Mejía, S.T., & Hooker, K. (2013). Relationship processes within the social convoy: structure, function, and social goals. Journals of Gerontology, Series B: Psychological Sciences and Social Sciences,
69(3), 376–386, doi:10.1093/geronb/gbt011. Advance Access publication April 10, 2013
Relationship Processes Within the Social
Convoy: Structure, Function, and Social Goals
Shannon T. Mejía and Karen Hooker
School of Social and Behavioral Health Sciences, Oregon State University, Corvallis.
Objectives. The structure and function of older adults’ social convoys contribute to health and well-being in later life,
but little is known about how they may shape one another. In this study, we consider relationship quality as a withinperson process by examining its covariation with social goal progress and investigate variation in these relationship
processes across differences in convoy composition.
Method. We analyzed data from 99 older adult participants (age = 53–88 years) from the Personal Understanding of
Life and Social Experiences project, a web-based, 100-day microlongitudinal study. Participants logged daily social goal
progress and contact satisfaction with their 5 closest social partners.
Results. Multilevel analysis found social goal progress to be higher on days when individuals’ contact satisfaction
was above their average level. The strength of this association varied significantly across participants and was stronger
among those with family-intensive convoys. Daily contact satisfaction also explained more variation in goal progress
than a standard measure of relationship quality.
Discussion. Daily measures of contact satisfaction help us understand processes within older adults’ social convoys
and complement standard measures of relationship quality. Findings suggest that older adults’ utilization of their close
relationships varies in part by structural qualities of their convoys.
Key Words: Friends and family—Microlongitudinal—Relationship quality—Social convoy—Social goals—Withinperson process.
H
uman development is deeply embedded in social
experience, and social networks in older adulthood are
the product of a lifetime of life course transitions, development, and relational histories (Antonucci, Fiori, Birditt, &
Jackey, 2010; Blieszner, 2006; Fiori, Smith, & Antonucci,
2007). Integrating these perspectives, the social convoy
model (Antonucci et al., 2010; Kahn & Antonucci, 1980)
proposes that convoys of close relationships develop with
individuals over time in concert with changing roles and
life periods. Reflecting distinct life trajectories (Connidis,
2010), social positions (Fiori, Consedine, & Magai, 2008),
and social goal strategies (Lang, Staudinger, & Carstensen,
1998), convoys are notably heterogeneous later in life, and
some are better equipped to support health and well-being
more than others (Fiori, Antonucci, & Cortina, 2006; Rook,
Mavandadi, Sorkin, & Zettel, 2007). Notably, by setting
and working toward social goals, individuals participate in
shaping the structure and function of their convoys (Lang
et al., 1998) to optimize their health and well-being (Rook
et al., 2007). In this study, we examine the interplay of convoy structure and function by linking older adults’ social
goal progress to satisfaction with their closest social partners over a 100-day time period. We then explore variation
in these processes across differences in the convoy’s composition of friends and family.
376
The Social Convoy Over Time: Integrating
Structure and Function
The social convoy model (Antonucci et al., 2010; Kahn
& Antonucci, 1980) integrates social network structure,
relationship processes, and change over time. The convoy’s
structure is measured in terms of its size and composition of
relationship types, such as close friend or kin. Relationship
processes comprise the convoy’s function, which include
support, companionship, and also strain. Both structure and
function are not only characteristics of the person, such as
age, gender, temperament, and ability, but also of the situation, such as resources, marital status, social position, and
positive and negative life experiences.
Recognizing that the social convoy is more than just the
sum of its parts, recent research on relationships in older
adulthood used a person-centered approach to integrate
the convoy’s structure and function (Antonucci et al.,
2010). These methods applied cluster analysis to identify
common structural and functional convoy patterns and
found four robust typologies: family-intensive, diverse,
friend-intensive, and restrictive convoys. A growing body
of literature shows that network typologies account for
differences in mental health (Fiori et al., 2006), wellbeing (Birditt & Antonucci, 2007), morale (Litwin, 2001),
loneliness and anxiety (Litwin & Shiovitz-Ezra, 2011), and
© The Author 2013. Published by Oxford University Press on behalf of The Gerontological Society of America.
All rights reserved. For permissions, please e-mail: [email protected].
Received October 23, 2012; Accepted January 30, 2013
Decision Editor: Bob Knight, PhD
SOCIAL CONVOY RELATIONSHIP PROCESSES
mortality (Litwin & Shiovitz-Ezra, 2006). Guided by the
concept of the convoy as both the outcome and context of
development (Antonucci, Langfahl, & Akiyama, 2006) and
the six-foci model of personality, which integrates how
process and structure may shape one another over time
(Hooker & McAdams, 2003), we build on this important
research by examining convoy function as within-person
processes that may vary across differences in convoy
structure.
Linking Convoy Function to Social Goal Processes
Convoys have many functions, and in this study, we
focus on contact satisfaction with the closest social partners. Relationships are complex, especially in older adulthood (Fingerman, Hay, & Birditt, 2004). Unlike measures
of social support, which can at times be unwanted or perceived as burdensome or demeaning (Rafaeli, Cranford,
Green, Shrout, & Bolger, 2008), contact satisfaction represents an interaction with a close social partner that satisfies
one’s needs at a given moment (Rook, 1987). Therefore,
although support is a process by which social partners may
influence health and well-being, measures of contact satisfaction specify the quality of social interactions.
In the face of relationship complexities, older adults set
and work toward social goals in an effort to optimize their
social resources to meet their needs (Lang et al., 1998;
Rook et al., 2007). Social goals represent intentional efforts
to manage the quality of relationships and are known to differ across life periods. In older adulthood, as future time
perspective decreases, social goals shift to emphasize emotional closeness (Carstensen, Isaacowitz, & Charles, 1999).
Social goal progress is also linked to daily social experiences of support and hindrance (Mejía & Hooker, under
review). In this study, to explore how convoy structure may
interact with convoy function, we examine the link between
older adults’ daily variation in social goal progress and
contact satisfaction with their five closest social partners,
and the extent to which this link varies across differences in
convoy structure.
Microlongitudinal Study of Relationship Quality
When relationship quality is examined longitudinally,
measurements are generally separated by extended time
intervals. Longitudinal research suggests that relationship
quality varies within individuals over time (Birditt, Jackey,
& Antonucci, 2009), and that trajectories of relationship
quality differ by relationship type such as spouse, friend,
or acquaintance (Shaw, Krause, Liang, & Bennett, 2007).
What remains unexamined is how the process of relationship quality may ebb and flow over a timescale that developmentalists call microtime (Ram & Gerstorf, 2009), which
we undertake by examining daily measures of contact satisfaction with the closest social partners. This approach
offers several advantages. First, daily measures of contact
377
satisfaction are less sensitive to recall bias, which is known
to favor positive appraisals among older adults (Charles &
Carstensen, 2008). Second, daily measures of contact satisfaction allow the examination of within-person processes
(Hooker, Hoppmann, & Siegler, 2010), such as the extent to
which contact satisfaction on a given day may be linked to
social goal progress on that day. Third, daily measurements
highlight the strength of association between daily contact
satisfaction and goal progress, as well as the variation of
this association across individuals. Drawing from strategies
used in the study of daily stress reactivity (e.g., Bolger &
Zuckerman, 1995), we name this link sensitivity to contact satisfaction. Goal progress among those with higher
sensitivity is more tightly coupled to variation in contact
satisfaction, whereas goal progress and contact satisfaction
vary more independently among those with lower sensitivity. Finally, the daily measurement of relationship quality
allows us to explain variation in contact satisfaction sensitivity across individuals.
Convoy Structure
An important variation in convoy composition is the
proportion of friend and family relationships (Blieszner,
2006; Fiori et al., 2006). Although family roles and
responsibilities are often socially defined, friendships are
generally age peers and selected by choice (Connidis,
2010). Friendships, like kin relations, can also be conflicted. Although family relationships are tied to filial
obligations, friendships are more strongly governed by the
reciprocity norm and may also require time and resources
to maintain (Lang, Wagner, & Neyer, 2009). Convoy composition has yet to be examined in relation to social goal
progress, but we expect that friendships are more supportive of social goal progress for two reasons. First, friendintensive convoys reflect a life trajectories that require
extending beyond immediate kin ties (Connidis, 2010).
Second, friendships often provide stronger emotional
support than family members (Blieszner, 2006; Walen &
Lachman, 2000), which may be more assistive to goal pursuit, and also predict differences in sensitivity to contact
satisfaction.
Age, gender, and marital status all contribute to convoy
structure and may also influence relationship processes
within the convoy. The social convoy generally shrinks
in size as individuals age (Lang et al., 1998), and social
exchanges shift from support giving to support receiving
(Shaw et al., 2007). The meaning and function of
relationships in older adulthood are also known to vary by
gender. Men generally have smaller networks with fewer
close relationships than women and are more likely to
establish closeness through shared activities rather than
emotional exchanges (Connidis, 2010). Marital status is
related to support and relationship complexities such as
strain and conflict (e.g., Walen & Lachman, 2000).
378
MEJÍA AND HOOKER
The Current Study
By working toward social goals, individuals participate
in shaping their social convoys to meet their needs across
their life spans (Lang et al., 1998; Rook et al., 2007). Social
convoys are characterized by their structure (e.g., composition of friends and family) and function (e.g., relationship
quality), which are specific to characteristics of the person
and the context (Antonucci et al., 2010; Kahn & Antonucci,
1980). Some convoys are better optimized to fit individuals’ needs than others, and patterns of convoy structure and
function have been associated with differences in health and
well-being in older adulthood (Fiori et al., 2006; Litwin &
Shiovitz-Ezra, 2006, 2011). These studies have been invaluable in building our knowledge of social relationships.
However, they cannot speak to how convoy function is
linked to daily experiences within the individual, the extent
to which the salience of convoy function may vary across
individuals, or the potential for convoy structure to shape
convoy function. To address these gaps in the literature, we
examine relationship quality, as a within-person process,
which we measure as daily contact satisfaction with close
social partners. Our study has three aims.
Our first aim is to understand how convoy structure and
function contribute to within- and between-person variation in social goal progress. We address this aim with three
research questions: (a) Does the level of progress toward a
social goal vary across differences in the proportion of friend
and family relationships in a convoy? Because friend-focused
convoys reflect life trajectories that require extending beyond
kin ties (Blieszner, 2006), we expect that those with a higher
proportion of friendships will report higher goal progress.
(b) Is day-to-day variation in social goal progress linked to
experiences of contact satisfaction on that day? Given the
link between relationship quality and well-being (Birditt &
Antonucci, 2007; Birditt et al., 2009), we expect that goal
progress will be higher on days when contact satisfaction is
above the individual’s average. (c) Does the strength of this
association (which we term sensitivity) vary across individuals? Following evidence from research on support and hindrance processes (e.g., Mejía & Hooker, under review), we
expect individuals to vary in the extent to which their goal
progress is sensitive to variation in contact satisfaction.
Our second aim was to examine variation in convoy function across differences in convoy structure. Thus, a fourth
research question is: Does sensitivity to contact satisfaction
vary across differences in the proportion of friends and family in the convoy? Following theory that kinship ties foster closeness regulation (Lang et al., 2009), we expect that
goal progress among those with a higher proportion of family members will be more sensitive to variation in contact
satisfaction.
And finally, we aim to address an important methodological issue. Our fifth research question is: Does the aggregate
of daily contact satisfaction better explain variation in overall
social goal progress than a standard measure of relationship
quality? We expect that daily measurements of contact satisfaction will explain more variation in social goal progress
than a standard measure of relationship quality.
Method
Study Design
This research used data from the initial and daily
phases of the Personal Understanding of Life and Social
Experiences (PULSE) project. The PULSE project was
conducted completely via the Internet on a custom web
application that was designed and built by the research
team. The PULSE project consisted of an initial survey,
which was followed by daily surveys over a 100-day time
period. Its within-person design (Nesselroade, 1990) facilitated the investigation of within-person self-regulatory processes and between-person differences in those processes.
The 100-day temporal frame was chosen to allow enough
time for goal attainment and to capture a wide range of
variation in behavioral patterns. The PULSE study was also
designed to examine differences in temporal measurement
strategies (e.g., how many observations are necessary to
reliably capture intra-individual variation; Hooker, Mejía,
Pham, Metoyer, & Ram, 2012). A quarter of the sample
was therefore randomly assigned to a measurement-burst
group. Rather than completing 100 consecutive surveys, the
burst group completed four equally spaced 7-day measurement bursts (total observations = 28) during the 100-day
study period. There were no significant differences in terms
of demographics, convoy size, or the proportion of friends
and family between the two measurement groups; T 2 = .05,
F(1,2) = .76, ns. Data were collected between June and
October of 2010.
Participants and Procedure
PULSE participants were recruited by e-mail from an
existing human subjects registry of individuals aged 50
and older. One hundred and five older adults (Mage = 63.19,
SD = 7.80, range = 52–88) were initially recruited for the
project. Of those recruited, 88% were women, 97% were
White, 73% were married or partnered, and 47% were
retired. Five participants dropped out of the study, and one
participant was removed for completing only five sessions.
The remaining 99 participants had a median completion rate
of 92% (interquartile range = .20). Those who dropped out
were not significantly different from participants in terms
of age, education, marital status, proportion of friends, and
relationship quality; F(6,97) = .92, ns.
The PULSE study had two phases: (a) an initial survey and
(b) a series of daily surveys. In the initial survey, participants
provided demographic and psychosocial information, a
meaningful social goal, and information about their social
convoys. In the daily survey, which we designed to be
completed within five minutes, participants documented
SOCIAL CONVOY RELATIONSHIP PROCESSES
their daily goal progress and daily social experiences.
Participants accessed their daily surveys by following a link
that was e-mailed to them each morning, which then expired
at 2:00 a.m. the following day. Participants were instructed
in the daily e-mail to complete their PULSE session that
evening. Analysis of time-stamped data showed that 83%
of sessions were completed after 4:00 p.m.
Initial Survey Measures
Meaningful social goal.—Participants created a meaningful social goal by responding to the following prompt:
“Choose one goal that is important to you in the realm of
social relations (family and/or friends) that you expect to
be working on over the next 4 months.” Participants were
then asked to “describe this goal in as much detail as possible” in a text field and then answer “Why is it important to
you?” in a second text field. Participants also wrote a short
statement to remind them of their goal during the study, and
these words were programmed to automatically populate
their daily surveys.
Social convoy composition.—Participants’ social convoys
were measured using the hierarchical mapping technique
(Antonucci, 1986). Instructions on the web-based form
asked participants to imagine that the pictured diagram of
three concentric circles represented their social partners
who are currently significant in their lives. Participants were
instructed to place in the order of closeness social partners
they could not live without in the innermost circle, those with
whom they felt close to in the middle circle, and those with
whom they felt not quite that close in the outermost circle.
Participants specified their relationship to each person in a
text box, and these relationships were coded as either family
or friend. Spouses, life partners, significant others, siblings,
siblings-in-law, children, children-in-law, and grandchildren
were coded as family. Friends, neighbors, coworkers, and
godchildren were coded as friends. Given their inclusion in
the convoy diagram, we assumed that these relationships
were meaningful in the participants’ lives. To emphasize
convoy composition over convoy size, we calculated the
percentage of friends in the social convoy.
379
instructions that participants were to respond based on
experiences for that day. Participants responded by using
their mouse to move a handle along a slider. To encourage
independent assessment of each day, the scales’ underlying numbers were not visible to participants (Brose & Ram,
2012) but were recorded in the database.
Daily social goal progress.—Goal progress was measured daily on a continuous sliding scale between 0 (no
progress) and 100 (great progress). The daily goal prompt
was populated by the participants’ specific social goals
(in italics). An example prompt is as follows: Rate your
progress toward your goal of [improve daughter-in-law
relationship].
Daily contact satisfaction.—Our measure of contact satisfaction was adapted from Rook (1987) and was populated
with the names of the five closest social partners listed in
the social convoy measure. For participants with an inner circle smaller than five (61%), the daily questionnaire included
social partners from the middle circle. Participants responded
to the daily prompt, “Please indicate whom you interacted
with today,” by checking a box next to the social partners
they had interacted with. Participants then responded to the
prompt, “how satisfied were you with this interaction?” by
sliding the handle across the scale between 0 (not satisfied)
and 100 (very satisfied). Daily contact satisfaction was calculated as the average contact satisfaction across social partners
interacted with on that day. To allow the model to represent
goal progress on days with and without interactions with
close social partners, days where none of the listed social
partners were contacted were coded as zero.
Relationship quality.—Our standard measure of relationship quality was the Social Support Appraisal Scale
(Vaux et al., 1986). This 23-item scale measures feelings
of love, support, and involvement in the social network and
has been shown to have good validity in older populations.
The scale’s inter-item reliability in this sample was high
(Cronbach’s α = .94).
Covariates
To focus on contact satisfaction and convoy composition,
we controlled for important aspects of convoy function and
structure. A functional control was the participants’ daily
experiences of support toward their social goals, which was
measured with the prompt: “Did you receive any practical
or emotional assistance toward your social goal today?”
(adapted from Rafaeli et al., 2008). Support was analyzed
in depth in our previous work (Mejía & Hooker, under
review). Our structural controls included marital status
(1 = married or partnered), age, and gender (1 = female),
which are known to account for variation in both convoy
structure and function (Walen & Lachman, 2000). We also
included a measurement group dummy variable (Daily = 1;
Burst = 0) to control for differences in exposure to the daily
survey (28 days vs 100 days).
Daily Measures
Daily measures of social goal progress and contact satisfaction were completed on the daily survey and included
Analytic Strategy
Data were analyzed using a series of multilevel random
coefficient models, which accommodated the nesting of
380
MEJÍA AND HOOKER
repeated measurements within participants, and allowed
the association between daily contact satisfaction and
goal progress to vary across individuals. To examine the
contribution of convoy structure and function to social
goal progress, we considered both within-person (Level
1) and between-person (Level 2) models. Level 1 variables were time variant, represented convoy function, and
included within-person relationship processes of contact
satisfaction and support. Relationship processes were
group centered (subtracting the individual’s mean from
each observation). This removes individual differences
and examining variation in goal progress as relationship
processes vary above or below the person’s mean. When
time-varying covariates are group centered, the intercept represents goal progress on an average day for that
person. The Level 1 model was estimated as follows in
Equation 1:
(3)
Results
A correlation matrix and summary statistics of the participants’ social convoy, demographics, and mean convoy
functions are presented in Table 1. Table 2 displays the
intra-individual means, standard deviations, and correlations of relationship processes across differences in convoy
composition. In preliminary analysis, we modeled social
goal progress, contact satisfaction, and support unconditionally to calculate their proportion of within-person variance (1 – intraclass correlation): goal progress = .50; contact
satisfaction = .61; support = .45. Contact satisfaction varied
more within individuals than it did between individuals.
+ β 3i (SupportWPti ) + eti
Level 2 variables were measured once and include individual characteristics of convoy composition, age, gender,
marital status, measurement group, and person-means of
daily contact satisfaction and support. These variables were
used to predict between-person differences in both the level
of social goal progress and also sensitivity to variation in
relationship processes. To facilitate interpretation of the
intercept and cross-level interactions, all Level 2 variables
were grand-mean centered. Cross-level interactions were
used to examine variation in relationship processes across
convoy structure. Between-person variation in the intercept
(Equation 2) and contact satisfaction coefficient (Equation 3)
were modeled as follows:
Convoy Structure and Social Goal Progress
To address our first aim, we examined direct effects of convoy structure and function on social goal progress. Beginning
with our first research question, we modeled the proportion
of friends and family to predict between-person differences
in the level of goal progress across the 100-day study, controlling for marital status, time, age, gender, and measurement group. The results are presented in Model 1 on Table 3.
Consistent with our expectations, the proportion of friends
in the convoy was associated with the level of goal progress
β0i = γ 00 + γ 01 (Age i ) + γ 02 (Genderi ) + γ 03 (Groupi )
(2)
+γ 04 (SatisfactionBPi ) + γ 05 (SupportBPi )
+ γ 23 (%Friendsi ) + u2i
Models were constructed sequentially, beginning with
an unconditional model, and assessed in terms of improved
model fit (Δ –2*LL) and the random estimates’ pro­
portional reduction in variance ( R 2 = (σ 2u|b + σ 2u|m ) σ 2u|b;
Raudenbush & Bryk, 2002). Data were rendered weakly
stationary by assessing model residuals and variance across
time (Brose & Ram, 2012). A linear growth parameter sufficiently detrended the data. The autocorrelation function
showed that an AR(2) process sufficiently absorbed the correlation of residuals. The models were constructed using
the xtmixed command in STATA.
Social Goalti = β 0i + β 1i (Day ti ) + β 2i (SatisfactionWPti )(1)
β2i = γ 20 + γ 21 (SatisfactionBPi ) + γ 22 (Maritali )
+γ 06 (Maritali ) + γ 07 (%Friendsi ) + u0i
Table 1. Correlation Matrix of Descriptive Variables Describing Convoy Structure and Function From Cross-Sectional
and Daily Surveys Over 100 Days
1
Convoy structure
1. No. of convoy
2. %Friends
3. %Close
4. Partnered
Convoy function (mean over 100 days)
5. Contact
6. Satisfaction
7. Support
8. Social goal
Convoy function (initial survey)
9. Relationship quality
Note. *p < .05. **p < .01. ***p < .001.
2
3
4
5
6
7
.18
−.26**
−.12
−.35***
−.25**
.15
.02
.08
.01
.09
−.08
.05
.12
.28**
.07
.00
.13
−.07
.35***
.42***
.05
.04
.51***
.18
.19
.26**
.36***
.69***
−.00
.12
−.03
.26**
.15
.36***
.24**
8
.21*
381
SOCIAL CONVOY RELATIONSHIP PROCESSES
Table 2. Convoy Characteristics, Intra-Individual Means, Standard Deviations, and Correlations of Convoy Function
Convoy characteristics
Convoy size
Proportion close*
Married/partnered (%)
Intra-individual means
Contact
Contact satisfaction
Support
Social goal progress*
Intra-individual SD
Contact*
Contact satisfaction
Support
Social goal progress
Intra-individual correlations
rsatisfaction, goal progress
rgoal progress, support
rsatisfaction, support*
Family intensive
Diverse
Friend intensive
Total
N = 24
N = 34
N = 41
N = 99
M
SD
M
SD
M
SD
M
SD
15.71
39.09
0.79
6.28
17.05
17.06
33.19
0.76
8.60
17.51
19.90
26.45
0.68
10.24
14.34
17.91
31.83
0.74
9.03
16.92
1.82
75.67
47.33
58.06
0.96
15.01
24.02
21.50
1.44
71.66
49.50
59.57
0.93
17.75
20.50
18.78
1.58
76.89
51.31
68.32
0.81
18.64
26.99
19.03
1.59
74.80
49.72
62.83
0.90
17.73
24.22
20.11
1.24
14.87
18.58
19.14
0.38
9.80
9.02
10.76
1.14
19.28
20.72
18.23
0.28
11.44
6.78
7.08
1.07
18.82
19.27
17.17
0.29
10.68
8.30
6.72
1.14
18.02
19.60
18.01
0.32
10.89
8.05
8.04
.23
.58
.18
.23
.24
.16
.24
.58
.20
.23
.30
.20
.17
.50
.08
.19
.35
.20
.21
.55
.15
.22
.31
.20
Notes. Intra-individual correlations are pair-wise correlations of time-varying covariates for each individual. Family intensive < 35 ≥ diverse < 57 ≥ friend
intensive (Litwin, 2001).
Multivariate analysis of variance identified between-group difference, *p < .05.
over the 100-day study period (estimate = .28, SE = 0.09,
p = .002). Those with a higher proportion of friends in their
networks reported higher goal progress. This model explained
13% of the between-person variation in goal progress.
Daily Contact Satisfaction and Social Goal Progress
We continued by investigating the link between daily
social goal progress and contact satisfaction on that day.
The results from this analysis are presented in Model 2 on
Table 3. Addressing our second research question, social
goal progress was higher on days when individuals’ contact
satisfaction with their close social partners was above the
individual’s average (estimate = .10, SE = 0.02, p < .001).
This effect was independent of experiences of support on that
day (estimate = .48, SE = 0.03, p < .001). To answer our third
research question, we evaluated the between-person error
component for the contact satisfaction coefficient. Consistent
with our expectations, sensitivity to contact satisfaction varied
significantly across participants (χ2(3) = 43.23, p < .001). The
contact satisfaction coefficient varied across individuals by a
SD of 0.11 (SE = 0.02). Therefore, a plausible range (95%
CI) of the contact satisfaction coefficient in this sample falls
between −0.11 and 0.32 (see Figure 1). Contact satisfaction
is linked to variation in social goal progress, independent of
variation in support. The strength of this sensitivity, however,
varies significantly across individuals.
Convoy Structure and Function
To address our second aim, we added cross-level
interactions to examine the extent to which sensitivity to
contact satisfaction varied across the proportion of friends
in the convoy and marital status. We present the results
from this analysis in Model 3 on Table 3. Including these
moderators significantly improved model fit (χ2(4) = 17.72,
p < .01). Consistent with our expectations, as shown in
Figure 2, goal progress among those with a higher proportion
of family members was more sensitive to variation in contact
satisfaction (estimate = −.002, SE = 0.001, p = .003).
Sensitivity to contact satisfaction was also higher among
those who were married or partnered (estimate = .08,
SE = 0.03, p = .01). Model 3 predicts that on a day of
low (−1 SD) contact satisfaction, goal progress would be
43.72 among individuals with family-intensive convoys
(%friends < 35) and 68.25 among individuals with friendintensive convoys (%friends > 57). In other words, social
goal progress was more independent of contact satisfaction
among those with a friend-intensive convoy. The proportion
of friends and family in the convoy explained 23% of the
variation in sensitivity to contact satisfaction. The final
model, where both marital status and the composition of
friends and family moderated convoy function, accounted
for 47% of the between-person variation in sensitivity to
contact satisfaction.
Single Versus Daily Measurements of Relationship
Quality
To address our final aim, we examined whether initial
or daily measures of relationship quality better explained
variation in the level of social goal progress. We began by
modeling variation in social goal progress with a standard measure of relationship quality, controlling for time,
age, gender, and measurement group. Consistent with
382
MEJÍA AND HOOKER
Table 3. Multilevel Random Coefficient Model of Convoy Structure and Function on Daily Social Goal Progress
Fixed effects
Intercept
Day
Age
Gender
Group
Marital status
%Friends
Satisfaction WP
Satisfaction BP
Satisfaction WP × BP
Support WP
Support BP
Support WP × BP
Marital × Satisfaction
Marital × Support
%Friends × Satisfaction
%Friends × Support
Random effects (SD)
Intercept
Day
Satisfaction
Support
Residual
Φ1
Φ2
R2 within
R2 between
R2 satisfaction
−2*LL
Δ − 2*LL
Model 1
Model 2
Model 3
B (SE)
B (SE)
B (SE)
63.19*** (1.91)
0.11*** (0.02)
0.15 (0.26)
−6.35 (5.92)
−5.25 (4.61)
5.48 (4.71)
0.28** (0.09)
63.02*** (1.38)
0.06*** (0.01)
−0.13 (0.14)
0.98 (3.35)
−2.68 (2.84)
−1.47 (2.82)
0.18*** (0.05)
0.10*** (0.02)
0.19** (0.07)
0.002* (0.001)
0.48*** (0.03)
0.54*** (0.06)
0.002 (0.001)
63.03*** (1.38)
0.06*** (0.01)
−0.13 (0.14)
0.93 (3.33)
−3.00 (2.70)
0.50 (3.43)
0.19** (0.06)
0.11*** (0.02)
0.18** (0.07)
0.001 (0.001)
0.48*** (0.03)
0.53*** (0.05)
0.002 (0.001)
0.08** (0.03)
−0.04 (0.06)
−0.002** (0.001)
−0.001 (0.001)
18.62 (1.36)
0.14 (0.02)
13.45 (1.00)
0.11 (0.01)
0.11 (0.02)
0.26 (0.02)
14.68 (0.14)
.22 (.01)
.06 (.01)
.46
.55
13.45 (0.98)
0.11 (0.01)
0.08 (0.02)
0.26 (0.02)
14.68 (0.14)
.22 (.01)
.06 (.01)
.46
.55
.47
58,016.19
χ2(4) = 17.72**
19.34 (0.18)
.22 (.01)
.06 (.01)
.06
.13
61,944.99
58,033.91
χ2(12) = 3,638.72***
Notes. BP = between-person; WP = within-person. Random coefficients and improved model fit tested using Δ –2*LL. All random effects improved model fit.
Time varying covariates are group centered. Time invariant covariates are grand-mean centered. Estimates are unstandardized.
*p ≤ .05. **p ≤ .01. ***p ≤ .001.
Figure 1. Between-person variability in contact satisfaction sensitivity. Light grey lines represent empirical Bayes predictions of participant-specific regression
lines of daily contact satisfaction on daily social goal progress. The solid line represents the fixed effect of daily contact satisfaction on daily social goal progress.
Dashed lines represent the lower and upper distributions of sensitivity to contact satisfaction in this sample.
SOCIAL CONVOY RELATIONSHIP PROCESSES
383
Figure 2. Contact satisfaction sensitivity across differences in social convoy composition of friends and family. Discrete categories are for illustration only.
Multilevel analysis was conducted using a continuous measure of proportion of friends and family in the social convoy. Family intensive < 35 ≥ diverse < 57 ≥ friend
intensive (Litwin, 2001).
expectations from previous research, the standard measure
of relationship quality was significantly related to goal progress across the 100-day study (estimate = .33, SE = 0.16,
p = .04) and explained 4% of the between-person variation in goal progress. Adding between-person variation in
daily contact satisfaction significantly improved model fit
(χ2(1) = 8.71 p < .01), was significantly associated with
differences in goal progress (estimate = .35, SE = 0.12,
p =.002), rendered the standard measure of relationship
quality nonsignificant (estimate = .15, SE = 0.16, ns), and
explained an additional 9% of the between-person variation
in social goal progress. In other words, between-person differences in daily contact satisfaction explained more variation in social goal progress than a standard relationship
quality measure.
Discussion
Working toward social goals is a process by which
older adults may optimize their relationships to benefit
their health and well-being. In this study, we built on a
rich body of work that strives to integrate convoy structure
and function (e.g., Birditt & Antonucci, 2007; Fiori et al.,
2006; Litwin & Shiovitz-Ezra, 2006, 2011) by introducing
a within-person measure of relationship quality with individual’s closest social partners over a 100-day time period.
We demonstrated that daily measures of contact satisfaction allow for exploration into the dynamics of how convoy
structure may influence convoy function and also explain
more variation in social goal progress than a standard measure of relationship quality.
Between-Person Variation in Sensitivity to Contact
Satisfaction
Measuring contact satisfaction daily allowed us to examine its day-to-day covariation with social goal progress. We
found that, in general, individuals made more goal progress
on days when contact satisfaction with their closest social
partners was higher than their average. Perceived relationship quality has long been acknowledged to be as important
as received support (cf. Blieszner, 2006). By measuring relationship quality intensively over 100 days, we have learned
that its importance carries over to the daily experience and
in this sample actually varies more within individuals than
it does between individuals. Our findings justify further
investigation into contact satisfaction as a within-person
relationship process, which would allow the opportunity to
further explore its within- as well as between-person variation. Antonucci and colleagues (2010) have proposed that
the convoy develops parallel to changes in characteristics of
the person and situation. Sensitivity to contact satisfaction
may similarly vary across person and situation contexts.
The daily measure of contact satisfaction also allowed us
to focus on the link between goal progress and contact satisfaction, and whether sensitivity to variation in contact satisfaction is consistent or varies across individuals. We found
that individuals varied considerably in their sensitivity to
contact satisfaction. Therefore, the link between satisfying
social contact and variation in goal progress should not necessarily be generalized across individuals, even in a relatively homogenous sample. Instead, sensitivity to contact
satisfaction may itself be a meaningful outcome of interest
(Ram & Gerstorf, 2009).
384
MEJÍA AND HOOKER
Convoy Structure Moderates Convoy Function
In this study, we took a first step toward understanding the
source of between-person variation in older adults’ sensitivity to contact satisfaction by exploring differences in their
convoys’ composition of friend and family relationships and
marital status. We found that those with family-intensive
convoys were more sensitive to variation in contact satisfaction than those with friend-intensive convoys. Individual
variation in sensitivity to contact satisfaction is an important
avenue for future research. For example, relationship quality has been found to vary greatly within families across
generations (Birditt, Tighe, Fingerman, & Zarit, 2012);
however, variation in sensitivity to relationship quality
remains unexplored but may also vary considerably across
generations or within kin networks. By demonstrating that
convoy structure may influence convoy function, our work
extends an important body of research aimed at integrating
convoy function and structure (Birditt & Antonucci, 2007;
Fiori et al., 2006; Litwin & Shiovitz-Ezra, 2011).
Family relationships are both enduring and filled with
complex emotions (Fingerman et al., 2004), and when the
closest convoy members are kin, satisfying contact may
be necessary to work through ambivalent feelings and
circumstances (Lang et al., 2009), which may facilitate
becoming closer in the face of negative interactions (Fung,
Yeung, Li, & Lang, 2009). However, increased sensitivity
to contact satisfaction may also suggest a process by which
kin-intensive convoys may strain well-being (e.g., Birditt
et al., 2009; Fingerman et al., 2004; Litwin & ShiovitzEzra, 2011). In family intensive convoys, if progress
toward a social goal is especially sensitive to variation in
satisfaction with close family members, it may be more
difficult to expand the network to optimize social resources.
Longitudinal research is needed to tease out these processes
(Nesselroade, 1990; Ram & Gerstorf, 2009).
Those who were married or partnered were also more
sensitive to variation in contact satisfaction. In this study,
we considered partnered status as an aspect of convoy
structure (Litwin & Shiovitz-Ezra, 2011) and were therefore not able to tease out the nuances of how spouses may
coregulate their social goals (Hoppmann & Gerstorf, in
press). However, as a structural component of the social
convoy, marital status was associated with higher sensitivity to contact satisfaction above and beyond the proportion
of friends and family in the convoy. Spousal relationships
are unique compared with other relationships and also vary
in quality (Birditt & Antonucci, 2007). Therefore, our findings warrant further investigation into sensitivity to contact
satisfaction with spouses, and conditions under which this
sensitivity may vary.
Daily Measures of Relationship Quality
In this study, we found mean contact satisfaction over
the 100-day study to explain more variation in social goal
progress than a standard relationship quality measure. Our
findings suggest that a daily measure of relationship quality is complementary to a standard measure and provides
a distinct analytic lens. The standard relationship quality
measure taps into a global appraisal of close relationships.
Older adults are known to remember interpersonal events
more positively than their younger counterparts (Birditt &
Fingerman, 2003), and this positivity effect may be more
present in global measures of relationship quality. Daily
measures, on the other hand, access a more short-term
appraisal and provide insight to more proximate functional
processes within the social convoy, which were notable in
their day-to-day variability.
An important conceptual implication of this study is that
a single measurement of relationship quality may be indirectly linked to goal progress through daily experiences
of contact satisfaction. In this study, global perceptions of
relationship quality were associated but not synonymous
with experiences of contact satisfaction over a 100-day time
period (the variables share 12% of the variance). Therefore,
our findings suggest that the benefit of relationship quality
is contingent on the experience of satisfying social contact.
An important issue for future research is how global and
daily perceptions are related over extended timescales. For
example, low levels of contact satisfaction over an extended
timeframe may predict a decline in global perceptions of
relationship quality. Alternatively, global perceptions of
relationship quality may be a trait-like characteristic, which
although relatively stable, is shaped through relationship
processes (Hooker & McAdams, 2003).
Limitations and Future Directions
This study collected and examined rich data within a
sample of relatively healthy older adults over an extended
period of time. Nevertheless, because convoys patterns are
known to vary by socioeconomic status and race (Fiori
et al., 2008) and the meaning of relationships is known to
differ by social position (cf. Blieszner, 2006), the generalizabilty of our findings is constrained by our sample. We
also acknowledge that although these data were collected
on a daily basis, a causal direction between contact satisfaction and goal progress cannot be established.
The variability found in this relatively homogenous sample of older adults warrants further research into the extent
to which sensitivity to contact satisfaction varies across
characteristics of the situation and person both within and
between individuals. Beginning with variation between individuals, differences in contact sensitivity should be examined across cultures, socioeconomic status, and cohorts.
Based on this research and previous work (Antonucci,
Akiyama, & Takahashi, 2004; Antonucci et al., 2006), we
would predict that sensitivity would be higher among those
with more kin-intensive convoys. We also acknowledge that
the meaning of friendship and kinship roles varies across
SOCIAL CONVOY RELATIONSHIP PROCESSES
cultures. Although friend, family, and diverse convoy patterns have been identified across cultures (Fiori et al., 2006;
Litwin & Shiovitz-Ezra, 2006), sensitivity to variation in
relationship processes may vary across these contexts.
We also expect that sensitivity would vary within individuals over time. Similar to how exchange perspectives
appear to shift across the adult life span (Davey & Norris,
1998), sensitivity may vary across characteristics of the
individual, situation, and over time. Individuals may be
most sensitive at young and old ages, when support is
received more than it is given (Antonucci et al., 2004; Shaw
et al., 2007). Similarly, sensitivity may vary in response
to changes in the environment by decreasing when close
social partners are not available or increasing following a
transition. Longitudinal research with microlongitudinal
bursts would place sensitivity in the context of change over
time and distal outcomes (Ram & Gerstorf, 2009).
Conclusions
Well-being in older adulthood hinges on the ability to
maintain supportive and meaningful relationships (Fiori
et al., 2006; Lang et al., 1998; Walen & Lachman, 2000).
In this study, we demonstrate how the intensive measure
of relationship quality over 100 days provides a new lens
to deepen our understanding of close social partners’
engagement in older adults’ self-regulatory processes. We
showed that daily measures of contact satisfaction bring
focus to the link between contact satisfaction and goal
progress, which we found to vary across individuals, and
carry more explanatory power than a standard measure
of relationship quality. Older adults’ sensitivity to convoy
function may provide a new view into the social convoy. Not
only are convoys heterogeneous in terms of their function
and structure but also in the extent to which a convoy
function such as contact satisfaction is linked to an outcome
such as social goal progress. This work contributes to our
understanding of how convoy structure may influence its
function and sets the groundwork for further investigation
into sensitivity to contact satisfaction and its correlates.
Funding
This research was supported by a grant from the Center for Healthy
Aging Research at Oregon State University awarded to K. Hooker and by a
National Science Foundation Integrative Graduate Research and Education
Traineeship (IGERT) Grant (DGE 0956280). This research is based on the
first author’s master’s thesis submitted to Oregon State University.
Acknowledgments
The authors thank Ron Metoyer, Tuan Pham, and Soyoung Choun for
their help with the web-based data collection as well as the participants for
their effort and dedication during the 100-day study.
Correspondence
Correspondence should be addressed to Shannon T. Mejía, MS, Human
Development and Family Sciences, School of Social and Behavioral
Health Sciences, Oregon State University, 410 Waldo Hall, Corvallis, OR
97331-5102. E-mail: [email protected].
385
References
Antonucci, T. C. (1986). Measuring social support networks: Hierarchical
mapping technique. Generations: The Journal of the Western
Gerontological Society, 10, 10–12.
Antonucci, T. C., Akiyama, H., & Takahashi, K. (2004). Attachment
and close relationships across the life span. Attachment & Human
Development, 6, 353–370. doi:10.1080/1461673042000303136
Antonucci, T. C., Fiori, K. L., Birditt, K. S., & Jackey, L. M. H. (2010).
Convoys of social relations: Integrating life-span and life-course perspectives. In R. M. Lerner, M. E. Lamb, & A. M. Freund (Eds.), The
handbook of life-span development (Vol. 2, pp. 434–473). Hoboken,
NJ: Wiley.
Antonucci, T. C., Langfahl, E. S., & Akiyama, H. (2006). Relationships
as outcomes and contexts. In F. R. Lang & K. L. Fingerman (Eds.),
Growing together: Personal relationships across the lifespan (pp.
24–44). New York, NY: Cambridge University Press.
Birditt, K. S., & Antonucci, T. C. (2007). Relationship quality profiles and
well-being among married adults. Journal of Family Psychology, 21,
595–604. doi:10.1037/0893-3200.21.4.595
Birditt, K. S., & Fingerman, K. L. (2003). Age and gender differences in
adults’ descriptions of emotional reactions to interpersonal problems. The Journals of Gerontology, Series B: Psychological Sciences
and Social Sciences, 58, 237–245. doi:10.1093/geronb/58.4.P237
Birditt, K. S., Jackey, L. M., & Antonucci, T. C. (2009). Longitudinal patterns of negative relationship quality across adulthood. The Journals
of Gerontology, Series B: Psychological Sciences and Social
Sciences, 64B, 55–64. doi:10.1093/geronb/gbn031
Birditt, K. S., Tighe, L. A., Fingerman, K. L., & Zarit, S. H. (2012).
Intergenerational relationship quality across three generations. The
Journals of Gerontology, Series B: Psychological Sciences and
Social Sciences. doi:10.1093/geronb/gbs050
Blieszner, R. (2006). A lifetime of caring: Dimensions and dynamics
in late-life close relationships. Personal Relationships, 13, 1–18.
doi:10.1111/j.1475-6811.2006.00101.x
Bolger, N., & Zuckerman, A. (1995). A framework for studying personality
in the stress process. Journal of Personality and Social Psychology,
69, 890–902. doi:10.1037/0022-3514.69.5.890
Brose, A., & Ram, N. (2012). Within-person factor analysis: Modeling
how the individual fluctuates and changes across time. In M. R. Mehl
& T. S. Conner (Eds.), Handbook on research methods for studying
daily life (pp. 459–478). New York, NY: Guilford Press.
Carstensen, L. L., Isaacowitz, D. M., & Charles, S. T. (1999).
Taking time seriously: A theory of socioemotional selectivity. American Psychologist, 54, 165–181. doi:10.1146/annurev.
psych.093008.100448
Charles, S. T., & Carstensen, L. L. (2008). Unpleasant situations elicit different emotional responses in younger and older adults. Psychology
and Aging, 23, 495–504. doi:10.1037/a0013284
Connidis, I. A. (2010). Family ties & aging (2nd ed.). Thousand Oaks, CA:
Pine Forge Press.
Davey, A., & Norris, J. E. (1998). Social networks and exchange
norms across the adult life-span. Canadian Journal on Aging/La
Revue canadienne du vieillissement, 17, 212–233. doi:10.1017/
S0714980800009272
Fingerman, K. L., Hay, E. L., & Birditt, K. S. (2004). The best of ties,
the worst of ties: Close, problematic, and ambivalent social
relationships. Journal of Marriage and Family, 66, 792–808.
doi:10.1111/j.0022-2445.2004.00053.x
Fiori, K. L., Antonucci, T. C., & Cortina, K. S. (2006). Social network
typologies and mental health among older adults. The Journals of
Gerontology, Series B: Psychological Sciences and Social Sciences,
61, P25–P32.
Fiori, K. L., Consedine, N., & Magai, C. (2008). Ethnic differences
in patterns of social exchange among older adults: The role of
resource context. Aging and Society, 29, 495–324. doi:10.1017/
So144686X07006940
386
MEJÍA AND HOOKER
Fiori, K. L., Smith, J., & Antonucci, T. C. (2007). Social network types
among older adults: A multidimensional approach. The Journals of
Gerontology, Series B: Psychological Sciences and Social Sciences,
62, P322–P330.
Fung, H. H., Yeung, D. Y., Li, K.-K., & Lang, F. R. (2009). Benefits of
negative social exchanges for emotional closeness. The Journals of
Gerontology, Series B: Psychological Sciences and Social Sciences,
64B, 612–621. doi:10.1093/geronb/gbp065
Hooker, K., Hoppmann, C. A., & Siegler, I. (2010). Personality: Life span
compass for health. Annual Review of Gerontology and Geriatrics,
30, 210–232. doi:10.1891/0198-8794.30.199
Hooker, K., & McAdams, D. (2003). Personality reconsidered: A new
agenda for aging research. The Journals of Gerontology, Series
B: Psychological Sciences and Social Sciences, 58, 296–304.
doi:10.1093/geronb/58.6.P296
Hooker, K., Mejía, S., Pham, T., Metoyer, R., & Ram, N. (2012). Burst
vs. daily measurement: Issues in capturing intraindividual variability.
Gerontologist, 52(suppl 1), 359.
Hoppmann, C., & Gerstorf, D. (2013). Spousal goals, affect quality, and
collaborative problem solving: Evidence from a time-sampling
study with older couples. Research in Human Development 10
(Special Issue on Intraindividual Variability), 70–87. doi:10.1080/
15427609.2013.760260
Kahn, R. L., & Antonucci, T. C. (1980). Convoys over the life course:
Attachment, roles, and social support. In P. Baltes & O. Brim (Eds.),
Life-span development and behavior (Vol. 3, pp. 254–286). New
York, NY: Academic Press.
Lang, F. R., Staudinger, U. M., & Carstensen, L. L. (1998). Perspectives
on socioemotional selectivity in late life: How personality and
social context do (and do not) make a difference. The Journals of
Gerontology, Series B: Psychological Sciences and Social Sciences,
53B, 21–30. doi:10.1093/geronb/53B.1.P21
Lang, F. R., Wagner, J., & Neyer, F. J. (2009). Interpersonal functioning
across the lifespan: Two principles of relationship regulation. Advances
in Life Course Research, 14, 40–51. doi:10.1016/j.alcr.2009.03.004
Litwin, H. (2001). Social network type and morale in old age. The
Gerontologist, 41, 516–524. doi:10.1093/geront/46.6.735
Litwin, H., & Shiovitz-Ezra, S. (2006). Network type and mortality risk in
later life. The Gerontologist, 46, 735–743. doi:10.1093/geront/46.6.735
Litwin, H., & Shiovitz-Ezra, S. (2011). Social network type and subjective well-being in a national sample of older Americans. The
Gerontologist, 51, 379–388. doi:10.1093/geront/gnq094
Mejía, S., & Hooker, K. (in press). Social regulatory processes in later life:
A web-based microlongitudinal study. Psychology and Aging.
Nesselroade, J. R. (1990). Adult personality development: Issues in assessing constancy and change. In A. Rabin, R. A. Zucker, R. A. Emmons,
& S. Frank (Eds.), Studying persons and lives (pp. 41–85). New
York, NY: Springer.
Rafaeli, E., Cranford, J., Green, A., Shrout, P., & Bolger, N. (2008). The
good and bad of relationships: How social hindrance and social support affect relationship feelings in daily life. Personality and Social
Psychology Bulletin, 34, 1703–1718. doi:10.1177/0146167208323742
Ram, N., & Gerstorf, D. (2009). Time-structured and net intraindividual
variability: Tools for examining the development of dynamic characteristics and processes. Psychology and Aging, 24, 778–791.
doi:10.1037/a0017915
Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models (2nd
ed.). Newbury Park, CA: Sage.
Rook, K. S. (1987). Reciprocity of social exchange and social satisfaction
among older women. Journal of Personality and Social Psychology,
52, 145–154. doi:10.1037/0022-3514.52.1.145
Rook, K. S., Mavandadi, S., Sorkin, D. H., & Zettel, L. A. (2007).
Optimizing social relationships as a resource for health and wellbeing in later life. In C. M. Aldwin, C. L. Park, & A. Spiro (Eds.),
Handbook of health psychology and aging (pp. 267–285). New York,
NY: Guilford.
Shaw, B. A., Krause, N., Liang, J., & Bennett, J. (2007). Tracking
changes in social relations throughout late life. The Journals of
Gerontology, Series B: Psychological Sciences and Social Sciences,
62, S90–S99.
Vaux, A., Phillips, J., Holly, L., Thomson, B., Williams, D., & Stewart, D.
(1986). The social support appraisals (SS-A) scale: Studies of reliability and validity. American Journal of Community Psychology, 14,
195–218. doi:10.1007/BF00911821
Walen, H. R., & Lachman, M. E. (2000). Social support and strain from
partner, family, and friends: Costs and benefits for men and women
in adulthood. Journal of Social and Personal Relationships, 17, 5–
30. doi:10.1177/0265407500171001