Ferguson et al., 2007). Ferguson et al. found five reasons why college
students listened to music on MP3 players, including to relax/escape, for stimulation, for
entertainment, to avoid loneliness, and to reduce boredom. Albarran et al. found similar reasons
for college students’ MP3-player use. As referenced above, there may be additional reasons why
college students listen to music on an MP3 player. For example, one of the central questions
regarding people’s use of MP3 players is whether they use them primarily to avoid or to foster
49
social interaction with others. Some critics have raised concern about the former scenario (Bull,
2005, 2006; Chen, 1998; Diva, 2004) and some scholars and reporters have described accounts
regarding the latter (Christenson & Peterson, 1988; Hall, 2005; Hansen & Hansen, 2000;
Houghton-Larsen, 1982; McClung et al., 2007; Roe, 1985; Tarrant et al., 2000).
Unfortunately, researchers have not examined empirically social avoidance or social
utility as motives to listen to music on an MP3 player. Thus, the degree to which college students
listen to music on an MP3 player to avoid or to bolster social interaction is not known. In
addition to social avoidance and social utility, researchers have identified, but have not tested
empirically, atmosphere/mood control, lyrical content, or fashion/status as motives for listening
to music on an MP3 player, although they should be relevant (Christenson, 1994; Gantz et al.,
1978; Kahney, 2004; Levy, 2004; Lewis, 1981; Roe, 1985; Wheeler, 2006; Yaksich, 2007).
Researchers need to examine further the above-mentioned motives, including the five that
Ferguson et al. (2007) have identified (i.e., relaxation/escape, stimulation, entertainment,
loneliness, and boredom) because they may influence college students’ social interaction
(Albarran et al., 2007; Ferguson, personal communication, March 12, 2008). Therefore, the
following research question was proposed:
RQ1: What are college students’ motives for listening to music on an MP3 player?
According to uses and gratifications theory, people’s motives to use media influence their
exposure to media content, activity with media content, and media effects (Katz et al., 1974;
Lull, 1980; Roe, 1985; Rubin, 2002). Researchers have found that certain motives to use media
are related to exposure to media content (Charney & Greenberg, 2002; Ferguson et al., 2007;
Haridakis, 2006; Johnson & Kaye, 2003; Leung, 2007; McClung et al., 2007; Palmgreen &
Rayburn, 1982; Perse & Ferguson, 1993; Rubin, 1983, 1984; Rubin & Rubin, 1982; Sherry et al.,
50
2006). For example, Haridakis found that people who watched televised violence to pass time
and for arousal tended to spend a lot of time watching television. Also, McClung et al. found that
people who listened to the radio to escape and for social utility tended to spend a lot of time
listening to the radio. Furthermore, Ferguson et al. found that college students’ motives to listen
to music on an MP3 player were related to their time spent listening to music. Specifically, they
found that college students spent a lot of time listening to music on an iPod when they wanted to
relax or escape and for stimulation. Ferguson et al. suggested that researchers should examine the
relationships among additional motives to use MP3 players and consumers’ MP3-player
exposure. Therefore, the following research question was proposed:
RQ2: How do college students’ motives to listen to music on an MP3 player relate to
their time spent listening to music on an MP3 player?
Also, researchers have found that people’s motives to use media influence their activity
with media content (Hawkins et al., 2001; Perse, 1990; Rubin & Perse, 1987a, 1987b). For
example, Rubin and Perse (1987a) found that college students who watched soap operas for
exciting entertainment tended to pay close attention to the content and characters of the
programs. However, Perse found that adults who watched television to fill empty time tended to
engage in distractions from viewing (i.e., lessened attention). Also, Rubin and Perse (1987a)
found that college students who watched soap operas to pass time tended to engage in
distractions from the programs. Furthermore, Hawkins et al. found that people who watched
drama and sitcom television programs to manage their mood tended to think hard about the
programs and draw connections to their own lives.
In accordance with uses and gratifications theory and the above findings, college
students’ MP3-player motives should influence their MP3-player activities. However,
51
researchers have not fully examined college students’ motives to listen to music on an MP3
player or the relationship between these motives and MP3-player activity (Albarran et al., 2007;
Ferguson et al., 2007). As a result, we do not know which motives are related to college
students’ activity with MP3-player music. Thus, the following research question was proposed:
RQ3: How do college students’ motives to listen to music on an MP3 player relate to
their (a) attention to songs and (b) elaboration on songs?
Based on uses and gratifications theory, college students’ motives to use MP3 players
should influence their social interaction. For example, Hampton and Gupta (2008) observed and
interviewed some people who used laptop computers in coffee houses that provided free wireless
Internet access. They found that people who used their laptops in the coffee houses to get away
from co-workers, partners, or children tended not to interact much with other patrons or the
employees. However, people who used a laptop in a coffee house to hang out with others tended
to engage in social interactions. They “used their laptops as a premise to enter and engage in the
‘social hubbub’ of the space” (Hampton & Gupta, 2008, p. 842). It makes sense that if college
students listen to music on an MP3 player to avoid interaction with others, they would spend less
time socializing with others, participate in social activities less frequently, discuss music with
others after listening less frequently, and share music files less frequently than would those who
listen to an MP3 player to bolster their interaction with others. Researchers have identified the
above-mentioned motives, social avoidance and social utility, among others, as motives to use
MP3 players. Unfortunately, researchers have not tested empirically all of these identified
motives, including social utility and social avoidance, or their relationships with college
students’ social interaction. Therefore, the following research question was proposed:
52
RQ4: How do college students’ motives to listen to music on an MP3 player relate to
their (a) time spent socializing with others, (b) frequency of participation in social
activities, (c) frequency of post-listening discussion of music, and (d) frequency of music
file-sharing?
Some critics have raised concern that people who use MP3 players may feel lonely as a
result of their use (Doherty & Baker, 2005; Ferguson et al., 2007; Kadden, 2004; Rothman,
2006). Researchers need to examine differences in college students’ loneliness before assuming
that everyone who listens to MP3-player music is unhappy with their personal relationships.
According to uses and gratifications theory, people’s background characteristics influence their
motives to use media, media consumption, and outcomes (Katz et al., 1974; Rubin, 1993; Rubin,
2002; Rubin & Windahl, 1986). Therefore, differences in college students’ loneliness may
influence their motives to listen to MP3-player music, time spent listening, attention to songs,
elaboration on songs, and social interaction.
First, researchers need to examine the relationships among college students’ loneliness,
and their motives to listen to music on an MP3 player because critics have voiced concern that
people who use MP3 players are lonely (Doherty & Baker, 2005; Ferguson et al., 2007; Kadden,
2004; Rothman, 2006). We know that loneliness is related to specific motives to use media
(Austin, 1984; Finn & Gorr, 1988; Kraut et al., 1998; Leung, 2001; Moore & Schultz, 1983;
Perloff & Krevans, 1987; Perse & Rubin, 1990; Pornsakulvanich et al., 2008). As previously
discussed, people who perceive their relationships as unsatisfactory may use media to fulfill their
perceived social inadequacies (Finn & Gorr, 1988; Perloff & Krevans, 1987; Perse & Rubin,
1990). Indeed, researchers have found that people who are lonely tend to consume media content
for a sense of companionship (Finn & Gorr, 1988; Perloff & Krevans, 1987).
53
However, college students’ motives for listening to music on an MP3 player are not fully
known and researchers have not examined the influence of college students’ loneliness on their
reasons for listening to music on an MP3 player. Ferguson et al. (2007) noted that researchers
need to study the relationships between people’s background characteristics and their motives to
use MP3 players. This is necessary because differences in college students’ loneliness may help
explain potential differences among their motives to listen to MP3-player music. Therefore, the
following research question was proposed:
RQ5: How does college students’ loneliness relate to their motives to listen to music on
an MP3 player?
In addition to motives to listen to MP3-player music, there is some evidence that people
who are lonely tend to use media more than do less-lonely people (Caplan, 2003; Moore &
Schultz, 1983; Perloff et al., 1983; Rubin et al., 1985; Whitty & McLaughlin, 2007). For
example, lonely people tend to spend a lot of time watching television and listening to music
(Moore & Schultz, 1983; Perloff et al., 1983; Whitty & McLaughlin, 2007). It follows, then, that
college students’ degree of loneliness should influence their time spent listening to MP3-player
music as well. Specifically, based on the above discussion, college students who tend to be
lonely should be likely to spend more time listening to music on an MP3 player than would those
who are less lonely. Therefore, the following hypothesis was proposed:
H1: Higher levels of loneliness will be related to more time spent listening to music on an
MP3 player.
In addition to some critics’ concerns, mentioned above, loneliness is a particularly
important background characteristic to consider in my study because of its negative influence on
people’s social interactions. For example, researchers have found that lonely people tend to
54
avoid social engagements, social activities, intimate self-disclosure, and face-to-face interactions
with other people (Caplan, 2003; Morahan-Martin & Schumacher, 2003; Perse & Rubin, 1990;
Rubin et al., 1985; Solano et al., 1982). For example, Solano et al. found that lonely females
were unlikely to disclose information to others about their attitudes, tastes, work/study, and
personality. Also, Caplan found that people who felt lonely tended not to interact with others
face-to-face. It follows, from above, that lonely college students should not tend to spend a lot of
time socializing with others, participate in social activities, discuss music with others after
listening, or share music files. Therefore, the following hypothesis was proposed:
H2: Higher levels of loneliness will be related to (a) less time spent socializing with
others, (b) less frequent participation in social activities, (c) less frequent
post-listening discussion of music, and (d) less frequent music file-sharing.
Critics of MP3 players fear that most users are spending more time listening to their MP3
player than they are interacting with other people (Copeland, 2006; Doherty & Baker, 2005;
White, 2006). Researchers have refuted similar concerns that the use of certain media lessens
social interaction (Flanders, 1982; Humphreys, 2005; Johnsson-Smaragdi, 1983; Katz & Rice,
2002; Roberts, Foehr, & Rideout, 2005; Walker and Bellamy, 1991). Their findings suggest that
people’s time spent using media does not tend to reduce their social interaction with others and,
in some instances, relates to increased social interaction (Bickham & Rich, 2006; Jeffres et al.,
2003; Johnsson-Smaragdi, 1983; Katz & Rice, 2002; Kraut et al., 2002; Mares & Woodard,
2005).
Researchers have found that people tend to listen to music, especially MP3-player music,
by themselves, not interacting with others (Bull, 2005; Christenson, 1994; Ferguson et al., 2007;
Larson & Kubey, 1983; Lull, 1985). However, people’s time spent listening to music alone does
55
not necessarily displace their time spent interacting with others. Similar to the findings of
Internet users mentioned above, there are reports that some people’s time spent listening to
music and activity with music, including MP3-player music, may facilitate social interaction
(Christenson & Peterson, 1988; Doherty & Baker, 2005; Evangelista, 2005; Hansen & Hansen,
2000; Roe, 1985; Rose, 2006; Wheeler, 2006). Unfortunately, researchers have not examined the
relationships between college students’ time spent listening to MP3-player music and social
interaction. Thus, the following research question was proposed:
RQ6: How does college students’ time spent listening to music on an MP3 player relate
to their (a) time spent socializing with others, (b) frequency of participation in social
activities, (c) frequency of post-listening discussion of music, and (d) frequency of music
file-sharing?
In addition to people’s time spent listening to music on MP3 players, researchers need to
examine college students’ activity (i.e., attention to songs and elaboration on songs) and the
relationship between their activity and social interaction. A highly attentive and involved
audience should be likely to experience greater media effects than would a less active audience
(Blumler, 1979; Godlewski & Perse, 2007; Kim & Rubin, 1997; Levy, 1987). For example,
Godlewski and Perse found that higher levels of attention and elaboration during television
viewing related positively to more frequent discussion with others about the content. People who
pay close attention to songs and think hard about songs may have an increased potential to
discuss the music with others (Hansen & Hansen, 1991; Roe, 1985), attend musical concerts
(Dixon, 1979, 1980), and share-files with others (Ouellet, 2007). Therefore, based on the above
discussion, a highly active listener should be more likely to interact socially with others than
would someone who does not pay a lot of attention to songs or think much about songs during
56
listening. In an effort to examine the previously stated relationships, the following hypotheses
were proposed:
H3: Higher levels of attention to songs will be related to (a) more time spent socializing
with others, (b) more frequent participation in social activities, (c) more frequent postlistening discussion of music, and (d) more frequent music file-sharing.
H4: Higher levels of elaboration on songs will be related to (a) more time spent
socializing with others, (b) more frequent participation in social activities, (c) more
frequent post-listening discussion of music, and (d) more frequent music file-sharing.
In accordance with uses and gratifications theory, college students’ loneliness, motives to
listen to music on an MP3 player, time spent listening to MP3-player music, and activity with
MP3-player music should work in concert to influence their social interaction. Understanding the
combined influence of the antecedents on social interaction should help researchers explain
consumers’ MP3-player music consumption and effects with more depth than bivariate
relationships alone. Therefore, the following research question was proposed:
RQ7: How do college students’ loneliness, motives to listen to music on an MP3 player,
time spent listening to MP3-player music, and activity with MP3-player music (i.e.,
attention to songs and elaboration on songs) predict their (a) time spent socializing with
others, (b) frequency of participation in social activities, (c) frequency of post-listening
discussion of music, and (d) frequency of music file-sharing?
As previously discussed, researchers have found that high levels of loneliness are related
to decreased social interaction (Caplan, 2003; Morahan-Martin & Schumacher, 2003; Solano et
al., 1982). Accordingly, I had hypothesized that higher levels of loneliness will be related to
college students’ decreased social interaction. However, this expected relationship may
57
overshadow the influence of other antecedent variables on college students’ social interaction.
Thus, we need to examine the impact of college students’ motives to listen to MP3-player music,
time spent listening to MP3-player music, and activity with MP3-player music on their social
interaction, regardless of their loneliness. Therefore, the following research question was
proposed:
RQ8: How do college students’ motives to listen to music on an MP3 player, time spent
listening to MP3-player music, and activity with MP3-player music (i.e., attention to
songs and elaboration on songs) predict their (a) time spent socializing with others, (b)
frequency of participation in social activities, (c) frequency of post-listening discussion of
music, and (d) frequency of music file-sharing?
58
Chapter II
METHODOLOGY
One goal of this study was to examine the influence of college students’ MP3-player-use
motives on their social interaction. Another goal was to examine the influence of loneliness,
exposure to MP3-player music, and activity with MP3-player music, along with MP3-player-use
motives, on students’ interaction with others. Furthermore, this study sought to control
statistically for variations among college students’ demographic information. Therefore, an
online survey was created and administered to measure the following variables: (a)
demographics, including age, gender, grade level, household income, number of roommates, and
race/ethnicity (see Appendix B); (b) loneliness (see Appendix C); (c) MP3-player-musiclistening motives (see Appendix D); (d) time spent listening to MP3-player music (see Appendix
E); (e) audience activity, including attention to songs (see Appendix F) and elaboration on songs
(see Appendix G); and (f) social interaction, including time spent socializing with others (see
Appendix H), frequency of participation in social activities (see Appendix I), post-listening
discussion of music (see Appendix J), and frequency of music file-sharing (see Appendix K).
Typically, uses and gratifications researchers employ a survey methodology to collect
such data. Surveys are an effective and economical way to collect data from a large number of
participants. Furthermore, online surveys offer participants a convenient way to participate in
research studies like mine. Therefore, I used an online survey that was created and administered
with Qualtrics, an online survey management tool.
Sampling Procedure
The sample of the current study consisted of undergraduate students at Kent State
University who were 18 years of age or older, used a portable MP3 player, and were enrolled in
59
an introductory communication course (N = 479). Students received research credit for
participating in the study. College-aged students were an ideal sample for my study because they
are among those who are most likely to own and use an MP3 player (Arensman, 2005; Ferguson,
Greer, & Reardon, 2007; Harrigan, 2007; IFPI, 2007, 2008; Madden & Rainie, 2005; Pew
Internet & American Life Project, 2005; Rose & Lenski, 2008; Wheeler, 2006). Furthermore,
college students are more likely to own and use an MP3 player than would their peers in the
general population (Albarran et al., 2007; Ferguson et al., 2007).
Reported age ranged from 18 to 87 years old (M = 20.09, SD = 4.68), with 50 participants
not reporting their age. There were more females (n = 301) than there were males (n = 178). The
sample consisted of 291 freshmen, 114 sophomores, 48 juniors, and 25 seniors, with one
participant not reporting her grade level. Participants reported their annual household income as
less than $30,000 (n = 140), between $30,000 and $50,000 (n = 84), between $50,000 and
$75,000 (n = 102), or more than $75,000 (n = 152), with one participant not reporting her
household income. The reported number of roommates ranged from 0 to 30 (M = 3.14, SD =
1.91), with six participants not reporting their number of roommates. Most participants reported
their race/ethnicity as Caucasian (n = 414), followed by African-American (n = 25), other (n =
15), Asian or Pacific Islander (n = 9), Hispanic (n = 7), Middle Eastern (n = 4), and American
Indian or Alaskan native (n = 1). Four participants did not report their race/ethnicity. The
reported race/ethnicity of participants in this sample was similar to the reported race/ethnicity of
the 19,918 undergraduate students at Kent State University: White (n = 16,187); African
American (n = 1,772); Unknown (n = 642); International (n = 513); Hispanic (n = 388); Asian (n
= 316); and American Indian (n = 100; Student Body Profile, 2010).
60
Measures
Participants were provided with an online consent form explaining the nature of the study
and the voluntary nature of their participation. Students who acknowledged their consent to
participate in the study were allowed to continue to the online survey. First, participants were
prompted to complete the MP3 Motive Scale. Second, participants were asked to report their
time spent listening to MP3-player music. Third, participants were asked to complete a
questionnaire about their activities with MP3-player music (i.e., their attention to songs and their
elaboration on songs). Fourth, participants were directed to complete social interaction measures
(i.e., time spent socializing with others, frequency of participation in social activities, frequency
of post-listening discussion of music, and frequency of music file-sharing). Fifth, participants
were asked to fill out a measure of their loneliness. Sixth, and lastly, participants were instructed
to submit demographic information (age, gender, grade level, annual household income, number
of roommates, and race/ethnicity).
Loneliness
Loneliness was measured with the Revised University of California, Los Angeles
(UCLA) Loneliness Scale (Russell et al., 1980; Appendix C). The Revised UCLA Loneliness
Scale was composed of 20 statements that signify satisfaction or dissatisfaction with social
relationships, proportionately. For example, some of the statements included I do not feel alone, I
lack companionship, and I am unhappy being so withdrawn. Although Russell et al. asked
respondents to indicate how often they felt the way described in these statements on a 4-point
Likert-type scale, ranging from 1 (never) to 4 (often), some uses and gratifications researchers
have used a 5-point Likert-type scale, ranging from 1 (never) to 5 (always), to measure
loneliness (Perse & Rubin, 1990; Rubin et al., 1985). A 5-point Likert-type scale, ranging from 1
61
(never) to 5 (always), was used to stay consistent with other uses and gratifications research and
my other measures. Positively-worded items were reverse-coded. Higher scores indicate higher
levels or frequencies of loneliness (i.e., chronic loneliness) and lower scores indicate infrequent
loneliness (i.e., situational loneliness or less loneliness; Canary & Spitzberg, 1993).
Initially, Russell, Peplau, and Ferguson (1978) developed the UCLA Loneliness Scale to
improve upon the reliability and validity of extant self-report measures. Then, Russell et al.
(1980) revised the UCLA Loneliness Scale further to address concerns of negatively worded
items, internal validity, and social desirability. Researchers have found support for the validity of
the Revised UCLA Loneliness Scale (Bell & Daly, 1985; Russell et al., 1980; Solano & Koester,
1989). For example, Solano and Koester found that people who scored highly on the Revised
UCLA Loneliness Scale tended to be lonely in their social relationships with family members (r
= .14, p < .01), friends (r = .21, p < .001), romantic partners (r = .15, p < .01), and community
members (r = .24, p < .001).
Furthermore, Russell et al. (1980) found that high scores on the Revised UCLA
Loneliness Scale correlated negatively with high scores on extraversion (r = -.46, p < .001),
affiliative tendency (r = -.45, p < .001), and assertiveness (r = -.34, p < .001). Bell and Daly
(1985) found that loneliness correlated negatively with extraversion (r = -.47, p < .001) and
social assertiveness (r = -.39, p < .001). The above-mentioned relationships suggest that people
who were lonely were less likely to be outgoing, affiliative, and assertive than were less-lonely
people. Also, the previously discussed findings suggest that the Revised UCLA Loneliness Scale
has discriminant validity because they indicate that loneliness is distinct from dissimilar
concepts.
62
Researchers have found that the Revised UCLA Loneliness Scale is a reliable measure of
a person’s loneliness. Typically, researchers have reported Cronbach alpha reliability estimates
for this scale ranging from .86 to .94 (Anderson & Martin, 1995; Bell & Daly, 1985; Canary &
Spitzberg, 1993; Caplan, 2003; Finn & Gorr, 1988; Miczo, 2004; Perse & Rubin, 1990; Prisbell,
1988; Rubin et al., 1985; Wei & Lo, 2006). Responses to all 20 items were summed and
averaged to create the loneliness index (M = 2.04, SD = 0.62, α = .93). Table 1 provides item
means and standard deviations for each item.
MP3-Player-Use Motives
Ferguson et al.’s (2007) MP3 Motive Scale was adapted to measure college students’
motives for listening to music on a portable MP3 player (see Appendix D). Participants were
asked to rate various reasons for listening to MP3-player music. Response categories ranged
from 1 (strongly disagree) to 5 (strongly agree). Therefore, higher scores on items indicate that a
respondent agreed that he or she listens to music on an MP3 player for the reason represented by
the relevant item. My adapted version of Ferguson et al.’s MP3 Motive Scale included 21
statements that represented five motives: (a) relaxation/escape, (b) stimulation, (c) entertainment,
(d) loneliness, and (e) boredom.
Ferguson et al. (2007) found that the MP3 Motive Scale accounted for 66.5% of the
variance in college students’ MP3-player use. They reported moderate to moderately high alpha
reliabilities for each factor, representing a specific motive: (a) relaxation/escape (α = .85), (b)
stimulation (α = .82), (c) entertainment (α = .72), (d) loneliness (α = .81), and (e) boredom (α =
.67). Unfortunately, at the time of this study, researchers had not replicated the MP3 Motive
Scale to establish reliability estimates further.
63
Table 1
Revised UCLA Loneliness Scale: Item Means and Standard Deviations
Items
M
SD
I feel in tune with the people around me.a
2.37
0.78
I lack companionship
2.15
0.91
There is no one I can turn to.
1.66
0.85
I do not feel alone.a
2.37
1.05
I feel part of a group of friends.a
1.95
0.96
I have a lot in common with the people around me.a
2.16
0.91
I am no longer close to anyone.
1.73
0.97
My interests and ideas are not shared by those around me.
2.23
0.97
I am an outgoing person.a
2.16
0.97
There are people I feel close to.a
1.63
0.85
I feel left out.
2.22
0.88
My social relationships are superficial.
2.21
0.96
No one really knows me well.
2.14
1.03
I feel isolated from others.
1.98
0.86
I can find companionship when I want it.a
2.20
0.96
There are people who really understand me.a
2.00
0.96
I am unhappy being so withdrawn.
2.11
1.05
People are around me but not with me.
2.27
0.97
There are people I can talk to.a
1.62
0.85
There are people I can turn to.a
1.60
0.88
Note. N = 479
a
items were reverse coded for analysis.
64
In addition to the motives from Ferguson et al.’s (2007) MP3 Motive Scale, 19 items that
represent motives other researchers have identified as important for listening to music and for
using MP3 players were included (Bull, 2000, 2005; McClung et al., 2007; Roe, 1985; Wei &
Lo, 2006). The motives that were added to Ferguson et al.’s scale included (a) social utility, (b)
social avoidance, (c) atmosphere creation/mood control, (d) fashion/status, and (e) attention to
lyrics.
First, four social utility items from the McClung et al. (2007) Radio Listening
Gratifications Scale were adapted to measure college students’ motive to listen to music on an
MP3 player for social utility. These items represent listening to the radio to hear songs
recommended by friends, to talk with friends about things they hear, and to learn things about
others. McClung et al. found that these items were a reliable measure of people’s motive to listen
to the radio to bolster their social interaction (α = .79). Although McClung et al. developed the
Radio Listening Gratifications Scale to measure overall radio listening, they noted that most
respondents indicated that, primarily, they listened to music on the radio.
Second, in addition to listening to MP3-player music for social utility, some people listen
to music on their MP3 players to avoid social interaction (Bull, 2005, 2006; Diva, 2004). For
example, some of Bull’s (2005) interviewees stated that they listened to music on an MP3 player
to isolate themselves from others and to avoid conversations. Unfortunately, at the time of this
study, an adequate measure of people’s motive to use media to avoid social interaction did not
exist. Therefore, an item from the Rubin (1983) Television Viewing Motives Scale that seems to
represent a motive to avoid others (i.e., so I can get away from the rest of the family or others)
was adapted. Initially, Rubin included this item as an indicator of someone’s motive to escape, in
65
general. However, on its face, the item seemed to be particularly relevant to college students’ use
of media for social avoidance, specifically.
Also, five statements from Bull’s (2000, 2005) interviewees that seemed to represent
listening to a portable music device to avoid social interaction were adapted. Specifically,
college students were asked whether they listened to music on their portable MP3 player (a) so
they did not have to interact with others, (b) because it was an excuse to avoid talking to
somebody, (c) to avoid social interactions, (d) to isolate themselves from other people, and (e) so
they did not have to engage in conversations. Although Bull (2000, 2005) did not create a scale
based on these statements, they seemed to represent his and others’ reports of people’s use of
MP3 players to avoid others (Chen, 1998; Diva, 2004; Kadden, 2004; Rothman, 2006; White,
2006).
Third, researchers have found that atmosphere creation/mood control and attention to
lyrics are important reasons for listening to music (Christenson, 1994; Gantz et al., 1978; Lewis,
1981; Roe, 1985). These motives should be important reasons for college students’ MP3-playermusic listening as well. Therefore, atmosphere creation/mood control and attention to lyrics
items from the Roe (1985) Motivations for Listening Scale were included to measure college
students’ motives for listening to music on an MP3 player to create an atmosphere or to control a
mood and to pay attention to the lyrical content of songs. Roe identified three items that
represented adolescents’ motives to listen to music to create an atmosphere or control their
mood. Also, he identified two items that represented people’s motives to listen to music for the
lyrical content. I included all five of the items mentioned above to measure the degree to which
college students listened to music on their MP3 player to create an atmosphere or control their
mood and to pay attention to song lyrics.
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Fourth, some scholars have suggested that iPods are popular MP3 players because they
are a symbol of fashion and status (Kahney, 2004; Levy, 2004; Wheeler, 2006; Yaksich, 2007).
For example, Yaksich reported that some college students used iPods because they are trendy.
Furthermore, researchers have found that people’s use of media for fashion-status is especially
important among newer portable media such as cell phones (DeBaillon & Rockwell, 2005;
Leung, 2007) and electronic pagers (Leung & Wei, 1998). It follows, from above, that some
college students use portable MP3 players to be fashionable and to gain status.
Therefore, based on the above discussion, the four items from the Wei and Lo (2006)
fashion-status motive for using cell phones were adapted to measure that motive relevant to
MP3-player use. Wei and Lo found that fashion-status included using media to look fashionable,
cool, stylish, and to avoid looking old-fashioned. Participants were asked if these reasons were
like their reasons for listening to music on a portable MP3 player. Wei and Lo found that the
above-mentioned items constituted a reliable measure (α = .91) of people’s use of cell phones for
fashion-status.
A principal component factor analysis with varimax rotation was conducted on the 40item MP3-motive measure to reveal the underlying motive structure, as in previous uses and
gratification research (e.g., Ferguson et al., 2007; Leung & Wei, 2000; Song, LaRose, Eastin, &
Lin, 2004; Sun et al., 2008). Only factors that had an eigenvalue of 1.0 or more and at least two
items that met a .60-.40 loading criterion as a rough guide qualified for inclusion. After an initial
factor analysis, 8 of the 40 items did not meet the established criteria for inclusion. A second
principal component factor analysis with varimax rotation was conducted on the remaining 32
items. Seven factors were identified, explaining 62.60% of the variance, with only three items
failing to load based on the above-mentioned criteria. A third principal component factor
67
analysis with varimax rotation was conducted on the remaining 29 items to reveal the final
underlying motive structure. All of the 29 items met the inclusion criteria mentioned above.
Based on the 40-item MP3-player motive measure tested in this study, the sample size of this
study exceeded a minimum requirement of 5 participants per item for an exploratory factor
analysis (Bryant & Yarnold, 2000).
Seven MP3-player-use-motive factors, explaining 65.54% of the variance, after rotation,
were identified. The seven motive factors were (a) social avoidance, (b) fashion/status, (c) social
utility, (d) learning, (e) entertainment/relaxation, (f) companionship, and (g) boredom alleviation.
Results of the factor analysis are reported in Table 2. Responses that loaded on each of these
factors were summed and averaged to create indexes of each MP3-player-use motive. See Table
3 for item means and standard deviations.
Factor 1, social avoidance motivation, included five of the original six social avoidance
items (“So I don’t have to interact with others,” “To avoid social interaction,” “To avoid
conversations,” “Because it’s an excuse not to talk to somebody,” and “To isolate myself from
others”) (M = 2.31, SD = 0.94, α = .91).
Factor 2, fashion/status motivation, included all four of the original fashion/status items
(“To look fashionable,” “To look stylish,” “To look cool,” and “To avoid looking oldfashioned”) and one loneliness item (“So I can be like my friends and family who use MP3
players”) (M = 1.89, SD = 0.75, α = .88).
Factor 3, social utility motivation, included three of the original social utility items (“To
hear songs that my friends tell me about,” “Because my friends talk about the things they hear,”
and “Because I talk with friends about things I hear,”) and two stimulation items (“So I can try
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Table 2
Factor Loadings for the MP3-Player-Motive Items
MP3-Player-Use Motives
Motive Items
SOCA
FASH
SOCU
LEAR ENTR COMP BORE
So I don’t have to interact
with others
.87
.14
.00
.02
-.10
.09
.08
To avoid social interaction
.86
.17
-.01
.04
-.01
.08
.07
To avoid conversations
.86
.14
.03
.09
.01
.09
.01
Because it’s an excuse not
to talk to somebody
.83
.13
.02
-.02
.00
.10
.09
To isolate myself from
others
.78
.07
.05
.13
-.04
.09
.08
To look fashionable
.12
.88
.10
-.01
-.01
.09
.05
To look stylish
.12
.87
.12
-.01
-.03
.03
-.00
To look cool
.18
.83
.14
.08
-.00
.01
.02
To avoid looking oldfashioned
.15
.75
.05
.16
-.12
.06
-.00
So I can be like my friends
and family who use MP3
players.
.11
.60
.19
.22
-.05
-.02
.16
.07
.07
.79
.04
.07
.10
.14
Social Avoidance
Fashion/Status
Social Utility
To hear songs that my
friends tell me about
69
MP3-Player-Use Motives
Motive Items
SOCA
FASH
SOCU
LEAR ENTR COMP BORE
Because my friends talk
about the things they hear
.01
.12
.78
.14
-.01
.01
.16
Because I talk with friends
about things I hear
-.08
.13
.76
.13
.10
.26
.01
So I can try out media
content that my friends tell
me about
.07
.13
.72
.16
.10
-.04
.14
So I can talk with others
about what I find
-.01
.19
.68
.32
.08
.11
.03
To learn things about
myself and others
.07
.11
.31
.78
.11
.15
-.07
Because it helps me learn
things about myself and
others
.10
.09
.30
.77
.10
.20
-.01
Because it helps me learn
what could happen to me
.07
.19
.14
.72
-.08
.20
.09
Because it’s enjoyable
-.05
-.04
.08
.02
.75
.10
.03
Because it entertains me
-.08
-.03
.10
-.17
.74
.05
.16
Because it amuses me
.04
-.03
.07
.19
.69
-.24
.12
Because it relaxes me
-.04
-.12
.01
.11
.60
.28
.20
Learning
Entertainment/Relaxation
70
MP3-Player-Use Motives
Motive Items
SOCA
FASH
SOCU
LEAR ENTR COMP BORE
Because it makes me feel
less lonely
.24
.21
-.02
.26
-.12
.65
.28
So I won’t have to feel
alone
.28
.23
-.01
.29
-.09
.61
.28
Because I want to listen to
the words
.12
-.02
.29
.05
.21
.61
-.21
Because the words express
how I am feeling
.11
-.05
.26
.27
.19
.60
-.05
When I have nothing
better to do
.09
.04
.07
.13
.24
-.02
.69
Just because it is available
.15
.05
.26
.01
.04
-.03
.65
Because it gives me
something to occupy my
time
.04
.07
.14
-.18
.30
.19
.63
Eigenvalue
6.80
3.76
2.67
2.09
1.52
1.14
1.03
Variance Explained
23.45
12.96
9.21
7.19
5.24
3.94
3.56
Cronbach Alpha
0.91
0.88
0.85
0.82
0.70
0.70
0.61
M
2.31
1.89
3.03
2.49
4.27
3.17
3.54
SD
0.94
0.75
0.86
0.90
0.53
0.76
0.73
Companionship
Boredom Alleviation
Note. N = 479. SOCA = Social Avoidance, FASH = Fashion/Status, SOCU = Social Utility,
LEAR = Learning, ENTR = Entertainment/Relaxation, COMP = Companionship, BORE =
Boredom Alleviation
71
Table 3
MP3-Player Motive and Item Means and Standard Deviations
Motives/Items
M
SD
2.31
0.94
So I don’t have to interact with others
2.30
1.10
To avoid social interaction
2.23
1.08
To avoid conversations
2.32
1.07
Because it’s an excuse not to talk to somebody
2.41
1.12
To isolate myself from others
2.29
1.11
1.89
0.75
To look fashionable
1.94
0.94
To look stylish
1.97
0.96
To look cool
1.86
0.90
To avoid looking old-fashioned
1.82
0.88
So I can be like my friends and family who use MP3 players.
1.85
0.92
3.03
0.86
To hear songs that my friends tell me about
3.44
1.04
Because my friends talk about the things they hear
2.77
1.09
Because I talk with friends about things I hear
3.05
1.08
So I can try out media content that my friends tell me about
3.03
1.11
So I can talk with others about what I find
2.84
1.09
Social Avoidance
Fashion/Status
Social Utility
72
Motives/Items
M
SD
2.49
0.90
To learn things about myself and others
2.61
1.08
Because it helps me learn things about myself and others
2.72
1.08
Because it helps me learn what could happen to me
2.13
0.98
4.27
0.53
Because it’s enjoyable
4.47
0.69
Because it entertains me
4.40
0.65
Because it amuses me
3.92
0.85
Because it relaxes me
4.31
0.71
3.17
0.76
Because it makes me feel less lonely
2.61
1.16
So I won’t have to feel alone
2.53
1.12
Because I want to listen to the words
3.82
0.86
Because the words express how I am feeling
3.70
1.05
3.54
0.73
When I have nothing better to do
3.51
1.06
Just because it is available
3.29
0.98
Because it gives me something to occupy my time
3.81
0.89
Learning
Entertainment/Relaxation
Companionship
Boredom Alleviation
Note. N = 479
73
out media content that my friends tell me about” and “So I can talk with others about what I
find”) (M = 3.03, SD = 0.86, α = .85).
Factor 4, learning motivation, included one social utility item (“To learn things about
myself and others”) and two stimulation items (“Because it helps me learn things about myself
and others” and “Because it helps me learn what could happen to me”) (M = 2.49, SD = 0.90, α =
.82).Factor 5, entertainment/relaxation motivation, included all three of the original
entertainment items (“Because it’s enjoyable,” “Because it entertains me,” and “Because it
amuses me”) and one relaxation/escape item (“Because it relaxes me”) (M = 4.27, SD = 0.53, α =
.70).
Factor 6, companionship motivation, included two loneliness items (“Because it makes
me feel less lonely” and “So I won’t have to feel alone”) and all two of the original attention to
lyrics items (“Because I want to listen to the words” and “Because the words express how I am
feeling”) (M = 3.17, SD = 0.76, α = .70).
Factor 7, boredom alleviation motivation, included all three of the original boredom items
(“When I have nothing better to do,” “Just because it is available,” and “Because it gives me
something to occupy my time”) (M = 3.54, SD = 0.73, α = .61).
Time Spent Listening to Music
Lin’s (2006) Listening Time Index was adapted to measure the amount of time college
students spend listening to music on an MP3 player by themselves because this study focused on
the time they spend listening alone (Appendix E). Overall, 474 participants reported their time
spent listening to music on an MP3 player. In accordance with Lin’s (2006) procedure,
respondents’ average weekday and weekend listening times were summed, “representing a 7-day
listening total” (p. 150) and, then, the total was averaged (i.e., divided by 7) to produce an
74
estimate of the time they spend listening to MP3-player music by themselves on an average day
(M = 2.90 hours, SD = 2.70).
Audience Activity
Attention to songs. The Rubin, Perse, and Taylor (1988) Viewing Attention Scale was
adapted to measure the degree of attention that college students paid to songs they listened to on
a portable MP3 player (Appendix F). The Viewing Attention Scale originally contained five
statements about viewers’ attention to television programs (e.g., I pay close attention to the
program when I watch television). Perse (1990) adapted the Viewing Attention Scale to include
7 statements (e.g., when I watch television, I try to concentrate on the program and I put a lot of
mental effort into my television viewing). Seven statements were adapted from these scales to
reflect college students’ attention to their MP3-player content. For example, some of the adapted
statements included I pay close attention to the songs when I listen to music on an MP3 player
and when I listen to music on an MP3 player, I try to concentrate on the songs. Respondents
indicated their agreement with each statement on a 5-point Likert-type scale, ranging from 1
(strongly disagree) to 5 (strongly agree). Therefore, high scores indicate that respondents paid
close attention to songs when they listened to music on an MP3 player.
Although Rubin et al. (1988) used their Viewing Attention Scale to measure the degree of
attention that people paid to television programs, the attention concept is relevant to music
listening (Bull, 2000; Chen, 1998; Knobloch & Zillmann, 2002; Roe, 1985) and MP3-player use
(Bull, 2005) as well. For example, Roe found that some Swedish adolescents claimed that paying
attention to song lyrics was important. Therefore, college students’ attention to songs on their
portable MP3 player may be similar, conceptually, to their attention to television programs as
measured by the Viewing Attention Scale.
75
Rubin et al. (1988) found that the Viewing Attention Scale was a moderately reliable
measure of people’s attention to their favorite television programs (α = .77). Also, Perse (1990)
found that her scale measured consumers’ attention to cable television reliably (α = .83). Perse
(1998) used a variation of the previously-mentioned scales to measure viewers’ attention to a
specific television program and found that her scale was highly reliable (α = .90). Respondents’
scores were summed and averaged to represent their overall attention to songs (M = 2.86, SD =
0.55, α = .74). Table 4 provides item means and standard deviations for each item.
Elaboration on songs. Perse’s (1990) Elaboration Scale was adapted to measure the
degree to which college students think about the music they are listening to on their MP3 player
during their exposure (Appendix G). Specifically, four statements from the Elaboration Scale
were adapted to reflect consumers’ elaboration on their MP3-player music. For example, these
adapted statements included when I’m listening to music on an MP3 player, I think about what
the songs mean to me and when I’m listening to music on an MP3 player, I think about the songs
over and over again. Respondents rated their agreement with each statement on a 5-point Likerttype scale, ranging from 1 (strongly disagree) to 5 (strongly agree). Therefore, high scores on
the Elaboration Scale indicate that respondents think a lot about media content during their
consumption.
Perse (1990) found that her Elaboration Scale was a reliable measure of people’s degree
of elaboration on cable television programs (α = .79). Also, Perse (1998) found that this scale
was a reliable measure of viewers’ elaboration on a specific program (α = .83). Furthermore,
Kim and Rubin (1997) found that a 5-item version of Perse’s scale was a reliable measure of
consumers’ elaboration of televised soap operas (α = .81). Sun et al. (2008) found that a 5-item
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Table 4
Listening Attention Scale: Item Means and Standard Deviations
Items
M
SD
I’m often thinking about something else when I’m listening to music on
an MP3 player.a
2.31
0.85
I often miss parts of the songs when I listen to music on my MP3 player.a
3.01
0.99
My mind often wanders when I listen to music on an MP3 player.a
2.34
0.86
I pay close attention to the songs when I listen to music on an MP3
player.
3.30
0.82
I listen carefully when I listen to music on an MP3 player.
3.21
0.84
When I listen to music on an MP3 player, I try to concentrate on the
songs.
3.26
0.84
I put a lot of mental effort into my MP3 player music listening.
2.56
0.97
Note. N = 479
a
items were reverse coded for analysis.
version of Perse’s Elaboration Scale was a reliable measure of college students’ cognitive
involvement with the Internet (α = .87).
In addition to the four items from Perse’s (1990) Elaboration Scale, Lacher and
Mizerski’s (1994) Imaginal Response Scale was adapted to measure the degree to which college
students think about the music they are listening to on their MP3 player during their exposure.
Lacher and Mizerski developed the Imaginal Response Scale based on literature frompsychology
and music education fields (Hargreaves, 1982; Yingling, 1962). The adapted Imaginal Response
Scale included three statements that reflect respondents’ elaboration on songs, in general, that
77
they listen to on their portable MP3 player (e.g., when I’m listening to music on an MP3 player,
the songs prompt images in my mind). The response items were adapted to a 5-point Likert-type
scale consistent with Perse’s (1990) Elaboration Scale. Higher scores on the Imaginal Response
Scale indicate that the respondent agrees that they elaborate on songs.
Lacher and Mizerski (1994) found that the Imaginal Response Scale was a moderately
reliable measure of college students’ degree of elaboration on songs. In a pretest, they exposed
college students to two popular songs and asked them to record their degree of elaboration on the
songs with the Imaginal Response Scale. Although reliability estimates were low for the first
pretest (α = .60), the reliability estimates for the second pretest were higher (α = .71).
Unfortunately, Lacher and Mizerski did not report reliability estimates for the Imaginal Response
Scale they used in their main experiment. Responses to all seven items were summed and
averaged to create the index of overall elaboration on MP3-player music (M = 3.61, SD = 0.64, α
= .83). Table 5 provides item means and standard deviations.
Social Interaction
Time spent socializing with others. The Cole and Robinson (2002) Sociability
Questions were adapted to measure the amount of time college students spent socializing with
others (Appendix H). Specifically, the original Sociability Questions included two items that
asked respondents to indicate the hours and minutes they spent socializing face-to-face with
members of their household and friends outside their household during a typical week. In
addition to the two items concerning friends and family members, a question about the time
college students’ spend socializing with acquaintances was included. Also, the terms family,
instead of household members, and friends, instead of friends outside the household, were used
to avoid confusion among respondents who may live with friends and not family members.
78
Table 5
Listening Elaboration Scale: Item Means and Standard Deviations
Items
M
SD
When I’m listening to music on an MP3 player, I think about what the
songs mean to me.
3.74
0.90
When I’m listening to music on an MP3 player, I think about how the
songs relate to other things that I know.
3.77
0.87
When I’m listening to music on an MP3 player, I think about what the
songs mean to other people.
3.00
1.01
When I’m listening to music on an MP3 player, I think about the songs
over and over again.
3.24
0.99
When I’m listening to music on an MP3 player, the songs create a picture
in my mind.
3.73
0.91
When I’m listening to music on an MP3 player, the songs make me
remember something.
3.99
0.77
When I’m listening to music on an MP3 player, the songs prompt images
in my mind.
3.80
0.87
Note. N = 479
Furthermore, college students who live far away from their family members, friends, and
acquaintances may not have many opportunities to socialize with them face-to-face. However,
they may use other forms of media, including the Internet, e-mail, and the telephone to interact
socially with their friends, family members, and acquaintances (Mikami, 2002). Therefore, in
each item, some examples of the various types of interpersonal and mediated channels that
respondents may use to socialize with others were included. Respondents’ scores were summed
to create an index of overall hours spent socializing with friends, family members, and
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acquaintances per week (M = 55.58, SD = 43.78). To consider the possibility that time spent
socializing with family members, friends, and acquaintances were not mutually exclusive and
may overlap, I also separated the three categories to determine the hours spent socializing with
family members (M = 11.04, SD = 15.23), friends (M = 33.65, SD = 30.05), and acquaintances
(M = 10.88, SD = 14.82) in a typical week in order to conduct separate analyses of interaction
with these different groups.
Frequency of participation in social activities. The 2001 version of the Social
Participation Scale, as reported by Shklovski et al. (2004), was adapted to measure the frequency
with which college students participated in various social activities (Appendix I). The Social
Participation Scale was originally used in the PEW Internet and American Life project as part of
a national telephone survey of American’s Internet use and social habits. The project surveyed
3,533 adults in 2000 and interviewed 1,501 of the original respondents in 2001. Shklovski et al.
re-examined the results of the Social Participation Scale based on the 2000 and 2001 interviews.
They noted that the 2000 version of the Social Participation Scale contained only two questions
about the frequency of respondents’ social activities, including (a) calling friends or relatives just
to talk and (b) visiting with family or friends. Three activities were added in the 2001 version: (a)
going out to dinner with friends or family, (b) doing volunteer work, and (c) attending religious
services. Because the current study focused on college students’ participation in activities with
other people, the item regarding religious services was adapted by asking participants how often
they attend religious services with friends or family. Also, the instructions were adapted to
emphasize that all of the items in the adapted measure refer to participation in activities with
other people.
80
In addition to the five items from the 2001 version of the Social Participation Scale
(Shklovski et al., 2004), three items from the e-Living Survey that measure college students’
participation in social activities were adapted and included in my study (Anderson, 2008). The eLiving Survey consisted of two waves of telephone interviews in 2001 and 2002 and represented
respondents from six European countries. Researchers conducted the e-Living Survey to assess,
in part, the extent to which people engage in social leisure activities. The social leisure items
included (a) attending activity groups such as evening classes; (b) playing sport, keeping fit, or
going walking; (c) going to the cinema, a concert, theatre, or watching live sport; (d) having a
meal in a restaurant or café, or going for a drink to a bar; and (e) meeting with friends.
Items from the Anderson (2008) e-Living Survey were adapted in several ways. First, one
e-Living Survey item, attend activity groups such as evening classes, was not included because
of the possibility that this study’s sample population, college students, may attend classes and
that fact would have artificially inflated their social participation score based on their response to
this item. Second, the following items were adapted to indicate that they are performed with
friends or family members: (a) play sport, keep fit, or go walking and (b) gone to the cinema, a
concert, theater, or watch live sport. Third, the item from the Social Participation Scale
(Shklovski et al., 2004) regarding going out to dinner and the e-Living Survey item regarding
having a meal in a restaurant were combined. Therefore, based on the above discussion, the five
items from the Social Participation Scale and three items from the e-Living Survey were used in
the current study, for a total of eight items, to measure college students’ participation in social
activities.
In the 2001 version of the Social Participation Scale (Shklovski et al., 2004), respondents
used a 5-point Likert-type scale, including the following response categories: (1) never, (2) only
81
once or twice a year, (3) a few times a month, (4) a few times a week, and (5) every day.
Although the response categories are ordinal, there are unequal differences between the intervals.
Similarly, the response categories of the Anderson (2008) e-Living Survey are not equidistant.
To ensure more equidistant intervals between response categories and to maintain consistency
with other measures in the current study, the response categories of the Social Participation Scale
were adapted to a 5-point Likert-type scale, including the following response categories: (1)
never, (2) rarely, (3) sometimes, (4) often, and (5) very often. The adapted response categories
represented the original intention of the Social Participation Scale and were the same as the
response categories in the current study’s measure of college students’ frequency of file-sharing.
Higher scores on the adapted Social Participation Scale indicate more frequent participation in
social activities. Respondents’ scores were summed and averaged to represent their overall
frequency of participation in social activities (M = 3.72, SD = 0.59, α = .73). Table 6 provides
item means and standard deviations.
Frequency of post-listening discussion of music. Rubin and Perse’s (1987a) PostViewing Discussion Scale was adapted to measure how often college students discussed their
MP3-player music with others after listening (Appendix J). Specifically, three of the original
statements pertaining to talking about the story and characters were adapted to talking about the
songs and album artists or bands, respectively (e.g., after I listen to music on an MP3 player, I
often talk about the songs with others). In addition to the three items from the Post-Viewing
Discussion Scale, two statements regarding college students’ post-listening discussion about
song lyrics and music genres that they have listened to on their MP3 players (e.g., I often talk
with others about the genre(s) of music that I have recently listened to on an MP3 player) were
included because researchers have indicated that people may discuss other topics that are
82
Table 6
Social Participation Scale: Item Means and Standard Deviations
Items
M
SD
Called a friend or relative just to talk.
3.87
1.02
Visited with family or friends
4.21
0.83
Done volunteer work.
2.75
1.02
Attended religious services with friends or family.
2.68
1.29
Met with friends.
4.48
0.79
Had a meal in a restaurant or café, or gone for a drink to a bar with
friends or family.
4.25
0.85
Gone to the cinema, a concert, theatre or watched live sport with friends
or family.
3.82
0.96
Played sports, kept fit or gone walking with friends or family.
3.69
1.09
Note. N = 479
germane to music listening, such as song lyrics (Roe, 1985) and music genres (Katz, 2006;
Rentfrow & Gosling, 2003). Respondents indicated their agreement with each statement on a 5point Likert-type scale, ranging from 1 (strongly disagree) to 5 (strongly agree). Therefore,
higher scores on the Post-Listening Discussion Scale indicate that respondents tended to discuss
music content with others after they listened to music on their MP3 players.
Other researchers have used measures of people’s discussion about media content similar
to Rubin and Perse’s (1987a) Post-Viewing Discussion Scale (Levy, 1987; Levy & Windahl,
1984; Lin, 2006). For example, Levy asked VCR owners how often they discussed the movies
83
they watched on video with their family members and friends. Also, Lin’s measure of radio
listeners’ activity included discussing what they had heard. Levy and Windahl (1984) assessed
people’s post-exposure discussion of news programs by asking them how often they discussed
with others what they had recently watched on televised news.
However, the original Post-Viewing Discussion Scale contained multiple items for
assessing post-viewing discussion and was a reliable measure. Rubin and Perse (1987a) found
that the Cronbach alpha reliability estimates ranged from .68 to .89, indicating that the PostViewing Discussion Scale was a moderately reliable measure of people’s post-exposure
discussion about media content (Perse & Rubin, 1988, 1990; Rubin & Perse, 1987a).
Respondents’ scores were summed and averaged to create an index of their frequency of postlistening discussion of music (M = 2.99, SD = 0.88, α = .89). Table 7 provides item means and
standard deviations.
Frequency of music file-sharing. Unfortunately, researchers had not developed a
specific measure of digital music file-sharing frequency at the time of this study. However,
researchers had reported various ways that people download and share music with others, both
online and face-to-face (Brown & Sellen, 2006; Evangelista, 2005; Madden & Rainie, 2005;
Rainie et al., 2004; Rose, 2006). Madden and Rainie identified the sources that people use to
download music and movies, including online and interpersonal sources. The sources that they
identified seem to be similar to the channels that people may use to share digital music files with
others. Therefore, six items from the Madden and Rainie (2005) Daily Tracking Survey were
adapted to measure how often college students use each source to share music files (Appendix
K).
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Table 7
Post-Listening Discussion of Music Scale: Item Means and Standard Deviations
Items
M
SD
After I listen to music on an MP3 player, I often talk about the songs with
others.
2.87
1.03
After I listen to music on an MP3 player, I often talk about the artist(s) or
band(s) with others.
3.11
1.04
I often discuss with others the upcoming performances of artists or bands
that I have recently listened to on an MP3 player.
2.93
1.06
I often discuss with others the lyrics of songs I have recently listened to
on an MP3 player.
3.04
1.07
I often talk with others about the genre(s) of music that I have recently
listened to on an MP3 player.
2.99
1.05
Note. N = 479
Specifically, Madden and Rainie (2005) asked respondents to indicate the sources from
which they download music or video files (e.g., do you currently download music or video files
from any of the following places). Ferguson et al. (2007) noted that “the use of the word
‘download’ may [create] some confusion because a respondent might transfer music from a CD
(or a friend’s iPod) without using the Internet” (p. 118). Therefore, respondents were asked to
indicate how often they used each source to share music files with others, as opposed to
downloading files.
The Daily Tracking Survey included the following possible sources: (a) an online music
service, (b) e-mail or instant messages, (c) music-related websites, (d) a peer-to-peer network,
(e) someone’s iPod or other MP3 player, (f) movie-related websites, (g) music or movie blogs,
85
and (f) an online movie download service. The two items that represent video sources, solely
(i.e., movie-related websites and an online movie download service) were not included because
they did not reflect sources of music and they would have been redundant if adapted to reflect
music sources. Also, the one item that represents both music and video (i.e., music or movie
blogs) was adapted to reflect music exclusively (i.e., music blogs). In addition to altering the
previously mentioned item to focus on music, a definition of blogs (i.e., online journals) was
added for those who may have not been familiar with the colloquial term. One of the items, email or instant messages you receive, was adapted to include e-mail or instant messages that
people send as well as receive (i.e., e-mail or instant messages you send or receive) to reflect the
interactivity of file-sharing.
Originally, Madden and Rainie (2005) asked their respondents to indicate their agreement
or disagreement with each of questions mentioned above by saying yes or no. However,
Ferguson et al. (2007) noted that measuring the frequency with which people download music
would be a better than measuring whether they do or do not download music because responses
to frequency questions provide more information about consumers’ average use than responses
to yes or no questions. Therefore, the response options were adapted to reflect how often
respondents shared music files with others. Specifically, participants were asked to indicate their
response on a 5-point Likert-type scale, ranging from 1 (never) to 5 (very often) with 3
(sometimes) as a middle point. Higher scores indicate frequent music file-sharing with others.
Respondents’ scores were summed and averaged to create a music file-sharing index (M = 2.41,
SD = 0.67, α = .57). Unfortunately, the music file-sharing index did not appear to be a reliable
measure because participants tended to frequent only a few methods for file-sharing. Therefore,
in addition to scoring responses to the entire scale, I created measures of use of the two most
86
used file-sharing methods, online music services (M = 3.27, SD = 1.35) and someone’s iPod or
other MP3 player (M = 3.04, SD = 1.17) as separate outcome variables that represented different
types social interaction via file-sharing. Table 8 provides item means and standard deviations.
Statistical Analyses
Based on uses and gratifications theory and research, my literature review, and my rationale and
objectives, I proposed a model of MP3-player-music listening that illustrates relationships among
loneliness, motives, time spent listening to MP3-player music, activity with MP3-player music
(i.e., attention to songs and elaboration on songs), and social interaction (i.e., time spent
socializing with others, frequency of participation in social activities, frequency of post-listening
discussion of music, and frequency of music file-sharing) (see Figure 2). In order to answer the
first research question regarding college students’ motives for listening to music on a portable
MP3 player (RQ1), a principal component factor analysis of the MP3 Motive Scale was
conducted (Appendix D).
To test hypotheses 1 through 4 and to answer research questions 2 through 6, a series of
partial correlation analyses were conducted. Age, gender, grade level, household income, and
number of roommates were partialled out of each correlation. In other words, the partial
correlations controlled, statistically, for age, gender, grade level, household income, and number
of roommates.
To test hypothesis 1, a correlation was conducted to examine the relationship between
college students’ loneliness and their time spent listening to music on an MP3 player.
Specifically, hypothesis 1 stated that increased loneliness would be related to increased time
spent listening to MP3-player music. Hypothesis 2 stated that higher levels of loneliness would
be related to (a) less time spent socializing with others, (b) less frequent participation in social
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Table 8
Music File-Sharing Scale: Item Means and Standard Deviations
Items
M
SD
A peer-to-peer network like Kazaa or Morpheus.
1.68
1.08
An online music service like iTunes or BuyMusic.com.
3.27
1.35
Music blogs or online journals.
1.70
1.03
Other music-related websites, such as online music magazines or
musicians’ homepages.
2.27
1.17
Someone’s iPod or other MP3 player.
3.04
1.17
E-mail or instant messages you send or receive.
2.47
1.30
Note. N = 479
activities, (c) less frequent post-listening discussion of music, and (d) less frequent music filesharing. Hypothesis 3 stated that higher levels of attention to songs would be related to (a) more
time spent socializing with others, (b) more frequent participation in social activities, (c) more
frequent post-listening discussion of music, and (d) more frequent music file-sharing. Hypothesis
4 stated that higher levels of elaboration on songs would be related to (a) more time spent
socializing with others, (b) more frequent participation in social activities, (c) more frequent
post-listening discussion of music, and (d) more frequent music file-sharing.
To answer research question 2, a series of correlations was conducted to examine the
relationships between college students’ MP3-player-use motives and their time spent listening to
MP3-player music. The next analysis examined the relationships between college students’
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Loneliness
RQ5
MP3-Player-Music-Listening Motives
(relaxation/escape, stimulation,
entertainment, loneliness, boredom,
social utility, social avoidance,
atmosphere creation/mood control,
attention to lyrics, fashion/status)
RQ 1
H1
RQ3
RQ2
Exposure
Audience Activity
(time spent listening to music)
(attention to songs, elaboration on songs)
RQ6
RQ4
H3, H4
Social Interaction
RQ7, RQ8
(time spent socializing with others, frequency of participation in
social activities, frequency of post-listening discussion of music;
frequency of music file-sharing)
Figure 2. Proposed Relationships Regarding Loneliness, Motives to Listen to MP3-Player
Music, Exposure to MP3-Player Music, and Audience Activity with MP3-Player Music as
Predictors of Social Interaction.
H2
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motives to listen to MP3-player music and their (a) attention to songs and (b) elaboration on
songs (RQ3). Research question 4 inquired about the relationship between college students’
motives to listen to music on an MP3 player and their (a) time spent socializing with others, (b)
frequency of participation in social activities, (c) frequency of post-listening discussion of music,
and (d) frequency of music file-sharing.
As previously mentioned, in addition to overall time spent socializing with others, three
separate variables were created from the data to specify types of people with which college
students spent time socializing (i.e., family members, friends, and acquaintances). Also, in
addition to overall file-sharing, two items (i.e., using an online music service and using an MP3
player) were analyzed as separate types of file-sharing. The additional variables regarding time
spent socializing with others and file-sharing mentioned above were included in all analyses that
examined time spent socializing with others and file-sharing.
For research question 5, correlation analyses were conducted to examine relationships
between college students’ loneliness and their MP3-player-use motives. To answer research
question 6, I examined the correlations between college students’ time spent listening to music
on an MP3 player and their (a) time spent socializing with others, (b) frequency of participation
in social activities, (c) frequency of discussion of music after listening, and (d) frequency of
music file-sharing.
Research question 7 asked how college students’ loneliness, motives to listen to music on
an MP3 player, time spent listening to MP3-player music, and audience activity (i.e., attention to
songs and elaboration on songs) predicted their (a) time spent socializing with others, (b)
frequency of participation in social activities, (c) frequency of post-listening discussion of music,
and (d) frequency of music file-sharing. Separate hierarchical multiple regression analyses were
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conducted for each type of social interaction (i.e., spending time socializing with others,
participating in social activities, discussing music with others after listening, and sharing music
files) to answer this research question. In addition, separate hierarchical multiple regression
analyses were conducted for the additional groups (i.e., family members, friends, and
acquaintances) and methods of file-sharing (i.e., using an online music service and using an MP3
player) discussed above.
Uses and gratifications theory suggests that people’s background characteristics, motives
to use media, exposure to media content, and activity with media content influence media
effects. Accordingly, my control and predictor variables of each type of social interaction were
entered in four conceptual steps: (a) age, gender, grade level, household income, and number of
roommates; (b) loneliness; (c) motives to listen to music on an MP3 player; and (d) time spent
listening to MP3-player music, attention to songs, and elaboration on songs. The multiple
regression analyses assessed the contributions of the antecedent variables to predicting the
different social interaction outcome variables.
Research question 8 asked how motives to listen to MP3-player music, time spent
listening to MP3-player music, and activity with MP3-player music predicted the different types
of social interaction. Separate hierarchical multiple regression analyses were conducted for each
type of social interaction and predictor variable were entered in the order as they were in the
analysis of research question 7. However, loneliness was not included as a predictor variable in
the analysis of research question 8 because of concerns that loneliness could suppress variance
explained by other antecedent variables.
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Chapter III
RESULTS
In this section, I present the results of the analyses testing the hypotheses and answering the
research questions posed above. The theoretical implications of the relationships reported are
discussed in greater detail in the final chapter.
Hypotheses
As referenced above, all correlation analyses controlled for age, gender, grade level,
household income, and number of roommates. Hypothesis 1 posited that higher levels of
loneliness would be related to more time spent listening to MP3-player music. The partial
correlation between loneliness and time spent listening to music was not significant (partial r =
.05, p = .32). Therefore, H1 was not supported.
Hypotheses 2a, 2b, 2c, and 2d predicted relationships between loneliness and four types
of social interaction. Hypothesis 2a posed that higher levels of loneliness would be related to less
time spent socializing with others. There was a significant negative partial correlation between
loneliness and overall time spent socializing with others (partial r = -.20, p < .001). Further
analysis revealed significant negative partial correlations between loneliness and time spent
socializing with family members (partial r = -.13, p < .05) and between loneliness and time spent
socializing with friends (partial r = -.21, p < .001). Therefore, H2a was supported. Hypothesis 2b
stated that higher levels of loneliness would be related to less frequent participation in social
activities. There was a significant negative partial correlation between loneliness and students’
participation in social activities (partial r = -.35, p <.001). Thus, H2b was supported. Hypothesis
2c stated that higher levels of loneliness would be related to less frequent post-listening
discussion of music. The partial correlation between loneliness and post-listening discussion was
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not significant (partial r = -.02, p = .71). Accordingly, H2c was not supported. Hypothesis 2d
stated that higher levels of loneliness would be related to less frequent music file-sharing. The
partial correlation between loneliness and overall file-sharing was not significant (partial r = .03,
p = .61). However, further analysis revealed significant negative partial correlations between
loneliness and the two types of file-sharing most used by participants – an online music service
(partial r = -.14, p < .01) and an MP3 player (partial r = -.12, p < .05). Therefore, H2d was
partially supported.
Hypotheses 3a, 3b, 3c, and 3d predicted relationships between attention to MP3-player
songs and four types of social interaction. The partial correlations between attention to songs and
overall time spent socializing with others (partial r = -.01, p = .78) and attention to songs and
participation in social activities (partial r = .03, p = .58) were not significant. Accordingly, H3a
and H3b were not supported. Hypothesis 3c stated that higher levels of attention to songs would
be related to more frequent post-listening discussion of music. There was a significant positive
partial correlation between attention to songs and post-listening discussion (partial r = .27, p <
.001). Therefore, H3c was supported. Hypothesis 3d stated that higher levels of attention to
songs would be related to more frequent music file-sharing. There was a significant positive
partial correlation between attention to songs and overall file-sharing (partial r = .19, p < .001).
Thus, H3d was supported. Attention to songs also was positively related to the most used source
of file-sharing, online music services (partial r = .10, p < .05).
Hypotheses 4a, 4b, 4c, and 4d predicted relationships between elaboration on songs and
four types of social interaction. Hypothesis 4a posed that higher levels of elaboration on songs
would be related to more time spent socializing with others, including family members, friends,
and acquaintances. The partial correlation between elaboration and overall time spent socializing
93
with others was not significant (partial r = .04, p = .41). Accordingly, H4a was not supported.
Hypothesis 4b stated that higher levels of elaboration on songs would be related to more frequent
participation in social activities. There was a significant positive partial correlation between
elaboration and participation in social activities (partial r = .20, p < .001). Thus, H4b was
supported. Hypothesis 4c stated that higher levels of elaboration would be related to more
frequent post-listening discussion of music. There was a significant positive partial correlation
between elaboration and post-listening discussion (partial r = .44, p < .001). Therefore, H4c was
supported. Hypothesis 4d stated that higher levels of elaboration would be related to more
frequent music file-sharing. There was a significant positive partial correlation between
elaboration and overall file-sharing (partial r = .25, p < .001). Further analysis revealed
significant positive partial correlations between elaboration and file-sharing using an online
music service (partial r = .12, p < .05) and between elaboration and file-sharing using an MP3
player (partial r = .20, p < .001). Therefore, H4d was supported.
Research Questions
Research question 1 asked about some of the reasons college students had for listening to
music on a portable MP3 player. As previously discussed, the final factor analysis produced a
seven-factor solution. These factors represented using MP3 players for (a) social avoidance, (b)
fashion/status, (c) social utility, (d) learning, (e) entertainment/relaxation, (f) companionship, and
(g) boredom alleviation. Data related to this analysis are provided in Tables 2 and 3 above.
Research question 2 inquired about the relationship between college students’ motives to
listen to music on an MP3 player and their time spent listening to music on an MP3 player. Time
spent listening to music on an MP3 player positively correlated with several motives to listen to
MP3-player music: social avoidance (partial r = .10, p < .05), social utility (partial r = .11, p <
94
.05), learning (partial r = .20, p < .001), entertainment/relaxation (partial r = .10, p < .05),
companionship (partial r = .18, p < .001), and boredom alleviation (partial r = .11, p < .05)
motives. The partial correlation between fashion/status motivation and time spent listening was
not significant (partial r = .04, p = .47).
Research question 3a inquired about the relationships between MP3-player-use motives
and attention to songs. Attention to songs positively correlated with using an MP3 player for
social utility (partial r = .13, p < .01), learning (partial r = .15, p < .01), entertainment/relaxation
(partial r = .12, p < .05), and companionship (partial r = .20, p < .001). There were no significant
partial correlations between attention to songs and using an MP3 player for social avoidance
(partial r = -.06, p = .22), fashion/status (partial r = -.03, p = .48), or boredom alleviation (partial
r = -.05, p = .35).
Research question 3b inquired about the relationships between MP3-player-use motives
and elaboration on songs. Elaboration on songs was significantly related to using an MP3 player
for social avoidance (partial r = .15, p < .001), social utility (partial r = .37, p < .001), learning
(partial r = .39, p < .001), entertainment/relaxation (partial r = .29, p < .001), companionship
(partial r = .45, p < .001), and boredom alleviation (partial r = .18, p < .001), but not
fashion/status (partial r = .08, p = .09).
Research questions 4a, 4b, 4c, and 4d asked about the relationships between students’
MP3-player-use motives and four types of social interaction. Results are reported in Table 9.
Research question 4a inquired about the relationship between MP3-player-use motives and time
spent socializing with others. Overall time spent socializing with others was negatively related to
listening to MP3 players for social avoidance and for fashion/status. There was a significant
positive partial correlation between overall time spent socializing with others and listening to
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Table 9
Partial Correlations between MP3-Player-Use Motives and Social Interaction
Social Interaction
Music-Listening
Motives
TO
TFA
TFR
TA
PSA
DIS
FS
FSS
FSM
Social
Avoidance
-.12*
-.10*
-.11*
-.03
-.12* .03
.12*
.01
.01
Fashion/Status
-.10*
-.09
-.09
-.02
.02
.19***
.26***
.11*
.09
Social Utility
-.02
-.14**
-.01
.12*
.09
.55***
.29***
.10*
.20***
Learning
-.06
-.09
-.04
-.01
.05
.45***
.26***
.09
.20***
Entertainment/
Relaxation
.05
.00
.08
-.00
.12*
.23***
.17**
.17***
.14**
Companionship
-.08
-.08
-.07
-.02
-.00
.36***
.15**
.00
.04
Boredom
Alleviation
.10*
-.07
.14**
.07
.12*
.19***
.16**
.11*
.12*
Note. n = 407. TO = Time Spent Socializing with Others, TFA = Time Spent Socializing with
Family, TFR = Time Spent Socializing with Friends, TA = Time Spent Socializing with
Acquaintances, PSA = Participation in Social Activities, DIS = Post-Listening Discussion, FS =
File-Sharing, FSS = File-Sharing Using Music Service, FSM = File-Sharing Using an MP3 Player
* p < .05, ** p < .01, *** p < .001
MP3 players to alleviate boredom. Further analysis revealed time spent socializing specifically
with family members was negatively related to social avoidance and social utility motives. Time
spent socializing with friends correlated with listening to MP3-player music for social avoidance
96
and to alleviate boredom. Time spent socializing with acquaintances correlated with listening to
music for social utility.
Research question 4b inquired about the relationships between college students’ MP3player-use motives and their frequency of participation in social activities. Using an MP3 player
for social avoidance correlated negatively with participation in social activities. Participation in
social activities related positively to two MP3-player-use motives: entertainment/relaxation and
boredom alleviation.
Research question 4c inquired about the relationships between college students’ MP3player-use motives and their post-listening discussion of music. Post-listening discussion related
positively to six MP3-player-use motives, including fashion/status, social utility, learning,
entertainment/relaxation, companionship, and boredom alleviation.
Research question 4d inquired about the relationships between MP3-player-use motives
and frequency of music file-sharing. Overall file-sharing related positively to all seven of the
MP3-player-use motives. File-sharing using an online music service related positively to
listening to MP3-player music for fashion/status, social utility, entertainment/relaxation, and
boredom alleviation. File-sharing using an MP3 player related positively to listening to an MP3
player for social utility, learning, entertainment/relaxation, and boredom alleviation.
Research question 5 asked about the relationships between loneliness and MP3-playeruse motives. Loneliness was positively related to using MP3 players for social avoidance (partial
r = .35, p < .001), learning (partial r = .11, p < .05), and companionship (partial r = .25, p <
.001). Loneliness was negatively related to two MP3-player-use motives:
entertainment/relaxation (partial r = -.24, p < .001) and boredom alleviation (partial r = -.13, p <
.01).
97
Research questions 6a, 6b, 6c, and 6d inquired about the relationships between time spent
listening to MP3-player music and each of the different types of social interaction. Time spent
listening was not related significantly to time spent socializing with others (partial r = .01, p =
.91; RQ6a) or with participation in social activities (partial r = -.05, p = .35; RQ6b). Time spent
listening did relate positively to post-listening discussion of music (partial r = .11, p < .05;
RQ6c) and overall file-sharing (partial r = .16, p < .01; RQ6d).
Research question 7 inquired about the influence of college students’ demographics (i.e.,
age, gender, grade level, household income, and number of roommates), loneliness, MP3-playeruse motives, time spent listening to MP3-player music, attention to songs, and elaboration on
songs on (a) time spent socializing with others, (b) frequency of participation in social activities,
(c) frequency of post-listening discussion of music, and (d) frequency of file-sharing. As
discussed above, separate hierarchical multiple regression analyses were conducted to examine
the contribution of the antecedent variables to explaining each of the social interaction outcome
variables. Results of all regression analyses are summarized in Appendix L. The abovementioned variables were entered in a particular conceptual order, based on uses and
gratifications theoretical framework that guided this study. The first multiple regression analysis
assessed the contribution of the antecedent variables to predicting overall time spent socializing
with others. The second analysis assessed the contribution of the antecedent variables to
predicting time spent socializing specifically with family members. The third analysis assessed
the contribution of the antecedent variables to predicting time spent socializing specifically with
friends. The fourth analysis assessed the contribution of the antecedent variables to predicting
time spent socializing with acquaintances. The fifth analysis assessed the contribution of the
antecedent variables to predicting participation in social activities. The sixth analysis assessed
98
the contribution of the antecedent variables to predicting post-listening discussion of music. The
seventh analysis assessed the contribution of the antecedent variables to predicting frequency of
overall file-sharing. The eighth analysis assessed the contribution of the antecedent variables to
predicting file-sharing specifically using an online music service. The ninth analysis assessed the
contribution of the antecedent variables to predicting file-sharing using just an MP3 player. The
specific results of research question 7 are discussed below.
Overall Time Spent Socializing with Others
Demographic variables (age, gender, grade level, household income, and number of
roommates), entered on the first step, accounted for only 1.1% of the variance in overall time
spent socializing with others. There were no significant predictors (see Table 10 in Appendix L).
Loneliness was entered on the second step and accounted for an additional 4.3% of the
variance. The F change was significant (p < .001). Loneliness (β = -.21, p < .001) was a
significant negative predictor of time spent socializing with others.
MP3-player-use motives (i.e., social avoidance, fashion/status, social utility, learning,
entertainment/relaxation, companionship, and boredom alleviation) were entered on the third
step and accounted for an additional 1.8% of the variance. The F change was not significant (p =
.37). Listening to alleviate boredom (β = .12, p < .05) was the only significant predictor.
Loneliness (β = -.18, p < .01) continued to be a significant predictor.
Time spent listening to MP3-player music, attention to songs, and elaboration on songs
were entered on the fourth and final step, accounting for only 0.7% of additional variance. The F
change was not significant (p = .40) and none were predictors. Loneliness (β = -.18, p < .01) and
boredom alleviation (β = .12, p < .05) continued to be significant predictors.
99
Accordingly, after all variables were entered, the final equation accounted for 7.8% of the
variance in time spent socializing with others. The results suggest that less-lonely college
students who tended to listen to MP3-player music to alleviate boredom tended to spend more
time socializing with other people than did their counterparts.
Time Spent Socializing with Family Members
Demographic variables were entered on the first step and accounted for 9.3% of the
variance in time spent socializing with family members. Age (β = .29, p < .001) and gender (β =
.14, p < .01) were significant predictors of time spent socializing with family members (see
Table 11 in Appendix L).
Loneliness, entered on the second step, increased explained variance by 1.7%. The F
change was significant (p < .01). Loneliness (β = -.13, p < .01) was a significant predictor. Age
(β = .30, p < .001) and gender (β = .11, p < .05) continued to be significant predictors.
MP3-player-use motives were entered on the third step and accounted for an additional
2.5% of the variance. The F change was not significant (p = .12). Social utility (β = -.13, p < .05)
was a significant predictor. Age (β = .30, p < .001), gender (β = .11, p < .05), and loneliness (β =
-.14, p < .01) continued to be significant predictors.
Time spent listening to MP3-player music, attention to songs, and elaboration on songs,
entered on the fourth and final step, accounted for an additional 0.9% of the variance. The F
change was not significant (p = .26) and none of these variables were predictors. Age (β = .30, p
< .001), gender (β = .11, p < .05), loneliness (β = -.14, p < .01), and listening for social utility (β
= -.14, p < .05) remained significant predictors.
After all variables were entered, the final equation accounted for 14.3% of the variance in
time spent socializing with family members. The results suggest that older, less-lonely, female
100
college students, who did not tend to listen to MP3-player music for social utility, tended to
spend more time socializing with family members than did their counterparts.
Time Spent Socializing with Friends
On the first step, demographic variables accounted for 3.2% of the variance in time spent
socializing with friends. Age (β = -.16, p < .01) was a significant predictor of time spent
socializing with friends (see Table 12 in Appendix L).
Entered on the second step, loneliness explained an additional 4.3% of the variance. The
F change was significant (p < .001), and loneliness was a significant predictor (β = -.21, p <
.001). Age (β = -.14, p < .01) continued to be a significant predictor.
Motives, entered on the third step, accounted for an additional 2.6% of the variance. The
F change was not significant (p = .12). Listening to MP3-player music to alleviate boredom (β =
.16, p < .01) was the only significant predictor. Age (β = -.15, p < .01) and loneliness (β = -.17, p
< .01) continued to be significant predictors.
Time spent listening to MP3-player music, attention to songs, and elaboration on songs,
entered on the fourth step, accounted for 0.2% of additional variance in time spent socializing
with friends. The F change was not significant (p = .83) and none of these variables were
predictors. Age (β = -.14, p < .01), loneliness (β = -.17, p < .01), and listening to alleviate
boredom (β = .16, p < .01) continued to be significant predictors.
The final equation accounted for 10.3% of the variance in time spent socializing with
friends. The results suggest that younger, less-lonely college students, who tended to listen to
MP3-player music to alleviate boredom, tended to spend more time socializing with friends than
did their counterparts.
101
Time Spent Socializing with Acquaintances
Demographic variables, entered on the first step, accounted for only 0.8% of variance in
time spent socializing with acquaintances. There were no significant predictors (see Table 13 in
Appendix L).
Loneliness, entered on the second step, accounted for only 0.3% of additional variance.
The F change was not significant (p = .25) and loneliness was not a predictor.
MP3-player-use motives, entered on the third step, accounted for an additional 2.5% of
the variance. The F change was not significant (p = .18). However, listening to MP3-player
music for social utility (β = .17, p < .01) was a significant predictor of time spent socializing with
acquaintances.
Time spent listening to MP3-player music, attention to songs, and elaboration on songs,
entered on the final step, accounted for an additional 0.7% of the variance. The F change was not
significant (p = .38) and none of these variables were predictors. Listening for social utility (β =
.16, p < .05) continued to be the only significant predictor of time spent socializing with
acquaintances.
Accordingly, after all variables were entered, the final equation accounted for only 4.4%
of the variance in time spent socializing with acquaintances. The results suggest that college
students who listened to music on an MP3 player for social utility tended to spend more time
socializing with acquaintances than did their counterparts.
Participation in Social Activities
Demographic variables were entered on the first step and accounted for 14.8% of the
variance in participation in social activities. Age (β = -.16, p < .01), gender (β = .24, p < .001),
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household income (β = .10, p < .05), and number of roommates (β = .12, p < .01) were
significant predictors of participation in social activities (see Table 14 in Appendix L).
Entering loneliness increased explained variance by 9.6%. The F change was significant
(p < .001). Loneliness (β = -.32, p < .001) was a significant predictor. Age (β = -.13, p < .01),
gender (β = .17, p < .001), and number of roommates (β = .11, p < .05) continued to be
significant predictors. Household income (β = .09, p = .06) ceased to be a predictor.
Entering MP3-player-use motives on the third step accounted for an additional 1.5% of
the variance. The F change was not significant (p = .33). None of the motives were significant
predictors of participation in social activities. Age (β = -.12, p < .05), gender (β = .16, p < .01),
number of roommates (β = .11, p < .05), and loneliness (β = -.31, p < .001) continued to be
significant predictors. Household income (β = .09, p < .05) re-emerged as a significant predictor
at this step.
Time spent listening, attention to songs, and elaboration on songs were entered on the
fourth step, accounting for 3.1% of additional variance. The F change was significant (p < .01).
Elaboration on songs (β = .22, p < .001) was a significant predictor. Age (β = -.10, p < .05),
gender (β = .14, p < .01), household income (β = .11, p < .05), number of roommates (β = .10, p
< .05), and loneliness (β = -.30, p < .001) continued to be significant predictors.
The final equation accounted for 28.9% of the variance in participation in social
activities, after all variables were entered. The results suggest that younger, less-lonely, female
college students with more roommates and higher household incomes, who tended to elaborate
on songs to which they listened, tended to participate in social activities more frequently than did
their counterparts.
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Post-Listening Discussion
Demographic variables entered on the first step accounted for 4.5% of the variance in
participation in social activities. Age (β = -.14, p < .01) and household income (β = -.16, p < .01)
were the only significant predictors (see Table 15 in Appendix L).
Loneliness, entered on the second step, did not account for any additional variance. The F
change was not significant (p = .85) and loneliness was not a predictor of post-listening
discussion. Age (β = -.14, p < .01) and household income (β = -.16, p < .01) continued to be
significant predictors at this step.
MP3-player-use motives were entered on the third step and explained an additional
36.2% of the variance. The F change was significant (p < .001). Several motives were significant
predictors: social avoidance (β = -.10, p < .05), social utility (β = .38, p < .001), learning (β =
.20, p < .001), entertainment/relaxation (β = .10, p < .05), and companionship (β = .14, p < .01).
Age (β = -.07, p = .11) ceased to be a significant predictor. Household income (β = -.10, p < .05)
continued to be a significant predictor.
Entering time spent listening, attention to songs, and elaboration on songs explained an
additional 4.4% of variance. The F change was significant (p < .001). Attention to songs (β =
.12, p < .01) and elaboration on songs (β = .19, p < .001) were significant predictors. Household
income (β = -.09, p < .05), social avoidance motivation (β = -.09, p < .05), social utility
motivation (β = .35, p < .001), and learning motivation (β = .17, p < .01) continued to be
significant predictors. Entertainment/relaxation (β = .05, p = .29) and companionship (β = .06, p
= .23) motives ceased to be significant predictors.
After all variables were entered, the final equation accounted for 45.1% of the variance in
post-listening discussion of music. The results suggest that college students from low income
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households who listened to MP3-player music for social utility and to learn about themselves but
not to avoid others and who paid attention to and elaborated on songs to which they listened
tended to discuss music with others frequently.
Overall File-Sharing
Demographics variables, entered on the first step, accounted for 3.7% of the variance in
overall file-sharing. Age (β = -.14, p < .01) was a significant predictor of overall file-sharing (see
Table 16 in Appendix L).
Entering loneliness accounted for only 0.1% of additional variance in overall file-sharing.
The F change was not significant (p = .53) and loneliness was not a predictor. Age (β = -.14, p <
.01) continued to be a significant predictor.
Entering MP3-player-use motives accounted for an additional 13.9% of the variance. The
F change was significant (p < .001). Fashion/status (β = .16, p < .01), social utility (β = .15, p <
.01), learning (β = .15, p < .05), and entertainment/relaxation (β = .14, p < .01) motives were
significant predictors of overall file-sharing. Age (β = -.11, p < .05) continued to be a significant
predictor of overall file-sharing.
Time spent listening, attention to songs, and elaboration on songs, entered on the final
step, accounted for an additional 4.3% of the variance. The F change was significant (p < .001).
Time spent listening (β = .11, p < .05) and attention to songs (β = .15, p < .01) were significant
predictors of overall file-sharing. Companionship motivation (β = -.15, p < .05) emerged as a
significant predictor. Age (β = -.11, p < .05), fashion/status motivation (β = .19, p < .001), social
utility motivation (β = .12, p < .05), and entertainment/relaxation motivation (β = .10, p < .05)
continued to be significant predictors of overall file-sharing. Learning motivation (β = .11, p =
.06) ceased to be a significant predictor of overall file-sharing.
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After all variables were entered, the final equation accounted for 22% of the variance in
overall file-sharing. The results suggest that younger college students, who tended to listen to
MP3-player music for fashion/status, social utility, and entertainment/relaxation, but not for
companionship, and who spent more time listening and paid more attention to songs, shared
music files with others more frequently than did their counterparts.
File-Sharing Using an Online Music Service
On the first step, demographic variables explained 9.3% of the variance in participants’
most-used source of file-sharing, an online music service. Gender (β = .19, p < .001) and grade
level (β = -.14, p < .01) were significant predictors of using an online music service to share files
(see Table 17 in Appendix L).
Entering loneliness on the second step increased explained variance by 1.4%. The F
change was significant (p < .05). Loneliness (β = -.12, p < .05) was a significant predictor of filesharing using an online music service. Students’ gender (β = .17, p < .01) and their grade level (β
= -.15, p < .01) continued to be significant predictors.
MP3-player-use motives, entered on the third step, accounted for an additional 4.1% of
the variance. The F change was significant (p < .01). Fashion/status motivation (β = .11, p < .05)
and entertainment/relaxation motivation (β = .14, p < .01) were significant predictors. Gender (β
= .18 p < .001) and grade level (β = -.15, p < .01) continued to be significant predictors.
Loneliness (β = -.09, p = .10) ceased to be a predictor of file-sharing using an online music
service.
Time spent listening, attention to songs, and elaboration on songs, entered on the fourth
and final step, accounted for an additional 1.6% of the variance and none of these variables were
significant predictors. The F change was not significant (p = .06). Gender (β = .20, p < .001),
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grade level (β = -.14, p < .01), fashion/status motivation (β = .13, p < .05), and
entertainment/relaxation motivation (β = .11, p < .05) continued to be significant predictors.
Companionship (β = -.13, p < .05) emerged as a significant predictor of file-sharing using an
online music service.
After all variables were entered, the final equation accounted for 16.4% of the variance in
file-sharing using an online music service. The results suggest that female college students in
lower grade levels, who tended to listen to MP3-player music for fashion/status and
entertainment/relaxation reasons but not for companionship, tended to use online music services
to share music files.
File-Sharing Using an MP3 Player
Demographic variables explained 7.6% of the variance in using an MP3 player to share
music files. Age (β = -.16, p < .01) and grade level (β = -.15, p < .01) were significant predictors
(see Table 18 in Appendix L).
Loneliness, entered on the second step, accounted for an additional 1.1% of the variance.
The F change was significant (p < .05). Loneliness (β = -.11, p < .05) was a significant predictor
of using an MP3 player to share music files. Age (β = -.15, p < .01) and grade level (β = -.15, p <
.01) continued to be significant predictors.
On the third step, MP3-player-use motives were entered and explained an additional
6.3% of the variance. The F change was significant (p < .001). Listening to MP3-player music to
learn (β = .19, p < .01) was a significant predictor of file-sharing using an MP3-player. Age (β =
-.13, p < .01) and grade level (β = -.13, p < .01) continued to be significant predictors. Loneliness
(β = -.08, p = .12) ceased to be a significant predictor.
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Time spent listening, attention to songs, and elaboration on songs accounted for an
additional 1.3% of the variance. The F change was not significant (p = .11). However,
elaboration on songs (β = .14, p < .05) was a significant predictor of file-sharing using an MP3
player. Age (β = -.12, p < .05), grade level (β = -.13, p < .01), and learning (β = .16, p < .01)
continued to be significant predictors. Companionship (β = -.14, p < .05) emerged as a
significant predictor.
After all the variables were entered, the final equation accounted for 16.2% of the
variance in file-sharing using an MP3 player. The results suggest that younger college students in
lower grade levels who tended to listen to music on an MP3 player to learn about themselves but
not for companionship and who elaborated on the songs tended to use an MP3 player to share
music files.
Research Question 8
Research question 8 was posed to determine the contributions of antecedents, excluding
loneliness, on social interaction. As previously discussed, I anticipated that loneliness would
relate to decreased social interaction. It was a concern that the strength of the relationship
between loneliness and social interaction might overshadow the contributions of the other
antecedent variables to explaining social interaction. Therefore, I examined the contributions of
the other antecedents to explaining social interaction, excluding the contribution of loneliness.
Similar to the analyses conducted to answer research questions 7, separate hierarchical
multiple regression analyses were conducted for each of the social interaction variables to
answer research question 8, albeit excluding loneliness as a predictor variable. Below, I report
the main differences between the results of research questions 7 and 8. The tables of the
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hierarchical multiple regressions conducted to answer research question 8 appear in Tables 19
through 27 in Appendix M.
Antecedent variables including loneliness (RQ7) explained only slightly more variance in
time spent socializing and participation in social activities than did antecedent variables
excluding loneliness (RQ8). Without the influence of loneliness, listening to MP3-player music
for social avoidance (β = -.16, p < .01) and to alleviate boredom (β = .11, p < .05) were
significant predictors of participation in social activities on the final step of the regression.
However, these motives were not significant predictors on the final step of the regression that
included loneliness as an antecedent variable. Listening to music on an MP3 player for
entertainment/relaxation was a significant predictor of overall file-sharing on the final step of the
regression accounting for the influence of loneliness. However, entertainment/relaxation
motivation was not a significant predictor of overall file-sharing on the final step of the
regression without loneliness included as an antecedent. There were essentially no differences
between the outcome of the regression with loneliness and the outcome of the regression without
loneliness in predicting discussion of music with others after listening and file-sharing. Overall,
with the exception of the differences noted above, the outcomes of the regressions with
loneliness and the regressions without loneliness were essentially the same, with the same
direction of the significant predictor variables and only slight variations in the strength of some
the beta-weights (see Appendices L and M).
Summary of Results
The previously discussed results of this study’s research questions and hypotheses have
been summarized below to provide a quick reference:
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RQ1: What are college students’ motives for listening to music on an MP3 player?
ƒ Entertainment/relaxation (M = 4.27, SD = 0.53)
ƒ Boredom alleviation (M = 3.54, SD = 0.73)
ƒ Companionship (M = 3.17, SD = 0.76)
ƒ Social utility (M = 3.03, SD = 0.86)
ƒ Learning (M = 2.49, SD = 0.90)
ƒ Social avoidance (M = 2.31, SD = 0.94)
ƒ Fashion/status (M = 1.89, SD = 0.75)
RQ2: How do college students’ motives to listen to music on an MP3 player relate to their time
spent listening to music on an MP3 player?
ƒ Time spent listening related positively to all motives, except fashion/status.
RQ3: How do college students’ motives to listen to music on an MP3 player relate to their (a)
attention to songs and (b) elaboration on songs?
ƒ Attention related positively to social utility, learning, entertain/relax, and companionship.
ƒ Elaboration related positively to all motives, except fashion/status.
RQ4: How do college students’ motives to listen to music on an MP3 player relate to their (a)
time spent socializing with others, (b) frequency of participation in social activities, (c)
frequency of post-listening discussion of music, and (d) frequency of music file-sharing?
ƒ Social avoidance related negatively to time spent socializing overall, with family and
friends, participation in social activities, and file-sharing overall.
ƒ Fashion/status related negatively to time spent socializing overall, but related positively to
discussion, file-sharing overall, and online.
ƒ Social utility related negatively to time spent socializing with family, but related positively
to time spent socializing with acquaintances, discussion, and all types of file-sharing.
ƒ Learning related positively to discussion and file-sharing overall and online.
ƒ Entertain/relax related positively to participation in social activities, discussion, and all
types of file-sharing.
ƒ Companionship related positively to discussion and file-sharing overall.
ƒ Boredom alleviation related positively to time spent socializing overall and with friends,
participation in social activities, discussion, and all types of file-sharing.
RQ5: How does college students’ loneliness relate to their motives to listen to music on an MP3
player?
ƒ Loneliness related positively to social avoidance, learning, and companionship.
ƒ Loneliness related negatively to entertain/relax and boredom alleviation.
RQ6: How does college students’ time spent listening to music on an MP3 player relate to their
(a) time spent socializing with others, (b) frequency of participation in social activities, (c)
frequency of post-listening discussion of music, and (d) frequency of music file-sharing?
ƒ Time spent listening related positively to discussion and file-sharing overall.
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H1: Higher levels of loneliness will be related to more time spent listening to music on an
MP3 player.
ƒ Not significant; not supported
H2: Higher levels of loneliness will be related to (a) less time spent socializing with others, (b)
less frequent participation in social activities, (c) less frequent post-listening discussion of music,
and (d) less frequent music file-sharing.
ƒ Partially supported for overall time spent socializing, time spent socializing with family
and friends, social activities, and file-sharing sharing online and with an MP3 player.
H3: Higher levels of attention to songs will be related to (a) more time spent socializing with
others, (b) more frequent participation in social activities, (c) more frequent post-listening
discussion of music, and (d) more frequent music file-sharing.
ƒ Partially supported for discussion, overall file-sharing, and file-sharing online.
H4: Higher levels of elaboration on songs will be related to (a) more time spent socializing with
others, (b) more frequent participation in social activities, (c) more frequent post-listening
discussion of music, and (d) more frequent music file-sharing.
ƒ Partially supported for participation in social activities, discussion, overall file-sharing,
and sharing online and with an MP3 player.
RQ7: How do college students’ loneliness, motives to listen to music on an MP3 player, time
spent listening to MP3-player music, and activity with MP3-player music (i.e., attention to songs
and elaboration on songs) predict their (a) time spent socializing with others, (b) frequency of
participation in social activities, (c) frequency of post-listening discussion of music, and (d)
frequency of music file-sharing?
ƒ Antecedent variables differentially predicted different types of social interaction (see
Appendix L).
RQ8: How do college students’ motives to listen to music on an MP3 player, time spent listening
to MP3-player music, and activity with MP3-player music (i.e., attention to songs and
elaboration on songs) predict their (a) time spent socializing with others, (b) frequency of
participation in social activities, (c) frequency of post-listening discussion of music, and (d)
frequency of music file-sharing?
ƒ Antecedent variables differentially predicted different types of social interaction (see
Appendix M).
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Chapter IV
DISCUSSION
In this study, I examined whether specific background characteristics, motives for
listening to music on an MP3 player, time spent listening, attention to songs, and elaboration on
songs influenced college students’ social interaction. Some critics have claimed that MP3-player
use detracts from users’ social interaction (Armour, 2006; Copeland, 2006; Doherty & Baker,
2005; Harris, 2005; Kadden, 2004; Rose, 2006; Rothman, 2006; Stapp, 2007; White, 2006; Yzer
& Southwell, 2008). However, some reports have claimed that people listen to MP3 players to
facilitate their social interaction (Doherty & Baker, 2005; Evangelista, 2005; Rose, 2006;
Wheeler, 2006). Prior to this study, there was no empirical research that had tested claims about
the influence of people’s MP3-player-music listening on their social interaction. Furthermore,
there had been little research of personal stereo use and our understanding of the uses and effects
of MP3-player music had been limited (Albarran et al., 2007; Bull, 2004, 2005; Ferguson et al.,
2007; Madden & Rainie, 2005).
In accordance with uses and gratifications theory, my review of the literature, and my
rationale and objectives, I proposed that certain antecedent variables – loneliness, MP3-playermusic-listening motives, time spent listening to music on an MP3 player, and audience activity –
would influence college students’ social interaction. Overall, the findings suggest that although
college students’ MP3-player-music listening did not have a large impact on time spent
socializing or participation in social activities, listening to MP3-player music tended to facilitate
post-listening discussion of music and file-sharing. In other words, college students’ MP3-player
use influenced some types of social interaction more than other types of social interaction. In the
following section, I will discuss my findings regarding (a) the influence of antecedent variables
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on different types of social interaction, (b) relationships among some of the antecedent variables,
and (c) some limitations of the present study and future directions for research.
Influence of Antecedent Variables on Social Interaction
In this study, I examined the influence of specific antecedent variables on time spent
socializing with others, participation in social activities, post-listening discussion, and filesharing because researchers had suggested that these specific types of social interaction are
affected by media use, including MP3-player-music listening (Anderson, 2008; Copeland, 2006;
Hall, 2005; Hansen & Hansen, 2000; Levy, 1987; Stapp, 2007). The results of the present study
suggest that college students’ background characteristics and motives for listening to MP3-player
music were stronger predictors of some types of social interaction than were their time spent
listening to MP3-player music, attention to songs, and elaboration on songs. Specifically,
background characteristics (i.e., demographics and loneliness) were the strongest predictors of
college students’ time spent socializing with others and participation in social activities. College
students’ MP3-player use did not have a strong impact on their time spent socializing or their
participation in social activities. Critics who have suggested that people’s MP3-player use may
be displacing their social interaction (Armour, 2006; Copeland, 2006; Doherty & Baker, 2005;
Harris, 2005; Kadden, 2004; Rose, 2006; White, 2006) should consider the influence of listeners’
background characteristics as a more viable influence of differences in their time spent
interacting with others and participation in social activities.
Similar to college students’ time spent socializing and participation in social activities,
their time spent listening to MP3-player music, attention to songs, and elaboration on songs did
not have a strong impact on their discussion or sharing of music. Rather, students’ motives to
listen to MP3-player music were the strongest predictors of their post-listening discussion and
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file-sharing. Most motives to listen to MP3-player music were positive predictors of postlistening discussion and file-sharing. Critics who have raised concern that MP3-player use may
have a negative effect on social interaction should consider this finding as an indication that the
reasons college students have for listening to MP3-player music can have a positive effect on
their discussion of music after listening and their file-sharing.
Demographic Variables
Overall, demographics explained a small to moderate amount of variance in the different
types of social interaction and were especially influential on time spent socializing with family
members, participation in social activities, and file-sharing using a music service or an MP3
player. Younger students were more likely to spend time socializing with friends, participate in
social activities, and share music files with others using an MP3 player than were older students.
Also, college students in lower grade levels were more likely than their counterparts to share
music with others using an online music service or an MP3 player. This could be due, in part, to
the fact that younger students in the early stages of their college career may not have had as wellestablished social circles as did upper-class students. Paul and Brier (2001) noted that many
students who make the transition to college experience friendsickness, a felt loss of their precollege friends. Younger college students in this study may have been spending time with others,
participating in social activities, and sharing music files in an effort to make new college friends.
Also, Shah et al. (2002) found that younger people were more likely than older people to engage
in public activities such as attending a music concert. Ellison, Steinfield, and Lampe (2007)
found that freshmen were more likely than juniors and seniors to use Facebook, an online social
network site, to meet people in their area. Freshmen may have been participating in social
activities and sharing music files with others to meet people as well.
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However, older students tended to spend more time socializing with family members than
did younger students. Chen and Katz (2009) found that some mobile phone users had better
relationships with their parents in college than they did in high school because they used mobile
phones to keep in touch when they wanted. Chen and Katz suggested that younger students may
use their cell phone to emancipate themselves from their parents control whereas older students
use their cell phone to stay in touch with their parents. It makes sense that younger college
students may be enjoying independence from their parents whereas older students may be reconnecting with their parents.
Also, college students who lived with roommates were more likely to participate in social
activities than were students who lived alone. Living with roommates may have provided
students with more opportunities to socialize with others. Cole and Robinson (2002) found that
people tended to spend time socializing with members of their household. Similarly, college
students may have tended to participate in social activities with their roommates.
The finding that female students were more likely than male students to socialize with
family members, participate in social activities, and share music files with others online has
mixed support in previous research. Some researchers have found that females tended to spend
more time socializing with relatives (Chen & Katz, 2009; Neustadtl & Robinson, 2002) and
tended to engage more in informal social activities such as going out to dinner with others (Shah
et al., 2002) than did males. For example, Chen and Katz found that female participants were
more likely than males to contact family members via cell phone for advice and support.
However, other researchers have found that men were more likely than women to download
songs (Kinnally et al., 2008) and share music files with others (Hargittai & Walejko, 2008).
Hargittai and Walejko found that women were as likely to share music files as were men when
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their Internet skill levels were the same. Female college students in this sample may have been
more skilled in music file-sharing.
Household income was a positive predictor of participation in social activities and a
negative predictor of post-listening discussion. Students from higher income households may
have had more financial means to participate in social activities such as eating out with friends at
a restaurant or attending concerts and theater performances. Shah et al. (2002) found that income
positively predicted people’s informal socialization, including attending and catering dinner
parties. However, students from households with lower incomes may have tended to engage in
post-listening discussion of music because it was less expensive than participating in social
activities, such as those mentioned above.
Loneliness
Loneliness was a consistent negative predictor of time spent socializing with others and
participation in social activities. It makes sense that college students who were lonely because
they felt like they did not have a lot in common with others were less likely to spend time
socializing with others and participate in social activities than were less-lonely students.
Research has shown that loneliness can have a negative influence on people’s social interaction
(Bell, 1985; Bell & Daly, 1985; Caplan, 2003; Perse & Rubin, 1990; Solano et al., 1982). For
example, Bell found that lonely students talked to others less during conversations than did their
counterparts. Also, Solano et al. found that lonely students’ pattern of self-disclosure inhibited
their social interaction. Lonely college students’ difficulty interacting with others may be a
disincentive for them to spend time socializing with others. Also, if students felt out of step with
others, it follows that they would not have been likely to engage in social activities with others.
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For example, Shah et al. (2002) found that those who felt socially withdrawn tended not to
participate in public concerts or go out to dinner with others.
MP3-Player-Music-Listening Motives
The results of this study suggest that college students’ strongest reasons for listening to
MP3-player music were for relaxing entertainment and to alleviate boredom. Although college
students were somewhat motivated to listen to music on an MP3 player for companionship and
social utility, they were not strongly motivated to listen for learning, social avoidance, or
fashion/status. Atmosphere creation/mood control was not identified as a reason for MP3-playermusic listening. Therefore, based on the above findings, there is not much support for critics’
claims that people typically use MP3 players to prevent social interaction with others (Armour,
2006; Doherty & Baker, 2005; Kadden, 2004; Rose, 2006). Rather, there is evidence that college
students are somewhat more motivated to listen to MP3-player music to bolster their social
interaction.
Primarily, college students tended to listen to music on their MP3 players because they
found it to be an amusing and relaxing experience. This finding is consistent with previous
research that has identified entertainment and relaxation as important reasons people listen to
music (Christenson, 1994; Lichtenstein & Rosenfeld, 1983) and use other media (Abelman &
Atkin, 2000; Greenberg, 1974; Patwardhan, 2004; Perse, 1990; Rubin, 1983; Sun et al., 2008).
For example, Ferguson et al. (2007) found that entertainment was the primary reason college
students used iPods. It makes sense that college students tended to listen to MP3-player music
for entertainment and relaxation because entertainment is one of music’s primary roles (Lull,
1985) and research has shown that college students tend to listen to music on the radio for
relaxation (Albarran et al., 2007).
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College students’ motivation to listen to MP3-player music for entertainment/relaxation
had a positive influence on their music file-sharing, especially for using an online music service.
This is consistent with Haridakis and Hanson’s (2009) finding that students who watched videos
online for entertainment tended to use a video-sharing website, YouTube, to share them with
others. Haridakis and Hanson suggested that some students shared videos on YouTube to
augment their social interaction. Similarly, college students who enjoyed listening to MP3-player
music may have used online services to share music files with others as a form of social
interaction.
Boredom alleviation was also a salient reason college students listened to music on MP3
players. This is consistent with other studies that found that adolescents listened to music to
alleviate boredom (Roe, 1985; Tarrant et al., 2000). Also, researchers have found that using MP3
players to occupy time was a strong reason for college students’ MP3-player-music listening
(Albarran et al., 2007; Ferguson et al., 2007). College students may have been listening to music
on their MP3 players when they had down-time such as commuting to and from school, between
classes, and before or after social engagements (Bull, 2005; Chen, 1998). Based on the fact that
students in the present study listened to MP3-player music by themselves for about 3 hours per
day, on average, it makes sense that those who listened to MP3-player music out of boredom
listened to occupy some of their time alone.
College students who listened to music on their MP3 players to alleviate boredom were
more likely to spend time socializing with others, especially with friends. Wei and Lo (2006) had
found that people who used cell phones to alleviate boredom tended to call friends more
frequently and spend more time making socially-oriented calls than did their counterparts.
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College students who were highly susceptible to boredom may have found that listening to MP3player music and spending time socializing with others helped occupy their time.
Although companionship (M = 3.17) was not as strong of a reason for college students’
MP3-player-music listening as were entertainment/relaxation (M = 4.27) and boredom
alleviation (M = 3.54), students were somewhat motivated to listen to MP3-player music to feel
less lonely and because the words expressed their feelings. This is consistent with previous
findings that people listened to music for lyrical content themes (Christenson, 1994; Gantz et al.,
1978; Lewis, 1981; Roe, 1985). It makes sense that someone who listened to reduce feelings of
loneliness may have also listened to pay attention to the lyrics of songs as a possible form of
social compensation for conversation (Armstrong & Rubin, 1989; Bull, 2000). Chen (1998)
found that college students listened to portable cassette players (i.e., Walkmans) for
companionship. One student stated, “Listening to my Walkman made me feel like I was not
alone” (p. 265). Tarrant et al. (2000) suggested music’s affective content may help listeners feel
less lonely.
College students who listened to MP3-player music for companionship were less likely to
share music files than were their counterparts. In other words, file-sharing does not appear to
gratify students’ motivation to feel less lonely. Haridakis and Hanson (2009) examined the
relationships among college students’ reasons for using YouTube and their video file-sharing.
Although they found that social interaction motivation (e.g., to meet others) was a positive
predictor of video file-sharing, interpersonal connection motivation (e.g., to feel less lonely) was
not a predictor. Haridakis and Hanson suggested that file-sharing may appeal to those who seek
general social interaction and not to those who seek an intimate, interpersonal connection.
Similarly, students who listened to MP3-player music for companionship may not have tended to
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share music files with others because they felt that file-sharing was not an intimate form of
interpersonal interaction.
Social utility was not a very strong reason for college students’ MP3-player-music
listening, although previous research had suggested that social utility was an important reason for
people’s television viewing (Lee & Lee, 1995; Palmgreen & Rayburn, 1979; Perse & Rubin,
1990; Rubin, 1979) and music listening (Hall, 2005; Hansen & Hansen, 2000; Houghton-Larsen,
1982; McClung et al., 2007; Roe, 1985; Tarrant et al., 2000). Students who listened to MP3player music for social utility tended to spend time socializing with acquaintances, discussing
music, and sharing music files and they may have done so to get to know people better. This is
consistent with reports that people have used MP3-player playlists to flirt with others
(Evangelista, 2005) and learn about others’ music preferences (Rose, 2006). Haridakis and
Hanson (2009) found that students who watched videos on YouTube to meet new people and to
participate in discussions tended to share and recommend videos to others. For some students,
listening to MP3-player music seems to have enhanced their efforts to socialize with others. It
also makes sense that students who listened to MP3-player music to hear songs that their friends
told them about (i.e., for social utility) tended to share music files with others. File-sharing
appears to have served as a type of social currency-exchange for students who listened to music
so they could interact with others (Kinnally, Lacayo, McClung, & Sapolsky, 2008).
However, students who listened to MP3-player music for social interaction were less
likely to socialize with family members than with acquaintances. As Weiss (1974) suggested,
people interact with different types of people, such as family members and friends, for different
reasons. Christenson (1994) noted that adolescents’ music listening tends to be oriented to their
peer groups and not their family members. College students who listen to MP3-player music for
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social utility may be spending more time with their peers than with their family members
because students may want to spend time socializing with those who share their musical
interests.
The findings of this study suggest that college students were not strongly motivated to
listen to MP3-player music to learn about themselves and others. Lull (1985) suggested that
adolescents listen to music “to learn about the world outside the home, neighborhood, or school”
(p. 365). However, college students may have been more likely to listen to terrestrial radio than
MP3-player music for news and information (Albarran et al., 2007).
College students who listened to MP3-player music to learn about themselves and others
tended to discuss music with others and share music files using an MP3 player. Those college
students who listened to MP3-player music to learn about themselves may have been focusing on
the messages of the songs. Roe (1985) suggested that music often contains information that fans
may find useful for promulgating their self-identities. For example, he noted that punk music
contains messages concerning values that may be important to the punk subculture. Students may
have been discussing some information that they had learned from listening to MP3-player
music. Also, it makes sense that college students who listened to MP3-player music to learn
about others tended to share music files with others using an MP3 player. Researchers have
found that people exchange music with others so they can get to know them and to learn about
their music preferences (Evangelista, 2005; Rose, 2006).
Contrary to some critics’ concerns discussed previously, the results of this study suggest
that social avoidance was not a strong reason for college students’ MP3-player-music listening.
Although there are reports that some people used MP3 players to avoid interacting with others
(Chen, 1998; Diva, 2004; Kadden, 2004; Rothman, 2006; White, 2006), this was not one of the
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main reasons college students listened to MP3 players. Any reduction in students’ social
interaction appeared to be influenced, in part, by their motivation to avoid social interaction and
not necessarily by mere exposure as is discussed below. Specifically, those students who listened
to MP3-player music for social avoidance were less likely than their counterparts to discuss
music after listening. This is consistent with reports that people who listen to music on
Walkmans and iPods to avoid social interaction are able to thwart unwanted conversations (Bull,
2000; 2006, Diva, 2004). For example, Bull (2000) noted that some people may use portable
audio players as a do-not-disturb sign to ward off unwanted conversations.
Among the motives examined in this study, listening to MP3-player music for
fashion/status was the least important reason for college students’ MP3-player-music listening.
This is inconsistent with prior research findings that people used some portable media devices,
such as pagers and cell phones, to be fashionable and to display their status (Kahney, 2004; Katz
& Sugiyama, 2006; Leung and Wei, 1998, 2000). Contrary to suggestions that MP3 players have
become part of users’ social identity (Katz, 2007; Katz & Sugiyama, 2005; Levy, 2004; Wheeler,
2006), college students in the present study did not tend to listen to MP3-player music because it
was a symbol of their fashion or status. This finding may be due to the fact that MP3 players are
not often used as visibly in public as are cell phones and pagers. Wei and Lo (2006) noted that
cell phones have become fashion accessories that are worn and used in noticeable ways.
Students who listened to MP3-player music to be fashionable and to express their status
tended to engage in file-sharing. Cenite, Wang, Peiwen, and Chan (2009) found that students
shared music with others to form social bonds and friendships with others who had similar
interests. Similarly, sharing music files with others may be a way for students in the present
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study to express their fashionable tastes in music and the depth and breadth of their music
collection (i.e., status).
Exposure
MP3-player-music listening was a popular past-time among college students. On average,
students spent about 3 hours per day, or about 21 hours per week, listening to MP3-player music.
This coincides with Ferguson et al.’s (2007) finding that college students spent an average of
about 2.5 hours per day using their iPods.
Students who tended to spend a lot of time listening to MP3-player music tended to share
music files with others and may have done so to acquire more music to feed their listening
appetite for novel music. As previously discussed, some critics of MP3-player-music listening
have claimed that people’s time spent listening to music on an MP3 player may displace
listeners’ time spent socializing with others (Armour, 2006; Copeland, 2006; Doherty & Baker,
2005; Harris, 2005; Kadden, 2004; Rose, 2006; Rothman, 2006; Stapp, 2007; White, 2006; Yzer
& Southwell, 2008). However, critics should reconsider their position based on this study’s
preliminary finding that college students who tended to spend a lot of time listening to MP3player music were more likely to share music files with others than were their counterparts. This
is consistent with previous research that has found that time spent using media does not tend to
decrease social interaction (Kraut et al., 2002; Mares & Woodard, 2005) and, in some cases, can
facilitate social interaction (Bickham & Rich, 2006; Jeffres et al., 2003; Katz & Rice, 2002).
Attention and Elaboration
Elaboration on songs was a significant, albeit weak, predictor of participation in social
activities. College students who thought about what the songs meant to them and others were
more likely to have participated in social activities with others than were their counterparts. This
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is consistent with research that has suggested that people who tend to elaborate on songs are
more likely than those who do not tend to think about songs a great deal to participate in social
activities, especially activities involving music such as attending a concert (Dixon, 1979, 1980).
However, some social activities, such as doing volunteer work or attending religious services
seem difficult to explain in terms of elaboration on songs. As will be discussed later, more
details, such as the genre of the song (e.g., pro-social or religious music) may help to explain the
findings more precisely in future studies.
Students who paid close attention to songs and elaborated on songs were more likely than
their counterparts to discuss music after listening and share music files with others. This finding
supports previous research that has suggested and found links among increased audience activity
(i.e., attention and elaboration) and increased social interaction (Dixon, 1979, 1980; Godlewski
& Perse, 2007; Hansen & Hansen, 1991; Ouellet, 2007; Roe, 1985). College students who paid
close attention to the songs to which they listened on their MP3 players may have had more to
talk about and share with others regarding music than did their counterparts who tended to pay
little attention to the songs.
College students whose MP3-player-music listening prompted images and memories
tended to share music files with others and may have done so to acquire songs on which they
could elaborate. Lacher and Mizerski (1994) found that college students whose music listening
prompted images and memories had a stronger intention to purchase songs than did their
counterparts. Those students who tended to think about songs and relate them to their prior
knowledge and experience may have developed a deep knowledge and understanding of songs
that served as fodder for subsequent discussions and file-sharing. Hansen and Hansen (1991)
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noted that “the amount of information extracted from lyrics depends on the depth of cognitive
processing that occurs in the course of listening” (p. 375).
As previously discussed, uses and gratifications theory claims that consumers are active
in their media use and that their activity with media influences their media effects (Blumler,
1979; Katz et al., 1974; Rubin, 2002; Rubin & Windahl, 1986). The results discussed above
suggest that college students’ increased MP3-player-music-listening activity influenced their
increased post-listening activity. Although the influence was small, this relationship supports
uses and gratification theory. Also, it is important to note that college students’ activity with
MP3-player music influenced specific types of social interaction (i.e., participation in social
activities, post-listening discussion, and file-sharing). It appears that students’ MP3-playermusic-listening activity influenced those types of social interaction that involved music.
Overall, the results of this study support uses and gratifications theory which holds that
background characteristics, motives to use media, media exposure, and activity with media
influence media effects. Together, the antecedent variables had the strongest influence on postlistening discussion, explaining almost half of the variance. Contrary to critics’ concerns that
MP3-player-music listening is displacing social interaction, these preliminary findings suggest
that college students’ MP3-player-music listening tended to facilitate their social interaction,
especially their post-listening discussion of music.
Also, the findings indicate that college students’ MP3-player use influenced certain types
of social interaction more than it did other types. Specifically, college students’ motives to listen
to MP3-player music were stronger predictors of post-listening discussion and specific types of
file-sharing than they were of time spent socializing and participation in social activities. As
discussed above, students’ time spent listening to MP3-player music and activity with MP3-
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player music influenced certain types of social interaction but not other types of social
interaction. It appears that certain types of social interaction, especially those involving music,
were more relevant to college students’ MP3-player use than were other types of social
interaction.
Relationships among Some of the Antecedent Variables
In the present study, there was no significant relationship between time spent listening to
MP3-player music and loneliness. Researchers have found that people tend to listen to music
when they feel lonely (Moore & Schultz, 1983; Perse & Rubin, 1990) and that lonely people tend
to use media more than do their counterparts (e.g., Caplan, 2003; Whitty & McLaughlin, 2007).
However, college students tended to spend time listening to MP3-player music, regardless of
loneliness.
The results of the present study appear to be consistent with some researchers’ suggestion
that certain media use tends to be instrumental, purposeful, and active (Perse, 1990; Rubin,
1984; Rubin & Perse, 1987b). Almost all of the motives to listen to MP3-player music examined
in this study related to increased exposure (i.e., time spent listening) and activity (i.e., attention
to songs and elaboration on songs). This supports Ferguson et al.’s (2007) finding that students
who were highly motivated to use iPods for relaxation and to learn about themselves spent more
time using their iPods. As previously discussed, college students’ MP3-player-music listening
may have tended to be active because MP3 players require a certain amount of physical
interaction such as wearing headphones, creating playlists of music, and selecting or skipping
songs (Bull, 2005; Knobloch & Zillmann, 2002). Also, focused attention and elaboration may
have helped college students, who listened to MP3 players for social utility and to learn about
themselves, garner topics for discussion and information for learning. For the most part, college
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students in this sample who were motivated to listen to MP3-player music invested time,
attention, and thought into music listening and their efforts seem to have paid off in increased
social interaction.
In addition to attention to songs and elaboration on songs, college students’ motives to
listen to music on an MP3 player related to loneliness. College students who were lonely because
they had been dissatisfied with their personal relationships listened to MP3-player music to avoid
conversations with others, to feel less lonely, and to learn about themselves and others. Although
lonelier college students listened to MP3-player music to avoid social interaction with others,
they may have been listening for companionship to compensate for their unsatisfactory
relationships (Armstrong & Rubin, 1989; Finn & Gorr, 1988; Perloff & Krevans, 1987; Perse &
Rubin, 1990). As previously discussed, uses and gratifications researchers have suggested that
people may be motivated to use media as a substitute for social interaction (Ebersole, 2000;
Rubin & Martin, 1998; Rubin & Rubin, 1985, 2001). Ferguson et al. (2007) suggested that
people may listen to MP3-player music as a functional alternative to social interaction. Listening
to MP3-player music for companionship included listening to feel less lonely and this motivation
related positively to loneliness. As researchers have found, people are more likely to use media
as a substitute for social interaction when they feel lonely or lacking in their interpersonal
relationships (Finn & Gorr, 1988; Papacharissi & Rubin, 2000; Perloff & Krevans, 1987; Perse
& Rubin, 1990).
The relationship between loneliness and learning is more difficult to explain. Peplau et al.
(1979) suggested that lonely people tend to feel that they have an inadequate number of
relationships. Lonely students in the present study may have been obtaining information from
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their MP3-player music because they did not feel that they had many people to whom they could
turn for information.
The results of this study suggest that lonely college students were less likely than their
counterparts to listen to music on an MP3 player for entertainment/relaxation and to alleviate
boredom. This is consistent with Perse and Rubin’s (1990) finding that lonely people were less
likely than their counterparts to watch televised soap operas for entertainment. Lonely college
students’ prolonged dissatisfaction with their personal relationships may have made it difficult
for them to have found music listening entertaining, relaxing, or an alleviation from boredom.
Limitations and Future Directions
In this study I examined the influence of certain background characteristics, motives
college students had for listening to MP3-player music, their time spent listening, attention to
songs, and elaboration on songs on their social interaction. The preliminary findings should help
shed light on the relationships among college students MP3-player use and their social
interaction. However, the results of this study are limited and should be augmented with future
research. Specifically, the sample, scope, measurement, and data collection of this study can and
should be improved upon.
Firstly, the sample of the study had some limitations. I chose to examine a convenience
sample of college students because prior research suggested that they were likely owners and
users of MP3 players (Ferguson et al., 2007). However, the results of this study are limited to
this specific population and should not be generalized to different types of users. Rather,
researchers should replicate this study with other populations to build upon the findings and
make comparisons between populations. The race/ethnicity of the current sample was primarily
Caucasian (86.4%). Future research should seek to study a more diverse population. Although
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the results of this study found that loneliness was a significant predictor of social interaction, the
participants, on average, were not highly lonely (M = 2.04, SD = 0.62). It may be worthwhile to
replicate this study with a sample that has more variability in terms of loneliness. Also, some of
the background characteristics examined in this study, such as grade level and number of
roommates, may be less relevant to some other populations.
Secondly, the scope of this study was limited to examining only (a) a few background
characteristics and motives; (b) one type each of exposure, attention, and elaboration; and (c)
four types social interaction. Also, the measurement of these variables had some limitations. In
accordance with uses and gratifications theory, the results of this study suggest that background
characteristics were important predictors of media effects. Specifically, loneliness and MP3player-use motives were stronger predictors of some types of social interaction than were college
students’ time spent listening and activity with MP3 player music. Therefore, other background
characteristics may help to explain additional variance in some types of social interaction. For
example, people who tend to be introverted may be less likely than extraverts to engage in types
of social interaction. Extraversion is a background characteristic associated with being talkative,
sociable, and outgoing. Someone who is low in extraversion (i.e., introverted) tends to be quiet,
passive, and unsociable (Eysenck & Eysenck, 1985). Also, researchers have linked extraversionintroversion, as well as other personality traits, to people’s music genre preferences, a type of
exposure that should be considered in future studies (Hall, 2005; Rentfrow & Gosling, 2003).
Also, researchers have found important relationships among people’s unwillingness to
communicate, their media use, and their social interaction (Armstrong & Rubin, 1989; Leung,
2007; Ma & Leung, 2006; Papacharissi & Rubin, 2000). Unwillingness to communicate
describes an individual’s “chronic tendency to avoid and/or devalue oral communication”
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(Burgoon, 1976, p. 60). Armstong and Rubin found that people who were unwilling to
communicate tended to listen to talk radio programs to escape and for companionship. Also,
Papacharissi and Rubin (2000) found that Internet users who felt rewarded from their
communication with others tended to go online to participate in discussions. Furthermore, Ma
and Leung found that people who were unwilling to communicate because they felt socially
anxious were less likely to disclose information about themselves to others via an online instant
messaging program than were those who were willing to communicate. Researchers need to
examine users’ degree of unwillingness to communicate further because this background
characteristic may influence their use of MP3 players and their social interaction.
Researchers should acknowledge the potential for individual characteristics such as
loneliness, extraversion, and unwillingness to communicate to be outcome variables of people’s
MP3 player use. Uses and gratifications theory claims that these types of background
characteristics influence media use and effects. However, media uses and effects are often
cyclical and linear perspectives such as uses and gratifications may not capture the complex
relationships among people’s MP3 player listening and their social interaction. A panel study of
people’s MP3-player use and their social interaction may help researchers examine changes in
background characteristics and their social interaction over time.
In this study, I examined only a few motives for listening to MP3-player music that were
derived from previous research and reports. However, a more comprehensive set of MP3-playermusic-listening motives could be developed. Researchers should consider examining motives
derived from previous research that were beyond the scope of this study. For example, Wei and
Lo, (2006) found that some people used cell phones for mobility, to avoid having to rely on fixed
public phones. People’s motive to use media for mobility may be especially important for music
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delivery devices that have converged with other portable media technologies (Albarran et al.,
2007).
In addition to examining other motives, researchers should re-examine the motives
identified in this study to test their reliability. For example, the findings of this study suggest that
college students listened to music on MP3 players to alleviate boredom. However, the reliability
of the boredom-alleviation factor was low. Also, listening to MP3-player music for fashion/status
was not a strong motivation for college students in this sample. College students may have not
used MP3 players for to set themselves apart from their peers if most college students use an
MP3 player. Fashion/status may be an important motivation to consider in studies of other
populations in which MP3 player use may be less pervasive. Future studies should also
differentiate among users’ types of MP3 players to examine fashion/status differences.
Also, researchers should use qualitative and quantitative methods of inquiry to explore
and examine people’s motives to listen to music on an MP3 player. For example, Bull (2005)
interviewed people about their MP3-player-listening habits. He found common themes of MP3player use and speculated about their reasons for their MP3-player use. Some of the items used
in this study to measure college students’ motives to listen to MP3-player music were derived
from Bull’s summarized reports. However, researchers should strive to perform content analysis
and factor analysis of interview data first-hand. For example, researchers could ask students to
list as many reasons as they can for their MP3-player-music-listening and subject the responses
from a large sample to factor analysis to reveal the underlying structure of their motives.
It may have been difficult for participants to estimate the amount of time they spent
listening to MP3-player music and socializing with other people. A more direct method of
assessing exposure and social interaction may provide more accurate data. For example,
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Gershuny (2002) used data from time-use diaries to study people’s time spent using a personal
computer. Participants were asked to keep track of their computing time each day for a week.
Future researchers could incorporate time-use diaries to better estimate people’s time spent
listening to MP3-player music.
The results of the present study suggest that audience activity (i.e., attention to songs and
elaboration on songs) influenced participation in social activities, post-listening discussion, and
file-sharing. However, researchers should examine other types of activity that may occur before,
during, and after MP3-player-music listening. Levy and Windahl (1984) suggested that people’s
activity with media before consumption, such as selectivity of program content, may be an
important predictor of media effects. Pre-listening activities, such as creating a playlist, may be
an important part of people’s MP3-player use and may influence types of social interaction such
as post-listening discussion and file-sharing. For example, Bull (2005) found that some iPod
users spent a lot of time preparing playlists of songs for future events such as commuting to
work.
Also, the results of this study suggest that social interaction is a multidimensional concept
and college students’ MP3-player use influences some types of social interaction more than
others. Therefore, there may be additional types of social interaction that may be relevant to
college students’ post-listening activity. For example, the size and variation of students’ social
circles may indicate their potential for social interaction with others (Cole & Robinson, 2002;
Meeuwesen, 2006; Russell et al., 1980). Kraut et al. (2002) examined the size of Internet users’
social circles as an indicator of their social interaction. College students’ MP3-player-music
listening may influence the size and type of their social circles as well.
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Students’ time spent interacting socially included a combination of online and offline
interactions. Although students’ time spent interacting with others was analyzed separately as
time spent interacting with family members, friends, and acquaintances, it is not clear whether
their interaction was online or offline. Future research should examine social interaction online
and offline separately. Furthermore, the types of people with whom college students spent time
socializing were important to consider in my study. For example, students who listened to MP3player music for social utility were more likely to spend time socializing with acquaintances than
with family members. However, participants may have had some difficulty estimating their time
spent socializing with specific types of people during a typical week Future studies’ estimates of
social interaction with family members, friends, and acquaintances should be derived with
instruments such as time-use diaries or questionnaires with specific time-charts (e.g., Gershuny,
2002). These alternate forms of measurement may be more accurate measures of students’ time
spent socializing with family members, friends, and acquaintances.
Similar to the measure of time spent socializing with others, the instrument used to
measure college students’ frequency of music file-sharing proved to be problematic. It was
assumed that college students who shared files with others would use a variety of sources to
exchange music. However, students in this sample identified with only two of the six sources
adapted from the Madden and Rainie (2005) Daily Tracking Survey. Therefore, students’
average score was not a reliable measure of file-sharing activity and the two most-reported
sources were treated as separate outcome variables. Future research should develop and use a
more robust measure of file-sharing to help explain the nuances of people’s music exchanges.
For example, the single-item measure of file-sharing using an MP3 player did not differentiate
among the various ways students may have used the device to share music such as connecting an
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MP3 player to someone’s computer to download certain files or exchanging playlists or entire
MP3 players (Evangelista, 2005; Madden & Rainie, 2005; Rainie et al., 2004; Rose, 2006;
Yaksich, 2007).
Thirdly, the data collection method used in this study had some limitations. I used a selfreport online survey to collect participants’ information. Online surveys have proven to be an
efficient and cost-effective method of collecting accurate information (Davis, 1999; Pettit, 1999).
However, Schmidt (1997) noted that online surveys may be susceptible to multiple submissions
from one participant or intentionally inaccurate submissions from uninvited participants. He
suggested that researchers need to take certain precautions such as monitoring the origin of
survey submissions to guard against duplicate or unauthorized guests.
Also, Davis (1999) compared online and paper-and-pencil survey results and he found
that, online, women reported higher amounts of self-focused rumination than did women who
completed the paper-and-pencil version of the survey. Davis suggested that women may have felt
less inhibited about sharing their feelings online than they did on the paper-and-pencil survey.
Although this may be an advantage for some types of research, women’s increased disclosure in
online surveys may artificially inflate differences between men’s and women’s self-reports.
Ideally, multiple methods of inquiry should be utilized by researchers when re-examining the
results of this study to guard against any methodological effects.
Overall, critics have raised concerns that people’s MP3-player use may be reducing their
social interaction (Copeland, 2006; Doherty & Baker, 2005; Harris, 2005; Kadden, 2004; Rose,
2006; Rothman, 2006; Stapp, 2007; White, 2006). However, the preliminary findings of the
present study suggest that MP3-player-music listening had a positive effect on certain types of
social interaction. Specifically, college students’ MP3-player-music listening tended to facilitate
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their discussion of music after listening and file-sharing with others. MP3-player use did not
have as much influence on time spent socializing and participation in social activities as did
loneliness and certain demographics. College students’ background characteristics and reasons
for listening to MP3-player music had a greater influence on their social interaction than did their
time spent listening to MP3-player music or their activity with MP3-player music. Students
tended to listen to MP3-player music for entertainment/relaxation and to alleviate boredom. They
tended to listen to socialize with others somewhat but did not listen much to avoid interacting
with others.
Students’ time spent listening to MP3-player music and their activity with MP3-player
music had a small impact on types of social interaction concerning music. Ultimately, students’
time spent listening to MP3-player music did not displace their time spent socializing with others
as critics had suggested. Rather, time spent listening to MP3-player music facilitated postlistening discussion and file-sharing. These findings largely support previous media effects
studies that have found that people’s use of media does not necessarily displace their social
interaction and, in some circumstances, people bolster their social interaction by using media
(Cole & Robinson, 2002; Hampton & Wellman, 2003; Katz & Rice, 2002; Kraut et al., 2002;
Larson & Kubey, 1983; Mares & Woodard, 2005; Mikami, 2002; Shah et al., 2002). Therefore,
based on the above discussion, the findings of this study address some criticisms of MP3-player
use and extend uses and gratifications research to shed light on a previously understudied
medium, MP3-player music.
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Appendix A
Kent State University Consent Form
Informed Consent to Participate in a Research Study
Kent State University
Study Title: MP3 Player Use
Principle Investigator: Peter N. Miraldi, Doctoral Candidate
School of Communication Studies
Taylor Hall; Kent State University; Kent, OH 44242
Phone: (814) 633-1080; E-mail: [email protected]
You are being invited to participate in a research study. This consent form will provide you with
information on the research project, what you will need to do, and the associated risks and
benefits of the research. Your participation is voluntary. Please read this form carefully. It is
important that you fully understand the research in order to make an informed decision.
Purpose: The purpose of this research is to understand college students’ MP3 player use better.
To that end, this survey asks questions about your behavior regarding your MP3 player use,
including your reasons for listening to music on an MP3 player, time spent listening, activity
with music, social interaction, background characteristics, and demographics.
Procedures: If you decide to take part in this study, you will be asked to complete a survey about
yourself and your MP3 player use. The survey should take about 30 minutes to complete.
Benefits: This research will not benefit you directly. However, your participation in this study will
help us to better understand the uses and effects MP3 players.
Risks & Discomforts: There are no anticipated risks beyond those encountered in everyday life.
Privacy & Confidentiality: Your study related information will be kept confidential within the
limits of the law. Research participants will not be identified in any publication or presentation of
research results; only aggregate data will be used.
Compensation: You will receive 2.5 research participation points for participating in this study.
Voluntary Participation: Taking part in this research study is entirely up to you. You may
choose not to participate or you may discontinue your participation at any time without penalty
or loss of benefits to which you are otherwise entitled.
Contact Information: If you have any questions or concerns about this research, you may
contact Peter N. Miraldi at (814) 633-1080 or Dr. Paul Haridakis at (330) 672-0174. This project
has been approved by the Kent State University Institutional Review Board. If you have any
136
questions about your rights as a research participant or complaints about the research, you may
call the IRB at (330) 672-2704.
Consent Statement: You must be 18 years of age or older and use a portable MP3 player to
participate in this study. Your completion and submission of this survey will be indicative of
your consent to participate in this research study. You may print a copy of this consent form.
Once you submit your consent, you will be directed to the first page of the study. If you do not
feel comfortable participating in this study, you may stop at any time.
Submit
137
Appendix B
Demographics
Please answer the following demographic questions. Your answers will remain confidential and
will not be shared with anyone. Thank you for your help.
1. How old are you as of your last birthday? __________________
2. What is your gender?
_____ Male
_____ Female
3. What is your grade level?
_____ Freshman
_____ Sophomore
_____ Junior
_____ Senior
4. What is your household income?
_____ less than $30,000
_____ between $30,000 and $50,000
_____ between $50,000 and $75,000
_____ more than $75,000
5. How many people live in your home in addition to yourself (i.e., not counting yourself)? ____
138
6. What is your race/ethnicity?
_____ Caucasian
_____ African-American
_____ Hispanic
_____ Asian or Pacific Islander
_____ Middle Eastern
_____ American Indian or Alaskan native
_____ Other
139
Appendix C
The Revised UCLA Loneliness Scale
Adapted from:
Russell, D., Peplau, L. A., & Curtona, C. E. (1980). The revised UCLA Loneliness Scale:
Concurrent and discriminant validity evidence. Journal of Personality and Social
Psychology, 39(3), 467-480.
Directions: Indicate how often you feel the way described in each of the following statements.
Never
Rarely
Sometimes
Often Always
1. I feel in tune with the people around me.*
1
2
3
4
5
2. I lack companionship.
1
2
3
4
5
3. There is no one I can turn to.
1
2
3
4
5
4. I do not feel alone.*
1
2
3
4
5
5. I feel part of a group of friends.*
1
2
3
4
5
6. I have a lot in common with the
people around me.*
1
2
3
4
5
7. I am no longer close to anyone.
1
2
3
4
5
8. My interests and ideas are not shared by
those around me.
1
2
3
4
5
9. I am an outgoing person.*
1
2
3
4
5
10. There are people I feel close to.*
1
2
3
4
5
11. I feel left out.
1
2
3
4
5
12. My social relationships are superficial.
1
2
3
4
5
13. No one really knows me well.
1
2
3
4
5
14. I feel isolated from others.
1
2
3
4
5
15. I can find companionship when I want it.*
1
2
3
4
5
140
16. There are people who really understand me.* 1
2
3
4
5
17. I am unhappy being so withdrawn.
1
2
3
4
5
18. People are around me but not with me.
1
2
3
4
5
19. There are people I can talk to*
1
2
3
4
5
20. There are people I can turn to.*
1
2
3
4
5
*Item should be reverse coded before scoring.
141
Appendix D
MP3 Motive Scale
Adapted from:
Ferguson, D. A., Greer, C. F., & Reardon, M. E. (2007). Uses and gratifications of MP3 players
by college students: Are iPods more popular than radio? Journal of Radio Studies, 14(2),
102-121.
Additional items adapted from:
Bull, M. (2000). Sounding out the city: Personal stereos and the management of everyday life.
New York: Berg.
Bull, M. (2005). No dead air! The iPod and the culture of mobile listening. Leisure Studies,
24(4), 343-355.
McClung, S., Pompper, D., & Kinnally, W. (2007). The functions of radio for teens: Where radio
fits among youth media choices. Atlantic Journal of Communication, 15(2), 103-119.
Roe, K. (1985). Swedish youth and music: Listening patterns and motivations. Communication
Research, 12(3), 353-362.
Wei, R., & Lo, V. (2006). Staying connected while on the move: Cell phone use and social
connectedness. New Media & Society, 8(1), 53-72.
Instructions: Here are some reasons that people have given for why they listen to music on a
portable MP3 player. Please mark whether you strongly disagree, disagree, are neutral, agree, or
strongly agree that each reason is like your own reason for listening to music on a portable MP3
player.
“I listen to music on a portable MP3 player...”
Strongly
disagree
Disagree
Neutral
Agree
Strongly
agree
1. Because it’s a habit, just something I do.
1
2
3
4
5
2. Because it relaxes me.
1
2
3
4
5
3. Because it allows me to unwind.
1
2
3
4
5
4. So I can forget about school, work
or other things.
1
2
3
4
5
5. Because it’s a pleasant rest.
1
2
3
4
5
6. So I can get away from what I’m doing.
1
2
3
4
5
Relaxation/Escape
142
Stimulation
1. Because it helps me learn things about
myself and others.
1
2
3
4
5
2. Because it’s thrilling.
1
2
3
4
5
3. So I can talk with others about what I find.
1
2
3
4
5
4. Because it’s exciting.
1
2
3
4
5
5. Because it helps me learn what
could happen to me.
1
2
3
4
5
6. So I can try out media content that my friends
tell me about.
1
2
3
4
5
1. Because it entertains me.
1
2
3
4
5
2. Because it’s enjoyable.
1
2
3
4
5
3. Because it amuses me.
1
2
3
4
5
1. Because it makes me feel less lonely.
1
2
3
4
5
2. So I won’t have to feel alone.
1
2
3
4
5
3. So I can be like my friends and family
who use MP3 players.
1
2
3
4
5
1. Because it gives me something to
occupy my time.
1
2
3
4
5
2. Just because it is available.
1
2
3
4
5
3. When I have nothing better to do.
1
2
3
4
5
Entertainment
Loneliness
Boredom
143
Social Utility
1. Because I talk with friends
about things I hear.
1
2
3
4
5
2. To hear songs that my friends tell me about.
1
2
3
4
5
3. To learn things about myself and others.
1
2
3
4
5
4. Because my friends talk about
the things they hear.
1
2
3
4
5
1. So I can get away from the rest of the family
or others.
1
2
3
4
5
2. So I don’t have to interact with others.
1
2
3
4
5
3. Because it’s an excuse not to talk to somebody.
1
2
3
4
5
4. To avoid social interaction.
1
2
3
4
5
5. To isolate myself from others.
1
2
3
4
5
6. To avoid conversations.
1
2
3
4
5
1. Because it helps me get into the right mood
1
2
3
4
5
2. Because it creates a good atmosphere
when I am with others.
1
2
3
4
5
3. Because music fits well in my life
1
2
3
4
5
1. Because I want to listen to the words.
1
2
3
4
5
2. Because the words express how I am feeling.
1
2
3
4
5
Social Avoidance
Atmosphere Creation/Mood Control
Attention to Lyrics
144
Fashion/Status
1. To look fashionable.
1
2
3
4
5
2. To look cool.
1
2
3
4
5
3. To look stylish.
1
2
3
4
5
4. To avoid looking old-fashioned.
1
2
3
4
5
145
Appendix E
Time Spent Listening
Adapted from:
Lin, C. A. (2006). Predicting satellite radio adoption via listening motives, activity, and format
preference. Journal of Broadcasting & Electronic Media, 50(1), 140-159.
1. How many hours and minutes do you spend listening to music by yourself on a portable MP3
player on an average weekday?
______ hours ______ minutes
2. How many hours and minutes do you spend listening to music by yourself on a portable MP3
player on an average weekend day?
______ hours ______ minutes
146
Appendix F
Listening Attention
Adapted from:
Rubin, A. M., Perse, E. M., & Taylor, D. S. (1988). A methodological examination of
cultivation. Communication Research, 15, 107-134.
Additional items adapted from:
Perse, E. M. (1990). Audience selectivity and involvement in the newer media environment.
Communication Research, 17(5), 675-697.
Instructions: Read each statement and indicate whether you strongly disagree, disagree, are
neutral, agree, or strongly agree with each.
Strongly
disagree
Disagree
Neutral
Agree
Strongly
agree
1. I’m often thinking about something else when
I’m listening to music on an MP3 player.*
1
2
3
4
5
2. I often miss parts of the songs when I listen
to music on my MP3 player.*
1
2
3
4
5
3. My mind often wanders when I listen to
music on an MP3 player.*
1
2
3
4
5
4. I pay close attention to the songs when I
listen to music on an MP3 player.
1
2
3
4
5
5. I listen carefully when I listen to music
on an MP3 player.
1
2
3
4
5
6. When I listen to music on an MP3 player,
I try to concentrate on the songs.
1
2
3
4
5
7. I put a lot of mental effort into my MP3
player music listening.
1
2
3
4
5
* Item is reverse coded for analysis
147
Appendix G
Listening Elaboration Scale
Adapted from:
Lacher, K. T., & Mizerski, R. (1994). An exploratory study of the responses and relationships
involved in the evaluation of, and the intention to purchase music. Journal of Consumer
Research, 21(2), 366-380.
Additional items adapted from:
Perse, E. M. (1990). Audience selectivity and involvement in the newer media environment.
Communication Research, 17(5), 675-697.
Instructions: Read each statement and indicate whether you strongly disagree, disagree, are
neutral, agree, or strongly agree with each.
Strongly
disagree
Disagree
Neutral
Agree
Strongly
agree
1. When I’m listening to music on an MP3 player,
I think about what the songs mean to me.
1
2
3
4
5
2. When I’m listening to music on an MP3 player,
I think about how the songs relate to other
things that I know.
1
2
3
4
5
3. When I’m listening to music on an MP3 player,
I think about what the songs mean to
other people.
1
2
3
4
5
4. When I’m listening to music on an MP3 player,
I think about the songs over and over again.
1
2
3
4
5
5. When I’m listening to music on an MP3 player,
the songs create a picture in my mind.
1
2
3
4
5
6. When I’m listening to music on an MP3 player,
the songs make me remember something.
1
2
3
4
5
7. When I’m listening to music on an MP3 player,
the songs prompt images in my mind.
1
2
3
4
5
148
Appendix H
Sociability Questions
Adapted from:
Cole, J., & Robinson, J. P. (2002). Internet use and sociability in the UCLA data: A simplified
MCA analysis. IT & Society, 1(1), 202-218.
Instructions: Please answer each of the following questions about your contacts with friends,
family, and acquaintances by providing your information in the spaces provided.
1. During a typical week, how many hours or minutes do you spend socializing (face-to-face,
online, by phone, etc.) with family members?
______ hours _______ minutes
2. During a typical week, how many hours or minutes do you spend socializing (face-to-face,
online, by phone, etc.) with friends?
______ hours _______ minutes
3. During a typical week, how many hours or minutes do you spend socializing (face-to-face,
online, by phone, etc.) with acquaintances?
______ hours _______ minutes
149
Appendix I
Social Participation
Adapted from:
Shklovski, I., Kraut, R., & Rainie, L. (2004). The Internet and social participation: Contrasting
cross-sectional and longitudinal analyses. Journal of Computer-Mediated
Communication, 10(1).
Additional items adapted from:
Anderson, B. (2008). The social impact of broadband household Internet access. Information,
Communication, & Society, 11(1), 5-24.
Instructions: Over the past year, how often have you done each of the following things with
other people?
Never
Rarely
Sometimes
Often
Very Often
1. Called a friend or relative just to talk.
1
2
3
4
5
2. Visited with family or friends.
1
2
3
4
5
3. Done volunteer work.
1
2
3
4
5
4. Attended religious services
with friends or family.
1
2
3
4
5
5. Met with friends.
1
2
3
4
5
6. Had a meal in a restaurant or café, or gone for
a drink to a bar with friends or family.
1
2
3
4
5
7. Gone to the cinema, a concert, theatre or
watched live sport with friends or family.
1
2
3
4
5
8. Played sports, kept fit or gone walking
with friends or family.
1
2
3
4
5
150
Appendix J
Post-Listening Discussion of Music
Adapted from:
Rubin, A. M., & Perse, E. M. (1987a). Audience activity and soap opera involvement: A uses
and effects investigation. Human Communication Research, 14, 246-268.
Instructions: Read each statement and indicate whether you strongly disagree, disagree, are
neutral, agree, or strongly agree with each.
Strongly
disagree
Disagree
Neutral
Agree
Strongly
agree
1
2
3
4
5
2. After I listen to music on an MP3 player, I often
talk about the artist(s) or band(s) with others.
1
2
3
4
5
3. I often discuss with others the upcoming
performances of artists or bands that
I have recently listened to on an MP3 player.
1
2
3
4
5
4. I often discuss with others the lyrics of songs
I have recently listened to on an MP3 player.
1
2
3
4
5
5. I often talk with others about the genre(s)
of music that I have recently listened to on
an MP3 player.
1
2
3
4
5
1. After I listen to music on an MP3 player,
I often talk about the songs with others.
151
Appendix K
Music File-Sharing
Adapted from:
Madden, M., & Rainie, L. (March, 2005). Music and video downloading moves beyond P2P.
Pew Internet & American Life Project. Retrieved April 27, 2009 from
http://www.pewinternet.org/pdfs/PIP_Filesharing_March05.pdf
Instructions: Please indicate how often you use each of the following sources to share music files
with others:
Never
Rarely
Sometimes
Often
Very Often
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
music magazines or musicians’ homepages. 1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
1. A peer-to-peer network
like Kazaa or Morpheus.
2. An online music service like iTunes
or BuyMusic.com.
3. Music blogs or online journals.
4. Other music-related websites, such as online
5. Someone’s iPod or other MP3 player.
6. E-mail or instant messages
you send or receive.
152
Appendix L
Regression Analysis Tables for Research Question 7
Table 10
Summary of Regression Analysis for Variables Predicting Overall Time Spent Socializing with
Others
Variable
B
SE B
β
Step 1
Age
Gender
Grade Level
Household Income
Number of Roommates
.06
6.61
-1.66
1.69
-.23
.66
4.59
2.63
1.86
1.12
.01
.07
-.03
.05
-.01
Step 2
Age
Gender
Grade Level
Household Income
Number of Roommates
Loneliness
.29
2.93
-1.96
1.27
-.41
-15.31
.65
4.58
2.58
1.82
1.10
3.57
.02
.03
-.04
.04
-.02
-.21***
.19
2.05
-1.95
1.25
-.35
-12.94
.66
4.74
2.60
1.85
1.10
4.08
.02
.02
-.04
.03
-.02
-.18**
-2.03
-4.84
-.81
-.69
-2.38
-.17
6.95
2.73
3.20
3.07
3.03
4.46
3.71
3.32
-.04
-.08
-.02
-.01
-.03
-.00
.12*
Step 3
Age
Gender
Grade Level
Household Income
Number of Roommates
Loneliness
MP3-Player-Use Motives
Social Avoidance
Fashion/Status
Social Utility
Learning
Entertainment/Relaxation
Companionship
Boredom Alleviation
153
Variable
Step 4
Age
Gender
Grade Level
Household Income
Number of Roommates
Loneliness
MP3-Player-Use Motives
Social Avoidance
Fashion/Status
Social Utility
Learning
Entertainment/Relaxation
Companionship
Boredom Alleviation
Time Spent Listening
Audience Activity
Attention to Songs
Elaboration on Songs
B
SE B
β
.30
1.14
-1.86
1.65
-.45
-12.74
.67
4.88
2.60
1.87
1.10
4.09
.02
.01
-.04
.05
-.02
-.18**
-2.38
-4.29
-1.55
-1.47
-4.01
-1.97
6.87
.28
2.76
3.22
3.11
3.08
4.58
3.90
3.35
.80
-.05
-.07
-.03
-.03
-.05
-.03
.12*
.02
-1.88
7.30
4.34
4.34
-.02
.11
Note. R = .10, R² = .01, F(5, 406) = 0.88, p = .50 for step 1. R = .23, R² = .05, Δ R² = .04, F(6,
405) = 3.82, p < .001 for step 2. R = .27, R² = .07, Δ R² = .02, F(13, 398) = 2.36, p < .01 for step
3. R = .28, R² = .08, Δ R² = .01, F(16, 395) = 2.10, p < .01 for step 4.
* p < .05, ** p < .01, *** p < .001
154
Table 11
Summary of Regression Analysis for Variables Predicting Time Spent Socializing with
Family Members
Variable
β
B
SE B
Step 1
Age
Gender
Grade Level
Household Income
Number of Roommates
1.24
4.30
-1.33
.34
-.34
.22
1.50
.86
.61
.37
.29***
.14**
-.08
.03
-.05
Step 2
Age
Gender
Grade Level
Household Income
Number of Roommates
Loneliness
1.29
3.51
-1.39
.25
-.37
-3.26
.22
1.51
.85
.60
.36
1.18
.30***
.11*
-.08
.02
-.05
-.13**
1.27
3.35
-1.59
.10
-.33
-3.51
.22
1.56
.85
.61
.36
1.34
.30***
.11*
-.09
.01
-.04
-.14**
-.44
-.59
-2.17
-.35
.06
.84
-.92
.90
1.05
1.01
1.00
1.46
1.22
1.09
-.03
-.03
-.13*
-.02
.00
.04
-.05
1.29
3.47
-1.51
.17
-.36
.22
1.60
.85
.61
.36
.30***
.11*
-.09
.01
-.05
Step 3
Age
Gender
Grade Level
Household Income
Number of Roommates
Loneliness
MP3-Player-Use Motives
Social Avoidance
Fashion/Status
Social Utility
Learning
Entertainment/Relaxation
Companionship
Boredom Alleviation
Step 4
Age
Gender
Grade Level
Household Income
Number of Roommates
155
Variable
Loneliness
MP3-Player-Use Motives
Social Avoidance
Fashion/Status
Social Utility
Learning
Entertainment/Relaxation
Companionship
Boredom Alleviation
Time Spent Listening
Audience Activity
Attention to Songs
Elaboration on Songs
B
SE B
Β
-3.53
1.34
-.14**
-.42
-.35
-2.47
-.64
.61
.06
-.81
.07
.91
1.06
1.02
1.01
1.50
1.28
1.10
.26
-.03
-.02
-.14*
-.04
-.02
.00
-.04
.01
1.01
2.22
1.42
1.42
.04
.09
Note. R = .30, R² = .09, F(5, 406) = 8.30, p < .001 for step 1. R = .33, R² = .11, Δ R² = .02,
F(6, 405) = 8.30, p < .001 for step 2. R = .37, R² = .14, Δ R² = .03, F(13, 398) = 4.77, p <
.001 for step 3. R = .38, R² = .14, Δ R² = .01, F(16, 395) = 4.13, p < .001 for step 4.
* p < .05, ** p < .01, *** p < .001
156
Table 12
Summary of Regression Analysis for Variables Predicting Time Spent Socializing with Friends
Variable
B
SE B
β
Step 1
Age
Gender
Grade Level
Household Income
Number of Roommates
-1.38
.42
-.72
.86
.41
.45
3.15
1.80
1.27
.77
-.16**
.01
-.02
.04
.03
Step 2
Age
Gender
Grade Level
Household Income
Number of Roommates
Loneliness
-1.22
-2.12
-.93
.57
.30
-10.59
.45
3.14
1.77
1.25
.75
2.45
-.14**
-.03
-.03
.02
.02
-.21***
-1.27
-2.81
-1.01
.58
.31
-8.52
.45
3.23
1.77
1.26
.75
2.78
-.15**
-.05
-.03
.02
.02
-.17**
-1.53
-3.07
-1.63
.68
-.78
-.54
6.65
1.86
2.18
2.09
2.07
3.04
2.53
2.27
-.05
-.08
-.05
.02
-.01
-.01
.16**
-1.23
-3.26
-1.00
.75
.27
.46
3.34
1.78
1.28
.76
-.14**
-.05
-.03
.03
.02
Step 3
Age
Gender
Grade Level
Household Income
Number of Roommates
Loneliness
MP3-Player-Use Motives
Social Avoidance
Fashion/Status
Social Utility
Learning
Entertainment/Relaxation
Companionship
Boredom Alleviation
Step 4
Age
Gender
Grade Level
Household Income
Number of Roommates
157
Variable
Loneliness
MP3-Player-Use Motives
Social Avoidance
Fashion/Status
Social Utility
Learning
Entertainment/Relaxation
Companionship
Boredom Alleviation
Time Spent Listening
Audience Activity
Attention to Songs
Elaboration on Songs
SE B
β
-8.42
2.80
-.17**
-1.70
-2.89
-1.87
.40
-1.32
-1.12
6.58
.13
1.89
2.20
2.13
2.10
3.13
2.67
2.29
.55
-.05
-.07
-.05
.01
-.02
-.03
.16**
.01
-1.17
2.64
2.96
2.97
-.02
.06
B
Note. R = .18, R² = .03, F(5, 406) = 2.69, p < .05 for step 1. R = .27, R² = .08, Δ R² = .04, F(6,
405) = 5.46, p < .001 for step 2. R = .32, R² = .10, Δ R² = .03, F(13, 398) = 3.43, p < .001 for step
3. R = .32, R² = .10, Δ R² = .00, F(16, 395) = 2.83, p < .001 for step 4.
* p < .05, ** p < .01, *** p < .001
158
Table 13
Summary of Regression Analysis for Variables Predicting Time Spent Socializing with
Acquaintances
Variable
B
SE B
β
Step 1
Age
Gender
Grade Level
Household Income
Number of Roommates
.20
1.89
.39
.49
-.31
.23
1.60
.92
.65
.39
.05
.06
.02
.04
-.04
Step 2
Age
Gender
Grade Level
Household Income
Number of Roommates
Loneliness
.22
1.54
.36
.45
-.33
-1.46
.23
1.63
.92
.65
.39
1.27
.05
.05
.02
.04
-.04
-.06
.19
1.51
.65
.57
-.33
-.91
.23
1.68
.92
.65
.39
1.45
.04
.05
.04
.05
-.04
-.04
-.06
-1.18
2.99
-1.02
-1.66
-.48
1.22
.97
1.13
1.09
1.07
1.58
1.31
1.18
-.00
-.06
.17**
-.06
-.06
-.02
.06
.24
.93
.65
.74
-.36
.24
1.73
.92
.66
.39
.06
.03
.04
.06
-.05
Step 3
Age
Gender
Grade Level
Household Income
Number of Roommates
Loneliness
MP3-Player-Use Motives
Social Avoidance
Fashion/Status
Social Utility
Learning
Entertainment/Relaxation
Companionship
Boredom Alleviation
Step 4
Age
Gender
Grade Level
Household Income
Number of Roommates
159
Variable
Loneliness
MP3-Player-Use Motives
Social Avoidance
Fashion/Status
Social Utility
Learning
Entertainment/Relaxation
Companionship
Boredom Alleviation
Time Spent Listening
Audience Activity
Attention to Songs
Elaboration on Songs
B
SE B
β
-.79
1.45
-.03
-.26
-1.05
2.79
-1.24
-2.08
-.90
1.10
.09
.98
1.14
1.10
1.09
1.62
1.38
1.18
.28
-.02
-.05
.16*
-.07
-.07
-.05
.05
.02
-1.72
2.43
1.53
1.54
-.06
.10
Note. R = .09, R² = .01, F(5, 406) = 0.69, p = .63 for step 1. R = .11, R² = .01, Δ R² = .00, F(6,
405) = 0.80, p = .57 for step 2. R = .19, R² = .04, Δ R² = .03, F(13, 398) = 1.16, p = .31 for step
3. R = .21, R² = .04, Δ R² = .01, F(16, 395) = 1.14, p = .32 for step 4.
* p < .05, ** p < .01, *** p < .001
160
Table 14
Summary of Regression Analysis for Variables Predicting Participation in Social Activities
Variable
β
B
SE B
Step 1
Age
Gender
Grade Level
Household Income
Number of Roommates
-.03
.29
-.02
.05
.04
.01
.06
.03
.02
.01
-.16**
.24***
-.03
.10*
.12**
Step 2
Age
Gender
Grade Level
Household Income
Number of Roommates
Loneliness
-.02
.21
-.03
.04
.03
-.31
.01
.06
.03
.02
.01
.04
-.13**
.17***
-.04
.09
.11*
-.32***
-.02
.19
-.02
.05
.03
-.30
.01
.06
.03
.02
.01
.05
-.12*
.16**
-.03
.09*
.11*
-.31***
-.04
.01
.00
.03
.01
.04
.05
.03
.04
.04
.04
.05
.04
.04
-.06
.02
.01
.05
.01
.05
.06
-.02
.17
-.02
.05
.03
.01
.06
.03
.02
.01
-.10*
.14**
-.03
.11*
.10*
Step 3
Age
Gender
Grade Level
Household Income
Number of Roommates
Loneliness
MP3-Player-Use Motives
Social Avoidance
Fashion/Status
Social Utility
Learning
Entertainment/Relaxation
Companionship
Boredom Alleviation
Step 4
Age
Gender
Grade Level
Household Income
Number of Roommates
161
Variable
Loneliness
MP3-Player-Use Motives
Social Avoidance
Fashion/Status
Social Utility
Learning
Entertainment/Relaxation
Companionship
Boredom Alleviation
Time Spent Listening
Audience Activity
Attention to Songs
Elaboration on Songs
β
B
SE B
-.30
.05
-.30***
-.04
.02
-.02
.02
-.03
.00
.05
-.01
.03
.04
.04
.04
.05
.05
.04
.01
-.06
.03
-.03
.03
-.03
.00
.07
-.05
-.04
.20
.05
.05
-.03
.22***
Note. R = .39, R² = .15, F(5, 417) = 14.47, p < .001 for step 1. R = .49, R² = .24, Δ R² = .10,
F(6, 416) = 22.31, p < .001 for step 2. R = .51, R² = .26, Δ R² = .02, F(13, 409) = 10.94, p <
.001 for step 3. R = .54, R² = .29, Δ R² = .03, F(16, 406) = 10.30, p < .001 for step 4.
* p < .05, ** p < .01, *** p < .001
162
Table 15
Summary of Regression Analysis for Variables Predicting Post-Listening Discussion
Variable
β
B
SE B
Step 1
Age
Gender
Grade Level
Household Income
Number of Roommates
-.04
-.06
-.06
-.11
.02
.01
.09
.05
.04
.02
-.14**
-.03
-.06
-.16**
.04
Step 2
Age
Gender
Grade Level
Household Income
Number of Roommates
Loneliness
-.04
-.06
-.06
-.11
.02
-.01
.01
.09
.05
.04
.02
.07
-.14**
-.03
-.06
-.16**
.04
-.01
Step 3
Age
Gender
Grade Level
Household Income
Number of Roommates
Loneliness
MP3-Player-Use Motives
Social Avoidance
Fashion/Status
Social Utility
Learning
Entertainment/Relaxation
Companionship
Boredom Alleviation
-.02
-.13
.00
-.07
.01
.03
.01
.08
.04
.03
.02
.07
-.07
-.07
.00
-.10*
.03
.02
-.10
.02
.40
.20
.16
.17
-.00
.04
.05
.05
.05
.07
.06
.05
-.10*
.02
.38***
.20***
.10*
.14**
-.00
Step 4
Age
Gender
Grade Level
Household Income
Number of Roommates
Loneliness
-.02
-.10
.01
-.07
.01
.02
.01
.08
.04
.03
.02
.06
-.06
-.06
.01
-.09*
.02
.01
163
Variable
MP3-Player-Use Motives
Social Avoidance
Fashion/Status
Social Utility
Learning
Entertainment/Relaxation
Companionship
Boredom Alleviation
Time Spent Listening
Audience Activity
Attention to Songs
Elaboration on Songs
β
B
SE B
-.09
.05
.35
.16
.07
.07
.02
.00
.04
.05
.05
.05
.07
.06
.05
.01
-.09*
.04
.35***
.17**
.05
.06
.01
.00
.19
.26
.07
.07
.12**
.19***
Note. R = .21, R² = .05, F(5, 417) = 3.95, p < .01 for step 1. R = .21, R² = .05, Δ R² = .00,
F(6, 416) = 3.29, p < .01 for step 2. R = .64, R² = .41, Δ R² = .36, F(13, 409) = 21.66, p <
.001 for step 3. R = .67, R² = .45, Δ R² = .04, F(16, 406) = 20.87, p < .001 for step 4.
* p < .05, ** p < .01, *** p < .001
164
Table 16
Summary of Regression Analysis for Variables Predicting Overall File-Sharing
Variable
β
B
SE B
Step 1
Age
Gender
Grade Level
Household Income
Number of Roommates
-.03
-.12
-.07
-.00
.01
.01
.07
.04
.03
.02
-.14**
-.08
-.10
-.01
.02
Step 2
Age
Gender
Grade Level
Household Income
Number of Roommates
Loneliness
-.03
-.11
-.07
-.00
.01
.03
.01
.07
.04
.03
.02
.06
-.14**
-.08
-.10
-.00
.02
.03
Step 3
Age
Gender
Grade Level
Household Income
Number of Roommates
Loneliness
MP3-Player-Use Motives
Social Avoidance
Fashion/Status
Social Utility
Learning
Entertainment/Relaxation
Companionship
Boredom Alleviation
-.02
-.09
-.06
.02
.00
.06
.01
.07
.04
.03
.02
.06
-.11*
-.07
-.08
.03
.00
.06
.03
.15
.11
.11
.18
-.07
.03
.04
.05
.04
.04
.06
.05
.05
.05
.16**
.15**
.15*
.14**
-.08
.03
Step 4
Age
Gender
Grade Level
Household Income
Number of Roommates
-.02
-.05
-.06
.02
.00
.01
.07
.04
.03
.02
-.11*
-.04
-.07
.04
.00
165
Variable
Loneliness
MP3-Player-Use Motives
Social Avoidance
Fashion/Status
Social Utility
Learning
Entertainment/Relaxation
Companionship
Boredom Alleviation
Time Spent Listening
Audience Activity
Attention to Songs
Elaboration on Songs
B
SE B
β
.05
.06
.04
.05
.16
.09
.08
.12
-.13
.04
.03
.04
.04
.04
.04
.06
.05
.05
.01
.06
.19***
.12*
.11
.10*
-.15*
.04
.11*
.18
.10
.06
.06
.15**
.10
Note. R = .19, R² = .04, F(5, 417) = 3.22, p < .01 for step 1. R = .20, R² = .04, Δ R² = .00,
F(6, 416) = 2.75, p < .05 for step 2. R = .42, R² = .18, Δ R² = .14, F(13, 409) = 6.78, p <
.001 for step 3. R = .47, R² = .22, Δ R² = .04, F(16, 406) = 7.16, p < .001 for step 4.
* p < .05, ** p < .01, *** p < .001
166
Table 17
Summary of Regression Analysis for Variables Predicting File-Sharing Using an Online
Music Service
Variable
B
SE B
β
Step 1
Age
Gender
Grade Level
Household Income
Number of Roommates
-.03
.54
-.22
.07
.01
.02
.14
.08
.06
.03
-.07
.19***
-.14**
.07
.01
Step 2
Age
Gender
Grade Level
Household Income
Number of Roommates
Loneliness
-.02
.47
-.23
.07
.01
-.28
.02
.14
.08
.05
.03
.11
-.06
.17**
-.15**
.06
.01
-.12*
Step 3
Age
Gender
Grade Level
Household Income
Number of Roommates
Loneliness
MP3-Player-Use Motives
Social Avoidance
Fashion/Status
Social Utility
Learning
Entertainment/Relaxation
Companionship
Boredom Alleviation
-.02
.51
-.23
.08
.00
-.20
.02
.14
.08
.05
.03
.12
-.05
.18***
-.15**
.07
.00
-.09
.03
.20
.02
.13
.34
-.15
.05
.08
.10
.09
.09
.13
.11
.10
.02
.11*
.01
.09
.14**
-.08
.03
Step 4
Age
Gender
Grade Level
Household Income
Number of Roommates
-.02
.56
-.22
.09
-.00
.02
.14
.08
.06
.03
-.05
.20***
-.14**
.08
-.00
167
Variable
Loneliness
MP3-Player-Use Motives
Social Avoidance
Fashion/Status
Social Utility
Learning
Entertainment/Relaxation
Companionship
Boredom Alleviation
Time Spent Listening
Audience Activity
Attention to Songs
Elaboration on Songs
B
SE B
β
-.21
.12
-.10
.04
.23
-.01
.09
.27
-.23
.07
.03
.08
.09
.09
.09
.13
.11
.10
.02
.03
.13*
-.00
.06
.11*
-.13*
.04
.06
.22
.15
.13
.13
.09
.07
Note. R = .31, R² = .09, F(5, 417) = 8.53, p < .001 for step 1. R = .33, R² = .11, Δ R² = .01,
F(6, 416) = 8.32, p < .001 for step 2. R = .39, R² = .15, Δ R² = .04, F(13, 409) = 5.49, p < .001
for step 3. R = .41, R² = .16, Δ R² = .02, F(16, 406) = 4.99, p < .001 for step 4.
* p < .05, ** p < .01, *** p < .001
168
Table 18
Summary of Regression Analysis for Variables Predicting File-Sharing Using an MP3
Player
Variable
β
B
SE B
Step 1
Age
Gender
Grade Level
Household Income
Number of Roommates
-.05
.20
-.20
-.01
.02
.02
.12
.07
.05
.03
-.16**
.08
-.15**
-.01
.04
Step 2
Age
Gender
Grade Level
Household Income
Number of Roommates
Loneliness
-.05
.15
-.20
-.02
.02
-.21
.02
.12
.07
.05
.03
.09
-.15**
.06
-.15**
-.02
.03
-.11*
Step 3
Age
Gender
Grade Level
Household Income
Number of Roommates
Loneliness
MP3-Player-Use Motives
Social Avoidance
Fashion/Status
Social Utility
Learning
Entertainment/Relaxation
Companionship
Boredom Alleviation
-.05
.17
-.18
-.00
.02
-.16
.02
.12
.07
.05
.03
.10
-.13**
.07
-.13**
-.00
.03
-.08
.04
.02
.13
.25
.16
-.16
.05
.07
.08
.08
.08
.11
.09
.09
.03
.01
.10
.19**
.07
-.10
.03
Step 4
Age
Gender
Grade Level
Household Income
Number of Roommates
-.04
.15
-.18
.01
.01
.02
.12
.07
.05
.03
-.12*
.06
-.13**
.01
.02
169
Variable
Loneliness
MP3-Player-Use Motives
Social Avoidance
Fashion/Status
Social Utility
Learning
Entertainment/Relaxation
Companionship
Boredom Alleviation
Time Spent Listening
Audience Activity
Attention to Songs
Elaboration on Songs
B
SE B
β
-.16
.10
-.08
.03
.04
.10
.21
.10
-.22
.06
.01
.07
.08
.08
.08
.12
.10
.09
.02
.03
.02
.08
.16**
.04
-.14*
.03
.02
-.02
.26
.11
.11
-.01
.14*
Note. R = .28, R² = .08, F(5, 417) = 6.85, p < .001 for step 1. R = .29, R² = .09, Δ R² = .01,
F(6, 416) = 6.57, p < .001 for step 2. R = .39, R² = .15, Δ R² = .06, F(13, 409) = 5.52, p <
.001 for step 3. R = .40, R² = .16, Δ R² = .01, F(16, 406) = 4.91, p < .001 for step 4.
* p < .05, ** p < .01, *** p < .001
170
Appendix M
Regression Analysis Tables for Research Question 8
Table 19
Summary of Regression Analysis for Variables (Excluding Loneliness) Predicting Time
Spent Socializing with Others Overall
Variable
Step 1
Age
Gender
Grade Level
Household Income
Number of Roommates
Step 2
Age
Gender
Grade Level
Household Income
Number of Roommates
MP3-Player-Use Motives
Social Avoidance
Fashion/Status
Social Utility
Learning
Entertainment/Relaxation
Companionship
Boredom Alleviation
Step 3
Age
Gender
Grade Level
Household Income
Number of Roommates
MP3-Player-Use Motives
Social Avoidance
Fashion/Status
Social Utility
Learning
B
SE B
β
.06
6.61
-1.66
1.69
-.23
.66
4.59
2.63
1.86
1.12
.01
.07
-.03
.05
-.01
.02
5.23
-1.72
1.39
-.18
.67
4.68
2.63
1.87
1.11
.00
.06
-.03
.04
-.01
-4.64
-4.12
-.30
-.72
.21
-2.42
8.57
2.63
3.23
3.10
3.06
4.43
3.68
3.32
-.10
-.07
-.01
-.02
.00
-.04
.14**
.14
4.05
-1.65
1.82
-.29
.67
4.85
2.63
1.89
1.12
.01
.05
-.03
.05
-.01
-5.01
-3.59
-1.07
-1.51
2.65
3.25
3.14
3.11
-.11
-.06
-.02
-.03
171
Variable
Entertainment/Relaxation
Companionship
Boredom Alleviation
Time Spent Listening
Audience Activity
Attention to Songs
Elaboration on Songs
B
SE B
β
-1.48
-4.17
8.42
.24
4.55
3.88
3.35
.81
-.02
-.07
.14*
.02
-2.63
7.77
4.38
4.38
-.03
.11
Note. R = .10, R² = .01, F(5, 406) = 0.88, p = .50 for step 1. R = .22, R² = .05, Δ R² = .04,
F(12, 399) = 1.68, p = .07 for step 2. R = .24, R² = .06, Δ R² = .01, F(15, 396) = 1.56, p = .08
for step 3.
* p < .05, ** p < .01, *** p < .001
172
Table 20
Summary of Regression Analysis for Variables (Excluding Loneliness) Predicting Time Spent
Socializing with Family Members
Variable
Step 1
Age
Gender
Grade Level
Household Income
Number of Roommates
Step 2
Age
Gender
Grade Level
Household Income
Number of Roommates
MP3-Player-Use Motives
Social Avoidance
Fashion/Status
Social Utility
Learning
Entertainment/Relaxation
Companionship
Boredom Alleviation
Step 3
Age
Gender
Grade Level
Household Income
Number of Roommates
MP3-Player-Use Motives
Social Avoidance
Fashion/Status
Social Utility
Learning
Entertainment/Relaxation
Companionship
Boredom Alleviation
Time Spent Listening
β
B
SE B
1.24
4.30
-1.33
.34
-.34
.22
1.50
.86
.61
.37
.29***
.14**
-.08
.03
-.05
1.23
4.21
-1.53
.14
-.28
.22
1.53
.86
.61
.36
.28***
.14**
-.09
.01
-.04
-1.15
-.39
-2.03
-.56
.76
.23
-.48
.86
1.06
1.02
1.00
1.46
1.21
1.09
-.07
-.02
-.12*
-.02
.03
.01
-.02
1.24
4.27
-1.46
.22
-.31
.22
1.58
.86
.62
.37
.28***
.14**
-.09
.02
-.04
-1.15
-.15
-2.34
-.64
.09
-.55
-.38
.06
.87
1.06
1.03
1.02
1.49
1.27
1.09
.26
-.07
-.01
-.14*
-.04
.00
-.03
-.02
.01
173
Variable
Audience Activity
Attention to Songs
Elaboration on Songs
B
.80
2.35
SE B
1.43
1.43
β
.03
.10
Note. R = .30, R² = .09, F(5, 406) = 8.30, p < .001 for step 1. R = .35, R² = .12, Δ R² = .03,
F(12, 399) = 4.53, p < .001 for step 2. R = .36, R² = .13, Δ R² = .01, F(15, 396) = 3.89, p <
.001 for step 3.
* p < .05, ** p < .01, *** p < .001
174
Table 21
Summary of Regression Analysis for Variables (Excluding Loneliness) Predicting Time
Spent Socializing with Friends
Variable
Step 1
Age
Gender
Grade Level
Household Income
Number of Roommates
Step 2
Age
Gender
Grade Level
Household Income
Number of Roommates
MP3-Player-Use Motives
Social Avoidance
Fashion/Status
Social Utility
Learning
Entertainment/Relaxation
Companionship
Boredom Alleviation
Step 3
Age
Gender
Grade Level
Household Income
Number of Roommates
MP3-Player-Use Motives
Social Avoidance
Fashion/Status
Social Utility
Learning
Entertainment/Relaxation
Companionship
Boredom Alleviation
Time Spent Listening
B
SE B
β
-1.38
.42
-.72
.86
.41
.45
3.15
1.80
1.27
.77
-.16**
.01
-.02
.04
.03
-1.39
-.72
-.86
.67
.42
.45
3.19
1.79
1.27
.76
-.16**
-.01
-.03
.03
.03
-3.25
-2.60
-1.29
.66
.93
-2.02
7.72
1.79
2.20
2.11
2.09
3.02
2.51
2.26
-.10
-.07
-.04
.02
.02
-.05
.19***
-1.34
-1.34
-.86
.86
.37
.46
3.31
1.80
1.29
.76
-.15**
-.02
-.03
.03
.02
-3.44
-2.43
-1.56
.38
.35
-2.58
7.60
.10
1.81
2.22
2.14
2.12
3.11
2.65
2.28
.55
-.11
-.06
-.04
.01
.01
-.06
.18***
.01
175
Variable
Audience Activity
Attention to Songs
Elaboration on Songs
B
-1.66
2.95
SE B
β
2.99
2.99
-.03
.06
Note. R = .18, R² = .03, F(5, 406) = 2.69, p < .05 for step 1. R = .28, R² = .08, Δ R² = .05,
F(12, 399) = 2.88, p < .001 for step 2. R = .29, R² = .08, Δ R² = .00, F(15, 396) = 2.36, p <
.01 for step 3.
* p < .05, ** p < .01, *** p < .001
176
Table 22
Summary of Regression Analysis for Variables (Excluding Loneliness) Predicting Time
Spent Socializing with Acquaintances
Variable
Step 1
Age
Gender
Grade Level
Household Income
Number of Roommates
Step 2
Age
Gender
Grade Level
Household Income
Number of Roommates
MP3-Player-Use Motives
Social Avoidance
Fashion/Status
Social Utility
Learning
Entertainment/Relaxation
Companionship
Boredom Alleviation
Step 3
Age
Gender
Grade Level
Household Income
Number of Roommates
MP3-Player-Use Motives
Social Avoidance
Fashion/Status
Social Utility
Learning
Entertainment/Relaxation
Companionship
Boredom Alleviation
Time Spent Listening
B
SE B
β
.20
1.89
.39
.49
-.31
.23
1.60
.92
.65
.39
.05
.06
.02
.04
-.04
.18
1.73
.67
.58
-.32
.23
1.64
.92
.65
.39
.04
.06
.04
.05
-.04
-.24
-1.13
3.02
-1.02
-1.48
-.64
1.33
.92
1.13
1.09
1.07
1.55
1.29
1.16
-.02
-.06
.17**
-.06
-.05
-.03
.06
.23
1.11
.66
.75
-.35
.24
1.70
.92
.66
.39
.05
.04
.04
.06
-.05
-.42
-1.01
2.82
-1.24
-1.92
-1.04
1.20
.08
.93
1.14
1.10
1.09
1.59
1.36
1.17
.28
-.03
-.05
.16*
-.07
-.07
-.05
.06
.02
177
Variable
Audience Activity
Attention to Songs
Elaboration on Songs
B
SE B
β
-1.77
2.46
1.53
1.53
-.06
.10
Note. R = .09, R² = .01, F(5, 406) = 0.69, p = .63 for step 1. R = .19, R² = .04, Δ R² = .03,
F(12, 399) = 1.23, p = .26 for step 2. R = .21, R² = .04, Δ R² = .01, F(15, 396) = 1.20, p =
.27 for step 3.
* p < .05, ** p < .01, *** p < .001
178
Table 23
Summary of Regression Analysis for Variables (Excluding Loneliness) Predicting
Participation in Social Activities
Variable
Step 1
Age
Gender
Grade Level
Household Income
Number of Roommates
Step 2
Age
Gender
Grade Level
Household Income
Number of Roommates
MP3-Player-Use Motives
Social Avoidance
Fashion/Status
Social Utility
Learning
Entertainment/Relaxation
Companionship
Boredom Alleviation
Step 3
Age
Gender
Grade Level
Household Income
Number of Roommates
MP3-Player-Use Motives
Social Avoidance
Fashion/Status
Social Utility
Learning
Entertainment/Relaxation
Companionship
Boredom Alleviation
Time Spent Listening
β
B
SE B
-.03
.29
-.02
.05
.04
.01
.06
.03
.02
.01
-.16**
.24***
-.03
.10*
.12**
-.02
.27
-.01
.05
.04
.01
.06
.03
.02
.01
-.14**
.22***
-.02
.10*
.12**
-.09
.03
.01
.03
.07
-.01
.09
.03
.04
.04
.04
.05
.05
.04
-.15**
.03
.02
.05
.06
-.01
.11*
-.02
.24
-.01
.06
.03
.01
.06
.03
.02
.01
-.13**
.20***
-.02
.12*
.11*
-.10
.03
-.01
.02
.03
-.04
.09
-.01
.03
.04
.04
.04
.06
.05
.04
.01
-.16**
.04
-.01
.03
.03
-.06
.11*
-.06
179
Variable
Audience Activity
Attention to Songs
Elaboration on Songs
B
SE B
-.05
.21
.05
.05
β
-.05
.22***
Note. R = .39, R² = .15, F(5, 417) = 14.47, p < .001 for step 1. R = .43, R² = .19, Δ R² =
.04, F(12, 410) = 7.95, p < .001 for step 2. R = .47, R² = .22, Δ R² = .03, F(15, 407) = 7.71,
p < .001 for step 3.
* p < .05, ** p < .01, *** p < .001
180
Table 24
Summary of Regression Analysis for Variables (Excluding Loneliness) Predicting PostListening Discussion
Variable
Step 1
Age
Gender
Grade Level
Household Income
Number of Roommates
Step 2
Age
Gender
Grade Level
Household Income
Number of Roommates
MP3-Player-Use Motives
Social Avoidance
Fashion/Status
Social Utility
Learning
Entertainment/Relaxation
Companionship
Boredom Alleviation
Step 3
Age
Gender
Grade Level
Household Income
Number of Roommates
MP3-Player-Use Motives
Social Avoidance
Fashion/Status
Social Utility
Learning
Entertainment/Relaxation
Companionship
Boredom Alleviation
Time Spent Listening
β
B
SE B
-.04
-.06
-.06
-.11
.02
.01
.09
.05
.04
.02
-.14**
-.03
-.06
-.16**
.04
-.02
-.14
.00
-.07
.01
.01
.07
.04
.03
.02
-.06
-.08
.00
-.10*
.03
-.09
.02
.39
.20
.15
.17
-.01
.04
.05
.05
.05
.07
.06
.05
-.10*
.02
.38***
.20***
.09*
.15**
-.01
-.02
-.11
.01
-.07
.01
.01
.07
.04
.03
.02
-.06
-.06
.01
-.09*
.02
-.08
.04
.35
.16
.07
.07
.02
.00
.04
.05
.05
.05
.07
.06
.05
.01
-.09*
.04
.35***
.17***
.04
.06
.01
.00
181
Variable
Audience Activity
Attention to Songs
Elaboration on Songs
B
SE B
.19
.26
.07
.07
β
.12**
.19***
Note. R = .21, R² = .05, F(5, 417) = 3.95, p < .01 for step 1. R = .64, R² = .41, Δ R² = .36,
F(12, 410) = 23.50, p < .001 for step 2. R = .67, R² = .45, Δ R² = .04, F(15, 407) = 22.31, p
< .001 for step 3.
* p < .05, ** p < .01, *** p < .001
182
Table 25
Summary of Regression Analysis for Variables (Excluding Loneliness) Predicting Overall
File-Sharing
Variable
Step 1
Age
Gender
Grade Level
Household Income
Number of Roommates
Step 2
Age
Gender
Grade Level
Household Income
Number of Roommates
MP3-Player-Use Motives
Social Avoidance
Fashion/Status
Social Utility
Learning
Entertainment/Relaxation
Companionship
Boredom Alleviation
Step 3
Age
Gender
Grade Level
Household Income
Number of Roommates
MP3-Player-Use Motives
Social Avoidance
Fashion/Status
Social Utility
Learning
Entertainment/Relaxation
Companionship
Boredom Alleviation
Time Spent Listening
B
-.03
-.12
-.07
-.00
.01
SE B
.01
.07
.04
.03
.02
β
-.14**
-.08
-.10
-.01
.02
-.02
-.11
-.06
.02
.00
.01
.07
.04
.03
.02
-.11*
-.08
-.08
.03
.00
.05
.14
.11
.11
.16
-.06
.02
.04
.05
.04
.04
.06
.05
.05
.07
.16**
.15**
.15*
.13**
-.07
.02
-.02
-.06
-.06
.02
.00
.01
.07
.04
.03
.02
-.11*
-.05
-.08
.04
-.00
.05
.16
.09
.08
.11
-.13
.03
.03
.04
.04
.04
.04
.06
.05
.05
.01
.08
.18***
.12*
.11
.09
-.14*
.04
.11*
183
Variable
Audience Activity
Attention to Songs
Elaboration on Songs
B
SE B
.19
.10
.06
.06
β
.15**
.10
Note. R = .19, R² = .04, F(5, 417) = 3.22, p < .01 for step 1. R = .42, R² = .18, Δ R² = .14,
F(12, 410) = 7.26, p < .001 for step 2. R = .47, R² = .22, Δ R² = .04, F(15, 407) = 7.60, p <
.001 for step 3.
* p < .05, ** p < .01, *** p < .001
184
Table 26
Summary of Regression Analysis for Variables (Excluding Loneliness) Predicting FileSharing Using an Online Music Service
Variable
Step 1
Age
Gender
Grade Level
Household Income
Number of Roommates
Step 2
Age
Gender
Grade Level
Household Income
Number of Roommates
MP3-Player-Use Motives
Social Avoidance
Fashion/Status
Social Utility
Learning
Entertainment/Relaxation
Companionship
Boredom Alleviation
Step 3
Age
Gender
Grade Level
Household Income
Number of Roommates
MP3-Player-Use Motives
Social Avoidance
Fashion/Status
Social Utility
Learning
Entertainment/Relaxation
Companionship
Boredom Alleviation
Time Spent Listening
B
SE B
β
-.03
.54
-.22
.07
.01
.02
.14
.08
.06
.03
-.07
.19***
-.14**
.07
.01
-.02
.56
-.23
.08
.00
.02
.14
.08
.06
.03
-.06
.20***
-.15**
.07
.00
-.01
.21
.03
.13
.38
-.18
.08
.08
.09
.09
.09
.13
.11
.10
-.01
.12*
.02
.08
.15**
-.10
.04
-.02
.61
-.22
.09
.00
.02
.14
.08
.06
.03
-.06
.22***
-.14**
.08
.00
-.00
.24
.00
.09
.32
-.26
.09
.03
.08
.09
.09
.09
.13
.11
.10
.02
-.00
.13*
.00
.06
.13*
-.14*
.05
.06
185
Variable
Audience Activity
Attention to Songs
Elaboration on Songs
B
SE B
β
.21
.15
.13
.13
.08
.07
Note. R = .31, R² = .09, F(5, 417) = 8.53, p < .001 for step 1. R = .38, R² = .14, Δ R² = .05,
F(12, 410) = 5.69, p < .001 for step 2. R = .40, R² = .16, Δ R² = .02, F(15, 407) = 5.08, p <
.001 for step 3.
* p < .05, ** p < .01, *** p < .001
186
Table 27
Summary of Regression Analysis for Variables (Excluding Loneliness) Predicting FileSharing Using an MP3 Player
Variable
Step 1
Age
Gender
Grade Level
Household Income
Number of Roommates
Step 2
Age
Gender
Grade Level
Household Income
Number of Roommates
MP3-Player-Use Motives
Social Avoidance
Fashion/Status
Social Utility
Learning
Entertainment/Relaxation
Companionship
Boredom Alleviation
Step 3
Age
Gender
Grade Level
Household Income
Number of Roommates
MP3-Player-Use Motives
Social Avoidance
Fashion/Status
Social Utility
Learning
Entertainment/Relaxation
Companionship
Boredom Alleviation
Time Spent Listening
B
-.05
.20
-.20
-.01
.02
SE B
.02
.12
.07
.05
.03
β
-.16**
.08
-.15**
-.01
.04
-.05
.21
-.18
.00
.02
.02
.12
.07
.05
.03
-.14**
.09
-.13**
.00
.03
.01
.03
.14
.24
.19
-.18
.07
.07
.08
.08
.08
.11
.09
.08
.01
.02
.10
.19**
.09
-.12*
.05
-.05
.19
-.17
.01
.02
.02
.12
.07
.05
.03
-.13**
.08
-.13**
.01
.03
-.00
.04
.11
.21
.13
-.25
.07
.01
.07
.08
.08
.08
.11
.10
.08
.02
-.00
.03
.08
.16**
.06
-.16*
.05
.02
187
Variable
Audience Activity
Attention to Songs
Elaboration on Songs
B
SE B
β
-.03
.26
.11
.11
-.02
.14*
Note. R = .28, R² = .08, F(5, 417) = 6.85, p < .001 for step 1. R = .38, R² = .14, Δ R² = .07,
F(12, 410) = 5.76, p < .001 for step 2. R = .40, R² = .16, Δ R² = .01, F(15, 407) = 5.05, p <
.001 for step 3.
* p < .05, ** p < .01, *** p < .001
188
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