CELL PHONE COMMUNICATION VERSUS FACE-TO-FACE COMMUNICATION:
THE EFFECT OF MODE OF COMMUNICATION ON RELATIONSHIP
SATISFACTION AND THE DIFFERENCE IN QUALITY OF COMMUNICATION
A thesis submitted
to Kent State University in partial
fulfillment of the requirements for the
degree of Master of Arts
By
Rebecca M. Schwarz
December 2008
Thesis written by
Rebecca M. Schwarz
B.A., Kent State University, 2007
M.A., Kent State University, 2008
Approved by
_____________________
Richard T. Serpe
_____, Advisor
___________________________________, Chair, Department of Sociology
Richard T. Serpe
___________________________________, Dean, College of Arts and Sciences
John R. D. Stalvey
TABLE OF CONTENTS
LIST OF TABLES AND FIGURES ………………….……………….…………...…….v
ACKNOWLEDGMENTS ……………………...………………………………….....…vii
INTRODUCTION…………………………………………………………………...……1
Hypotheses……………………………………………………………………..….4
LITERATURE REVIEW….………………………………………………………...……8
METHODOLOGY…..………………………………………………………………..…11
Sample...………………………………………………………………………….11
Data Collection.....…………………………………………………………….…11
Measurement.…………………………………………………………………….19
Analysis……...……...…………………………………………………………....21
RESULTS……………………………………………………………………………..…29
Descriptives…………………………………………………………………...….29
Bivariate Correlations…………………...………………………………....…….31
Hypotheses……………………………………………………………………….32
DISCUSSION……………………..........………………………………………….……65
Limitations……………………………………………………………………….78
Future Considerations..………………………………………………….……….81
APPENDIX I: Email Solicitation …….……………………………………………..…..83
APPENDIX II: Online Consent Form……………..……………………………….…....84
APPENDIX III: Questionnaire……..….………………………………….…………..…85
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APPENDIX IV: Bivariate Correlations for Friend Variables ……………….…………107
APPENDIX V: Bivariate Correlations for Romantic Partner Variables ……….………109
APPENDIX VI: Bivariate Correlations for Family Variables …………………………111
BIBLIOGRAPHY……………….…………………...………….…………………..…113
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LIST OF TABLES AND FIGURES
TABLE 3.1 Comparison of Modified RAS Items to Original RAS Items………………28
TABLE 4.1 Sample Descriptives Compared to KSU Demographics………..………......48
TABLE 4.2 Descriptive Statistics for Variables Used in Analysis……………..…..…….49
TABLE 4.3 Quality of Face-to-Face Communication Scale Reliability…….…….……..51
TABLE 4.4 Quality of Cell Phone Communication Scale Reliability……….…………..51
TABLE 4.5 Overall Relationship Satisfaction Scale Reliability………………….….…..51
TABLE 4.6 Hypotheses 1 and 2: Friendships……………………………………...…….52
TABLE 4.7 Hypotheses 1 and 2: Romantic Partners……………………….……………53
TABLE 4.8 Hypotheses 1 and 2: Family Members……………………...………………54
TABLE 4.9 Hypothesis 3: Paired Samples T-Test Results……..….……………………55
TABLE 4.10 Hypothesis 3: Friendships…………………………….…………….……..56
TABLE 4.11 Hypothesis 3: Romantic Partners………………….………………………57
TABLE 4.12 Hypothesis 3: Family Members………………………….....……………...58
TABLE 4.13 Hypothesis 4: Friendships…………………………………………………59
TABLE 4.14 Hypothesis 4: Romantic Partners……………………………….…………60
TABLE 4.15 Hypothesis 4: Family Members………………………………..………..….61
TABLE 4.13 Summary of Findings for Friendships ……………………………………62
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TABLE 4.14 Summary of Findings for Romantic Relationships………….…….………63
TABLE 4.15 Summary of Findings for Family Relationships…………….…………….64
TABLE 5.1 Summary of Hypotheses……………………………………………………82
FIGURE 4.1 Visual Description of Mediation……………………………………..……42
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ACKNOWLEDGMENTS
I would like to thank my committee members for all of their invaluable feedback
and support that guided me in the writing of this thesis. I feel privileged to have worked
with such wonderful professors, and appreciate the time, effort, and support you have
given to this project, as well as to myself. I do hope that we will have the opportunity to
work together in the future. Thank you, Dr. Serpe, for allowing me to take the reigns of
this project and truly make it my own. You have provided me with numerous
opportunities to learn and grow, as a researcher, and as a Sociologist in general, and
learning from you has been a huge part of my graduate experience. You are a wonderful
mentor, and friend, and I look forward to working with you in the future.
I would also like to thank my family for all their help and support through my years
in college. Mom and Dad, I could not have made it as far as I have without your extreme
generosity, love, and support, even in times of your distress. You have instilled in me both
the value of education and a great work ethic that will aide me throughout my life. To my
best friend and big sister Sarah, for her guidance, friendship, humor, and love at all times.
Calls from you never fail to brighten my mood. To my Grandma Starkey, who has been like a
second mother to me, giving me all kinds of support when it was needed, bringing me on
trips all over the country, and showering me with love.
Thank you Jason, for always pushing me towards my goals, right from the beginning,
and for letting me know whenever you thought I was selling myself short. You are the
biggest support I have had through all of this. Thank you also for putting up with my low
quality of cell phone communication throughout the four years of our long distance
relationship. I’m so happy the distance is over, and I can finally enjoy being with you without
the sadness of counting down the days before I have to leave.
CHAPTER I
INTRODUCTION
With the advent of wireless technology comes latent consequences; unintended
consequences that may affect individuals in society on multiple levels. It is therefore
important that we learn more about this technology in order to understand how, and in
what realms, it affects our lives. Specific to this research is the use of the cell phone. 1 In
November of 2007, 82.4 percent of Americans were estimated to have a cell phone
subscription (“U.S. Cell-Phone Penetration Tops 82 Percent”). Such an increase in this
wireless communications technology has brought about many changes in the nature of
social interactions, both positive and negative (Geser 2003; Palen 2002). One such
change has occurred in the maintenance and support of relationships occurring over long
distances, which previously occurred by way of written letters, long-distance telephone
calls, or time consuming travel (Mok, Wellman, and Basu 2007). The ability to use cell
phones anywhere, and at anytime, frees communication from the boundaries which were
once imposed by such distance and time (Wellman and Tindall 1993; Palen 2002; Wei
and Lo 2006), therefore making the maintenance of relationships across
1
Landline telephones are also a mode through which people can stay connected to one another
(Wellman et al. 1993), and so one might wonder, ‘ why not study telephones in general?’ My answer to this
question is that there has already been research done on the functions of the landline telephone (King 1991;
Wellman et al. 1993), though little research in this area has been conducted on cell phones within the
discipline of sociology. More importantly though, I also argue that the cell phone carries with it a different
meaning than does the landline telephone (Vincent 2006), and also has the ability to intrude an individuals
daily life much more so than the landline telephone (since the cell phone is not restricted to the home as is
its counterpart) (Geser 2003; Palen 2002). Therefore, the use of the cell phone requires its own research
attention. I address these issues in the literature review section of this proposal.
1
2
distance considerably more possible, and certainly much easier. On top of this, the cell
phone is also a useful communications tool that is used to support and maintain those
relationships which are not constrained by physical proximity (Wellman et al. 1993;
Campbell and Russo 2003). Thus, the general findings here are clear: cell phones have
become an extremely common and accessible mode through which the maintenance and
support of relationships often occurs.
However, there is yet to be an acceptable research project that looks at how this
relatively new, yet extremely common, mode of communication affects the level of
satisfaction in relationships, which it is claimed to be enhancing. More explicitly, what if
the quality of communication is significantly different between face-to-face and cell
phone interactions, and what would that mean for the maintenance and support that goes
into our relationships through these modes? In face-to-face communication, the
experience of physical communication, such as non-verbal cues, gestures, and intimate
contact, can aid verbal communication. As previous research has shown, this physical
communication is needed in order to maintain close and satisfying relationships
(Wellman and Tindall 1993; Emmers-Sommer 2004; Mok et al. 2007).
Conversations occurring over the cell phone, however, are absent of physical
communication, and are more dependent upon the focus and attention of the persons
involved. Also, since cell phones are typically always present on a person, this form of
communication has the ability to intrude multiple aspects of an individuals’ daily life
more so than for face-to-face contact (Geser 2003; Palen 2002). For instance, an
incoming call on one’s telephone in general tends to provoke a sense of expectation to
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answer for as Wellman and Tindall (1993) stated, “Except for those disciplined and antisocial enough to remain hidden behind their home answering machines, answering a
telephone call is still largely an involuntary act.” This may be in part due to an obligation
to maintain the social relationship through communication, likely regardless of whether
they lack the motivation to speak with a specific person, or would rather not answer the
call due to the task at hand. In particular, attempting to juggle both the task at hand and
the conversation may reduce the quality of the communication since multitasking has
been shown to result in lower focus on each coinciding activity, as the human mind
cannot do two things at once, but rather jumps back and forth between tasks (Brown
2006). This reduction in the focus on behalf of the reactive participant (and possibly the
proactive (caller) participant as well) may in turn reduce the quality of communication
experienced for both the reactive and proactive participants. Over time, a general
reduction in the quality of communication between individuals may also lead to a
reduction in the level of relationship satisfaction that is experienced within those
relationships, as previous research has shown (Emmers-Sommer 2004; Ramirez 2002).
Overall then, the quality of communication may be lower within cell phone
communication compared to face-to-face communication due to the processes involved in
the former mode of communication. If this is true, then the reduction in the quality of
communication may also have an effect on relationship satisfaction, on average, in
relationships where much of the communication that occurs takes place over the cell
phone. These differences I have highlighted between face-to-face and cell phone
communication are worthy of attention, and lie at the basis of this research.
4
HYPOTHESES
In order to better understand these differences in communication between face-toface and cell phone interactions, and their effects on relationship satisfaction, I have
conducted research here at Kent State University to test hypotheses which I believe will
lead to valuable knowledge applicable to the understanding of this subject matter. The
first of these hypotheses focus on the potential relationship between the mode of
communication and relationship satisfaction:
Hypothesis 1: As communication using the cell phone increases, relationship satisfaction
will decrease.
Hypothesis 2: As face-to-face communication increases, relationship satisfaction will
increase.
Does the mode through which communication occurs lead to different outcomes
of participants’ relationship satisfaction? Particularly, does cell phone communication
lead to lower relationship satisfaction than that of face-to-face communication? The
above hypotheses may seem simple, but multiple problems may arise when analyzing the
data. For instance, it may be that there are floor and ceiling values of face-to-face
communication which limit the variability of relationship satisfaction beyond these
values: individuals may have constantly high relationship satisfaction if they see each
other more than (X) number of times, or constantly low relationship satisfaction if they
see each other less than (X) number of times in a given time frame, regardless of how
frequently they communicate over the cell phone. For instance, Dainton and Aylor (2001)
found that long distance relationships characterized by less than one face-to-face
interaction per week had significantly lower relationship satisfaction than those long
5
distance relationships defined by at least one face-to-face interaction per week. In all of
these cases, the number of cell phone interactions may have no effect on relationship
satisfaction, thus biasing the statistical findings. Therefore, when analyzing the data, I
will need to check the bivariate distribution of relationship satisfaction and face-to-face
interaction to check for values of face-to-face communication in which relationship
satisfaction remains constant. If these floor and ceiling effects are apparent in the data, I
will need to truncate values above and below them in order to test these hypotheses.
The next research question asks whether the quality of communication varies
according to the mode through which communication occurs. In particular, does cell
phone communication yield lower quality of communication than that of face-to-face
communication? From these questions, I have constructed the following hypothesis
which will test the relationship between the mode of communication and the quality of
communication.
Hypothesis 3: On average, the quality of communication for cell phone communication
will be lower than the quality of communication for face-to-face communication.
As with the first two, this hypothesis may also have biases associated with it. In
particular, the quality of communication may not vary as much within cell phone
interactions characterized by Microcoordination communication compared to
Hypercoordination communication.
Microcoordination refers to the instrumental use of the mobile phone for
logistical purposes, such as determining the place and time for a meeting.
Hypercoordination entails the use of the mobile phone as a means of selfpresentation and personal expression, such as romance, chatting, and
sharing jokes with friends. (Campbell:320).
6
The reasoning here is that within microcoordination communication, interactions may be
impersonal, short, and less effective on the perceived quality of communication than that
of hypercoordination communication which would include much lengthier, personal, and
emotive invoking conversations. It is important then that I measure the communication
style of respondents’ individual interactions so that they can be controlled for in the
regression models. A related issue that will need to be measured is the length of
conversations. Shorter conversations may be less effective on the quality of
communication than conversations that allow for more interaction. In addition, as was the
case for face-to-face communication and relationship satisfaction, there may be floor and
ceiling effects for the length of the conversation on quality of communication:
conversations lasting less than, or more than, a certain time span may be relatively
constant in terms of the quality of communication experienced. Thus, I will also need to
visually analyze the bivariate distribution between the length of communication and the
quality of communication to see if, in fact, there are floor and ceiling effects.
The final research question I seek to answer is whether the relationship between
the mode of communication and relationship satisfaction is mediated by the quality of
communication. Previous research has supported the relationship between quality of
communication and relationship satisfaction, with lower quality of communication
leading to lower overall relationship satisfaction (Emmers-Sommer 2004; Ramirez 2002).
One explanation for this relationship is that the “[quality of communication] reflects
characteristics of the message exchange process, whereas [relationship satisfaction]
reflects an outcome of that process”, and therefore the former has a direct influence on
7
the latter (Ramirez 2002:110). In fact, quality of communication had a moderate
association with relationship satisfaction in Ramirez’s (2002) study, with quality of
communication explaining 36 percent of the variation in relationship satisfaction.
Emmers-Sommer (2004) found similar, though somewhat weaker, results, with 19
percent of the variation in relationship satisfaction being explained by seven quality of
communication indicators (using the adjusted R²). With the support of these previous
findings, the final hypothesis below is empirically justifiable.
Hypothesis 4: The relationship between the mode of communication and relationship
satisfaction will be mediated by the quality of communication.
If the frequency of cell phone, or face-to-face, communication is significantly
related to the overall relationship satisfaction of respondents, through what process does
it occur? This hypothesis offers the theory that it is partly the quality of communication
experienced during conversations that this relationship operates. There are likely to be
other processes through with this potential relationship occurs, but their detection is not
the focus of this research. If the first two hypotheses are supported, I would suggest that
future researchers engage in exploratory research to identify other potential processes
under which this relationship holds true.
CHAPTER II
LITERATURE REVIEW
Research in the social sciences on this topic is scarce. To my knowledge there is
only one researcher who has looked at the relationship between different modes of
communication and relationship satisfaction (Emmers-Sommer 2004). Emmers-Sommer
collected data to test the effect of both communication quantity (face-to-face and cell
phone) and quality on relationship satisfaction. The results of this study found that faceto-face communication had a significant (positive) effect on relationship satisfaction,
though cell phone communication did not. It was also found that the quality of
communication had a positive effect on relationship satisfaction, with the former
explaining 19 percent of the variation in relationship satisfaction (using the adjusted R²).
As mentioned above, this finding has been supported in previous research (Ramirez
2002), though to my knowledge, no other researcher has looked at how this relationship
differs between telephone and face-to-face communication (mediation) as I do in this
research.
Although Emmers-Sommer did not yield a significant relationship between cell
phone communication and relationship satisfaction, I find that my hypotheses are still
justifiable due to the sample limitations of Emmers-Sommer’s study, which included a
convenience sample of 79 undergraduate students. With a sampling method that leads to
a sample that is possibly biased, these findings are nongeneralizable, and can therefore
8
9
only describe the characteristics of the sample. With my design including both a
representative sampling frame, and a random sample drawn from that frame, my sample
is a close representation of my target population (displayed in table 4.1), and will
therefore provide reliable estimates of the true relationship between the mode of
communication and relationship satisfaction, (possibly being mediated by the quality of
communication), in my target population.
A second study, conducted by Wellman and Tindall (1993), also resembles this
study closely by looking at how the frequency of communication using landline
telephones affected the strength of relationships for 29 Torontonians in 1977-1978. They
found that the frequency of telephone communication did have a positive effect on the
strength of relationships: the more individuals communicated over landline telephone, the
stronger their relationships were. However, they also found that the telephone played a
larger role in keeping long-distance, strong kinship ties in contact compared to loose knit
ties such as friendships (1993:90).
Unlike Wellman and Tindall (1993), I focus on the use of cell phones for
communication rather than landline telephone communication. Over the past 15 years,
the cell phone has become an everyday technological tool for communication at all levels
of society, and therefore focusing on the cell phone seems to merely fit the era that we
live in, especially for college populations who often times do not subscribe to a landline
telephone. It could also be argued that cell phones carry with them a different meaning
than does the landline telephone. In fact, previous research has shown that many
individuals have an emotional attachment to their cell phones, with some even feeling as
10
though their cell phones are a part of their identity (Vincent 2006): to my knowledge,
there are no similar findings for landline telephones. Another argument for studying cell
phones rather than landline telephones is that the former has a much greater capacity to
invade one’s daily life than the latter, as I discussed in the Introduction.
A second difference between this research and that of Wellman and Tindall
(1993) is that I have compared cell phone communication to face-to-face communication
in terms of the quality of communication experienced within these modes of
communication, and the relationship satisfaction for those who communicate using both
modes. Wellman and Tindall looked at how the frequency of telephone communication
helped to sustain active, intimate, and significant relationships within respondents
personal communication networks. In their study, personal communication networks “…
are composed of the 10 to 20 relationships outside of [the respondents] households with
whom [respondents] are actively and significantly in contact” (Wellman and Tindall
1993:65). The focus then was placed on the quantity of communication rather than the
quality of communication, and did not compare telephone and face-to-face contact, but
rather viewed telephone contact as an aid to face-to-face contact. This research is
different in this respect, as I have measured both the quantity and quality of
communication for both cell phone and face-to-face communication, along with the
respondents’ relationship satisfaction within these relationships, in order to test for
differences. This was not necessary for Wellman and Tindall’s (1993) research since they
did not intend to make any such comparisons across the separate modes of
communication.
CHAPTER III
METHODOLOGY
SAMPLE
The population I chose to base my study on, and therefore sample from, included
undergraduate and graduate students currently enrolled at Kent State University’s main
campus, who, during the spring 2008 semester, had a cell phone, as well as a working,
registered email address listed in the campus directory. These email addresses made up
the sampling frame from which my sample was drawn. Being the owner of a cell phone
was also important, as it was necessary for comparing cell phone communication to faceto-face communication. Lastly, the reason for specifying the main campus was that
students at KSU branches may be different from students at the main branch in terms of
the variables in my study.
DATA COLLECTION
The data for this research were collected using a web-based survey that was
implemented through the Kent State Survey Research Lab on campus. This increasingly
common mode of data collection is one of the most efficient forms of data collection for a
number of reasons. In this research, the use of a web-based survey reduced time and costs
since both the sampling and questionnaire distribution were done through the Kent State
University email directory, eliminating the time that would need to be put into preparing
11
12
and mailing paper questionnaires, supplying return postage, or hiring and training
telephone interviewers. Because everyone in my sampling population has a “kent.edu”
email address, as well as access to the internet on campus and likely off campus, this
seemed the most logical form of data collection, which I believe yielded lower coverage
error than would have other modes of data collection due to the nature of this sample.
Another benefit to using this mode of data collection was that I was able to add skips and
insertions (such as the names of the friends, romantic partners, and family members)
throughout the questionnaire. Even measurement errors were reduced as the data were
automatically uploaded from the web-based survey into a data file that opened directly
into SPSS, rather than having it entered by hand which would have subjected the data to
human error (Bronwyn and Ghadialy 2003; Groves et al. 2004).
There are also negative aspects to using web-based surveys though. One issue is
that, in many cases, they can yield high nonresponse rates due to limitations in internet
access of respondents (Groves et al. 2004). However, as I mentioned above, all students
enrolled at KSU are provided with a kent.edu email address, which they can access at any
of the on campus open computer labs. In the case that students do not physically come to
the main campus for their classes, it is possible that they may be enrolled in a web-based
course, which naturally means that they have access to the Internet at some point.
Therefore, all of the students in my population should have some access to the Internet,
reducing the problem of coverage error.
There was also coverage error anticipated in the sampling frame itself. It is
possible that there were email addresses included in the sampling frame that belonged to
13
students who had stopped attending the university, but were still included in the campus
directory. However, in the very beginning of the questionnaire, these ineligible
respondents (n=11) were identified and informed of their ineligibility for the survey, as
will be discussed below. It was also possible that some respondents had more than one
email address in the sampling frame. For instance, if a respondent changed their name,
they may have been granted a new kent.edu email address, though their old one may not
have been taken out of the directory. To control for this, the end of the questionnaire
(included in appendix 3) included an item which asked respondents if they had a second
kent.edu email address. Though 89 students did have a second kent.edu email address,
none of these secondary addresses were included in my sampling frame. The last issue
with my sampling frame was that many students may not use their kent.edu email
account. I believe that the seven “quota full” messages mentioned below were for this
reason (due to the limiting size of the universities email system) and these individuals are
therefore considered to be noncontacts.
Web Survey Development
Located in appendixes 1 and 2 are the email solicitation for the survey, and the
questionnaire consent form, respectively. The actual questionnaire can be located in
appendix 3. It consists of a total of 201 items, including the items composing scales, all
skips, demographics, and open and closed items. Since I was interested in separating the
effects of mode of communication on relationship satisfaction between friends, romantic
partners, and family members, the questionnaire measured respondents’ interactions
within all three of these relationship conditions. If, however, the respondent did not have
14
a romantic partner, the questionnaire automatically skipped over this section and any
questions pertaining to this type of relationship.
At first, it was of concern that including all three relationship conditions in
the survey would reduce the response rate, as research has shown that the longer the
survey, the lower the response rate will be as respondents begin to perceive the survey as
costing them more than they are personally gaining (Groves et al. 2004:193; Dillman
2007:18). However, pretesting with all three of these relationship conditions included did
not show the survey to be too long (around 14 minutes), and there were no complaints
from pretesters that all three sections were too much for one sitting. Therefore, all three
conditions were included in the questionnaire as described above.
To determine eligibility, the first two questions on the questionnaire asked
respondents if they were currently enrolled in classes at KSU’s main campus, and
whether or not they owned a cell phone. Those respondents who answered ‘no’ to either
of these screening questions were brought to a new page where they were informed that
they were ineligible for the study, thanked for their time, and their web browser session
ended. These pages can be viewed at the end of the questionnaire in appendix 3.
A few complications arose during the programming of the survey. For instance,
one decision that needed to be made was whether or not the questions should be forced
choice, or if each question should have “no answer” as one of its options. This latter
option was especially problematic when it came to the quality of communication scales
(described under Measures), since it was important to keep the “no answer” option
separate from the actual 7-point scale, which seemed impossible to actually program. A
15
related problem was whether or not the “check-off” command, which makes it so that
respondents can move on to the next page without having to respond to all questions on
the current page, should be used on pages where there were open ended questions. If this
command was not included, then the respondent had to put in a number, but, if the
command was used, then the respondent could actually skip any question on that page
(thereby potentially increasing the number of item-missing data). The final decision was
to include this check off command wherever there was an open ended item so that the
Institutional Review Board’s (IRB) rules for voluntary participation would not be
violated. For this same reason, the decision was also made to include the “no answer”
option for each close ended question as well.
Implementation
The actual sample consisted of two separate randomly drawn samples obtained
from the university’s registrar’s office. The reason for having two separate samples is that
there was a problem with the university’s computer system which delayed the original
sample by three weeks. Because the survey was ready and time constraints were at hand,
the first random sample of 1,000 student emails were drawn from a random sample that
had been obtained by the Survey Research Lab from the exact same target population,
just days earlier. The survey went out to this first sample (sample A) in mid-February.
Once the second random sample (sample B) arrived from the registrars office three weeks
later, totaling 5,000 student emails, a computerized check was run to make sure that
sample B did not contain any of the same emails as did sample A. There were around 10
duplicates that were removed from sample B, which was then split into three waves (two
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of 1,600 and one of 1,700), totaling four waves when the two sampling frames were
combined (n=6,000). The first of five email solicitations to sample B (n=1,600) was sent
out in the beginning of March, along with the second of five emails for sample A.
Response Rate
After only a week of sample B having gone out, the total response rate for the two
active waves was close to about 20 percent, leading my advisor to determine that this was
probably more than sufficient for my analysis (almost 500 respondents). The remaining
two waves of sample B would not be needed since they would likely not increase the
response rate, and I was not in need of more completes than I had already obtained. In an
attempt to reduce nonresponse, up to five emails were sent out, once a week, to those
students who were contacted to take the survey. Students who responded to the survey
were not further contacted, but those who partially completed the survey, or who did not
respond, were contacted weekly either until they finished the questionnaire, responded, or
until the fifth reminder was sent out. Although increasing the response rate does not
guarantee that there will not be nonresponse bias in my statistics, it at least reduced the
likelihood of such error being present in my estimates (Groves et al. 2004), and was
therefore a desirable goal. After five contacts for each of the two waves separately (over
exactly a two month period), there were 541 completes (516 eligible; 25 ineligible; 116
partials) for a total of a 20.8 percent response rate. Out of the 2,600 emails sent, only
seven bounced back with the error message “quota full” leaving the final sampling frame
to consist of 2,593 units that were contacted for the sample. Of course, of that 2,593,
there is still no way of telling if nonrespondents ever opened the email, or whether they
17
were even eligible for the survey had they responded to it. It can, however, be seen from
looking at the data that there was an even split for why individuals were ineligible for the
survey: only 10 respondents did not have a cell phone, and 11 respondents were not
currently enrolled at the main campus of Kent State (overcoverage). As with all modes of
data collection, there were also the “take me off your list” requests from students who did
not like being solicited through their emails, especially five times over a five week
period. This was to be expected though, and it was a surprise that we did not receive
more of these emails than we did.
Past researchers have had mixed results in terms of their response rates for webbased surveys of college student populations (McCabe 2004), though surveys that
included an incentive appear to have higher response rates than those that did not. For
instance, in two separate web-based surveys involving college students that did not
include an incentive for participation, Sills and Song (2002) had a response rate of 22
percent after three contacts, and Carini et al. (2003) obtained a response rate of 40
percent. When including a $100 gift card to a major bookstore, though, Boyle and
Boekeloo (2006) achieved a response rate of 57 percent after four contacts, and McCabe
(2007), having guaranteed a $10 gift card to all respondents, achieved a response rate of
63 percent after four contacts. Based on this empirical evidence, I decided that it would
be beneficial to my response rate to include an incentive for participation in this survey,
as it would increase the perceived reward for participation (Dillman 2007a). Students
were thus informed in the email solicitation for the survey that, for their participation,
they would be entered into a drawing to receive a $100 gift card to the university’s book
18
store. Unfortunately, including this incentive did not boost the response rate as it had in
past studies of college populations, though it is possible that the response rate may have
been much lower than 20.8 percent had it not been included.
There were other methods suggested by Groves et al. (2004) that were
incorporated into this survey to increase the response rate as well, such as prolonging the
length of data collection (5 full weeks for each wave), and increasing the number of
contacts (five contacts was determined to be the most efficient) . In addition, it was found
that when potential respondents feel as though they are in some way connected to the
sponsor of the research, or view the topic of the survey as salient, they are more likely to
participate in the survey (Groves et al. 2004). Therefore, conducting the survey through
the SRL here at Kent State University (with the KSU logo included on each web page of
the questionnaire) likely served in my favor as students may have felt more connected to
the survey in general. Additionally, because of the emotional attachment many
individuals have to their cell phones (Vincent 2006), the topic may have been very
salient, thus leading my response rate to be higher than if the topic were less salient to
such individuals. Lastly, the factor that I feel is of utmost importance in determining
response rates is that respondents understand and trust that both their responses and
participation will be kept completely confidential. A lack of trust in this issue may lead
individuals to refrain from participation for fear of what might be done with such
personal information. Therefore, as can be seen in appendix 2, an attempt to establish
trust was included in the consent form, in which there was written agreement that no one
19
except the primary research would be able to link their name and contact information to
their responses.
MEASUREMENT
The actual measures for this research can be viewed in appendix 3.
Relationship Satisfaction: To measure relationship satisfaction, I used a
modification of Hendrick’s (1988) Relationship Assessment Scale (RAS). With only
seven items, it is an efficient measure of relationship satisfaction that is highly correlated
with much longer scales, such as with Spanier’s Dyadic Adjustment Scale (α = .80), a
highly respected measure of satisfaction (Hendrick 1988).
The RAS was originally designed to measure relationship satisfaction for intimate
relationships, but Hendrick agreed that, with minimal changes, the scale can be modified
to measure relationship satisfaction for other relationship types (e.g. friendships).
Therefore, I have modified the RAS so that it can be used to measure relationship
satisfaction systematically for each type of relationship (friend, family member, and
romantic partner) so that I can compare relationship satisfaction between each of these
conditions more accurately.
The modifications to the RAS for this research are shown in table 3.1, and include
changing the format of the items from a question (How well does your partner meet your
needs?; In general, how satisfied are you with your relationship?, etc.), to a statement
(This relationship meets my needs; I am satisfied with this relationship, etc.). As a result
of this change, it was also necessary to change the response categories from “Low
20
Satisfaction” (1) to “High Satisfaction” (5), to the categories “Strongly Disagree” (1) to
“Strongly Agree” (5).
Quality of Communication: The Iowa Communications Record (ICR) is a well
known communications record which was developed by Steve Duck, an expert in
communication studies, and his colleagues in 1991. Included in the ICR is a quality of
communication scale composed of items that were found, using factor analysis, to have
high intercorrelations in previous daily diary versions of the ICR (Duck et al. 1991). I
decided to use this scale as it has been shown to have high reliability in measuring quality
of communication (with alpha coefficients between .80 and .90) (Duck et al. 1991), and
will be useful in comparing quality of communication across studies if necessary. I also
included on the questionnaire some additional items that I felt would add dimensions of
quality of communication that are not included in Duck et al.’s (1991) ICR. These
additional items are “Not Enjoyable/Enjoyable” and “Low Quality/High Quality”, and
were included in an exploratory fashion. The contribution of these additional items to this
scale will be discussed in the following chapter.
To collect this data, for both the respondent’s last cell phone conversation, and
face-to-face communication, with their friend, romantic partner, or family member,
respondents completed the quality of communication scale from Duck et al.’s (1991) ICR
to assess the quality of communication that was experienced within those conversations.
Therefore, for each relationship section of the survey, respondents responded to two
separate quality of communication scales.
21
Mode of Communication: The two modes of communication in this research are
face-to-face communication and cell phone communication. Respondents were asked
how frequently they talk to their friend, romantic partner, or, family member within both
modes of communication, with response categories ranging from less than once a month
to three or more times a day. This construct is therefore made up of two ordinal variables
that assess the frequency of communication through each respective mode of
communication (freqcell and freqf2ff).
Type of Relationship: For this research, type of relationship was measured by
three relationship conditions: Friend, Romantic Partner, and Family Member.
ANALYSIS
In this research, I utilized OLS regression to regress my dependent variables,
relationship satisfaction and quality of communication (described above), on the
frequency of each mode of communication, the length of the relationship, whether or not
the relationship is long distance, the duration of the last conversation, whether or not the
last conversation was just for fun (versus instrumental), whether or not the proactive or
reactive callers were multitasking during conversations, and the age and sex of
respondents.
The measures for mode of communication are described in the Measurements
section above. Since I have hypothesized that the quality of communication moderates
the potential relationship between mode of communication and relationship satisfaction,
the quality of communication is also included as an independent variable in the
regression of relationship satisfaction.
22
The length of the relationship was measured in both years and months since this
variable was likely to have much variation, with some friendships and romantic
relationships lasting less than one year, and most family relationships lasting many years.
On the questionnaire, respondents were thus asked, “How long have you been [friends
with, related to, dating] [Friend, Family Member, Romantic Partner]?”, with an open
ended numerical box for both “[ open ] Years and [ open ] Months“. In order to actually
use this as one single variable in analysis then, the years and months were computed
together into the one single variable to come up with a single number that represented the
total length of the relationship in years.
The duration of the last conversation, also an open ended numerical question, was
simply measured in minutes. On the questionnaire, respondents were asked, “Thinking
about your last conversation with [friend, family member, romantic partner], about how
long did the conversation last?” Whether or not the relationship is characterized as longdistance or not was a dichotomous measure based on respondents answer to the question
“Would you consider your relationship with [friend, romantic partner, or family member]
to be long-distance (for this study, a long-distance relationship is one in which you
cannot see your partner, face-to-face, most days)?” Response choices included “Yes” and
“No”.
Multitasking, which was measured within both modes of communication, was
also controlled for in the regression models. Multitasking during cell phone
communication was measured with two dichotomous variables. The first variable
(AVTYRESPcellFR*) measured whether or not the respondent was multitasking during the
23
conversation with the questions: “When you called [friend, family member, or romantic
partner], where you engaged in another activity during the conversation?” or “When
[friend, family member, or romantic partner] called you, were you engaged in another
activity during the conversation?” The second variable (AVTYFRcell*) of multitasking
measured whether or not the [friend, family member, or romantic partner] was
multitasking during the conversation: “When you called [friend, romantic partner, or
family member], was he/she engaged in another activity during the conversation?” or
“When [friend, family member, or romantic partner] called you, was he/she engaged in
another activity during the conversation?” Respondents were asked two of these four
questions depending on who initiated the cell phone conversation.
Multitasking during face-to-face conversations was measured using three
dichotomous variables. The first measured whether respondents and the friend, romantic
partner, or family member were engaged in an activity together (F2FavtyFR*). The
second measured whether or not the respondent was solely engaged in activity during the
face-to-face communication (ActFRb*), and the third, whether or not the friend, family
member, or romantic partner was engaged in an activity during the face-to-face
communication, separate from the respondent (ActFRc*).
The last variables included in my regression models include the respondents’ age
and sex, and were measured using standard demographic questions from Bradburn,
Sudman, and Wansink’s (2004) book, Asking Questions.
24
Analytical Plan
Including the independent variables I have described above yielded the following
regression equations for the four hypotheses*:
Relsat = y + b(FreqF2FFR) + b(FreqCellFR) + b(LengthRelFR) + b(LongDistFR) +
b(Female) + b(Age)
QualF2FFR = y + b(FreqF2FFR) + b(FreqCellFR) + b(LengthRelFR) + b(LongDistFR)
+ b(ActFRb) + (ActFRc) + b(Female) + b(Age)
QualCellFR = y + b(FreqF2FFR) + b(FreqCellFR) + b(LengthRelFR) + b(LongDistFR)
+ b(JustforfunFR) + b(lengthconvoFR) + b(AVTYFRcell) + b(AVTYRESPcellFR)+
b(Female) + b(Age)
Relsat = y + b(FreqF2FFR) + b(FreqCellFR) + b(QualF2FFR) + b(QualCellFR) +
b(LengthRelFR) + b(LongDistFR) + b(Female) + b(Age)
Prior to running the multiple regressions, confirmatory factor analyses were
conducted to see whether the items I added to the quality of communication measures in
my questionnaire correlated high with Duck et al.’s 1991 ICR quality of communication
items. Because these additional items did correlate high with the ICR quality of
communication items, which will be discussed further in the following chapter, they have
been included in the quality of communication scale that was used in the multiple
regressions. A confirmatory factor analysis was also run on the RAS items in the
25
questionnaire, prior to running the regressions, to verify the reliability of this scale in my
sample.
Because there are different types of relationships that need to be controlled for
when looking into my dependent variables (Duck et al. 1991), separate regressions were
run for each relationship condition. Therefore, there were a total of nine regression
analyses run to test my four hypotheses: one for mode of communication on relationship
satisfaction for each relationship condition, one for mode of communication on quality of
communication within each relationship condition, and one to test for mediation within
each relationship condition. However, each full regression was actually composed of two
or three models, depending on the hypothesis. Hypotheses 1 and 2 combined, as well as
hypothesis 4, are composed of three models each as will be seen in the following chapter.
Hypothesis 3, however, is composed of two models for each type of relationship: one
model with the quality of face-to-face communication as the dependent variable, and one
model with the quality of cell phone communication as the dependent variable.
Therefore, there are a total of nine complete regression tables, though actually 24
regression models were run between the three relationship conditions being studied.
But regressions were not the only form of analysis utilized. Because the quality of
communication was measured separately for both modes of communication, there could
not be a single regression of quality of communication on the predictor variables. Instead,
there were two separate regressions, within each type of relationship, in which each of the
two respective quality of communication variables were separately regressed on the
predictor variables. In order to test hypothesis 3 then, for each relationship condition, a
26
paired samples t-test was utilized to test for significant differences between the average
quality of face-to-face communication and the average quality of cell phone
communication. This test is appropriate for these measures and this hypothesis as it
computes the difference between the total scores of the two quality of communication
scales within each case, and then tests to see whether the average difference between
these total scores is significantly different from zero.
The next step in analysis was to test hypothesis 4, which reveals whether or not
the quality of communication variables act as mediators for the potential effects of mode
of communication on relationship satisfaction within hypotheses 1 and 2 for each
relationship condition. Baron and Kenny (1986) list the criteria that must be present for
mediation to exist. In my research, there must first be a significant relationship between
the mode of communication and relationship satisfaction, without controlling for the
quality of communication (hypotheses 1 and 2). Second, there must be a significant
relationship between the mode of communication and the quality of communication
(hypothesis 3). Thirdly, there must be a significant relationship between the quality of
communication and relationship satisfaction, as past research has found (EmmersSommer 2004; Ramirez 2002). If all three of these conditions hold true, then I will be
able to test for mediation (hypothesis 4). Mediation will be evident if, when including
quality of communication in the regression of relationship satisfaction on mode of
communication, the previously significant relationship between mode of communication
and relationship satisfaction becomes insignificant, or significantly reduced. Such
mediation would mean that the effect mode of communication had on relationship
27
satisfaction is either wholly, (if the coefficient equals zero), or partly (if the coefficient is
reduced, but not zero) accounted for by the effect the quality of communication has on
relationship satisfaction.
In the case that the above requirements for mediation are not met, or that the
relationship between mode of communication and relationship satisfaction is not
significantly reduced when quality of communication is added into the model, I will
reject the hypothesis that quality of communication is a significant process through which
the relationship between the mode of communication and relationship satisfaction holds
true. As I stated before, the effect of the mediator variable may be different across each
type of relationship. For example, I may find that hypothesis 4 only holds true for two
relationship conditions (ex. friends and romantic partners), but is stronger for one
relationship condition (ex. romantic partners) than it is for the other (ex. friends).
*Variables illustrated represent those for friendships, as denoted by the initials FR.
These variables are identical for romantic and familial relationships, though they are
separately denoted by the initials RP and FAM, respectively
Table 3.1 Comparison of Modified RAS Items to Original RAS Items
Original Items
Modified Items
How well does your partner meet your needs?
This [friendship/relationship] meets my needs
How good is your relationship compared to most?
[ ] and I have a very good [friendship/relationship]
compared to most
I often wish that I was not in this[friendship/relationship]
How often do you wish you had not gotten into this
relationship?
To what extent has your relationship met your original
expectations?
How many problems are there in your relationship?
In general, how satisfied are you with your relationship?
How much do you love your partner?
I get what I would expect from my
[friendship/relationship] with [ ]
There are problems in my [friendship/relationship] with [ ]
I am satisfied with this [friendship/relationship]
I care about [ ] very much
Original scale items taken from Hendrick’s (1988) Relationship Assessment Scale. Responses to original items range from 1 (low
satisfaction) to 5 (high satisfaction). Responses to modified items range from 1 (strongly disagree) to 5 (strongly agree)
28
CHAPTER IV
RESULTS
DESCRIPTIVES
Table 4.1 presents a comparison of the sample demographics to those of the target
population, Kent State University. Out of the sampling pool of 2,593, there were a total
of 541 respondents who responded to the survey, for an overall response rate of 20.8
percent. Of the 516 respondents who completed the survey, 76 percent were female, 81.6
percent were white, 9.30 percent Black, 3.14 percent Asian, and the approximately 3.5
percent remaining were of Hispanic, Native American, or “Other” decent. The age of
respondents ranged from 18 to 65 years old, with an average age of 26 years. No statistics
for the age of Kent State University students were found for comparison with this sample.
The nature of my sample compared to the parameters of the Kent State University student
body limits slightly my ability to generalize the findings presented in this chapter, to the
population of which my sample was drawn. The reader may refer to table 4.2 for the
descriptive statistics of the data obtained for the main variables used in analyses.
The overall reliability for the scales used in the analyses are very good, and can be
viewed in tables 4.3, 4.4, and 4.5. The quality of face-to-face communication scales,
which included two additional items along with the original items, had overall
29
30
reliabilities of .88 for friends, and .89 for both romantic partners and family members. To
see whether these additive items, not enjoyable/enjoyable and low quality/high quality,
actually add to this scale though, it is important to see how the scale would change if
these items were removed. In fact, if either of these two additional items were removed
from these scales, Cronbach’s alpha would drop to .86 for friends, .874 for romantic
partners, and to .883 and .886, respectively, for family members. In all three cases,
removing either of these items would lead to larger reductions in Cronbach’s alpha when
compared to removing most of the other items on this scale. Although removing these
items would still leave Cronbach’s alpha high, I still find it beneficial to keep these
additional items in the scale composing the overall quality of face-to-face communication
as I believe they do add dimensions to the scale which were not included initially.
For the quality of cell phone communication scales, which also included the two
additional items above along with the original items, the overall reliabilities were .894 for
friends, .887 for romantic partners, and .892 for family members. If either or these
additional items were removed from these scales, Cronbach’s alpha would drop to.877
for friends, .870 for romantic partners, and .875 for family members. Just as above,
removing either of these two items would lead to larger reductions in Cronbach’s alpha
when compared to removing most of the other items on this scale. This is a significant
finding, and shows that the items which were added to the scale in this research clearly fit
into this scale statistically, as well as theoretically, and therefore have remained in the
scales for analysis. It is also important to keep these items in the scales as above so that
the two scales will be comparable when it comes to testing hypothesis three. With both of
31
these quality of communication scales having reliability coefficients between .88 and
.894, they are consistent with previous research which has shown the reliability of these
scales to range from .80 to .90 (Duck et al. 1991).
As presented in table 4.5, the modified RAS items also appear to be measuring the
same underlying construct: relationship satisfaction. At .87, Cronbach’s alpha was
highest between the items measuring the overall relationship satisfaction of romantic
partners. Although still very reliable, in comparison to romantic partners, friends and
family members had notably smaller reliability coefficients at .83 and .82, respectively.
BIVARIATE CORRELATIONS
Prior to running the main analyses, zero order correlations between the variables
in this study were identified to check for evidence of potential multicollinearity. There
are three separate matrixes: one for the variables exclusive to each type of relationship.
The reader may refer to Appendixes 4, 5, and 6 to view these matrixes. Theoretically,
there were only a few associations that I feel should be mentioned as evidence of
potential multicollinearity. Within all three types of relationships, there were moderate to
strong negative associations between the frequency of face-to-face communication and
whether or not the relationship was long distance (friends: r = -.756; romantic partners: r
= -.798; family: r = -.625). It makes logical sense that this would be the case, though I do
feel that each of these two variables has its own, direct effect on the dependent variables
in this study. Therefore, although multicollinearity may be a threat, I have continued to
keep both variables in the regression models to see how each one affects the dependent
variables while controlling for the others. It is interesting to see that, in all three types of
32
relationships, the correlation is much smaller between the frequency of cell phone
communication and the variable long-distance (friends: r = -.321; romantic partners: r = .121; family: r = -.180). For friends and family members alike, there were also notable
associations between the frequency of face-to-face communication and the frequency of
cell phone communication, with correlations of.499 and .384 respectively. Lastly, in all
three relationship conditions, the quality of communication variables have high
intercorrelations, which may affect the influence these two variables have on relationship
satisfaction within the regression models (friends: r = .697; romantic partners: r = .739;
family: r = .778). As a result of these notable bivariate associations, I advise the reader to
keep in mind when reviewing the results in this chapter that the potential presence of
multicollinearity may have affected the outcome of the results presented.
HYPOTHESES
To make reviewing the data a little less arduous, the regressions for hypotheses
one, two, and four were combined into three separate models. The first of the three
models for each type of relationship included the frequency of face-to-face
communication, but left out the frequency of cell phone communication. Model two was
just the opposite, including the frequency of cell phone communication as a predictor
variable, and omitting the frequency of face-to-face communication. And lastly, the third
and final model included the frequency of both modes of communication. In hypothesis
four, which is a test of mediation, the quality of face-to-face communication and the
quality of cell phone communication were also split up into the three separate models.
Therefore, model one excludes to the frequency and quality of cell phone
33
communication, model two excludes the frequency and quality of face-to-face
communication, and model three includes all four of these quality and frequency of
communication variables. The tables presenting the results of the following hypotheses
can be found at the end of this chapter.
Hypotheses 1 and 2:
In Chapter I, I discussed the potential floor and ceiling affects of the frequency of
face-to-face communication, which could limit the variability of relationship satisfaction
beyond such values. Thus, it was therefore necessary to first check the bivariate
distribution of relationship satisfaction and frequency of face-to-face communication, to
check for such floor and ceiling effects. I was pleased to see that there was no evidence of
such values in any of the three types of relationships, allowing me to go forth with the
regressions unhindered.
Tables 4.6-4.8 present the results for hypotheses one and two. Hypothesis one
stated that, as the frequency of cell phone communication increases, the overall
relationship satisfaction will decrease. The results reveal that this hypothesis was not
supported by any of the three types of relationships studied. In fact, the relationship
between the frequency of cell phone communication and relationship satisfaction is
actually supported as a positive relationship for friends and romantic partners in both runs
two and three of the regressions. Therefore, as the frequency of cell phone
communication between friends increases by one standard deviation, the overall
relationship satisfaction also increases by .115 standard deviations. Results are similar for
romantic partners, where, as the frequency of cell phone communication between
34
romantic partners increases by one standard deviation, the overall relationship
satisfaction increases by .142 standard deviations. Interestingly, in model two, family
members also showed a highly significant positive relationship (β = .125; p < .007)
between the frequency of the cell phone communication and the overall relationship
satisfaction. However, in model three, when the frequency of face-to-face communication
was controlled for, the association was no longer significant.
Hypothesis two had similar results, in that the relationship between the frequency
of face-to-face communication and relationship satisfaction held true for two of the three
types of relationships studied: family members and romantic partners. This hypothesis
stated that, as the frequency of face-to-face communication increased, relationship
satisfaction would also increase. Results show that as the frequency of face-to-face
communication between family members increases by one standard deviation, their
overall relationship satisfaction increases by .141 standard deviations. For romantic
partners, as the frequency of face-to-face communication increases by one standard
deviation, their overall relationship satisfaction increases by .237 standard deviations.
The frequency of face-to-face communication between Friends, however, appeared to
have no significant relationship with their overall relationship satisfaction, though it came
close to significance (β = .138; p < .056) when the frequency of cell phone
communication was not controlled for (model one).
The variables that were controlled for in these two hypotheses, including whether
or not the relationship was long-distance, the length of the relationship, and the age and
35
gender of the respondents, showed no final association with relationship satisfaction for
friends or family members. 1 Though the age of the respondent had a significant, negative
correlation with relationship satisfaction in model one for friends, (β = -.107; p < .05) it
did not remain significant in models two or three, when the frequency of cell phone
communication was entered into the models. Two of these control variables did however
have significant associations with the relationship satisfaction for romantic partners. The
length of the relationship remained significant in all three models, though it was slightly
more significant in model two (β = .248; p < .004) than in model three (β = .221; p <
.011). To take the conservative coefficient, it could be said that as the length of the
romantic relationship increases by 6.68 years in my sample, the relationship satisfaction
reported increases by .221 standard deviations on the modified RAS. Whether or not the
relationship was long distance was the second variable to show a significant association
with relationship satisfaction for romantic partners, though the significance dropped off
in model two. In model one, the standardized coefficient was .218 (p < .019), whereas in
model three it dropped slightly to .192 (p < .039). As this variable was dummy coded,
this would mean that romantic partners who are in long-distance relationships reported
higher relationship satisfaction than their counterparts: an unexpected finding indeed,
though this association is not longer significant when the quality of communication
indicators are controlled for in the analysis of hypothesis 4.
1
For purely exploratory reasons, Race was originally included in the regression models, with White’s being
compared to African Americans (the two largest groups in my sample at 81.2 and 7.5 percent,
respectively). However, it was evident that there were no significant differences between the racial
categories, and that it would be best if the regressions were run again with this variable omitted. The new
regressions, described in this chapter, yielded much the same results as they had when race was included.
36
Of the nine separate regressions, split between the three types of relationships,
used to test hypotheses one and two, the adjusted R2 shows that the predictor variables
explained more of the variation in romantic partners relationship satisfaction than in the
other two types of relationships, though none of the adjusted R2‘s were particularly high.
In models one and two, the predictor variables explained approximately 5 percent of the
variance in relationship satisfaction between romantic partners. Including the frequency
of both modes of communication in model three, the adjusted R2 bumped up to .064,
meaning that knowing the predictor variables leads to a 6.4 percent reduction in error
when attempting to predict romantic partners overall relationship satisfaction. Though the
adjusted R2 showed slight changes in regards to family members and friends’ relationship
satisfaction over the three respective models, these statistics remained low. For friends
the adjusted R2 was only .019 in model one which included the frequency of face-to-face
communication, but not the frequency of cell phone communication. In model two, which
as opposed to model one, included the frequency of cell phone communication, but not
the frequency of face-to-face communication, the adjusted R2 was .033. Strangely, in the
third model, which included the frequency of both modes of communication, the adjusted
R2 dropped to .027. These statistics were even lower for family members, which fell at
.016 and .012 for models one and two, respectively, and inched only to .019 in model
three, which included the frequency of both modes of communication.
Hypothesis 3:
The next step in analysis was to test the relationship between the mode of
communication and the overall quality of communication. Hypothesis three stated that,
37
on average, the quality of communication for cell phone communication will be lower
than the quality of communication for face-to-face communication. Since the quality of
communication was measured separately for each mode of communication, it was not
possible to test for such differences using OLS regression. Instead, a Paired-Samples ttest was utilized to compare the means of the quality of face-to-face communication, and
the quality of cell phone communication, for each respective type of relationship. Results
of these three separate t-tests are shown in table 4.9. With all three of these pairedsamples t-tests yielding highly significant results (Friends p < .000; Romantic Partners p
< .000; Family p < .009), I am able to accept my research hypothesis that the quality of
communication is significantly related to the mode of communication, with the quality of
face-to-face communication being significantly higher on average than the quality of cell
phone communication. It should be noticed that, although this relationship is highly
significant for family members, it does show a slightly less significant correlation than
that of friends or romantic partners.
Although regression was not appropriate for testing hypothesis three, it was still
useful for seeing how the control variables affected the overall quality of communication
for both modes of communication. To do so, two separate regressions were model for
each type of relationship. The first, regressed the quality of face-to-face communication
on both the frequency of face-to-face, and cell phone communication, whether or not the
relationship was long distance, the length of the relationship, and the age and gender of
the respondent, as well as a few variables specific to face-to-face communication
(whether or not the respondent was multitasking, and whether or not the friend, family
38
member, or romantic partners were multitasking during the conversation). Interestingly,
these first sets of regressions showed no significant affects on the quality of face-to-face
communication, as can be seen in tables 4.10-4.12. Therefore, it appears that none of the
control variables had a significant effect on the overall quality of the face-to-face
communication between friends, family members, or romantic partners, leading the
adjusted R2’s for all three types of relationships to be very low. However, when looking
at the overall sample size for each of these three regressions, it can be seen that the
sample sizes dropped markedly from the overall final response rates for each of the three
relationship condition sections respectively (table 4.10: n = 72 ; table 4.11: n = 41 ; table
4.12: n = 142 ). This lack of units is likely one of the reasons why no such associations
were found within these three regressions, and the reason the sample sizes dropped so
low is due to two of the variables which were used in the models. Both whether or not the
respondent was multitasking, or the friend, family member, or romantic partner were
multitasking were included in the model, leading conversations that did not involve
multitasking by either participant to be eliminated from this model. In this case, these
latter conversations composed the majority of the sample for each relationship condition.
The second regression model for each type of relationship regressed the quality of
cell phone communication on the same basic control variables mentioned above, plus a
few which were specific to cell phone communication (including whether or not the
conversation was just for fun, the length of the conversation, and whether or not the
respondent, or family member, friend, or romantic partner was multitasking during the
conversation). The results of these three regression models, also shown in tables 4.10-
39
4.12, reveal numerous significant relationships. The most noteworthy finding is that in all
three types of relationships, female respondents in general reported higher overall quality
of cell phone communication than their male counterparts. This was the only variable
which had an effect on the quality of communication for all three types of relationships,
leading the remaining associations to be exclusive to each type of relationship I will
discuss.
For friends, the frequency of face-to-face communication had a negative effect on
the overall quality of cell phone communication: as the frequency of face-to-face
communication increases by one standard deviation, the overall quality of cell phone
communication between friends decreases by .212 standard deviations (β = -.212 (p <
.013). With an adjusted R2 of .049, these control variables appear to have explained a
small proportion of the variation in the overall quality of cell phone communication
occurring between friends.
Family members had the most significant associations between the control
variables and the overall quality of cell phone communication. Whereas the frequency of
face-to-face communication had a significant effect for friends, the frequency of cell
phone communication had a significant effect for family members. As the frequency of
cell phone communication increased by one standard deviation, the overall quality of cell
phone communication increased by .128 standard deviations (p < .011). Conversations
that were just for fun yielded higher quality of cell phone communication than
conversations that were for instrumental purposes (β = -.163; p < .001). The length of
40
conversations appears to have a positive affect on the overall quality of cell phone
communication between family members, with a .103 standard deviation increase in the
quality of cell phone communication for every 23:45 minute increase in the length of the
cell phone conversation (p < .035). In general, although the family member, friend, or
romantic partner being engaged in an activity during the conversation (AVTYFAMcell)
did not appear to have a significant effect on the overall quality of cell phone
communication, having the respondent alone engaged in an activity
(AVTYRESPCELLFAM) yielded a significant negative effect on the overall quality of cell
phone communication (β = -.135; p < .003). Lastly, the age of family members also had a
positive effect on their overall quality of cell phone communication: as the age of
respondents increased by 9.19 years, the overall quality of cell phone communication
increased as well by .105 standard deviations (p < .022). There are many significant
associations between the dependent variable and predictor variables with this regression,
and therefore it is not surprising that the adjusted R2 shows a 10.1 percent reduction in
error when using these predictor variables to explain the variation in the overall quality of
cell phone communication between family members. This does, however, leave a large
percentage (89.9) of the variance in the overall quality of cell phone communication
unaccounted for.
Aside from the gender difference noted above, romantic partners only showed one
other significant relationship between a control variable and the overall quality of cell
phone communication they experienced: whether or not the partner on the other line was
engaged in another activity during the cell phone conversation. This effect was negative,
41
with a β of -.189 (p < .003), and means that respondents reported lower overall quality of
cell phone communication when their partner was engaged in another activity during the
conversation. This finding is not that surprising; what is more surprising is that this is the
only type of relationship in which this finding was evident. The adjusted R2 for this
model (.045) was not as high as for friends or family members, but still shows that there
is a 4.5 percent reduction in error when using these predictor variables to explain the
variation in the overall quality of cell phone communication between romantic partners.
Hypothesis 4:
The final step in analysis was to identify whether or not the potential relationship
in hypotheses one and two was actually mediated by the overall quality of
communication. The fourth hypothesis, then, stated that the relationship between the
mode of communication and relationship satisfaction (hypotheses one and two) will be
mediated by the quality of communication. In order for this hypothesis to be tested
though, there were three conditions identified by Baron and Kenny (1986) (discussed in
my chapter on Methodology) that needed to be met. The first of these three conditions in
my research was that there must be a significant relationship between the mode of
communication and the quality of communication (hypothesis three). The second, that
there must be a significant relationship between the mode of communication and
relationship satisfaction, without controlling for the quality of communication
(hypotheses one and two). And thirdly, there must be a significant relationship between
the quality of communication and relationship satisfaction, which can be checked for in
the OLS regression of hypothesis four.
42
At this point in the analysis, however, it was realized that the nature of the
measures complicated the analysis, leading to a situation where there is no
straightforward indication of mediation, as was hypothesized. Because of the way mode
of communication was measured (two separate variables measuring frequency) as well as
the corresponding way that quality of communication was measured (again, measured
separately for each mode of communication), the actual analysis of mediation was as
follows:
Frequency of F2F
Communication
Quality of F2F
communication
Overall Relationship
Satisfaction
Frequency of Cell
phone Communication
Quality of Cell Phone
communication
Figure 4.1: Visual Description of Mediation
In figure 4.1, you can see that, for example, although the quality of cell phone
communication may mediate the relationship between the frequency of cell phone
communication and the overall relationship satisfaction, the quality of face-to-face
communication may not mediate the relationship between the frequency of face-to-face
communication and the overall relationship satisfaction. If the relationship between the
mode of communication and overall relationship satisfaction were truly mediated, both
quality of communication indicators would need to mediate the relationship between their
43
respective mode of communication and the overall relationship satisfaction. I find in the
analysis, however, that in not one of the three types of relationship is this the case.
Although I do not find myself able to empirically state that mediation exists as
hypothesized, it is still interesting to see what the analyses revealed, and I will therefore
continue now to present these results which can be found in tables 4.13-4.15. As could be
expected by this point in the analysis, the results of the analyses differed between the
three types of relationships. Thus, I will report the results of hypothesis four for each type
of relationship separately.
For friendships, there is slight evidence of the quality of cell phone
communication mediating the effect of the frequency of cell phone communication on the
overall satisfaction of the friendship. Table 4.6 for hypotheses 1 and 2 show that there is
no significant relationship between relationship satisfaction and the frequency of face-toface communication, which rules out the possibility of mediation existing for this mode
of communication. There is, however, a significant relationship between the frequency of
cell phone communication and relationship satisfaction, leading to further investigation
of mediation. However, in table 4.10, there is not a significant relationship between the
frequency of cell phone communication, and the quality of cell phone communication,
which actually rules out the possibility of mediation since the effect the frequency of cell
phone communication has on relationship satisfaction would need to work at least in part
through the quality of cell phone communication.
44
Regardless, there are some interesting findings to note in the results of the
analysis for hypothesis 4 found in table 4.13. The slight evidence of mediation I
mentioned previously is shown in model three. Although in model 2, the effect the
frequency of cell phone communication has on relationship satisfaction was slightly
reduced, it did not become insignificant, or significantly reduced. In model three,
however, the relationship between the frequency of cell phone communication and
relationship satisfaction becomes insignificant, though the quality of cell phone
communication does not (it is however, reduced by fifty percent!). It is interesting that
this is the case in model 3, but not in model 2. Clearly, the presence of the frequency and
quality of face-to-face items are influencing these statistics in model 3. The second
interesting finding in this table is that, although the frequency of face-to-face
communication showed no significant correlation with relationship satisfaction in table
4.6, (which did not include the quality of communication indicators), it did become
significant in table 4.13, after the quality of face-to-face communication was added into
the model. It appears that the quality of face-to-face communication may have been a
suppressor variable for the relationship between the frequency of face-to-face
communication and relationship satisfaction.
Results for romantic partners also evidence of some mediation, though for the
relationship between the frequency of face-to-face communication on relationship
satisfaction, rather than cell phone communication. In table 4.7, both modes of
communication show a significant relationship with overall relationship satisfaction, yet,
in table 4.11, both modes of communication fail to show a significant relationship with
45
the quality of either mode of communication. This right here invalidates the ability to say
true mediation exists. Yet, as with friendships, the analysis of hypothesis 4, shown in
table 4.14, also lends some interesting findings. In model 1, both the frequency and
quality of face-to-face communication are significantly related to the overall relationship
satisfaction, though the standardized coefficient for the effect that frequency of face-toface communication has on relationship satisfaction dropped by over one-third the effect
it had when the quality of face-to-face communication was not included in the model.
This appears to be evidence of mediation. In model 3, when the frequency and quality of
cell phone communication items are also included in the model, the effect that the
frequency of face-to-face communication had on relationship satisfaction becomes
insignificant. Just the opposite is the case for the frequency of cell phone communication
though. In model 2, both the frequency and quality of cell phone communication are
shown to be significantly related to relationship satisfaction, though in model 3, the
quality of cell phone communication is no longer significant. These are interesting
findings to which I will discuss in the proceeding chapter.
Lastly, the results for family members appear to show the closest case where
mediation may actually exist—most notably so for cell phone communication.
Hypotheses 1 and 2 showed, in table 4.8, that there was a significant relationship between
the frequency of cell phone communication and overall relationship satisfaction between
family members. This was only the case in model 2, meaning it was not the case when
the items for face-to-face communication were included in the models. In table 4.12,
there was also a relationship between the frequency of cell phone communication, and the
46
quality of cell phone communication, which satisfies the second requirement for
mediation to exist. And at last, in model 2 of table 4.15 for hypothesis 4, when the quality
of cell phone communication is entered into the model, the effect of the frequency of
communication on relationship satisfaction loses its significance, leading me to suggest
that this is evidence of mediation, though not so when face-to-face communication is
controlled for.
There may also be evidence of mediation for such face-to-face communication as
well though. In table 4.8, you can see a significant relationship between the frequency of
face-to-face communication and relationship satisfaction. Then, in table 4.15, when the
quality of face-to-face communication is controlled for, the effect that the frequency of
face-to-face communication has on relationship satisfaction is reduced by about forty
percent in model 1 (from β = .177 to β= .100) and by fifteen percent (from β = .141 to β =
.116) in model 3. Though the relationship does not become entirely insignificant, the
presence of the quality of face-to-face communication indicator clearly leads to a
substantial reduction the direct effect that the frequency of face-to-face communication
has on relationship satisfaction. Unfortunately though, as was the case in the previous
types of relationships, there was no direct relationship between the frequency and quality
of face-to-face communication in the results for hypothesis 3, found in table 4.12.
Therefore, the potential mediation discussed for this latter mode of communication is still
considered to be insufficient as evidence of true mediation.
47
Although the inclusion of the quality of communication variables did not show
much in terms of mediating effects, it did end up explaining a lot of the variance in the
overall relationship satisfaction of the respondents. For friendships, the quality of
communication indicators explained an additional 21 percent of the variance in
relationship satisfaction for model 3, with face-to-face communication explaining more
of the variation than the frequency of cell phone communication. The variance in
romantic partners’ relationship satisfaction was due in large part to the quality of
communication indicators as well. In model 3 of table 4.14, the adjusted R2 sits at .400,
with the quality of face-to-face communication explaining more of the variance than the
quality of cell phone communication. In fact, the effect that the quality of cell phone
communication has on relationship satisfaction in model 2 (significant at .001) becomes
insignificant when the quality of face-to-face communication is included in model 3.
Again, these quality of communication indicators also explain much of the variance in
relationship satisfaction between family members, with an adjusted R2 of .37 in model
three of table 4.15, up from .019 in model 3 of table 4.8. In all three types of relationships
then, it appears to be the case that the quality of face-to-face communication has a bigger
impact on the overall relationship satisfaction of the respondents than does the quality of
cell phone communication, though both are important in explaining relationship
satisfaction in most cases. I may now turn to a discussion of the results presented in this
chapter.
48
Table 4.1: Sample Descriptives Compared to KSU Demographics
KSU
Demographics
Percentage
Size (N)
Sample
Statistics
Percentage
SD
Min
Max
22,819
516
--
--
--
Not provided
26 (years)
9.19
18
65
Gender
Female
Male
60.8
39.1
75.4
24.6
---
---
---
Race
Asian
Black
Hispanic
White
Other
1.4
7.5
1.4
81.2
3.4
3.14
9.30
1.16
81.6
2.30
------
------
------
Class Standing
Freshman
Sophomore
Junior
Senior
Masters
Ph.D
25.2
15.7
15.6
20.6
13.8
4.6
10.3
12.2
15.9
28.7
18.8
13.2
-------
-------
-------
Status
Full time
Part time
80.2
19.8
80.6
18.8
---
---
---
Age
Kent State University Demographics taken from the following website:
http://www.rpie.kent.edu/newwebsite/Main.jsp?pageName=RPIE>University+Profile>C
ampus+Flash+Facts&campusCode=KC , accessed August 28th, 2008. These statistics are
based on the preceding Fall semester, 2007, since Spring 2008 statistics are not yet
available.
49
Table 4. 2: Descriptive Statistics
Mean
SD
Min
Max
4.41
4.50
4.35
0.63
0.58
0.73
1.71
1.57
2.00
5.00
5.00
5.00
3.74
5.49
3.02
2.15
1.86
1.89
1.00
1.00
1.00
7.00
7.00
7.00
4.74
6.30
4.72
1.67
1.39
1.61
1.00
1.00
1.00
8.00
8.00
Q
6.03
5.98
5.76
0.91
1.00
1.06
1.00
2.00
1.50
7.00
7.00
7.00
5.67
5.67
5.69
1.02
1.05
1.02
1.08
2.00
1.50
7.00
7.00
7.00
9.19
----6.41
6.68
8.96
18.0
----0.00
0.00
0.00
65.0
----25.92
45.50
60.00
-------
-------
-------
----
----
----
(%)
Dependent Variables
Relationship Satisfaction (FR)
Relationship Satisfaction (RP)
Relationship Satisfaction (FAM)
Explanatory Variables
Frequency of Face-to-Face Communication
With Friend
With Romantic Partner
With Family Member
Frequency of Cell Phone Communication
With Friend
With Romantic Partner
With Family Member
Quality of Face-to-Face Communication
With Friend
With Romantic Partner
With Family Member
Quality of Cell Phone Communication
With Friend
With Romantic Partner
With Family Member
Control Variables
Age of respondent
26.05
Female (= 1)
(75.4)
Long-Distance Relationship w/ Friend (= 1)
(47.7)
Long-Distance Relationship w/Romantic Partner(=1)
(25.4)
Long-Distance Relationship w/ Family member (= 1)
(71.8)
Length of Relationship w/ Friend
7.16
Length of Relationship w/ Romantic Partner
3.53
Length of Relationship w/ Family Member
23.69
Multitasking During Face-to-Face Communication
Respondent while w/ Friend (= 1)
(40.5)
Friend while w/ Respondent (= 1)
(37.0)
Respondent while w/ Romantic Partner (= 1)
(31.3)
Romantic Partner while w/ Friend (= 1)
(30.4)
Respondent while w/ Family Member (= 1)
(34.4)
Family Member while w/ Respondent (= 1)
(39.9)
Multitasking During Cell Phone Communication
Friend while talking to Respondent (= 1)
(51.2)
Romantic Partner while talking to Respondent (= 1)
(34.9)
Family Member while talking to Respondent (= 1)
(49.4)
Table 4.2 continued on following page
50
Table 4. 2 (continued): Descriptive Statistics
Mean
(%)
Multitasking During Cell Phone Communication
Respondent while talking to Friend (= 1)
Respondent while talking to Romantic Partner (= 1)
Respondent while talking to Family Member (= 1)
Length of Phone Conversation w/ Friend
Length of Phone Conversation w/ Romantic Partner
Length of Phone Conversation w/ Family Member
Spoke w/ Friend on phone Just for Fun (= 1)
Spoke w/ Romantic Partner on phone Just for Fun (=1)
Spoke w/ Family Member on phone Just for Fun (= 1)
(60.7)
(37.4)
(48.3)
17.91
13.62
16.98
(45.3)
(49.7)
(47.9)
SD
Min
Max
---23.74
18.42
18.84
----
---1.00
1.00
0.00
----
---200
150
150
----
51
Table 4.3: Quality of Face-to-Face Communication Scale Reliability
Cronbach’s Alpha
Cronbach’s Alpha
without additive items
including additive items
Romantic
Romantic
Friend
Family
Friends
Family
Partners
Partners
0.839
0.85
0.864
0.88
0.89
0.89
*Additive Items include “Not Enjoyable/Enjoyable” and “Low Quality/High Quality”
Table 4.4: Quality of Cell Phone Communication Scale Reliability
Cronbach’s Alpha
Cronbach’s Alpha
without additive items
including additive items
Romantic
Romantic
Friend
Family
Friends
Family
Partners
Partners
0.855
0.848
0.857
0.894
0.887
0.892
Original scale items taken from a portion of Duck et al.’s (1991) Iowa Communications Record.
*Additive Items include “Not Enjoyable/Enjoyable” and “Low Quality/High Quality”
Table 4.5: Overall Relationship Satisfaction Scale Reliability
Cronbach’s Alpha
Romantic
Friend
Family
Partners
0.83
0.87
0.82
Scale items taken and modified from Hendrick’s
(1988) Relationship Assessment Scale.
Table 4.6 Hypotheses 1 and 2: Friendships
Model 1
Frequency of face to face
Communication
Frequency of Cell Communication
Long Distance Relationship
Length of Relationship
Age
Female
R2
Adjusted R2
Model 2
B
SE
BETA
.041
.021
.138
.172
.007
-.007
.116
.089
.005
.003
.067
.030**
.019
N = 485
.137
.074
-.107*
.079
B
.058
.098
.008
-.006
.111
SE
.019
.061
.005
.003
.067
.043**
.033
N = 487
Model 3
1
BETA
.151*
.077
.079
-.091
.075
B
SE
BETA
.022
.023
.076
.044
.161
.008
-.006
.099
.020
.089
.005
.003
.067
.039**
.027
N = 485
.115*
.128
.077
-.092
.067
Dependent Variable: Relationship Satisfaction
*
Significant at p < .05
**
Significant at p < .01
52
Table 4.7 Hypotheses 1 and 2: Romantic Partners
Model 1
Frequency of face to face
Communication
Frequency of Cell Communication
Long Distance Relationship
Length of Relationship
Age
Female
R2
Adjusted R2
Model 2
B
SE
BETA
.123
.037
.312**
.366
.021
-.011
.130
.155
.009
.007
.098
.064**
.049
N = 319
.218*
.205*
-.129
.072
B
.101
.023
.025
-.010
.083
SE
.030
.096
.009
.007
.098
.065**
.050
N = 318
Model 3
BETA
.189**
.014
.248**
-1.35
.046
B
SE
BETA
.093
.038
.237*
.076
.322
.022
-.010
.103
.031
.155
.009
.007
.098
.082**
.064
N = 318
.142*
.192*
.221*
-.119
.058
Dependent Variable: Relationship Satisfaction
*
Significant at p < .05
**
Significant at p < .01
53
Table 4.8 Hypotheses 1 and 2: Family Members
Model 1
B
Frequency of face to face
Communication
Frequency of Cell Communication
Long Distance Relationship
Length of Relationship
Age
Female
R2
Adjusted R2
.054
.134
-.002
.000
.082
Model 2
SE
BETA
.018
.177**
.076
.004
.004
.062
.026*
.016
N = 489
.104
-.029
-.007
.061
B
SE
Model 3
BETA
B
.043
.045
.015
-.002
-8E005
.073
.017
.060
.004
.004
.062
.022
.012
N = 493
.125**
.012
-.033
-.001
.054
.028
.125
-.002
.000
.070
SE
.019
.018
.076
.004
.004
.062
.031**
.019
N = 489
BETA
.141*
.078
.097
-.035
.004
.052
Dependent Variable: Relationship Satisfaction
*
Significant at p < .05
**
Significant at p < .01
54
Table 4.9 Paired Samples T Tests
Mean
Difference
Std.
Error
Quality of Face-to-Face Communication
Quality of Cell Phone Communication
.35181
Romantic Quality of Face-to-Face Communication
Partners Quality of Cell Phone Communication
Family Quality of Face-to-Face Communication
Members Quality of Cell Phone Communication
Friends
T-Test
T
DF
.03402
10.342**
477
.31896
.04204
7.587**
312
.08460
.03224
2.624**
459
** Significant at p < .01
55
56
Table 4.10 Hypothesis 3: Friends
Model 1+
Frequency face to face
Communication
Frequency Cell Communication
Long Distance Relationship
Length of Relationship
Respondent Multitasking
face to face
Friend Multitasking
face to face
Cell Communication
Just for Fun
Length of Cell Conversation
Friend Multitasking on Cell
Respondent Multitasking
on Cell
Age
Female
R2
Adjusted R2
Model 2++
B
SE
BETA
B
SE
BETA
.100
.102
.187
-.099
.040
-.212*
.036
.690
.003
-.517
.106
.423
.023
.499
.051
.284
.017
-.227
.063
-.104
-.001
.035
.152
.008
.103
-.052
-.007
.398
.520
.172
.090
.107
.045
.001
-.192
-.082
.002
.103
.107
.015
-.095
-.040
.017
.309
.017 .154
.371 .115
.087
-.029
N = 72
+ Dependent Variable: Quality of Face-to-Face Communication
++ Dependent Variable: Quality of Cell Phone Communication
*
Significant at p < .05
**
Significant at p < .01
.007
.349
.006
.067
.112 .147**
.070**
.049
N = 450
57
Table 4.11 Hypothesis 3: Romantic Partners
Model 1+
Frequency face to face
Communication
Frequency Cell
Communication
Long Distance Relationship
Length of Relationship
Respondent Multitasking
face to face
Partner Multitasking
face to face
Cell Communication
Just for Fun
Length of Cell Conversation
Partner Multitasking on Cell
Respondent Multitasking
on Cell
Age
Female
B
SE
BETA
B
SE
BETA
.273
.256
.388
.048
.058
.087
-.143
.151
-.173
.079
.050
.104
1.072
-.006
.735
1.27
.048
1.14
.313
-.041
.343
.067
.003
.225
.013
.028
.020
-.984
1.18
-.450
.165
.137
.059
.004
.130
.010
.021
-.189**
.092
.092
.015
.015
.527
R2
Adjusted R2
Model 2++
.039
.128
.001
-.395
.011
.039
.128
.011
.010
.367 .241
.138
-.077
N = 41
.326
.148 .131*
.077**
.045
N = 295
+ Dependent Variable: Quality of Face-to-Face Communication
++ Dependent Variable: Quality of Cell Phone Communication
*
Significant at p < .05
**
Significant at p < .01
58
Table 4.12 Hypothesis 3: Family Members
Model 1+
Frequency face to face
Communication
Frequency Cell Communication
Long Distance Relationship
Length of Relationship
Respondent Multitasking
face to face
Family Multitasking
face to face
Cell Communication
Just for Fun
Length of Cell Conversation
Family Multitasking on Cell
Respondent Multitasking
on Cell
Age
Female
Model 2++
B
SE
BETA
B
SE
BETA
.121
.076
.201
.051
.034
.096
-.006
.407
-.027
-.271
.071
.305
.018
.270
-.009
.156
-.201
-.106
.080
.082
-.001
.031
.132
.007
.128*
.036
-.005
-.288
.263
-.117
.329
.098
.163**
.006
-.028
-.273
.003
.093
.092
.103*
-.014
-.135**
.016
.250
.007 .148*
.109 .105*
.121**
.027
.175
R2
.017
.226
.071
.216
.065
Adjusted R2
.015
.101
N = 142
N = 460
+ Dependent Variable: Quality of Face-to-Face Communication
++ Dependent Variable: Quality of Cell Phone Communication
*
Significant at p < .05
**
Significant at p < .01
Table 4.13 Hypotheses 4: Friends
Model 1
Frequency of Face to Face
Communication
Frequency of Cell Communication
Quality of Face to Face
Communication
Quality of Cell Communication
Long Distance Relationship
Length of Relationship
Age
Female
R2
Adjusted R2
Model 2
B
SE
BETA
.062
.020
.212**
.301
.180
.009
-.005
.023
.029
.082
.005
.003
.062
.210**
.200
N = 463
B
SE
Model 3
BETA
SE
BETA
.059
.021
.203**
.050
.018
.132**
.035
.230
.018
.041
.093
.323**
.237
.035
.007
-.008
.020
.027
.059
.005
.003
.065
.375**
.027
.071
-.118*
.013
.118
.207
.009
-.004
-.009
.036
.082
.005
.003
.062
.188**
.166*
.097*
-.064
-.006
**
.435
.145*
.092*
-.076
.015
B
.176**
.166
N = 464
.254**
.240
N = 452
Dependent Variable: Relationship Satisfaction
*
Significant at p < .05
**
Significant at p < .01
59
Table 4.14 Hypotheses 4: Romantic Partners
Model 1
Frequency of Face to Face
Communication
Frequency of Cell Communication
Quality of Face to Face
Communication
Quality of Cell Communication
Long Distance Relationship
Length of Relationship
Age
Female
R2
Adjusted R2
Model 2
B
SE
BETA
.077
.030
.193*
.453
.130
.016
-.011
.019
.034
.127
.007
.006
.079
415**
.403
N = 307
B
SE
Model 3
BETA
SE
BETA
.058
.032
.147
.086
.028
.159**
.056
.407
.027
.051
.104*
.544**
.329
.017
.023
-.011
-.034
.036
.090
.008
.007
.092
.460**
.010
.226**
-.113
-.019
.040
.115
.017
-.010
.007
.048
.132
.007
.006
.083
.055
.068
.171*
-.126
.004
.603**
.077
.156*
-.137*
.011
B
.273**
.258
N = 298
.416**
.400
N = 294
Dependent Variable: Relationship Satisfaction
*
Significant at p < .05
**
Significant at p < .01
60
Table 4.15 Hypotheses 4: Family Members
Model 1
Frequency of Face to Face
Communication
Frequency of Cell Communication
Quality of Face to Face
Communication
Quality of Cell Communication
Long Distance Relationship
Length of Relationship
Age
Female
R2
Adjusted R2
Model 2
B
SE
BETA
.030
.015
.100*
.021
**
.338
.078
.001
-.008
-.041
.064
.003
.003
.051
.377**
.369
N = 459
B
SE
Model 3
BETA
SE
BETA
.035
.016
.116*
.009
.015
.026
-.011
.324
.015
.033
-.032
.586**
.274
-.006
-.005
-.004
-.027
.024
.055
.004
.003
.057
.481**
-.005
-.075
-.066
-.020
.019
.095
.001
-.009
-.048
.034
.065
.003
.003
.053
.034
.075
.014
-.142**
-.036
.605
.061
.014
-.132**
-.031
B
.235**
.225
N = 461
.381**
.370
N = 442
Dependent Variable: Relationship Satisfaction
*
Significant at p < .05
**
Significant at p < .01
61
Table 4. Summary of Findings for Friendships
Dependent Variable:
Hypotheses
1 and 2
Hypothesis 4
Relationship
Satisfaction
Relationship
Satisfaction
( + )**
Frequency of Face-to-Face Communication
Frequency of Cell Phone Communication
Quailty of Face-to-Face Communication
Quailty of Cell Phone Communication
Long-Distance Relationship ( = 1 )
Length of Relationship
Hypothesis 3
Quality of
Face-to-Face
Communication
Quality of
Cell Phone
Communication
( - )*
( + )*
( + )**
( + )**
*
( + )*
Age of Resondent
Female ( = 1 )
** p < .05
* p < .01
**
62
Table 4. Summary of Findings for Romantic Partners
Dependent Variable:
Frequency of Face-to-Face Communication
Frequency of Cell Phone Communication
Hypotheses
1 and 2
Hypothesis 4
Relationship
Satisfaction
Relationship
Satisfaction
( + )*
( + )*
Quailty of Face-to-Face Communication
Hypothesis 3
Quality of
Face-to-Face
Communication
Quality of
Cell Phone
Communication
( + )*
( + )**
Quailty of Cell Phone Communication
( - )**
Romantic Partner Multitasking on Cell Phone
Long-Distance Relationship ( = 1 )
Length of Relationship
*
( + )*
( + )*
Age of Resondent
Female ( = 1 )
** p < .05
* p < .01
*
63
Table 4. Summary of Findings for Family Relationships
Dependent Variable:
Frequency of Face-to-Face Communication
Hypotheses
1 and 2
Hypothesis 4
Relationship
Satisfaction
Relationship
Satisfaction
( + )*
( + )*
Quality of
Face-to-Face
Communication
Quality of
Cell Phone
Communication
( + )*
Frequency of Cell Phone Communication
Quailty of Face-to-Face Communication
Hypothesis 3
( + )**
Quailty of Cell Phone Communication
( + )**
( + )*
**
Cell Conversation was Just for Fun
Length of Cell Phone Conversation
Respondent Multitasking on Cell Phone
Long-Distance Relationship ( = 1 )
Length of Relationship
Age of Resondent
Female ( = 1 )
** p < .05
* p < .01
( - )**
( - )*
*
64
CHAPTER V
DISCUSSION
The results from this research yield interesting findings between the three relationship
conditions in terms of how the mode of communication individuals’ use affects their relationship
satisfaction, and how the two modes of communication differ in the overall quality of
communication that is experienced within each mode. With these findings, the question of
whether or not communication over the cell phone is as beneficial or useful to a relationship as
face-to-face communication appears to be, can now be answered. A summary of the following
hypotheses can be found in table 5.1 at the end of this chapter.
The results show that the more friends talk on the phone with each other, the higher
relationship satisfaction they report in their friendship. Unfortunately, due to the method in which
data were collected, causality cannot be determined. It is possible that more satisfying friendships
lead to more phone calls with each other. However, this finding could also suggest that having
more contact with friends on the cell phone leads to higher relationship satisfaction with those
friends. In this case, it would mean that mere contact is what is important in a friendship. This
could suggest that friendships are based on how much maintenance and effort (by both persons) is
put into keeping in touch with a friend, and the psychological meaning that comes about from
such actions. It was also found that the frequency of face-to-face contact did not appear to be
related to relationship satisfaction between friends. This suggests, when paired with the former
finding, that it is less important for friends to meet up and do things together to maintain their
relationship, and more important that they stay in contact through calls on the phone. Therefore,
65
66
in the case of friendships, the cell phone does serve as a sufficient proxy to face-to-face
communication when the quality of such communication is not controlled for.
The results also showed that, in general, older individuals reported higher relationship
satisfaction with friends than did younger respondents. This may be a selection effect. For
example, many of the traditional college age students may have used friends they have met during
their time at college to respond to this survey, meaning that the friendships they reported on were
less long-term and possibly more unstable. Non-traditional college students, on the other hand,
likely have made fewer close friends at college for numerous reasons. For instance, they do not
tend to live on or around campus where many friends are made, and likely have much less free
time for making friends as they may have an immediate family of their own, a full time job, or
other responsibilities that they invest their time in. Therefore, older, non-traditional college age
students may have used one of their long-time friends when responding to this survey. Long-term
friendships likely have higher relationship satisfaction than short-term friendships, as the nonsatisfying friendships likely weed themselves out over the years, and the satisfying relationships
likely strengthen. This possible selection effect may explain why older respondents reported
higher relationship satisfaction with their friends than younger respondents in model one.
Family relationships are just the opposite of friendships in terms of maintaining their
relationships. The results show that the more family members see each other, the higher the
relationship satisfaction they report, and the amount they speak on the cell phone makes no
difference in their overall relationship satisfaction when this face-to-face communication is
accounted for. Though no causality can be determined here either, these findings suggest that it is
more important for family members to make contact physically than it is for them to stay in touch
on the cell phone. Thus, the result within familial relationships is that the cell phone does not
67
serve as a sufficient proxy for face-to-face communication when the quality of such
communication is not controlled for. But why does seeing each other face-to-face trump speaking
to each other on the cell phone? One explanation for this finding may be that a visit with a family
member can be a comforting experience, especially for traditional age college students who have
moved out of the nest and off to college, and may appreciate the time they have with their family
members more as a result. These visits may have great psychological benefits to individuals,
making them feel closer to their family members than the individuals who get to see their family
members less frequently. It is also likely that family relationships are much more stable than
friends or romantic relationships, which are much more likely to end without relationship
maintenance on the cell phone. Therefore, one possible explanation for the finding that
communicating in person is more beneficial than communicating on the phone may be that
individuals see speaking to family members on the phone as more burdensome than the rewarding
face-to-face visits, since they may at least subconsciously understand that their familial
relationship is not going to end due to a lack of cell phone communication.
Maintaining a satisfied romantic relationship appears to be more involving than
maintaining satisfied friendships or familial relationships. The results for the first two
hypotheses showed that the frequency of both face-to-face and cell phone communication
affect the overall relationship satisfaction in romantic relationships. Again, there is no
way to determine causality in this survey. However, these findings likely suggest that
romantic partners who get to see each other frequently, as well as speak to each other on
the phone frequently, develop higher relationship satisfaction than those relationships
where there is less frequent face-to-face and cell phone contact, although this is
contradicted by the finding that partners in long distance relationship actually reported
68
higher relationship satisfaction than their counterparts. However, this latter association is
no longer significant when the quality of communication variables are controlled for in
the analysis of hypothesis 4. Thus, these findings suggest that although the cell phone
does appear to add a positive dynamic to romantic relationships, it is not a sufficient
means to building and maintaining a satisfied romantic relationship.
One must ask why utilizing both modes of communication is necessary for
romantic relationships, but not for friendships or familial relationships? This could be due
in part to the maintenance that likely must go into romantic relationships, since they may
demand more maintenance than the other relationship conditions as romantic
relationships are naturally more fragile than family ties in the majority of cases, yet
possibly more intense than friendships. The term maintenance here includes many
different aspects that need attended to, including communication, intimacy, trust,
developing social ties, bonding, and numerous other possibilities. This would suggest that
it requires more work to build satisfying romantic relationships, and therefore more
communication and contact is needed, no matter what mode the communication occurs
through. Also, the feelings involved in all three relationship conditions likely differ, and I
would argue that the feelings involved in romantic relationships would lead individuals to
also desire contact with their partner more often than not: contact in any form is
beneficial to their relationship, with each mode of communication bringing with it
different benefits than the other.
69
Lastly, although it was found that the longer individuals are in a romantic
relationship the higher their relationship satisfaction is, I would argue that this is much
more of a selection effect than an actual causal relationship: unhappy couples are more
likely to end their relationship, leaving a greater ratio of satisfying relationships to
unsatisfying relationships over time.
The previous findings revealed the effect that the mode through which individuals
communicate affects their overall satisfaction within their relationships when the quality
of such communication is not controlled for. The next step, though, was to see how the
quality of communication compares between the two modes of communication, possibly
revealing a process by which the two modes of communication have an effect on
relationship satisfaction. The Paired Samples T Test revealed that in all three types of
relationships, talking face-to-face yielded higher quality of communication than did
talking on the cell phone. In order to better understand why this quality of
communication gap exists between the two modes of communication, it is beneficial to
understand how certain variables may affect the quality of face-to-face and cell phone
communication. Interestingly, as can be seen in table 4.10-4.12, none of the models
which regressed the quality of face-to-face communication on the predictor variables
were significant, though all three models which regressed the quality of cell phone
communication on the predictor variables were highly significant. It appears then, that the
influential characteristics affecting the quality of face-to-face communication were not
included in this study. However, this lack of significance may also be due to the number
of units the regression was based on, in which case the predictor variables in these three
70
models may actually have significant effects on the quality of face-to-face
communication, though the regression models lack power.
Results for the quality of cell phone communication models show that in all three
types of relationships, females reported higher quality of communication than did males.
Though there is a considerable amount of research suggesting that females and males
have different communication styles (see for instance Tannen 1990 and James 2003), I
have been unsuccessful in finding an empirical theory as to why females would, on
average, report higher quality of cell phone communication than would males. This
statistic was also evident in Duck et al’s (1991) research, though they provided no
theoretical explanation for such findings. Having no empirical evidence to provide a
theoretical explanation, I find that it may be beneficial to the study of communications if
more in-depth research be conducted to identify why such quality of communication
differences exist between the two separate genders.
For romantic partners, it was found that respondents whose partners were
multitasking during their cell phone conversation reported lower quality of cell phone
communication than when their partner was not multitasking. This finding suggests that
romantic partners may need to feel as though their partner is giving them their full
attention in order to be satisfied with the communication. Having their partner only half
paying attention could potentially be insulting as it may lead individuals to feel as though
their partner does not really care to be on the phone with them, but rather is treating the
conversation as a task. Another potential explanation for this finding is that romantic
71
conversations may require more emotional expression, and when one is engaged in a
separate activity, it may be difficult to reach that emotional aspect of communication as
the brain has to jump back and forth between tasks (Brown 2006).
The predictor variables in these models statistically explain more of the variance
in family members reported quality of cell phone communication than the latter
relationship conditions. Family members reported higher quality of cell phone
communication when they spoke just for fun rather than for instrumental purposes. It is
interesting that this finding was true for family relationships, yet not for friends or
romantic partners. This may be due to the content of communication that occurs between
family members, particularly within instrumental conversations. For instance, if a college
student calls home and speaks to a parent for instrumental purposes such as trying to
organize a ride home for the weekend, or discussing money or food plans, the
conversation may be stressful. Instrumental conversations between friends or romantic
partners are likely to be much less stressful: discussing where to meet for lunch, what
movie to go see, which person is going to drive to see who and when, etc.
It is also interesting that, whereas respondents did not like their romantic partners
multitasking during a conversation, respondents who themselves were multitasking
during the conversation with a family member reported lower quality of cell phone
communication. Since their relationship is not greatly affected by communication on the
cell phone, respondents may actually feel burdened to speak to their family members
when they are trying to focus on a separate task, thus making the communication more of
72
a task itself. The lower quality of communication may arise from this situation as
respondents have trouble focusing on both tasks, possibly leading to distress, and
potentially leading the actual content of the communication to suffer as a result. It was
also found that older respondents report higher quality of communication with family
than younger respondents. Though I have no theoretical explanation for this finding, it
may be interesting for future research to be done to see why this age difference exists.
The final two of these findings may be selection effects. For instance, the more
family members spoke on the cell phone, the higher was their overall quality of cell
phone communication. Though it is possible that this is a causal effect, it is likely that the
higher the overall quality of cell phone communication between family members, the
more they choose to communicate with each other on the cell phone. Secondly, the longer
family members spoke on the cell phone, the higher their quality of cell phone
communication was, though it may be that high quality phone communication leads
family members to continue talking rather than ending a call.
The last of the four hypotheses tested whether or not the quality of the
communication was actually mediating the association between the mode of
communication and overall relationship satisfaction. Unfortunately, as was previously
discussed, because of the actual discrete measures used in this survey, it was impossible
to directly test for mediation. However, it is possible to see how the inclusion of these
quality of communication variables altered both the overall explanatory value of the
models themselves, and the original relationships found in the analyses for hypothesis 1
73
and 2. In all three relationship conditions, the quality of communication variables
increased the adjusted r2 by .13 to .36 from the analyses of hypothesis 1 and 2 to the
models for hypothesis 4. These increases were highest for family relationships and then
so for romantic partners (by .36 and .35, respectively, in the third models for each
regression). Though much smaller for friendships, it is still a large increase of .21 in
model three for each respective regression. These increases in the coefficient of
determination support past research that has found the quality of communication to
explain between 19 percent (Emmers-Sommer 2004) and 36 percent (Ramirez 2002) of
the variation in relationship satisfaction. It is clear from this current research that the
quality of communication has a far greater impact on the overall relationship satisfaction
of respondents than does the quantity and mode of communication, in all three
relationship conditions. Therefore, these findings suggest that it is more important that
individuals engage in high quality communication than it is to have frequent and lengthy
communication via both modes of communication: a finding that I would argue goes
against the feelings and behaviors of the majority of college students today.
For friendships, it was suggested that the quality of face-to-face communication
may have been a suppressor variable for the effect that the frequency of face-to-face
communication had on relationship satisfaction. If this is the case, then higher quality
face-to-face communication across all frequencies of communication between friends has
positive effects on relationship satisfaction, whereas lower quality of face-to-face
communication interactions (at all frequencies) has a negative effect on relationship
satisfaction. Thus, communicating face-to-face is better for friends than was found in the
74
results for hypothesis 1 and 2, though is it more dependent upon the quality of such
communication than was the case for cell phone communication, as when disregarding
the quality of cell phone communication, talking on the cell phone frequently still had a
positive effect on relationship satisfaction. On the whole though, it was still found that
the higher the quality of cell phone communication, the higher the overall relationship
satisfaction between friends. Therefore, even though lower quality/high frequency cell
phone communication between friends is good for friendships, high quality/high
frequency cell phone communication is most beneficial.
When all of the quality and frequency of communication variables for each mode
of communication were added into the model for romantic partners (model 3 of table
4.14), the frequency of face-to-face communication and the quality of cell phone
communication became insignificant in their effect on relationship satisfaction. Since in
models 1 and 2, both respective mode and quality variables were significant, this suggests
to me that the relationship between the quality of face-to-face communication and
relationship satisfaction accounted for most of the effect that the quality of cell phone
communication had on relationship satisfaction, though I can provide no theoretical
explanation for such a finding. This finding may be due to the intercorrelation of the two
quality of communication variables, as their bivariate correlation (mentioned in the
previous chapter) reached .739. To conclude the findings for this relationship condition, it
appears that the quality of face to face communication is more important for relationship
satisfaction between partners than is the actual frequency of face-to-face communication.
This is a beneficial finding for long distance relationships indeed as they can have high
75
quality communication as little as a few times a month and still have high relationship
satisfaction (while still communicating via cell phone). Secondly, the frequency of cell
phone communication appears to be more important for relationship satisfaction between
partners than the actual quality of such communication, though this may be a result of
multicollinearity between the two quality of communication variables. Together, these
two findings suggest that even just mere occasional higher quality face-to-face
communication is important for romantic partners, as long as it is supplemented by
frequent cell phone communication (regardless of the quality of cell phone
communication), and vice versa.
Potential mediation was suggested in the results of hypothesis 4 for family
members: when the frequency and quality of face-to-face communication were not
controlled for, the quality of cell phone communication appears to have mediated the
relationship between the frequency of cell phone communication and relationship
satisfaction in model two specifically. However, this statistical evidence of mediation for
the frequency and quality of cell phone communication on relationship satisfaction makes
no theoretical sense when it stands alone from the frequency and quality of face-to-face
communication. This is because the theoretical reasoning for testing for mediation was
that the potential difference in effects that the frequency of face-to-face and cell phone
communication have on relationship satisfaction would be due to the actual quality of
each respective mode of communication, with the quality of face-to-face communication
being higher than the quality of cell phone communication, leading the former mode of
communication to have a greater positive effect on relationship satisfaction than the
76
latter. Therefore, this research was unsuccessful in identifying any mediation between the
mode of communication and relationship satisfaction by the quality of communication.
Regardless, for family members it was still found that, even when controlling for
the quality of communication, it is still more important for the relationship satisfaction of
family members to communicate face-to-face than it is to communicate on the cell phone.
The quality of cell phone communication does have a positive effect on relationship
satisfaction meaning that having higher quality cell phone communication is positive for
family relationships. However, when the frequency and quality of face-to-face
communication variables are controlled for as well (model 3, table 4.15) the effect
aforementioned is no longer significant. In the end, higher quality and more frequent
face-to-face communication leads to higher relationship satisfaction within family
relationships than lower quality and less frequent face-to-face interactions.
Therefore, the final results for this research are that the frequency and quality of
face-to-face communication are more important in determining relationship satisfaction
than are the frequency and quality of cell phone communication with one exception: the
frequency of cell phone communication has a greater effect than the frequency of face-toface communication in romantic relationships. This serves as evidence that
communication over the cell phone is no match for face-to-face communication when it
comes to obtaining, or maintaining, satisfied relationships. In all three relationship
conditions, the quality of communication was also found to explain a larger proportion of
77
relationship satisfaction than did the frequency of communication, regardless of mode of
communication.
Though in some aspects this research supports Wellman and Tindall’s (1993)
conclusion that the telephone plays an important role in maintaining relationships that are
challenged by distance, it goes further to show that communication through the cell
phone is not a substitute for face-to-face communication, as the lack of quality face-toface communication in these relationship conditions has a negative effect on their overall
relationship satisfaction. This research also provides contradicting evidence for Wellman
and Tindall’s finding that long distance friendships were more difficult to maintain over
the telephone in their region of study than were strong kinship ties. In this study, it was
shown that the frequency of cell phone communication actually has a greater affect on
relationship satisfaction for friends than it does for family ties, when the quality of
communication indicators are not controlled for. For family members, more frequent
face-to-face communication has a greater impact on relationship satisfaction than does
the frequency of cell phone communication. Thus, infrequent face-to-face
communication is hard on a friendship, but can be aided significantly by having high
quality cell phone communication, whereas family members do not necessarily need the
phone in order to keep their ties going strong. It is important to keep in mind though, that
this research was based on cell phone communication, whereas Wellman and Tindall’s
was based on the landline telephone. Especially for the latter finding for friendships, the
convenience and availability of cell phones, which allow individuals to call friends with
78
no long distance charges, may explain part of the discrepancy between these clashing
findings.
The results of the analyses described above will add valuable knowledge to the
studies of communications, and relationship satisfaction, as well as to the growing area of
cell phone research in the social sciences. Such knowledge might work not only to further
research within these areas, but also to influence the proactive and reactive
communication behaviors of individuals in society. There are, however, a number of
limitations that have influenced this research.
LIMITATIONS
The first limitation of this study is the overall response rate. With only 516
respondents of the sampled 2,600 students (20.8 percent), there is a large possibility that
there is some form of nonresponse bias in these statistics. However, the presence of such
error in these results is not definitive, and there is little theoretical reasoning to assume
that such error based on demographics is present when comparing the sample statistics to
the population parameters (table 4.1). It is still a source of concern however, as the
research community must wonder why such a small response rate was obtained, when
efforts to increase the response rate were made. One possible explanation for this is that
the students may not have respected myself as a researcher, and rather seen me as a
fellow classmate whose research was of less importance than that of a professor. A
second explanation may be that the sampled students did not see interest in the survey
through the survey invitation email (appendix 1), which would suggest that the email was
79
not structured properly for eliciting excitement and a sense of urgency or need that should
have been portrayed by myself, the primary researcher.
The mode of data collection, though beneficial for many reasons, was also a
limitation to this study. Because this was a cross-sectional survey, it is impossible to
determine causality in those statistically significant relationships where temporal order
could come into question. Though a panel study would be beneficial for such a cause, it
would still be difficult to determine actual causal relationships such as that between the
frequency of cell phone communication and the overall quality of cell phone
communication between family members. In this case, a qualitative study may be more
appropriate, which future researchers may consider in order to gain a richer, more
detailed account of what explanatory variables are affecting the overall quality of both
face-to-face and cell phone communication.
The third main limitation of this study was that the measures for the quality of
communication and mode of communication did not allow for a direct test of mediation.
Through this research, it was realized that qualitative analysis may be more proper for
this hypothesis than quantitative. For instance, knowing now that the frequency and
quality of face-to-face communication leads to higher relationship satisfaction than the
frequency and quality of cell phone communication on average, interviews can be
conducted with respondents in which they can be probed to explain why they prefer to
communication via one mode of communication over the other, potentially revealing why
the quality of communication differs between both modes of communication. Personal
diaries may also be very beneficial here, as this would reduce the amount of human error
80
that occurs when respondents are asked to recall the quality of their last conversation,
which may have occurred several days or weeks prior.
There were also some limitations within the questionnaire itself. First, in order to
see which relationship conditions were valued over others (possibly aiding in the
explanation of why certain explanatory variables affected one relationship condition, but
not another) it would have also been beneficial to have asked respondents to rate their
three personal relationships in terms of their ‘level of importance’. For instance, if
romantic partners were valued higher than family members or friendships, this may help
to explain why it was just as important for romantic partners to keep in contact via both
face-to-face and cell phone communication in the results for hypotheses 1 and 2.
Secondly, the scales for quality of communication were based on the respondents last
conversation with their friend, family member, or romantic partner. Therefore, the
measured quality of communication from conversations that occurred as far as one month
before the respondent replied to this survey may include a decent amount of human error.
And lastly, for the analysis of hypothesis 3, it was also problematic that the final
sample size for models 1 in each respective relationship condition dropped (when the two
multitasking variables were controlled for) to sizes that may have jeopardized the power
of the regressions, and therefore the statistical findings. It was important to see how
multitasking affected the overall quality of face-to-face communication however, and so
future researchers may continue down this path of research with a larger sample.
81
FUTURE CONSIDERATIONS
Since the advent of the cell phone, communication and relationships have moved
from purely face-to-face or written interactions, to interactions that defy both space and
time. The purpose of this research was to identify how communication over the cell
phone compares to face-to-face communication in terms of building, or maintaining, a
satisfied relationship across friendships, familial relationships, and romantic
relationships. Is the cell phone a significant proxy for face-to-face communication—one
that can completely take the place of face-to-face communication, or at least fill in its
place in times of long abstances? Or, does it clutter relationships when it is abused with
frequent usage and interrupting behavior? The results presented in this thesis have shown
that the cell phone, though an aide to face-to-face communication, does not live up to
face-to-face communication in terms of creating and maintaining satisfying relationships.
Researchers interested in this area may consider looking into why such differences exist,
as this is an area untouched by research in the social sciences, which could also add on to
past studies of the landline telephone. With the rise in new communications technology
that is sure to come, future researchers will have the ability to retest these hypotheses to
see how communication via the “cell phone” (or whatever term will follow the new
technology) compares to face-to-face communication in the future.
These results also identified some of the variables that affect the overall quality of
cell phone communication. However, many of the variables which affect the quality of
cell phone communication, as well as the quality of face-to-face communication, are not
present in this study and are still in need of identification by future researchers. Though
82
quality differences may always exist between the two modes of communication, as
communications technology continues to evolve into more advanced forms, the gap
between the quality of cell phone communication and face-to-face communication may
come to a close. With video cell phones in particular, communicating in person and
communicating face-to-face may in time yield the same quality of communication on
average, as communication over the cell phone will then allow interactants to view
nonverbal communication cues on the other end of the line. Seeing how the quality of
communication affected the relationship between the mode of communication and
relationship satisfaction was also a goal of this study. However, it is clear that qualitative
analyses would be more appropriate for testing this hypothesis than quantitative analysis,
as well as for building onto the theory of mediation. Therefore, future researchers should
consider looking into such mediation by means of in-depth face-to-face interviews,
personal diaries, or even computer-assisted self-administered interviews that include
many more open ended questions. Such analysis is sure to lend rich information to future
studies of communications technology in sociology.
Table 5.1 Summary of Hypotheses
Relationship Condition
Friend
Family
Romantic
Partner
Hypothesis 1
Rejected
Rejected
Rejected
Hypothesis 2
Rejected
Accepted
Accepted
Hypothesis 3
Accepted
Accepted
Accepted
Hypothesis 4
Rejected
Rejected
Rejected
APPENDIX I: Email Solicitation
Dear Student,
My name is Rebecca Schwarz and I am a graduate student here at
Kent State University. I am currently conducting a web survey of
Kent State students to research the quantity and quality of
communication with friends and family, and you are among a portion
of students who have been randomly selected to participate. Your
participation is very important to provide a representative sample
of Kent State University students, and all participants will be
entered into a drawing to win a $100 gift card to the Kent State
University bookstore. This drawing will be held approximately one
week after the data collection period has ended.
To take part in this valuable study, click on the secure link
below and you will be brought to the survey. This survey should
take between 12 and 18 minutes to complete. If you would like
additional information about this research, you may contact the
Chair of my thesis committee, Dr. Richard Serpe, at the
information below.
https://srl.kent.edu/sw/wchost.asp?st=comm2&id=668&pw=YZ6MI3
Richard Serpe, Chair
215B Merrill Hall
330-672-4896
[email protected]
Rebecca Schwarz
203 Merrill Hall
330-672-4630 ext. 2
[email protected]
83
APPENDIX II: Online Consent Form
The research project that you have been invited to participate
in has been approved by the Kent State University Institutional
Review Board which has been created to protect the rights of all
parties involved in research involving humans. Participation is
voluntary and confidential. Therefore, you have the right to
skip any questions that you do not feel comfortable answering,
and may discontinue participation at any time without penalty.
In order to ensure confidentiality of your responses, you have
been assigned a respondent identification number so that no one
except the primary research will be able to link your name and
contact information to your responses. Please note that you must
be 18 years of age or over to participate in this study.
Additional information about Kent State University's rules for
research can be obtained from Dr. John L. West, Vice President
and Dean, Division of Research and Graduate Studies (330)672-2851.
For additional information about this research, you may contact
the Chair of my thesis committee, Dr. Richard Serpe, at the
information below.
I have read the above information and agree to participate
in this survey
[Link to questionnaire]YES, I consent to participate
[Link illustrated below]NO, I do not consent
Richard Serpe, Chair
Kent State University
215B Merrill Hall
330-672-4896
[email protected]
Rebecca Schwarz
Kent State University
203 Merrill Hall
[email protected]
[Respondents who did NOT consent were brought to the following web page]
You have chosen to refrain from participating in this survey, and will not be contacted for
further information.
[END of survey. You may now close this window]
84
APPENDIX III: Questionnaire
[SECTION 1: INTRODUCTION]
Please answer the questions below to the best of your knowledge. Remember that
you have the option to skip questions if you choose to, and may discontinue the
survey at any time without penalty. This questionnaire should take approximately
14 minutes to complete, and you may track your progress at the bottom of the
screen.
Are you currently enrolled in classes at Kent State University’s main campus?
Yes
No
Do you own a cell phone?
Yes
No
Thinking about times when you are NOT in class, how often do you turn your phone
either off, or on silent, to avoid unwanted interruptions?
Never
Once in a while
Sometimes
 Often
Always
Thinking about friends that you talk to at least once a month, choose one friend who is
important to you that we will ask you about in this survey. What is this friends name?
_____________
What is [friend]’s gender?
Male
Female
85
86
Would you consider your friendship with [Friend] to be long-distance (for this study, a
long-distance relationship is one in which you cannot see your friend, face-to-face, most
days)?
Yes
No
Thinking about family members that you talk to at least once a month, choose one family
member who is important to you that we will ask you about in this survey. What is this
family members name? _____________
What is [family]’s gender?
Male
Female
Would you consider your relationship with [Family] to be long-distance (for this study,
long-distance is defined as not being able to see this family member, face-to-face, most
days)?
Yes
No
How are you related to [family]?
 Parent
 Sibling
 My Child
 Other
Do you currently have a romantic partner that we can ask you about in this survey?
Yes
No
[IF YES] What is the name of your partner? _________________
[IF YES] What is [partner]’s gender?
Male
Female
[IF YES] What would you consider [partner] to be?
My Boyfriend
My Girlfriend
87
My Spouse
My Fiancé
My Spouse
My Life Partner
Other
[IF OTHER] A. Please Specify ____________
[IF YES] Would you consider your relationship with [partner] to be long-distance
(for this study, a long-distance relationship is one in which you cannot see your
partner, face-to-face, most days)?
Yes
No
[SECTION 2: FRIEND]
How long have you been friends with [friend]? Years _____ Months _____
On average, how often do you see [friend] in person?
 More than once a day
 Once a day
 A couple times a week
 Once a week
 A couple times a month
 Once a month
 Less than once a month
Last time you spent time with [friend] in person, were you engaged in an activity
together?
Yes
No
[IF NO] Were you yourself engaged in an activity separately from [friend]?
 Yes  No
[IF NO] Was [friend] engaged in an activity separately from you?
 Yes  No
[continue to next page]
88
Thinking about the last time you spent time with [friend] in person, how would you
describe the communication between the two of you?
Relaxed
1
2
3
4
5
6
7
Strained
Impersonal
1
2
3
4
5
6
7
Personal
Attentive
1
2
3
4
5
6
7
Poor Listening
Formal
1
2
3
4
5
6
7
Informal
In-Depth
1
2
3
4
5
6
7
Superficial
Smooth
1
2
3
4
5
6
7
Difficult
Guarded
Great Deal of
Understanding
1
2
3
4
5
6
7
1
2
3
4
5
6
7
Open
Great Deal of
Misunderstanding
Free of
Communication
Breakdowns
1
2
3
4
5
6
7
Free of Conflict
1
2
3
4
5
6
7
Laden with
Communication
Breakdowns
Laden with
Conflict
Enjoyable
1
2
3
4
5
6
7
Not Enjoyable
High Quality
1
2
3
4
5
6
7
Low Quality
Thinking about the face-to-face communication you had with [friend], would you say it
was better, or worse, than talking over the cell phone?
Better than talking on the cell phone
About equal to talking on the cell phone
Not as good as talking on the cell phone
About how often do you speak with [friend] on the cell-phone?
 4 or more times a day
 2-3 times a day
 Once a day
 A couple times a week
 Once a week
 A couple times a month
 Once a month
 Less than once a month
89
In general, do you worry about exceeding your cell phone minutes while you are on the
phone with [Friend]?
Yes
No
Thinking about the last time you spoke with [friend] on the cell-phone, who called
whom?
 I called [friend]
 [friend] called me
 I don’t remember
[IF ‘I CALLED [friend]’]
A. When you called [friend], was [he/she] engaged in an activity?
 Yes
No
B. When you called [friend], were you engaged in an activity?
Yes No
[IF ‘[friend] CALLED ME’]
A. When [friend] called you, was [he/she] engaged in an activity?
Yes
No
B. When [friend] called you, were you engaged in activity?
Yes  No
[IF ‘I DON’T REMEMBER’]
A. When you spoke to [friend], was [he/she] engaged in an activity?
 Yes
No
B. When you spoke to [friend], were you engaged in an activity?
Yes No
90
[IF YES TO EITHER A ABOVE]
During the conversation, did [friend] continue doing what [he/she] was doing?
continued doing what [he/she] was doing
stopped what [he/she] was doing
don’t remember
[IF YES TO EITHER B ABOVE]
During the conversation, did you continue in this activity, or stop what you were doing?
continued doing what I was doing
stopped what I was doing
don’t remember
In general, was there an instrumental reason you and [friend] spoke on the cell phone, or
was the conversation mainly just for fun? Instrumental reasons would include things like
giving directions, determining the place and time to meet, or asking/answering specific
questions.
 The conversation was mainly just for fun
 The conversation mainly served an instrumental purpose
About how many minutes did the cell phone conversation last? _______ minutes
In general, who typically calls whom?
I call [friend]
[friend] calls me
We call each other about the same amount
[continue to next page]
91
How would you describe the communication with [friend] over the cell phone?
Relaxed
1
2
3
4
5
6
7
Strained
Impersonal
1
2
3
4
5
6
7
Personal
Attentive
1
2
3
4
5
6
7
Poor Listening
Formal
1
2
3
4
5
6
7
Informal
In-Depth
1
2
3
4
5
6
7
Superficial
Smooth
1
2
3
4
5
6
7
Difficult
Guarded
Great Deal of
Understanding
1
2
3
4
5
6
7
1
2
3
4
5
6
7
Open
Great Deal of
Misunderstanding
Free of
Communication
Breakdowns
1
2
3
4
5
6
7
Free of Conflict
1
2
3
4
5
6
7
Laden with
Communication
Breakdowns
Laden with
Conflict
Enjoyable
1
2
3
4
5
6
7
Not Enjoyable
High Quality
1
2
3
4
5
6
7
Low Quality
Thinking about the communication you had with [friend] over the cell phone, would you
say it was better, or worse, than communicating face-to-face?
Better than communicating face-to-face
About equal to communicating face-to-face
Not as good as communicating face-to-face
[continue to next page]
92
Now I would like you to think about your overall friendship with [friend].
Please read through the following statements and rate your level of agreement or
disagreement with each statement.
This [friendship] meets my needs
Strongly Disagree
1
2
3
4
5
6
7
Strongly Agree
[Friend] and I have a very good relationship compared to most
Strongly Disagree
1
2
3
4
5
6
7
Strongly Agree
4
5
6
7
Strongly Agree
5
6
7
Strongly Agree
I often wish that I was not in this [friendship]
Strongly Disagree
1
2
3
I get what I would expect from my [friendship] with [Friend]
Strongly Disagree
1
2
3
4
There are problems in my [friendship] with [Friend]
Strongly Disagree
1
2
3
4
5
6
7
Strongly Agree
3
4
5
6
7
Strongly Agree
3
4
5
6
7
Strongly Agree
I am satisfied with this [friendship]
Strongly Disagree
1
2
I care about [Friend] very much
Strongly Disagree
1
[continue to next page]
2
93
[SECTION 3: ROMANTIC PARTNER] [IF YES to having Romantic Partner
in introduction section. If NO, skip to FAMILY section.]
How long have you been in a relationship with [Partner]? Years _____ Months _____
On average, how often do you see [Partner] in person?
 More than once a day
 Once a day
 A couple times a week
 Once a week
 A couple times a month
 Once a month
 Less than once a month
Last time you spent time with [Partner] in person, were you engaged in an activity
together?
Yes
No
[IF NO] Were you yourself engaged in an activity separately from [Partner]?
 Yes  No
[IF NO] Was [Partner] engaged in an activity separately from you?
 Yes  No
[continue to next page]
94
Thinking about the last time you spent time with [Partner] in person, how would you
describe the communication between the two of you?
Relaxed
1
2
3
4
5
6
7
Strained
Impersonal
1
2
3
4
5
6
7
Personal
Attentive
1
2
3
4
5
6
7
Poor Listening
Formal
1
2
3
4
5
6
7
Informal
In-Depth
1
2
3
4
5
6
7
Superficial
Smooth
1
2
3
4
5
6
7
Difficult
Guarded
Great Deal of
Understanding
1
2
3
4
5
6
7
1
2
3
4
5
6
7
Open
Great Deal of
Misunderstanding
Free of
Communication
Breakdowns
1
2
3
4
5
6
7
Free of Conflict
1
2
3
4
5
6
7
Laden with
Communication
Breakdowns
Laden with
Conflict
Enjoyable
1
2
3
4
5
6
7
Not Enjoyable
High Quality
1
2
3
4
5
6
7
Low Quality
Thinking about the face-to-face communication you had with [Partner], would you say it
was better, or worse, than talking over the cell phone?
Better than talking on the cell phone
About equal to talking on the cell phone
Not as good as talking on the cell phone
About how often do you speak with [Partner] on the cell-phone?
 4 or more times a day
 2-3 times a day
 Once a day
 A couple times a week
 Once a week
 A couple times a month
 Once a month
 Less than once a month
95
In general, do you worry about exceeding your cell phone minutes while you are on the
phone with [Partner]?
Yes
No
Thinking about the last time you spoke with [Partner] on the cell-phone, who called
whom?
 I called [Partner]
 [Partner] called me
 I don’t remember
[IF ‘I CALLED [Partner]’]
A. When you called [Partner], was [he/she] engaged in an activity?
 Yes
No
B. When you called [Partner], were you engaged in an activity?
Yes No
[IF ‘[Partner] CALLED ME’]
A. When [Partner] called you, was [he/she] engaged in an activity?
Yes
No
B. When [Partner] called you, were you engaged in activity?
Yes  No
[IF ‘I DON’T REMEMBER’]
A. When you spoke to [Partner], was [he/she] engaged in an activity?
 Yes
No
B. When you spoke to [Partner], were you engaged in an activity?
Yes No
96
[IF YES TO EITHER A ABOVE]
During the conversation, did [Partner] continue doing what [he/she] was doing?
Yes, continued doing what [he/she] was doing
No, stopped what [he/she] was doing
don’t remember
[IF YES TO EITHER B ABOVE]
During the conversation, did you continue in this activity, or stop what you were doing?
Yes, continued doing what I was doing
No, stopped what I was doing
don’t remember
In general, was there an instrumental reason you and [Partner] spoke on the cell phone, or
was the conversation mainly just for fun? Instrumental reasons would include things like
giving directions, determining the place and time to meet, or asking/answering specific
questions.
 The conversation was mainly just for fun
 The conversation mainly served an instrumental purpose
About how many minutes did the cell phone conversation last? _______ minutes
In general, who typically calls whom?
I call [Partner]
[Partner] calls me
We call each other about the same amount
[continue to next page]
97
How would you describe the communication with [Partner] over the phone? [COMM.
QUALITY]
Relaxed
1
2
3
4
5
6
7
Strained
Impersonal
1
2
3
4
5
6
7
Personal
Attentive
1
2
3
4
5
6
7
Poor Listening
Formal
1
2
3
4
5
6
7
Informal
In-Depth
1
2
3
4
5
6
7
Superficial
Smooth
1
2
3
4
5
6
7
Difficult
Guarded
Great Deal of
Understanding
1
2
3
4
5
6
7
1
2
3
4
5
6
7
Open
Great Deal of
Misunderstanding
Free of
Communication
Breakdowns
1
2
3
4
5
6
7
Free of Conflict
1
2
3
4
5
6
7
Laden with
Communication
Breakdowns
Laden with
Conflict
Enjoyable
1
2
3
4
5
6
7
Not Enjoyable
High Quality
1
2
3
4
5
6
7
Low Quality
Thinking about the communication you had with [Partner] over the cell phone, would you
say it was better, or worse, than communicating face-to-face?
Better than communicating face-to-face
About equal to communicating face-to-face
Not as good as communicating face-to-face
[continue to next page]
98
Now I would like you to think about your overall relationship with [Partner].
Please read through the following statements and rate your level of agreement or
disagreement with each statement.
This [relationship] meets my needs
Strongly Disagree
1
2
3
4
5
6
7
Strongly Agree
[Partner] and I have a very good relationship compared to most
Strongly Disagree
1
2
3
4
5
6
7
Strongly Agree
5
6
7
Strongly Agree
I often wish that I was not in this [relationship]
Strongly Disagree
1
2
3
4
I get what I would expect from my [relationship] with [Partner]
Strongly Disagree
1
2
3
4
5
6
7
Strongly Agree
There are problems in my [relationship] with [Partner]
Strongly Disagree
1
2
3
4
5
6
7
Strongly Agree
3
4
5
6
7
Strongly Agree
3
4
5
6
7
Strongly Agree
I am satisfied with this [relationship]
Strongly Disagree
1
2
I care about [Partner] very much
Strongly Disagree
1
[continue to next page]
2
99
[SECTION 4: FAMILY]
How long have you been related to [Family]? Years _____ Months _____
On average, how often do you see [Family] in person?
 More than once a day
 Once a day
 A couple times a week
 Once a week
 A couple times a month
 Once a month
 Less than once a month
Last time you spent time with [Family] in person, were you engaged in an activity
together?
Yes
No
[IF NO] Were you yourself engaged in an activity separately from [Family]?
 Yes  No
[IF NO] Was [Family] engaged in an activity separately from you?
 Yes  No
[continue to next page]
100
Thinking about the last time you spent time with [Family] in person, how would you
describe the communication between the two of you?
Relaxed
1
2
3
4
5
6
7
Strained
Impersonal
1
2
3
4
5
6
7
Personal
Attentive
1
2
3
4
5
6
7
Poor Listening
Formal
1
2
3
4
5
6
7
Informal
In-Depth
1
2
3
4
5
6
7
Superficial
Smooth
1
2
3
4
5
6
7
Difficult
Guarded
Great Deal of
Understanding
1
2
3
4
5
6
7
1
2
3
4
5
6
7
Open
Great Deal of
Misunderstanding
Free of
Communication
Breakdowns
1
2
3
4
5
6
7
Free of Conflict
1
2
3
4
5
6
7
Laden with
Communication
Breakdowns
Laden with
Conflict
Enjoyable
1
2
3
4
5
6
7
Not Enjoyable
High Quality
1
2
3
4
5
6
7
Low Quality
Thinking about the face-to-face communication you had with [Family], would you say it
was better, or worse, than talking over the cell phone?
Better than talking on the cell phone
About equal to talking on the cell phone
Not as good as talking on the cell phone
About how often do you speak with [Family] on the cell-phone?
 4 or more times a day
 2-3 times a day
 Once a day
 A couple times a week
 Once a week
 A couple times a month
 Once a month
 Less than once a month
101
In general, do you worry about exceeding your cell phone minutes while you are on the
phone with [Family]?
Yes
No
Thinking about the last time you spoke with [Family] on the cell-phone, who called
whom?
 I called [Family]
 [Family] called me
 I don’t remember
[IF ‘I CALLED [Family]’]
A. When you called [Family], was [he/she] engaged in an activity?
 Yes
No
B. When you called [Family], were you engaged in an activity?
Yes No
[IF ‘[Family] CALLED ME’]
A. When [Family] called you, was [he/she] engaged in an activity?
Yes
No
B. When [Family] called you, were you engaged in activity?
Yes  No
[IF ‘I DON’T REMEMBER’]
A. When you spoke to [Family], was [he/she] engaged in an activity?
 Yes
No
B. When you spoke to [Family], were you engaged in an activity?
Yes No
102
[IF YES TO EITHER A ABOVE]
During the conversation, did [Family] continue doing what [he/she] was doing?
Yes, continued doing what [he/she] was doing
No, stopped what [he/she] was doing
don’t remember
[IF YES TO EITHER B ABOVE]
During the conversation, did you continue in this activity, or stop what you were doing?
Yes, continued doing what I was doing
No, stopped what I was doing
don’t remember
In general, was there an instrumental reason you and [Family] spoke on the cell phone, or
was the conversation mainly just for fun? Instrumental reasons would include things like
giving directions, determining the place and time to meet, or asking/answering specific
questions.
 The conversation was mainly just for fun
 The conversation mainly served an instrumental purpose
About how many minutes did the cell phone conversation last? _______ minutes
In general, who typically calls whom?
I call [Family]
[Family] calls me
We call each other about the same amount
[continue to next page]
103
How would you describe the communication with [Family] over the phone? [COMM.
QUALITY]
Relaxed
1
2
3
4
5
6
7
Strained
Impersonal
1
2
3
4
5
6
7
Personal
Attentive
1
2
3
4
5
6
7
Poor Listening
Formal
1
2
3
4
5
6
7
Informal
In-Depth
1
2
3
4
5
6
7
Superficial
Smooth
1
2
3
4
5
6
7
Difficult
Guarded
Great Deal of
Understanding
1
2
3
4
5
6
7
1
2
3
4
5
6
7
Open
Great Deal of
Misunderstanding
Free of
Communication
Breakdowns
1
2
3
4
5
6
7
Free of Conflict
1
2
3
4
5
6
7
Laden with
Communication
Breakdowns
Laden with
Conflict
Enjoyable
1
2
3
4
5
6
7
Not Enjoyable
High Quality
1
2
3
4
5
6
7
Low Quality
Thinking about the communication you had with [Family] over the cell phone, would you
say it was better, or worse, than communicating face-to-face?
Better than communicating face-to-face
About equal to communicating face-to-face
Not as good as communicating face-to-face
[continue to next page]
104
Now I would like you to think about your overall relationship with [Family].
Please read through the following statements and rate your level of agreement or
disagreement with each statement.
This [relationship] meets my needs
Strongly Disagree
1
2
3
4
5
6
7
Strongly Agree
[Family] and I have a very good relationship compared to most
Strongly Disagree
1
2
3
4
5
6
7
Strongly Agree
4
5
6
7
Strongly Agree
I often wish that I was not related to [Family]
Strongly Disagree
1
2
3
I get what I would expect from my [relationship] with [Family]
Strongly Disagree
1
2
3
4
5
6
7
Strongly Agree
There are problems in my [relationship] with [Family]
Strongly Disagree
1
2
3
4
5
6
7
Strongly Agree
3
4
5
6
7
Strongly Agree
3
4
5
6
7
Strongly Agree
I am satisfied with this [relationship]
Strongly Disagree
1
2
I care about [Family] very much
Strongly Disagree
1
[continue to next page]
2
105
[SECTION 5: DEMOGRAPHIC ITEMS]
Are you a full-time, or part-time student here at Kent State University?
Full-time
Part-time
What is your current class standing based on the number of credit hours you have
completed in college?
Freshman
Sophomore
Junior
Senior
MA student
PHD student
What is your gender?
Male
Female
What is your age? ____
What race would you consider yourself to be? (Choose all that apply)
African American
Asian
Caucasian
Hispanic
American Indian or Alaska Native
Other
[IF OTHER] A. Please specify ________________
Are you currently employed
Full time (35 or more hours a week)
Part time (18-34 hours a week)
Part time (1-17 hours a week)
Not currently employed
106
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entered into the drawing to receive a $100 gift card to the Kent State University
Bookstore?
 YES
 NO
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have a second kent.edu email address. This email address WILL NOT be given out to a
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 YES, I have a second kent.edu email address. It is [open box]@kent.edu.
[Ineligible respondents were taken to the following web pages immediately following
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University’s main campus: question 1]
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Kent State University's main campus. If you are not enrolled at KSU's main campus,
you are not eligible for this survey.
Thank you for your time
[END of survey. You may now close this window]
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We are sorry, but this is a survey of Kent State University cell phone users.If you
do not currently own a cell phone, you are not eligible for this survey.
Thank you for your time
[END of survey. You may now close this window]
APPENDIX IV: Bivariate Correlations for Friend Variables
Frequency
Quality Quality of
Long
Frequency
face to
Relationship distance
Length of
of face
cell
cell phone
face
to face
phone satisfaction relationship relationship
comm.
(=1)
comm.
comm. comm.
Frequency face to face
communication
Pearson Corr.
Frequency cell phone
communication
Pearson Corr.
Quality of face to face
communication
Pearson Corr.
Quality of cell phone
communication
Pearson Corr.
Relationship satisfaction
1
511
N
N
N
N
.499(**) -.113(*) -.166(**)
511
487
486
0.02
500
-.756(**)
506
-.296(**)
511
.499(**)
511
1
515
0.04
489
0.03
489
.137(**)
503
-.321(**)
509
-.212(**)
515
-.113(*)
487
0.04
489
1
490
.697(**)
478
.435(**)
480
0.09
484
0.02
490
-.166(**)
486
0.03 .697(**)
489
478
1
490
.381(**)
480
.102(*)
484
0.06
490
0.02
500
.137(**) .435(**)
503
480
.381(**)
480
1
504
0.04
498
0.03
504
Pearson Corr.
N
-.756(**)
506
-.321(**)
509
0.09
484
.102(*)
484
0.04
498
1
509
.164(**)
509
-.296(**)
511
-.212(**)
515
0.02
490
0.06
490
0.03
504
.164(**)
509
1
516
0.15
0.14
-0.11
-0.21
-0.12
-0.12
0.09
74
74
73
70
73
74
74
Friend multitasking during Pearson Corr.
face to face communication
N
(=1)
0.11
0.16
-0.04
-0.16
-0.13
-0.07
0.04
73
73
73
70
72
73
73
Pearson Corr.
.355(**)
497
0
500
-0.03 -.123(**)
477
478
-0.01
490
-.360(**)
495
-.097(*)
500
-.326(**)
487
-0.07
490
0.01
468
.091(*)
472
0
480
.296(**)
486
0.04
490
Long distance relationship
(=1)
Length of relationship
Respondent multitasking
during face to face
communication (=1)
Spoke just for fun (=1)
Length of Conversation
Pearson Corr.
N
Pearson Corr.
N
Pearson Corr.
N
N
Pearson Corr.
N
Friend multitasking during
cell communication (=1)
Pearson Corr.
N
0.04
511
.129(**)
515
-0.03
490
-0.08
490
-0.08
504
0.01
509
0.07
516
Respondent multitasking
during cell communication
(=1)
Pearson Corr.
0.05
.172(**)
0.01
-0.04
-0.03
0.03
0.01
511
515
490
490
504
509
516
-.147(**)
502
-.222(**)
505
0
481
0.06
481
-.097(*)
494
-0.02
500
.406(**)
506
.104(*) .156(**)
.168(**)
.103(*)
0.07
-0.01
488
502
507
513
AGE
FEMALE
N
Pearson Corr.
N
Pearson Corr.
N
-0.06
509
512
** Correlation is significant at the 0.01 level (2-tailed).
* Correlation is significant at the 0.05 level (2-tailed).
107
488
108
Respondent
Friend
multitasking multitasking Spoke
during face during face just for
to face
fun (=1)
to face
comm.(=1) comm. (=1)
Frequency face to face
communication
0.15
74
0.11 .355(**)
73
497
Frequency cell phone
communication
0.14
74
0.16
73
Quality of face to face
communication
-0.11
73
-0.04
73
Quality of cell phone
communication
Friend
Respondent
Length of multitasking multitasking
Conver.
during cell during cell
comm. (=1) comm. (=1)
AGE
FEMALE
-.326(**)
487
0.04
511
0.05 -.147(**)
511
502
-0.06
509
0
500
-0.07
490
.129(**)
515
.172(**) -.222(**)
515
505
.104(*)
512
-0.03
477
0.01
468
-0.03
490
0.01
490
0
481
.156(**)
488
-0.21
70
-0.16 -.123(**)
70
478
.091(*)
472
-0.08
490
-0.04
490
0.06
481
.168(**)
488
Relationship satisfaction
-0.12
73
-0.13
72
-0.01
490
0
480
-0.08
504
-0.03
504
-.097(*)
494
.103(*)
502
Long distance relationship
(=1)
-0.12
74
-0.07 -.360(**)
73
495
.296(**)
486
0.01
509
0.03
509
-0.02
500
0.07
507
0.09
74
0.04 -.097(*)
73
500
0.04
490
0.07
516
0.01
516
.406(**)
506
-0.01
513
Length of relationship
Respondent multitasking
during face to face
communication (=1)
Friend multitasking during
face to face communication
(=1)
Spoke just for fun (=1)
Length of Conversation
1
.828(**)
.255(*)
-0.03
.303(**)
0.16
0.1
-.369(**)
74
73
69
67
74
74
72
74
.828(**)
1
0.21
0.01
0.23
0.1
0.16
-.417(**)
73
73
69
67
73
73
72
73
.255(*)
69
0.21
69
1
500
-.365(**)
484
0
500
-0.01
500
0.03
491
-0.08
498
0.01 -.365(**)
67
484
1
490
-0.02
490
-0.08
490
-0.04
482
0.05
488
-0.03
67
Friend multitasking during
cell communication (=1)
.303(**)
74
0.23
73
0
500
-0.02
490
1
516
.404(**)
516
0.02
506
.108(*)
513
Respondent multitasking
during cell communication
(=1)
0.16
0.1
-0.01
-0.08
.404(**)
1
0.05
.120(**)
74
73
500
490
516
516
506
513
0.1
72
0.16
72
0.03
491
-0.04
482
0.02
506
0.05
506
1
506
-0.07
503
-.369(**)
74
-.417(**)
73
-0.08
498
0.05
488
.108(*)
513
.120(**)
513
-0.07
503
1
513
AGE
FEMALE
** Correlation is significant at the 0.01 level (2-tailed).
* Correlation is significant at the 0.05 level (2-tailed).
APPENDIX V: Bivariate Correlations for Romantic Partners Variables
Frequency
Quality Quality
Long
Frequency
face to
Length of
of face of cell Relationship distance
cell phone
face
to face phone satisfaction relationship relationship
comm.
(=1)
comm.
comm. comm.
Frequency face to face
communication
Frequency cell phone
communication
Quality of face to face
communication
Quality of cell phone
communication
Relationship satisfaction
Pearson
Corr.
N
Pearson
Corr.
N
Pearson
Corr.
N
Pearson
Corr.
N
Pearson
Corr.
Respondent multitasking during
face to face communication (=1)
Partner multitasking during face
to face communication (=1)
Spoke just for fun (=1)
Respondent multitasking during
cell communication (=1)
AGE
-.798(**)
.259(**)
340
338
326
318
329
339
340
.262(**)
1
0.09
0.1
.182(**)
-.121(*)
-0.1
338
338
325
317
328
337
338
0.04
0.09
1 .739(**)
.618(**)
0.06
0.1
326
325
326
313
316
325
326
0.05
0.1 .739(**)
1
.485(**)
-0.03
0.06
318
317
318
308
317
318
.182(**) .618(**) .485(**)
1
-0.04
.148(**)
.151(**)
313
329
328
329
-.798(**)
-.121(*)
0.06
-0.03
-0.04
1
-.201(**)
339
337
325
317
328
339
339
.259(**)
-0.1
0.1
0.06
.148(**)
-.201(**)
1
N
340
338
326
318
329
339
516
Pearson
Corr.
0.2
0.11
-0.11
0.01
0.01
-0.21
-0.02
45
45
44
42
45
45
45
0.08
-0.06
-0.21
-0.04
-0.08
-0.08
0
46
46
45
43
46
46
46
.348(**)
-.134(*)
-0.03
-0.06
-0.03
-.320(**)
.245(**)
330
329
317
311
321
329
330
-.331(**)
-0.07
0
0.04
-0.01
.275(**)
-.173(**)
325
325
314
308
315
325
325
.110(*) -.119(*)
.174(**)
-0.01
-0.09
.342(**)
Pearson
Corr.
N
Pearson
Corr.
N
Pearson
Corr.
Pearson
Corr.
Pearson
Corr.
N
Pearson
Corr.
N
Pearson
Corr.
N
FEMALE
.151(**)
308
N
Partner multitasking during cell
communication (=1)
0.05
316
N
Length of Conversation
0.04
328
Pearson
Corr.
N
Length of relationship
.262(**)
329
N
Long distance relationship (=1)
1
Pearson
Corr.
N
.116(*)
340
338
326
318
329
339
516
.135(*)
.151(**)
-0.02
-0.07
-0.05
-0.1
.330(**)
340
338
326
318
329
339
516
.269(**)
-.112(*)
0.07
0.06
0.05
-.257(**)
.569(**)
333
331
320
312
322
332
506
-0.08
.109(*)
0.07 .119(*)
0.06
0.05
0
338
336
324
327
337
513
** Correlation is significant at the 0.01 level (2-tailed).
* Correlation is significant at the 0.05 level (2-tailed).
109
316
110
Respondent
Partner
Partner
Respondent
multitasking multitasking
Spoke
Length of multitasking multitasking
during face during face to just for
Conv.
during cell during cell
face comm. fun (=1)
to face
comm. (=1) comm. (=1)
comm.(=1)
(=1)
Pearson
Frequency face to
Corr.
face communication
N
Frequency cell
phone
communication
Quality of face to
face communication
Pearson
Corr.
N
Pearson
Corr.
N
Pearson
Quality of cell phone Corr.
communication
Relationship
satisfaction
Long distance
relationship (=1)
Length of
relationship
N
Pearson
Corr.
N
Pearson
Corr.
N
Pearson
Corr.
N
Pearson
Corr.
Respondent
multitasking during
face to face
N
communication (=1)
Partner multitasking Pearson
during face to face Corr.
communication (=1) N
Spoke just for fun
(=1)
Length of
Conversation
Pearson
Corr.
N
Pearson
Corr.
N
Partner multitasking Pearson
Corr.
during cell
communication (=1) N
Respondent
multitasking during
cell communication
AGE
Pearson
Corr.
N
Pearson
Corr.
N
FEMALE
Pearson
N
0.2
0.08
.116(*)
.135(*)
.269(**)
-0.08
45
46
330
325
340
340
333
338
0.11
-0.06
-.134(*)
-0.07
.110(*)
.151(**)
45
46
329
325
338
338
331
336
-0.11
-0.21
-0.03
0
-.119(*)
-0.02
0.07
0.07
44
45
317
314
326
326
320
324
0.01
-0.04
-0.06
0.04
-.174(**)
-0.07
42
43
311
308
318
318
312
316
0.01
-0.08
-0.03
-0.01
-0.01
-0.05
0.05
0.06
45
46
321
315
329
329
322
327
-0.08 -.320(**)
.275(**)
-0.09
-0.1 -.257(**)
0.05
325
339
339
332
337
0 .245(**) -.173(**)
.342(**)
.330(**) .569(**)
0
-0.21
45
46
-0.02
.348(**) -.331(**)
FEMAL
E
AGE
329
-.112(*) .109(*)
0.06 .119(*)
45
46
330
325
516
516
506
513
1
.948(**)
0.27
-0.19
0.24
0.12
0.22
0.01
45
45
43
42
45
45
42
45
.948(**)
1
0.26
0.06
0.16
0.04
0.24
-0.01
45
46
44
43
46
46
43
46
0.27
0.26
1 -.364(**)
0.06
.128(*) .217(**)
0.03
43
44
-0.19
330
319
330
0.06 -.364(**)
1
-.143(**)
325
325
325
319
323
0.06 -.143(**)
1
.535(**)
.093(*)
0.05
325
516
516
506
.128(*) -.176(**)
.535(**)
42
43
0.24
0.16
45
46
0.12
0.04
45
46
0.22
319
330
330
330
324
328
-.176(**) -.148(**)
-0.1
513
.145(*
1 .137(**)
*)
325
516
516
506
513
0.24 .217(**) -.148(**)
.093(*)
.137(**)
1
-0.07
42
43
324
319
506
506
506
503
0.01
-0.01
0.03
-0.1
0.05
.145(**)
-0.07
1
45
46
328
323
513
513
503
513
** Correlation is significant at the 0.01 level (2-tailed).
* Correlation is significant at the 0.05 level (2-tailed).
APPENDIX VI: Bivariate Correlations for Family Variables
Frequency
Quality of Quality of
Long
Frequency
face to
face to
cell
Relationship distance
Length of
cell phone
face
face
phone satisfaction relationship relationship
comm.
comm.
comm.
comm.
(=1)
Frequency face to face
communication
Frequency cell phone
communication
Quality of face to face
communication
Quality of cell phone
communication
Relationship satisfaction
Pearson
Corr.
N
Pearson
Corr.
N
Pearson
Corr.
N
Pearson
Corr.
N
Pearson
Corr.
N
Long distance relationship
(=1)
Length of relationship
Pearson
Corr.
N
Pearson
Corr.
N
Respondent multitasking
during face to face
communication (=1)
Pearson
Corr.
Family multitasking during
face to face communication
(=1)
Pearson
Corr.
Spoke just for fun (=1)
N
N
Pearson
Corr.
N
Length of Conversation
Pearson
Corr.
N
Pearson
Family multitasking during cell Corr.
communication (=1)
Respondent multitasking
during cell communication
(=1)
AGE
N
Pearson
Corr.
N
Pearson
Corr.
N
FEMALE
Pearson
1
.384(**)
.092(*)
0.02
.104(*)
-.625(**)
-.165(**)
510
509
478
475
502
509
510
1 .146(**) .147(**)
.131(**)
-.180(**)
-.092(*)
476
505
512
513
1 .778(**)
.599(**)
-0.03
-0.02
.384(**)
509
513
.092(*)
.146(**)
478
480
0.02
481
460
474
480
481
.147(**) .778(**)
1
.470(**)
0.03
0.09
477
472
477
477
.131(**) .599(**) .470(**)
1
0.01
-0.04
475
.104(*)
476
460
502
505
474
472
507
505
507
-.625(**)
-.180(**)
-0.03
0.03
0.01
1
.087(*)
509
512
480
477
505
514
514
-.165(**)
-.092(*)
-0.02
0.09
-0.04
.087(*)
1
510
513
481
477
507
514
516
0.09 -.163(*) -.224(**)
-.193(*)
-0.08
-.170(*)
.222(**)
159
160
152
147
154
159
160
.161(*)
0.15
-0.13
-0.08
-.183(*)
0.02
-.170(*)
157
158
150
144
151
157
158
-0.01 -.177(**) -.212(**)
-.169(**)
-.225(**)
-0.04
473
504
509
511
0.05 .153(**)
0.08
.243(**)
0.05
.264(**)
506
509
-.295(**)
-.103(*)
510
513
481
477
507
514
516
0.07
.178(**)
0.03
-0.01
0.01
-0.03
-0.04
510
513
481
477
507
514
516
.101(*)
.128(**)
-0.02 -.138(**)
-0.03
-0.07
0
510
513
481
477
507
514
516
-0.03
-.134(**)
0.06
.106(*)
-0.04
-0.09
.652(**)
504
472
468
.137(**) .143(**) .137(**)
497
0.08
504
.126(**)
506
0.07
504
512
513
500
-0.03
508
** Correlation is significant at the 0.01 level (2-tailed).
* Correlation is significant at the 0.05 level (2-tailed).
N
480
511
111
477
479
475
112
Respondent
Family
Family
Respondent
multitasking multitasking Spoke
Length of multitasking multitasking
during face during face just for
Conver. during cell during cell
to face
fun (=1)
to face
comm. (=1) comm. (=1)
comm.(=1) comm. (=1)
Pearson
Frequency face to face Corr.
communication
N
Frequency cell phone
communication
Quality of face to face
communication
Quality of cell phone
communication
Relationship
satisfaction
Long distance
relationship (=1)
Length of relationship
Pearson
Corr.
N
Pearson
Corr.
N
Pearson
Corr.
N
Pearson
Corr.
N
Pearson
Corr.
N
Pearson
Corr.
N
Pearson
Respondent
multitasking during face Corr.
to face communication
N
(=1)
Family multitasking
during face to face
communication (=1)
Spoke just for fun (=1)
Pearson
Corr.
N
Pearson
N
Pearson
Length of Conversation Corr.
N
Family multitasking
during cell
communication (=1)
Pearson
Corr.
N
Pearson
Respondent
multitasking during cell Corr.
communication (=1)
N
AGE
Pearson
Corr.
N
FEMALE
Pearson
N
.222(**)
159
.161(*) .264(**) -.295(**)
157
506
510
AGE
FEMALE
0.07
.101(*)
-0.03
-0.03
510
510
500
508
.128(**)
.137(**)
.134(**)
0.09
0.15
-0.01
-.103(*)
.178(**)
160
158
509
513
513
513
-0.13
.177(**)
0.05
0.03
-0.02
477
481
481
481
-0.08
.212(**)
.153(**)
-0.01
473
477
477
477
468
475
-.183(*)
.169(**)
0.08
0.01
-0.03
-0.04
0.08
504
507
507
507
497
504
0.02
.225(**)
.243(**)
-0.03
-0.07
514
-.163(*)
152
-.224(**)
147
-.193(*)
154
-0.08
150
144
151
504
511
0.06 .143(**)
472
479
-.138(**) .106(*) .137(**)
-0.09 .126(**)
159
157
509
514
514
-.170(*)
-.170(*)
-0.04
0.05
-0.04
160
158
511
516
516
516
506
513
1
.632(**)
0.12
-0.03
0.08
.182(*)
-0.11
-0.09
160
156
158
160
160
160
156
159
.632(**)
1
0.04
-0.03
0.01
0.1
-0.08
-0.01
156
158
158
158
154
157
1 -.356(**)
0.02
0.08
0.01 -.125(**)
156
158
0.12
0.04
158
156
-0.03
504
512
0 .652(**)
0.07
511
511
511
511
501
508
-0.03
.356(**)
1
-0.05
-.120(**)
0
0.03
506
513
160
158
511
516
516
516
0.08
0.01
0.02
-0.05
1
.240(**)
160
158
511
516
516
516
506
513
.182(*)
0.1
0.08 -.120(**)
.240(**)
1
-0.04
0.05
160
158
511
516
516
516
506
513
-0.11
-0.08
0.01
0
-0.02
-0.04
1
-0.07
156
154
501
506
506
506
506
503
-0.01
.125(**)
0.03
.115(**)
0.05
-0.07
1
513
513
513
503
513
-0.09
159
157
** Correlation is significant at the 0.01 level (2-tailed).
* Correlation is significant at the 0.05 level (2-tailed).
508
-0.02 .115(**)
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