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UNIVERSITY OF CALIFORNIA RIVERSIDE

The Measurement and Health Outcomes of Social Support

A Dissertation submitted in partial satisfaction of the requirements for the degree of

Doctor of Philosophy

in

Psychology

by

Keiko Anne Taga

December 2006

Dissertation Committee:Dr. Howard S. Friedman, ChairpersonDr. Daniel J. OzerDr. Chandra A. Reynolds

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The Dissertation o f Keiko Anne Taga is approved:

CommitteerChairperson

University of California, Riverside


ACKNOWLEDGEMENTS

This research was supported in part by a research grant from the National Institute

on Aging (#AG08825, Howard S. Friedman, Principal Investigator), and by a

Dissertation Grant from the University of California, Riverside.

I would like to express my deep appreciation for my dissertation committee chair,

Dr. Howard S. Friedman, for his guidance and mentorship throughout graduate school. I

would also like to thank Drs. Chandra A. Reynolds and Daniel J. Ozer, the other

members of my dissertation committee, for lending me their time, expertise, and patience.

Thanks are also due to Dr. Leslie R. Martin, for the limitless energy with which she

taught me about so many aspects of the research process. I also feel deep gratitude

toward the late Dr. John H. Ashe, for his confidence in my abilities and role as my

“comer man.”

My sources of social support were extremely helpful throughout my graduate

school experience; I would especially like to thank Seth A. Wagerman, AnnJudel C.

Enriquez, Melissa L. DiLorenzo, Desiree M. Despues, Patrick J. LaShell, and Deane H.

Zahn for their friendship and humor.

It is difficult to express the extent to which I feel grateful to my family, including

the Japanese branch and my newly acquired family, for their unconditional love, support,

and friendship.

iv


DEDICATION

This dissertation is dedicated to my husband, Mark P. Brynildsen, for his love,

patience, commitment, support, and humor.

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ABSTRACT OF THE DISSERTATION

The Measurement and Health Outcomes of Social Support

by

Keiko Anne Taga

Doctor of Philosophy, Graduate Program in Psychology University of California, Riverside, December 2006

Dr. Howard S. Friedman, Chairperson

An existing difficulty in interpreting the vast literature on social support and

health is the inconsistency in the measurement and conceptualization of social support.

The purpose of the present study was first to establish the primary factors of social

support that are measured by frequently-used social support scales, and second to

examine the relation between each of the resulting factors of social support with mortality

risk. A contemporary sample of 265 adults was recruited to complete six selected

measures of social support, which were subsequently subjected to a confirmatory factor

analysis to identify the aspects of social support measured by these often-used scales. To

establish the validity of a set of similar items in the archival Terman Life-Cycle Study

data set as representing these factors, comparisons were made between these participants’

responses to the items in these scales to their responses to items identified in the archival

data set as representing similar constructs. Finally, the resulting factors of social support

were used to predict mortality risk in the archival data set. The results of the

confirmatory factor analysis showed that the main factors of social support included in

contemporary scales are social network size, perceived available support, satisfaction

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with support, providing support to others, and negative interactions. The results of the

validity testing determined that three of these factors (social network size, perceived

available support, and providing support) are adequately measured by items in the

archival data set. The results of the analysis using the three factors of social support to

predict mortality risk demonstrated that a larger social network size is independently

associated with a decreased mortality risk, whereas when social network size and

perceived availability of support are controlled, giving support to others is positively

associated with longevity. The results of this study provide a clearer understanding of

what specific aspects of social support are measured in contemporary scales of social

support, and how each aspect of social support is associated with health outcomes.

Future researchers can use this model of social support to investigate further relations

between social support and health.

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TABLE OF CONTENTS

Page

LIST OF TABLES.............................................................................................................. x

LIST OF FIGURES.......................................................................................................... xii

INTRODUCTION...............................................................................................................1

Social Ties............................................................................................................... 2

Perceived Available Support................................................................................... 3

Satisfaction with Support........................................................................................ 5

Providing Social Support........................................................................................ 6

Negative Social Relationships................................................................................ 7

Measurement of Social Ties/Social Support........................................................... 8

THE PRESENT STUDY...................................................................................................10

Validity of Scales Constructed from Archival Data...............................................10

Hypotheses............................................................................................................ 13

METHOD..........................................................................................................................14

Contemporary Participants.....................................................................................14

Archival Participants..............................................................................................15

Measures................................................................................................................16

Procedures..............................................................................................................19

Analysis................................................................................................................. 20

RESULTS......................................................................................................................... 26

Confirmatory Factor Analysis of Contemporary Social Support Scales............... 26


Measurement Invariance....................................................................................... 26

Correlational Analysis.......................................................................................... 28

Rational Analysis.................................................................................................. 29

Mortality Risk....................................................................................................... 30

DISCUSSION................................................................................................................... 32

Summary of Findings............................................................................................ 32

Limitations............................................................................................................ 37

Implications............................................................................................................38

REFERENCES................................................................................................................. 40

ix


LIST OF TABLES

Table Page

1. Items Assessing Social Support in Archival Data Set, 1977 and 1986.................. 47

2. Means and Standard Deviations of Judges’ Ratings of Items’ Fit with Social

Networks Category............................................................................................... 48

3. Means and Standard Deviations of Judges’ Ratings of Items’ Fit with Perceived

Available Support Category.................................................................................. 50

4. Means and Standard Deviations of Judges’ Ratings of Items’ Fit with Satisfaction

with Support Category.......................................................................................... 52

5. Means and Standard Deviations of Judges’ Ratings of Items’ Fit with Providing

Support Category.................................................................................................. 54

6. Means and Standard Deviations of Judges’ Ratings of Items’ Fit with Negative

Interactions Category............................................................................................ 56

7. Factor Loadings of Items within Social Network Category...................................58

8. Factor Loadings of Items within Perceived Available Support Category..............59

9. Factor Loadings of Items within Satisfaction with Support Category....................60

10. Factor Loadings of Items within Negative Interactions Category..........................61

11. Items in Multidimensional Parcels Representing Social Networks.......................62

12. Items in Multidimensional Parcels Representing Perceived Available

Support.................................................................................................................. 63

13. Items in Multidimensional Parcels Representing Satisfaction with Support 64

14. Items in Multidimensional Parcels Representing Providing Support....................65

x


15. Items in Multidimensional Parcels Representing Negative Interactions.............. 66

16. Model-Fitting Results for Contemporary Social Support Items in Contemporary

Sample................................................................................................................... 67

17. Model-Fitting Results for Archival Social Support Items in Archival Sample....68

18. Model-Fitting Results for Archival Social Support Items in Contemporary

Sample................................................................................................................... 69

19. Model-Fitting Results for Establishing Measurement Invariance..........................70

20. Correlations among Archival and Contemporary Social Support Items within

Contemporary Sample.......................................................................................... 71

21. Correlations among Archival and Contemporary Social Support Items within

Contemporary Sample, Adjusting for Reliability................................................. 72

22. Means of Judges’ Ratings of Items in Archival Factors’ Fit with Factors Resulting

from Factor Analysis of Contemporary Social Support Items.............................. 73

23. Proportional Hazards Regressions Predicting Mortality Risk as of 2005 from

Factors of Social Support...................................................................................... 74

24. Simultaneous Proportional Hazards Regressions Predicting Mortality Risk as of

2005 from Factors of Social Support.................................................................... 75

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LIST OF FIGURES

Figure Page

1. Hypothesized Model of Social Support...................................................................76

2. Model Estimates for the Final 5-Factor Model of Items from Contemporary Social

Support Scales in Contemporary Sample................................................................ 77

3. Model Estimates for 4-Factor Model of Archival Items in Archival Sample..........78

xii


INTRODUCTION

An important aim in the field of health psychology is to identify psychological

and social predictors of health and longevity. The nature of the association between

social relationships and health is of particular interest given that relationships can clearly

have a substantial impact on individuals’ lives. In recent decades, a common finding in

health psychology is that there is a substantial link between social relations and health.

Generally, social integration (non-isolation), satisfying personal relationships, and a

relative absence of conflict point to positive psychological and physical health outcomes.

However, the literature on the relation between social support and social ties and health is

not entirely consistent. For example, although some studies find a strong positive

association between social networks and later health (e.g., Berkman & Syme, 1979;

House, Robbins, & Metzner, 1982), others find no effect of social networks (e.g.,

Schaefer, Coyne, & Lazarus, 1981), and social relations have even been associated with

negative psychological outcomes (e.g., Schaefer et al., 1981).

Part of the reason for this apparent inconsistency may be the ambiguity in the

conceptualization of social support (e.g., Glass, Mendes de Leon, Seeman, & Berkman,

1997; McNally & Newman, 1999; Schaefer et al., 1981; Veiel & Baumann, 1992), as

well as the variety of instruments used to measure social support (e.g., Sarason, Shearin,

Pierce, & Sarason, 1987). It is estimated that hundreds of different measures of social

support and social ties have been used in published studies, making it difficult to compare

results across studies (Bowling & Grundy, 1998). Therefore, when investigating the

1


relation between social support and health, it is important to make distinctions among the

various aspects of social support that are being measured (e.g., social integration,

perceived support, satisfaction with support; Sarason & Sarason, 1994). After the various

factors of social support are clarified, a better understanding of each factor’s individual

relation with health can be reached. That is, it is particularly important to understand

how social networks (or social isolation), perceived support, satisfaction with support,

conflict, and providing support (to others) individually relate to health; it is possible that

different aspects of social support have different types of associations with health. The

information gained from answers to these questions will contribute to the scientific study

of social support and physical health through a much more refined understanding of what

constitutes social support and its association with health.

Social Ties

Social integration, social ties, social networks, and social isolation generally refer

to the number of social connections an individual possesses (or lacks) (Seeman, 1996).

The health risks associated with having small social networks were demonstrated in a

landmark study of older adult residents of Alameda County, California (Berkman &

Syme, 1979). Specifically, lacking social contacts such as marriage, close friends and

relatives, informal and formal groups, and church membership predicted increased

mortality risk 17 years later (controlling for baseline self-reported health). This

correlation has been confirmed in many other studies (e.g., Eng, Rimm, Fitzmaurice, &

Kawachi, 2002; Rutledge, Matthews, Lui, Stone, & Cauley, 2003), including those

conducted in other countries such as France (Berkman, Melchior, Chastang, Niedhammer,

2


Leclerc, & Goldberg, 2004), Israel (Walter-Ginzburg, Blumstein, Chetrit, & Modan,

2002), and Japan (Iwasaki et al., 2002; Murata et al., 2005). Other studies replicating this

association between social ties and mortality risk also identified men as more vulnerable

to poor outcomes of social isolation (House, Robbins, & Metzner, 1982). Further, having

more social ties is associated with higher resistance to infection (Cohen, Doyle, Skoner,

Rabin, & Gwaltney, 1997). However, there is some indication that social networks are

not universally associated with better health outcomes; it has been shown that social

network size is unrelated to self-reported health (Schaefer et al., 1981). Although larger

social networks may have an impact on health by allowing for greater opportunity for

benefits of social support such as reduction in stress responses, decrease in negative

mood states, and improvement of health behaviors (Uchino, Uno, & Holt-Lunstad, 1999),

there is likely a psychological cost associated with large social networks. Large networks

involve a greater likelihood of conflict and burden than small networks (e.g., Antonucci,

Akiyama, & Lansford, 1998; Burg & Seeman, 1994).

Perceived Available Support

Perceived support is a subjective indicator of the amount of support appraised to

be available by the individual as well as satisfaction with the availability of support

(Schaefer et al., 1981; Wethington & Kessler, 1986). It has been suggested that

perceived support may be an important determinant of psychological and physical health

outcomes due to this subjective quality (Grundy, Bowling, & Farquhar, 1996; Schaefer et

al., 1981). Indeed, perceived support has been associated with psychological outcomes

such as positive self-perceptions (Sarason, Pierce, Shearin, Sarason, Waltz, & Poppe,

3


1991), fewer depressive symptoms (Comman, Goldman, Glei, Weinstein, & Chang, 2003;

DuPertuis, Aldwin, & Bosse, 2001; Krause, Liang, & Yatomi, 1989; Schaefer et al.,

1981), and lower levels of stress (Sarason & Sarason, 1994) and distress (Wethington &

Kessler, 1986) and physical outcomes such as higher self-rated health (Krause, 1987) and

lower mortality risk (Brummett et al., 2005; Krause, 1997). However, in addition to this

evidence of positive outcomes of perceived support, some studies show no relation

between perceived support and physical health (Comman et al., 2003; Sherboume &

Hays, 1990) or mortality (e.g., House, Robbins, & Metzner, 1982). A common

explanation for the generally positive outcomes of perceived support involves the stress-

buffering mechanism of perceived support; when individuals encounter potentially

stressful situations, the perception that support is available is thought to mitigate the

stress response (Cohen & Wills, 1985).

Perceived support is often considered as an individual difference variable rather

than a characteristic of the environment; unlike other conceptions of support such as

social network size, the perception of available support may be a stable, internal

characteristic (Lakey & Cassady, 1990; Sarason, Sarason, & Gurung, 1997). That is,

perceptions of social support may be stable sets of beliefs a person holds instead of an

assessment of the qualities of present relationships. In fact, perceived support is

correlated with self-esteem and attitudes, providing evidence for this perspective (Lakey

& Cassady, 1990). Early experiences with support from others (e.g., family) may

influence the development of schema for social relationships and attachment, which

persist into adulthood (Sarason et al., 1997). For example, individuals who experienced

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secure relationships with their parents as children might perceive future relationships as

secure as well, independent of their objective qualities. It also seems likely that

perceptions of support may be influenced (directly or indirectly) by genetics; a twin study

showed that for identical twin pairs, perceived support was more highly correlated than

for pairs of fraternal twins (Bergeman, Plomin, Pedersen, McCleam, & Nesselroade,

1990), whereas environmental influences alone explained similarity for objective social

support.

Satisfaction with Support

In contrast to other conceptualizations of support, another perspective is that

individuals’ satisfaction with support perceived or received is more important than more

objective characteristics of the support. Much like the arguments for the importance of

perceived support, satisfaction with support is thought to be essential in predicting health

outcomes, as it captures both positive and negative subjective aspects of social relations

(Krause, 1995; Krause et al., 1989). For example, questions assessing satisfaction with

social support also measure dissatisfaction; negative aspects of social relations may

indicate satisfaction with these relations more so than do positive aspects (Krause, 1995).

It appears that satisfaction with support is an important determinant of health-related

outcomes; higher levels of satisfaction are predictive of lower levels of depressive

symptoms (Antonucci, Fuhrer, & Dartigues, 1997; Krause et al., 1989) and better self-

rated health (Krause, 1987) and health-related quality of life (Doeglas et al., 1996).

These associations between satisfaction with support and better mental and physical

health can be explained by the feelings of “contentment and security” (Krause, 1987, p.

5


301) resulting from this satisfaction; this aspect distinguishes satisfaction with support

from more objective indicators of support such as social network size or received support.

Satisfaction with support may be a stronger predictor of health-related outcomes than

more objective indicators because it encompasses individual differences in need for

support; different individuals who experience the same amount and quality of support

may diverge in their levels of satisfaction with this support due to their unique needs

(Krause, 1987). Whereas the use of objective indicators does not allow consideration of

differences in needs and preferences for support, satisfaction with support captures these

differences nicely (Krause, 1987).

Providing Social Support

Although most findings relevant to social support and health focus on individuals’

social ties or factors related to the receipt of support, recent research indicates that

providing social support to others may result in health benefits. Providing social support

has shown to be more strongly related to increased longevity than receiving support (S. L.

Brown, Nesse, Vinokur, & Smith, 2003; W. M. Brown, Consedine, & Magai, 2005), and

is also predictive of decreased distress (Liang, Krause, & Bennett, 2001). This apparent

benefit may be due to the positive emotions that result from helping others; giving

support is related to heightened feelings of personal control (Krause, Herzog, & Baker,

1992) and self-esteem (Liang et al., 2001). Yet, giving support can also lead to negative

interactions, in that feelings of resentment may result from giving more support than is

reasonable (Liang et al., 2001). Further, providing too much support (e.g., as a caregiver)

can have consequences that are quite detrimental (i.e., caregiver stress; e.g., Patterson &

6


Grant, 2003). An alternative explanation to the importance of positive (and negative)

emotions resulting from providing support in psychological and health outcomes is that

perhaps individuals who give support are those who have adequate resources to do so.

These resources may both allow the individuals to give to others and contribute to their

own health. The evolutionary perspective has also been used as a basis for the apparent

health benefits of providing social support to others, in that reciprocal altruism is thought

to increase the likelihood of survival (W. M. Brown et al., 2005). Thus, providing social

support may be at least partially responsible for the benefits of social contact (S. L.

Brown et al., 2003).

Negative Social Relationships

Despite evidence for the psychological and physical benefits of social support,

there are also hints that social relations can yield some negative consequences. In fact, it

is argued that the negative aspects of social relations have a more powerful impact on

well-being than the positive aspects (Rook, 1984). Specifically, receiving social support

can lead to feelings of dependency and diminished self-respect (Grundy, Bowling, &

Farquhar, 1996). Further, the receipt of social support may represent the failure of an

individual’s own coping mechanisms (Wethington & Kessler, 1986). However,

associations found between received support and psychological distress (e.g., Bolger,

Zuckerman, & Kessler, 2000) may be explained by the increased need for support during

stressful times rather than a causal relation between received support and distress.

Conflict is another significant aspect of social relations that can have negative

outcomes. For example, relationship conflict is associated with psychological

7


consequences such as increases in psychological distress and decreases in well-being

(Antonucci et al., 1998; Newsom, Rook, Nishishiba, Sorkin, & Mahan, 2005; Rook, 1984)

and increases in negative affect (Ingersoll-Dayton, Morgan, & Antonucci, 1997), as well

as physical health-related outcomes such as increased susceptibility to infection (Cohen,

Frank, Doyle, Skoner, Rabin, & Gwaltney, 1998). Thus, it is important to note that

outcomes of social relationships are not restricted to benefits such as decreases in stress

and mortality risk; costs such as decreases in well-being and disease resistance are also

apparent.

Measurement o f Social Ties/Social Support

One problem encountered in the study of social relationships is the lack of

consistency in the measurement of social support and social ties. Many investigators

have noted the absence of clarity in the operationalization and measurement of social

support (Glass, Mendes de Leon, Seeman, & Berkman, 1997; Heitzmann & Kaplan, 1988;

Sarason, Sarason, & Gurung, 1997; Sarason et al., 1987; Schaefer et al., 1981), and some

have attempted to address this problem by differentiating among the outcomes of

different aspects of social support (Cohen, 2004; Schaefer et al., 1981), examining the

relations among social support measures (Sarason et al., 1987), and conducting a factor

analysis of various indicators of social networks (Glass et al., 1997). Cohen’s (2004)

research indicates that perceived social support and social integration lead to clearly

different health outcomes; perceived social support tends to act as a buffer in the face of

stress, whereas social integration is generally helpful during both stressful and non

stressful times. Perceived social support and social integration were also differentiated

8


by Schaefer, Coyne, and Lazarus (1981); perceived social support was more strongly

related to depression than was social integration. An examination of the interrelations

among various measures of social support indicated that received social support is

relatively unrelated to social network size (Sarason et al., 1987). Of particular interest to

the present study is the result of a factor analysis of social network items, which showed

that ties with four types of contacts comprise social networks: children, relatives, friends,

and a confidant (Glass et al., 1997). Despite these efforts, more work is needed to

determine the common components of social networks and social support measured by

the various scales that exist, and to compare the relative predictive values of each of the

resulting components of social support. The identification of these factors and their

relations with mortality are the first and second foci of the proposed study.

9


THE PRESENT STUDY

In an effort to determine the main factors of social support, the first aim of the

present study is to clarify the main components measured by six social support scales that

have been identified as widely-used and theoretically relevant. This clarification will be

approached through confirmatory factor analysis (CFA).

A subsequent step in uncovering each social support factor’s individual relation

with longevity would be to recruit a study sample, assess their levels of the main factors

of social support, and follow them over time to determine how long they live; however,

time constraints prevent the execution of such a study. Therefore, an alternative is to

access a longitudinal data set with information on both the participants’ levels of these

social support factors and their age at death. This alternative will be undertaken using

data from the archival longitudinal Terman Life-Cycle Study to determine the

associations between each resulting social support factor and longevity. Participants in

the Terman Life-Cycle Study (formerly called the Gifted Children Study) were originally

recruited for a study of gifted children; since the start of the study in 1921, they have

been providing psychological and social data every 4-12 years until their deaths (83% are

now dead). Thus, this rich source of life-span data is an ideal data set with which to

investigate relations between various aspects of social support and longevity.

Validity o f Scales Constructed from Archival Data

One issue, however, that must first be addressed is the consonance of the items

used in the factor analysis with a contemporary sample with those in the archival data set

10


(Martin & Friedman, 2000). A method must be implemented to ensure that each set of

archival items used to create these social support factors measures the same construct as

the items in the factors of the contemporary social support scales. To examine the

validity of the archival scales, a useful strategy is to assess measurement invariance of the

two sets of items, that is, to verify that participants respond to the contemporary and

archival items in the same way (Reise, Widaman, & Pugh, 1993), Measurement

invariance can be established by comparing the factor structure of the two sets of items;

equivalent factor structures indicate measurement invariance (de Frias & Dixon, 2005).

This method of assessing measurement variance is common among researchers seeking

to establish that an assessment device operates equivalently in different populations. For

example, Australian researchers used this technique to demonstrate that the General

Health Questionnaire measures equivalent constructs in both adults and adolescents

(French & Tait, 2004). Additionally, Facteau and Craig (2001) verified that a

performance appraisal rating system was invariant across different groups of raters by

comparing the factor structure of the instrument across groups. This technique has also

been used with the data set used in the present study: Martin (1996) established

measurement invariance of the responses to items in the Revised NEO Personality

Inventory (NEO PI-R; Costa & McCrae, 1992) among a sample of contemporary

participants and the personality items rated by archival participants. Using a comparison

of factor structures of a measure to establish measurement invariance is also particularly

useful to cross-cultural researchers seeking to use a measure in different cultures. Robie

and Ryan (1996), for example, determined with this method that a measure of cross-

11


cultural adjustment functions equivalently among international students in the United

States and American workers in Taiwan and Belgium. Likewise, the measurement

invariance of the Multicultural Personality Questionnaire was determined by the

equivalence of factor structures in Italian and Dutch samples (Leone, Van der Zee, van

Oudenhoven, Perugini, & Ercolani, 2005). In the present study, the factor structures of

the responses to the archival social support items by the archival and contemporary

participants will be compared to assess measurement invariance.

After measurement invariance has been established, rational analysis, a process in

which judges blind to the researcher’s predictions rate each item’s fit (McCrae, Costa, &

Piedmont, 1993) with the key factors of social support, was employed. McCrae, Costa,

and Piedmont (1993) used this process by asking judges to interpret each of the items and

make a determination about their representativeness of a category. In that case, judges

rated how well each item in the California Psychological Inventory (CPI) represented

each of the personality factors in the five-factor model as part of a comparison between

the CPI scales and the five-factor model. In the present study, the archival social support

items were compared to the social support factors resulting from the factor analysis. This

will involved using several trained judges (psychology graduate students) to rate the

correspondence of each of the archival items with the scales resulting from the factor

analysis with contemporary social support scales. Finally, correlations between the social

support factors resulting from the factor analysis and the relevant items in the Terman

data set were used to indicate the strength of their relations. This method follows that

developed by Martin (1996) to validate that items in the Terman data set represent the

12


Big Five personality factors. After it was verified that the items drawn from the Terman

data set represent these key aspects of social support, the second aim of the study can be

addressed; the resulting factors can be used to predict mortality in the Terman data set.

Hypotheses

With regard to the first aim of the study (factor analysis of social support scales),

it is predicted that the factors that emerge will replicate or be informative about the

following scheme: 1) social network size, 2) perceived available support, 3) satisfaction

with support, 4) providing support to others, and 5) negative interactions (see Figure 1).

Second, it is predicted that measurement invariance will be established for these factors

of social support.

Third, in terms of associations between the social support factors and mortality

risk, social network size and giving support to others are predicted to be independently

associated with lower mortality risk, whereas perceived available support and satisfaction

with support are predicted to be unassociated with mortality risk. We will not consider

negative interactions as a predictor of mortality because only one item exists in the

relevant years in the Terman data set related to negative interactions (i.e., indifferent or

hostile relations with family. In using these different factors to predict mortality, it is

possible to compare different aspects of social ties to determine which aspects are health-

beneficial, and which have no relation with health or are harmful.

13


METHOD

Contemporary participants

The participants in the first part of the study (CFA of social support scales and

validation of archival scales) were 265 adults (177 female, 87 male, 1 declined to indicate)

over the age of 35. These older adult participants were recruited via the University of

California, Riverside Psychology Department participant pool; these participant pool

recruits provided the names and addresses of parents and other relatives to whom surveys

containing the six contemporary social support measures and the archival social support

items were mailed. Of the 762 surveys distributed, 276 were returned, yielding a

response rate of 36%. The adult sample ranges in age from 36 to 81 years, with a mean

age of 50.13 years. Various ethnicities are represented; the sample consists of 104

Caucasian, 65 Asian/Pacific Islander, 51 Hispanic/Latino, 19 African American/Black,

11 Southeast Asian, 4 Middle Eastern, 4 biracial, and 5 participants who identified

themselves as “other” (2 participants declined to indicate their ethnicity). Despite

instructions to the participant pool students to provide names and addresses of relatives

who were at least 35 years old, 11 surveys returned were unusable due to their inability to

meet this age criterion. Participants were further eliminated from analyses on the basis of

their non-responses to items. Thirty-six participants failed to provide enough information

on certain items for complete data to be generated, resulting in a final sample size of 229

participants.

14


Archival participants

To establish measurement invariance, the factor structures of items drawn from

the archival data set thought to represent various facets of social support were compared

in the contemporary and archival samples. The participants in the archival sample, in

which the resulting social support factors were used to predict longevity, were from the

Terman Life-Cycle study data set. Initiated in 1921, the Terman Life-Cycle Study

(formerly the Gifted Children Study) included 1,528 school-age children (856 men and

672 women, average year of birth was 1910; Terman & Oden, 1947) who were followed

at 5-10 year intervals throughout their lives. The participants were recruited on the basis

of their intelligence (IQ > 135); Terman’s original aim was to study gifted children. The

data have been refined and updated by Friedman and colleagues (1995), culminating in

the collection of death certificates of the participants through 2005. Although the sample

is fairly homogeneous with respect to ethnicity (White), social class (middle class), and

intelligence (Terman, 1925), the psychological, social, and behavioral variables have

considerable variability.

Consistent with previous studies of psychosocial predictors of longevity using the

Terman data set (e.g., Friedman et al., 1993), participants who were not of school age at

the start of the study in 1921 (i.e., were not bom between 1904 and 1915, inclusive; N =

155) were not included in analyses. Furthermore, participants who died or were lost to

follow-up before 1940 (N = 77) were excluded from all analyses. Two hundred sixty-

seven of the remaining 1296 participants died by 1977, leaving 1029 participants. Of

these, the number of participants who responded to questions regarding their social

15


relationships in 1977 ranged from 616 (379 men, 237 women) to 726 (379 men, 347

women). Two hundred thirty-three participants died between 1977 and 1986. In 1986,

questions were again posed regarding various aspects of the participants’ social

relationships; the number of respondents to these questions ranged from 347 (193 men,

154 women) to 630 (327 men, 303 women). Because the response rate to eight of the

archival items under initial consideration was relatively low, these items were not used.

Complete data were available or able to be generated via a prorating method (described

below) for 437 participants in the archival sample.

Measures

Social Network Index (SNI; Berkman & Syme, 1977). The SNI uses 10 multiple-

choice items to assess the number of respondents’ social ties (e.g., “How many close

friends do you have?”). The sources of social contact included are marriage, close

friends and relatives, church membership, and informal and formal group associations.

Six-item short form o f the Social Support Questionnaire (SSQ6; Sarason et al.,

1983). The SSQ6 measures the number of respondents’ perceived available supports, the

number of perceived available family supports, and satisfaction with perceived available

support (6 items; e.g., “Whom can you really count on to distract you from your worries

when you feel under stress?”). In each item, the participants indicate how many people

provide them with a type of support, then rate their level of satisfaction with that support

on a 6-point Likert scale (1 = very dissatisfied to 6 = very satisfied). The original SSQ

items were derived from a factor analysis of a larger group of items measuring social

16


support. Validity and reliability testing have been conducted with the SSQ6, showing

high correspondence with the original SSQ as well as high internal reliability.

Items measuring the provision o f instrumental support to others (Brown et al.,

2003). Four dichotomous (yes/no) items were developed by Brown et al. (2003) to assess

whether or not the respondents have given instrumental support to friends, neighbors, and

relatives in the past 12 months. The specific types of instrumental support include help

with transportation, housework, child care, and other tasks (e.g., “In the past 12 months,

have you helped friends, neighbors, or relatives other than a spouse with child care?”).

National Health Interview Survey, 1985-1989 (Chyba & Washington, 1993). Five

items regarding social relationships were selected from Section KK (height, weight,

relationships, and social activities) of the larger National Health Interview Survey

conducted by the U.S. Department of Health and Human Services. These open-ended

questions assess the perceived availability of support and participation in social activities

(e.g., “How many relatives do you have that you can talk to about private matters or can

call on for help?”).

Lubben Social Network Scale (LSNS; Lubben, 1988). This scale was developed

to measure the social networks of elderly individuals. Items are based on the SNI

(Berkman & Syme, 1977), but were adapted to address the networks of older individuals,

who vary less in their participation in organizations and marital status than younger

individuals. Ten multiple-choice items inquire about family networks, friends networks,

confidant relationships, and helping others (e.g., “How many relatives do you see or hear

17


from at least once a month?”). High intercorrelations among the items signify the

reliability of the scale.

Social support items in the MacArthur Studies o f Successful Aging questionnaire

(Gurung, Taylor, & Seeman, 2003). Researchers involved in the MacArthur Studies of

Successful Aging developed 17 multiple-choice items to measure participants’ frequency

of receiving instrumental and emotional social support as well as conflict and excessive

demands in relationships with their spouse, children, friends, and other family (e.g.,

“How often are your children critical?”).

Archival measures o f social relationships

The 1977 questionnaire completed by participants in the Terman Life-Cycle

Study (mean age of the full sample 67 years) included 8 items related to the availability

of and satisfaction with social support. These items address the participants’ frequency

of visiting and communicating with relatives, informal visiting with friends and

neighbors, entertaining, helping friends or neighbors, doing community service with a

group, doing community service at home, and their satisfaction with friendships and

social contacts. In the 1986 questionnaire, 14 questions addressed various aspects of

social relations and activities, including the participants’ number of intimate and

companionate relationships with friends and intimate, companionate, and casual

relationships with family and close relatives; satisfaction with the amount of intimacy and

companionship in relationships with friends and family; and frequency of meetings with

social groups, informal visiting with friends, neighbors, and children, community service

18


with organizations, and helping others (Table 1 shows the archival social support items).

All of the responses to these items were self-reported.

Procedures

First, students in the participant pool read and signed an informed consent

statement and completed a survey with the six social support questionnaires and the

social support items from the archival data set in our laboratory (completion time ranged

from 15 to 45 minutes; all participants received course credit for their participation).

Next, trained research assistants explained to the participants the importance to the study

of also having other participants over the age of 35, and those participants who agreed to

provide their parents’ or other relatives’ mailing address were asked to sign a card to their

parents and address a mailing envelope to their parents (or other relatives). All

participants were debriefed before leaving the laboratory. We then mailed the relatives a

packet containing an informed consent statement, the social support survey containing the

SNI (Berkman & Syme, 1977), the SSQ6 (Sarason et al., 1983), four items measuring the

provision of instrumental support to others (Brown et al., 2003), five items from the

National Health Interview Survey, 1985-1989 (Chyba & Washington, 1993), the LSNS

(Lubben, 1988), 17 social support items in the MacArthur Studies of Successful Aging

questionnaire (Gurung, Taylor, & Seeman, 2003), and the archival items; a debriefing

statement, a letter requesting their consent to participate; the card signed by the student

who provided their address; a self-addressed, stamped envelope; and a pen as a token of

appreciation.

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Analysis

Factor analysis o f contemporary scales. The first set of analyses was conducted

to address the first hypothesis (regarding the factor structure of the contemporary social

support measures in a contemporary sample). Because the rating scale for items both

within and across the six contemporary scales is not consistent, some dichotomous items

were combined to maintain a uniform rating scale. First, the six items from the Social

Network Index (Berkman & Syme, 1977), which have a dichotomous (yes/no) response

format, were combined to form one summary item, with possible scores ranging from

zero to six. This method was also used to combine five dichotomous items from the scale

measuring giving support to others (Brown et al., 2003) and one dichotomous item from

the Lubben Social Network Scale (Lubben, 1988).

An additional issue regarding the rating scales should be noted. Six items in the

original Social Support Questionnaire (Sarason et al., 1983) ask participants to list

members of their social network who fulfill various social support needs, but participants

are asked to limit this number to nine or fewer members. Because this instruction was

confusing to participants in a pilot study, contemporary participants were not given this

limit, but responses were subsequently coded to reflect the limit (i.e., when more than

nine members were mentioned, the response was coded as nine).

To reduce the number of observed variables in the factor analysis, several-item

multidimensional parcels were constructed. Some experts advocate the use of item

parcels, rather than individual items, in factor analysis due to the greater reliability of

parceled than individual items, and thus a greater likelihood of obtaining adequate factor

20


solutions (Cattell, 1974). There has been some discussion in the literature regarding the

relative utility of using unidimensional parcels, which involves combining similar items

(e.g., based on face validity or factor loadings) and multidimensional parcels, in which

items representing different dimensions are combined into a parcel. Kishton and

Widaman (1994) found that the use of either unidimensional or multidimensional

(domain representative) parcels is effective. In the present study, multidimensional

parcels were used because each construct hypothesized to constitute social support (e.g.,

social networks, perceived available support) is thought to be multidimensional in nature.

The first step in constructing the multidimensional parcels was to determine which

construct within social support each item represents. To do so, six graduate students in

social/personality or developmental psychology were recruited to rate how well each item

represents each social support construct (social network size, perceived available support,

satisfaction with support, negative interactions, and providing support to others; using a

1-5 scale). For each item, the median rating was calculated within each construct; items

with a median of 3.5 or higher were considered representative of that construct (see

Tables 2-6 for the median ratings of each item for each category and assignments to

categories). When an item received a median rating of 3.5 or higher for more than one

category, it was assigned to the category for which it received the higher median rating

(N = 10). For cases in which an item median rating was equivalent across more than one

construct (N = 5), items were assigned to the construct for which the standard deviation

of the ratings was smaller. Next, exploratory factor analysis with varimax rotation was

employed to assign items to parcels; within each construct, the highest loading item in

21


each factor was assigned to be in parcel 1, the second highest loading item in each factor

was assigned to parcel 2, and so on. When the items were not distributed evenly across

factors, resulting in “leftover” items in a factor, the two items within the factor with the

lowest correlation were assigned to the same factor. For example, four items

representing the social networks category (number of friends with whom participant feels

at ease, number of friends heard from at least once a month, number of friends whom

participant can call on for help, and number of close friends) loaded on the same factor;

the two items with the lowest correlation (number of friends heard from at least once a

month, number of close friends; r — .52) were assigned to the same parcel (parcel 1),

whereas each of the other two items (number of friends with whom participant feels at

ease, number of friends whom participant can call on for help) were assigned to parcels 2

and 3, respectively. Tables 7-10 show the factor loadings of items within each category.

Because there were only 3 items related to providing social support to others, each of the

3 parcels representing this category contained only one item. In each parcel, the items

were summed and standardized using z-scores before being used as observed variables in

the CFA (Tables 11-15 show the items in each parcel for each category).

After all parcels were standardized, a correlation matrix for the 16 parcels in the

six contemporary social support scales was constructed to allow examination of the

relations among the parcels. Complete data are necessary for inclusion in the correlation

matrix; due to missing data, a prorating technique was employed to maximize the number

of cases of compete data. Specifically, if no more than two thirds of the items in a parcel

were missing data, the parcel score was calculated with the following formula: parcel

22


score = (sum of available responses x n of available and missing responses)/sum of

available responses. For example, the first parcel representing perceived available

support contains five items (number of people participant can count on when feeling

generally down-in-the-dumps, frequency of spouse making participant feel loved and

cared for, frequency of children listening to participant’s worries, frequency of

communication with friend with whom participant has most contact, and frequency of

being able to count on friends and relatives for help with daily tasks); if all items had

responses except for frequency of being able to count on friends and relatives for help

with daily tasks, the parcel score would be calculated by multiplying the sum of the four

available responses by 5, then dividing this product by 4. This method was used to

maximize the number of cases with complete data in both the contemporary and archival

samples.

Next, CFA was used to determine whether the factor structure of the scales has a

good fit to the proposed five-factor model (using Mx version 1.55; Neale, Boker, Xie, &

Maes, 2003). Chi-square, Akaike Information Criterion (AIC), and Root Mean Squared

Error Index (RMSEA) fit indices were used to determine the fit of the models, and the

Normed Fit Index (NFI) and the Tucker-Lewis Index (TLI) were used to compare the fits

of different models. Chi-square is useful in comparing the relative fit of different models

(Loehlin, 2004); a difference chi-square test signals whether one model is significantly

better than another. AIC is an indicator of the fit of the data with an estimated model

(Stevens, 2002); smaller values represent better fit (Ullman, 1996). RMSEA is a useful

indicator of model fit in that it does not rely heavily on sample size, where a common

23


criterion for reasonable fit is RMSEA of .08 or less (Loehlin, 2004). When seeking to

determine which of two nested models has a better fit, both the NFI and TLI can be used.

The NFI is an index of comparative fit that compares a specific model to a baseline

model, with higher values indicating a better fit (Loehlin, 2004). The TLI, also known as

the nonnormed fit index, compares the chi-square of each model, and takes degrees of

freedom into account (Ullman, 1996). A null model will be compared to a 1-factor, 4-

factor, and 5-factor model to determine the best fit (the 4-factor model combines the

factors of perceived available support and satisfaction with support into one factor per

previous research that fails to differentiate between these constructs).

Measurement invariance. When validating that scales from a new sample are

represented by items in an archival data set, it is important to ensure that the two cohorts

(contemporary and archival) respond to the items in a comparable manner (i.e.,

measurement invariance; Horn & McArdle, 1992); this matter is addressed by the second

hypothesis, that measurement invariance will be established for all five factors of social

support. In the present study, CFA was used to demonstrate that each sample produces

comparable factor structures of the scales (weak measurement invariance; Horn &

McArdle, 1992). CFA allows a comparison of model fit between two groups with a chi-

square difference test for nested models.

Rational analysis. The next important step in validating the social support scales

in the archival data set is to establish their validity using rational analyses. McCrae,

Costa, and Piedmont (1993) used a rational item content analytic process in which judges

interpret each of the items and make a determination about their representativeness of a

24


category. In that case, judges rated how well each item in the California Psychological

Inventory (CPI) represents each of the personality factors in the five-factor model as part

of a comparison between the CPI scales and the five-factor model. In the present study,

the archival social support items were compared to the social support categories resulting

from the factor analysis. This involved using six judges (psychology graduate students)

to rate the correspondence of each of the archival items with the scales resulting from the

factor analysis with contemporary social support scales. The reliability of the judges’

ratings was estimated by calculating the interjudge correlations for each pair of judges.

Correlations. The final step in validating the scales in the archival data set was

correlating the social support factors derived from the factor analysis with the

contemporary sample with the items in the Terman data set. These correlations indicate

how closely related the items from the contemporary scales and the archival scales are.

Prediction o f longevity. To address the third hypothesis, after the contemporary

social support scales were validated in the Terman sample, the archival data were used to

estimate the mortality risk through 2004 associated with each of the social support factors

(constructed from variables measured in 1977 and 1986). Of interest are both the relation

of the individual factors of social support with mortality risk (individual Cox proportional

hazards regressions) and each factor’s relative association with mortality risk

(simultaneous Cox proportional hazards regression). The simultaneous Cox proportional

hazards regression permits the examination of each factor’s association with mortality

risk as it relates to the others, such that each association takes into account the relation

between the other factors and mortality risk.

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RESULTS

Confirmatory Factor Analysis o f Contemporary Social Support Scales

The hypothesized five-factor model included the following factors: 1) social

network, 2) perceived available support, 3) satisfaction with support, 4) giving social

support, and 5) negative interactions. Confirmatory factor analysis, using a correlation

matrix of the 16 multidimensional item parcels, was used to perform maximum-

likelihood estimation of the models. To determine the best-fitting model, a null model

(with no factors) was compared to 1-factor, 4-factor, and 5-factor model. Table 16

displays the model-fitting results. As predicted, the 5-factor model showed the best fit to

the data (RMSEA = 0.06). Figure 2 shows the model estimates for the final 5-factor

model of items from contemporary social support scales.

Measurement Invariance

Before attempting to establish measurement invariance by comparing the factor

structure of the archival social support items across the contemporary and archival

samples, initial factor structures must be identified within each sample. Because the CFA

of the contemporary scales showed that five factors best represent items frequently used

to assess social support, this five-factor model was sought with the archival social support

items in both the contemporary and archival samples. However, due to the paucity of

archival items assessing negative social relations, only four factors could be explored.

These are social network size, perceived available support, satisfaction with support, and

providing support to others. Consistent with predictions, in the archival sample, the best-

26


fitting model was a 4-factor model (RMSEA = 0.09; model-fitting results are shown in

Table 17), with social networks, perceived available support, satisfaction with support,

and providing support representing the resulting factors (see Figure 3). This four-factor

structure of the archival social support items was replicated in the contemporary sample

(RMSEA = 0.10; see Table 18 for model-fitting results).

The next step in establishing measurement invariance involves fitting the same

factor model with each (archival and contemporary) sample, and comparing a constrained

model in which the factor loadings are forced to be equal across the two samples to a free

model that allows the inter-factor correlations, factor loadings, and error terms to vary

across the samples. Weak measurement invariance, which requires only the factor

loadings to be equivalent across samples, was examined; a chi-square difference test

indicated that the fully free model was significantly different from the model in which the

factor loadings were constrained to be equal across the two samples, but the inter-factor

correlations and error terms were free to vary (Ay2 = 46.30, Adf= 18,p = .0003). The

free, fully constrained, and partially constrained model comparisons are shown in Table

19.

Although this attempt at establishing measurement invariance was unsuccessful, it

was subsequently noted upon observation of the factor structures across the archival and

contemporary samples that only one factor (satisfaction with social support) appeared to

differ substantially across the two samples. The remaining factors (social networks,

perceived social support, giving social support), however, appeared to have similar factor

loadings in the archival and contemporary samples. Therefore, a new comparison of

27


models was made between the folly free model and a model in which the factor loadings,

correlations, and error terms associated with the satisfaction factor were free to vary, but

the remaining factor loadings, correlations, and error terms were fixed to be equal across

the archival and contemporary samples. The results of this comparison showed that

measurement invariance was established with respect to the social networks, perceived

available support, and giving social support factors; the folly free model and the model

with only the parameters related to satisfaction with support free to vary were not

significantly different (Ax2 = 28.48, Adf= 33,p = .69; see Table 19). Therefore,

measurement invariance was established for three of the four social support factors

(social networks, perceived available support, giving social support).

Correlational Analysis

After establishing measurement invariance of the three factors of social support,

correlations between the archival and contemporary factors were used to establish the

validity of the archival factors. Pearson correlations were computed among the social

support factors created from the archival and contemporary items (see Table 20). To

determine whether the reliability of the factors contributed to their inter-correlations, the

correlations were again computed using a structural equation model, which takes the

factors’ reliabilities into account (see Table 21). In each case, it is clear that the three

factors of social support, rather than being distinct, are quite related to one another. For

example, the correlation between the archival and contemporary items measuring social

networks is .54 (p < .0001), but the archival social network items are also strongly related

to the contemporary items assessing perceived available support (r = .53, p < .0001) and

28


providing support to others (r = .31 ,P< .0001). Further, the archival items representing

perceived available support are more strongly related to the contemporary social network

items (r = .44, p < .0001) than to the items representing perceived available support from

the contemporary scales (r = .34,/? < .0001). The archival items that measure providing

support to others strongly related to the contemporary items measuring the same

construct (r = .49, p < .0001), but have high correlations with those measuring perceived

available support (r = .48,/? < .0001) and social networks (r = .53,/? < .0001).

Rational Analysis

The final step in validating that the archival items represent social support factors

resulting from contemporary social support scales was to use rational analysis (to ensure

that the archival and contemporary items representing each factor are interpreted

similarly). Using the method established by McCrae, Costa, and Piedmont (1993), six

judges (graduate students in psychology) rated on a 5-point scale how well each archival

item represents each factor. To assess the judges’ reliability, inter-judge correlations

were computed and averaged for each factor of social support. For social networks, the

inter-judge correlations ranged from -.17 (p > .05) to .81 (p< .0001), with an average

inter-judge correlation of .25 (median inter-judge correlation = .17); for perceived

available support, the inter-judge correlations ranged from .33 (p > .05) to .97 (p < .0001),

with an average inter-judge correlation of .67 (median inter-judge correlation = .68); and

for providing support to others, the inter-judge correlations ranged from .21 (p > .05)

to .94 (p < .0001), with an average inter-judge correlation of .60 (median inter-judge

correlation = .66).

29


Employing judges to rate each item’s fit with each factor of social support was

used as an indicator of the rational content of the four factors. The mean rating for each

set of items archival items indicating the raters’ judgments of the fit of each item with the

factor of social support (social network size, perceived available support, and providing

support to others) are presented in Table 22. These ratings indicate that the judges were

in agreement that the items in the archival data set that best represents the factor of

perceived available support is that thought to represent perceived available support (mean

rating = 4.67). Additionally, the archival items highest rated as representing the

providing support factor were those assigned to providing support (mean rating = 4.39).

However, the judges did not perceive the items selected by the researcher to assess social

network size to strongly represent social network size (mean rating = 2.83), although

ratings were higher for this set of archival items than for the other factors that could have

been assigned.

Mortality Risk

Cox proportional hazards regression, a form a survival analysis which can account

for censored data and does not make an assumption about the shape of the survival

function, was used to estimate each social support factor’s independent association with

mortality risk in the archival participants. The results indicate that, of the three

established factors of social support, only social networks were reliability associated with

mortality risk, indicating a slight decrease in risk with increasing size of social networks

(rh = 0.94, p < .04, N = 533). These analyses were also conducted separately by sex; it

appears that the benefits of social networks are not specific to men or women, but rather

30


to the total sample of participants. The remaining 2 factors (perceived available support,

providing support) were unassociated with mortality risk (see Table 23 for results for

men, women, and the total sample).

A simultaneous Cox proportional hazards regression was also conducted to

examine how each factor of social support relates to mortality risk while taking into

account the other two factors. The results of the simultaneous analysis show that when

all of the social support factors are entered into the equation at the same time, giving

social support to others emerges as a slight protective factor (rh = 0.94,/? < .004, N =

301). Again, the analyses were conducted separately for men and women; the results

indicate that for men in particular, there is a relation between providing support and

decreased mortality risk when social networks and perceived available support are taken

into account (rh = 0.93,/? < .01, N = 158; see Table 24).

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DISCUSSION

Summary o f Findings

The goals of the present study were to identify the primary factors measured by

commonly used contemporary measures of social support, validate that certain items in

an archival data set measure these factors of social support, and determine how each

factor of social support is related to mortality risk. With regard to the first goal, it was

hypothesized that the primary factors of social support are social network ties, perceived

available support, satisfaction with support, providing support to others, and negative

interactions. A confirmatory factor analysis revealed that these five hypothesized factors

do, indeed, represent the constructs being measured by contemporary social support

measures such as the Social Network Index (Berkman & Syme, 1977) and the scale used

by the MacArthur Studies of Successful Aging (Gurung et al., 2003). This goal sought to

address the inconsistency in the operationalization of social support in the vast literature,

as well as determine if such definitional inconsistency might help account for the absence

of consistent findings linking social support with health outcomes. Similar studies

striving to identify the primary factors of social support have found different factors of

social support; however, most of these studies restricted their investigation to only more

limited, specific types of social support (e.g., social networks; e.g., Glass et al., 1997).

Given the social support literature’s need for a clear identification of the main factors of

social support, and the present study’s examination of commonly-used social support

scales addressing the many aspects of social support, the present results provide a step

32


toward a better understanding of what constitutes social support, as well as how the

different aspects of social support can be effectively measured.

The second goal of the present study was to determine whether items drawn from

an archival data set could measure those factors of social support resulting from the factor

analysis of contemporary social support scales (social networks, perceived available

support, satisfaction with support, providing support to others, and negative interactions).

To do so, the factor model identified in the contemporary sample was modeled in the

archival sample (with the exception of negative social relationships, for which there were

not enough items in the archival data set). The best-fitting model in the archival sample

was a four-factor model, with social networks, perceived available support, satisfaction

with support, and providing support to others. When a model constraining the factor

structures of the items to be equivalent across samples was compared to the model

allowing the factor structures to vary across samples, it was determined that measurement

invariance could not be established fully; the factor models across the two samples

differed significantly. However, when the factor representing satisfaction with support

was removed from the model due to observation of its poor fit indicators, the criteria for

strict measurement invariance were met. Thus, it was concluded that the factors of social

networks, perceived available support, and providing support to others from the

contemporary social support scales were indeed represented by items drawn from the

archival data set. These items were therefore available for use in examining how each of

these factors relates to mortality risk.

33


Although it was hypothesized that full measurement invariance would be

established, having only partial measurement invariance, with three of the four factors

measured consistently across the two sets of items, is useful nonetheless. An

understanding of how the three factors for which measurement invariance could be

established (social network size, perceived available support, and providing support to

others) individually and simultaneously relate to mortality risk is of great interest. Why

was the measurement of satisfaction with support different across time and samples?

Perhaps generational difference in the social norms regarding expressing dissatisfaction

with family and other relations is responsible for this difference.

With regard to the correlational analysis of the congruence between the archival

and contemporary social support items, it was hoped that there would be clear

distinctions between the four aspects of social support, with the items representing the

same factor of social support having strong correlations across samples, but with weak

correlations with the other factors. The results showed that although there were strong

correlations across samples between the same factors of social support, there were also

strong correlations between each factor and other factors across the two samples. In fact,

in the case of the archival factors of both perceived available support and providing

support, the inter-sample correlations were higher with the contemporary factors of social

network size than with the same factor. This result may be explained by the nature of the

construct of social support, which perhaps is not composed of distinct, orthogonal factors,

but instead factors that are very much related to each other. It makes intuitive sense that

the amount of support one perceives to be available to him or her is highly dependent on

34


one’s social network size. Likewise, the amount of support one provides to others is

surely affected by the size of one’s social network. Therefore, although it was initially

expected that each factor of social support represented by archival items would be most

highly correlated with the same factor measured by contemporary items, it is not

surprising that the factors are all highly intercorrelated.

Rational analysis, with six trained judges, was employed to investigate the

rational content of each archival item and to what extent each represents the associated

factor of social support. These ratings indicate that, on the whole, the archival factors

reasonably reflect the judges’ understanding of these factors of social support, and

provide evidence beyond the measurement invariance of the scales that the archival items

are appropriate to measure social network size, perceived available support, and

providing support to others.

The third goal of the study was to understand how different aspects of support,

both individually and together, relate to later mortality risk. Previous research has shown

that social network size is a strong predictor of mortality risk in the long-term; the results

of the present study were consistent with these prior findings. It was hypothesized that

perceived available support would not be associated with mortality risk; although

previous research has shown that perceived available support is important to

psychological outcomes (e.g., Sarason & Sarason, 1994), ties to mortality risk have not

been reported. Consistent with this hypothesis, perceived available support was not

related to mortality risk in the archival sample. Finally, due to recent findings that giving

support to others is associated with longevity, it was hypothesized that giving support

35


would be predictive of mortality risk in the archival sample. This hypothesis was not

supported by the results of the individual Cox proportional hazards regression; there was

no association between giving support and mortality risk. However, when all three of

these social support factors were simultaneously examined as predictors of mortality risk,

giving support was shown to be related to mortality risk.

The result that social network size is predictive of decreased mortality risk is

consistent with much of the previous literature on the relation between social networks

and mortality risk (e.g., Berkman & Syme, 1979; House et al., 1982). Thus, it appears

that the number of social contacts one has, rather than the perceived availability of

support, is important in later health outcomes. It was also not surprising that perceived

available support was unrelated to mortality risk; previous literature has shown that,

while the perceived availability of support may be crucial for psychological outcomes,

links to physical health outcomes have not been demonstrated. It was surprising, in light

of recent research pointing to providing social support as a key predictor of longevity

(Brown et al., 2003; Brown et al., 2005), that the results found here show no relation

between providing support and longevity. However, further information about the nature

of the relations between different aspects of social support and mortality risk was

revealed by the simultaneous proportional hazards regression with social network size,

perceived available support, and providing support to others as predictors. Results of this

analysis show that providing support is, in fact, a predictor of decreased mortality risk

when social network size and perceived availability of support are taken into account.

Perhaps it is the case that, due to the relation between providing support and social

36


network size, it is difficult to detect any association between providing support and

mortality risk unless the variance attributed to social network size is controlled. That

providing support is, in fact, a predictor of lower mortality risk is consistent with

previous findings (Brown et al., 2003; Brown et al., 2005).

Limitations

Although much can be learned from these results, it is important to note several

limitations of the present study. First, the archival sample is homogeneous in terms of

ethnicity (mostly White), social class (mostly middle), and intelligence (all highly

intelligent). These sample restrictions provide some benefits for investigations related to

health outcomes; any effects of differential access to health care or similar opportunities

are minimal, allowing a clearer picture of relations between psychosocial variables and

health outcomes to emerge. However, these restrictions also limit the generalizability of

results to other populations. Despite these differences between the archival sample and

other populations, it is unlikely that any relations found between psychological or social

factors and later mortality risk in the archival sample are different from these relations in

other populations. Yet, there may be noteworthy differences in the social relationships

between a group of individuals bom in the early 20th century and later generations. The

tenor of social times partially dictates family structure, social organizations, and other

sources of social ties, perhaps making comparisons between the social ties of individuals

in the archival sample and later generations difficult. In spite of this potential limitation,

the results of the analysis of measurement invariance show that, for the factors of social

37


network, perceived available support, and providing support to others, the interpretation

of questions assessing these factors does not appear to be different across decades.

A second potential limitation regards the nature of the contemporary sample

recruited for the present study. This sample consisted of the parents and other relatives of

undergraduate students at a public university. First, given that all of these participants are

related to a university student (and, in most cases, a parent of a university student), there

may be a floor effect on the size of participants’ social networks, perceived available

support, and provision of support. Second, there were 72 cases in which more than one

participant was recruited via the same undergraduate student (e.g., both mother and father

of a student), causing non-independence of observations. To determine whether this non

independence might change the outcome, confirmatory factor analyses were conducted

within a reduced sample, in which all observations were independent (N = 165). Similar

results emerged; the five-factor model was still the best fit to the data, demonstrating that

the same pattern results whether or not the sample includes non-independent observations.

Implications

After selecting six frequently-used measures of different aspects of support and

conducting factor analyses on the items, it was determined that the main constructs being

measured by these scales are social network size, perceived available support, satisfaction

with support, providing support, and negative interactions. The results of this factor

analysis serve to clarify the existing confusion and disagreement regarding how social

support should be measured; it appears that these five factors of social support encompass

what is being measured by social support measures in use. Furthermore, after identifying

38


these five factors, those for which measurement invariance could be established (social

network size, perceived available support, and providing support) were used to predict

mortality risk; an advantage to the present design is that these different aspects of social

support can be examined simultaneously as predictors of mortality risk. Support was

found for the importance of both the size of one’s network and providing support to

others in later health, though the perceived availability of support was not related to

mortality risk. Unfortunately, one of the resulting factors of social support, negative

interactions, could not be explored further in relation to mortality risk because only one

item assessing negative interactions was available in the archival data set. Future studies

should investigate the role of the negative aspects of social interactions in health

outcomes, particularly in light of research pointing to interpersonal conflict as a

significant predictor of both psychological and physical health outcomes (e.g., Burg &

Seeman, 1994; Ingersoll-Dayton et al., 1997; Newsom, Nishishiba, Morgan, & Rook,

2003; Newsom et al., 2005; Rook, 1984).

39


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Table 1

Items Assessing Social Support in Archival Data Set, 1977 and 1986

Year of Assessment Item1977 Number of organizational affiliations

Frequency of participating in visiting with relativesFrequency of participating in visiting with friends and neighborsFrequency of participating in entertainingFrequency of participating in helping friends and neighborsFrequency of participating in community serviceLifetime satisfaction with friendships/social contactsLifetime satisfaction with community service activities

Number of companionable friendships Number of casual friendshipsSatisfaction with the amount of intimacy and companionship provided by friendsNumber of intimate family relationshipsNumber of companionable family relationshipsNumber of casual family relationshipsNumber of indifferent or hostile family relationshipsSatisfaction in the amount of intimacy and companionship provided byfamilyProviding care or assistance to a friend or relativeFrequency of meetings of social groups, clubsFrequency of informal visiting with friends, neighbors, childrenFrequency of community service with organizationsFrequency of helping others (friends, neighbors, children)_________

1986 Number of intimate friendships

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Table 2

Means and Standard Deviations ofJudges ’ Ratings o f Items ’ Fit with Social NetworksCategory

Item Median SDNumber of close friends* 5.0 0.41Number of friends whom participant can call on for help* 5.0 0.41Number of relatives whom participant can call on for help* 5.0 0.41Number of close relatives* 5.0 0.52Number of friends with whom participant feels at ease* 5.0 0.82Number of relatives with whom participant feels at ease* 5.0 0.84Number of relatives seen or heard from at least once a month* 4.5 1.47Number of friends or relatives seen or talked to at least once a month* 4.0 1.38Summary of six dichotomous items assessing group membership* 3.5 0.82Number of people participant can count on when feeling generally down-in-the-dumps° 3.5 0.82Frequency of participation in group meetings or activities* 3.5 1.05Number of friends heard from at least once a month* 3.5 1.05Frequency of attendance at religious services* 3.5 1 . 2 1

Number of people participant can count on to care about him or her 3.0 0.75Number of people participant can count on to console him/her when veryupset 3.0 0.75Frequency of having someone to talk to when participant has an importantdecision to make 3.0 0.75Number of people participant can count on to help him/her feel morerelaxed when under pressure 3.0 0.98Frequency of communication with friend with whom participant has mostcontact 3.0 0.98Number of people participant can count on to distract from worries 3.0 1.03Number of people who accept participant totally 3.0 1.17Frequency of others talking to participant about important decisions theyneed to make 3.0 1.17Summary of four dichotomous items assessing frequency of helping friends,neighbors, or relatives with tasks and one dichotomous item measuringwhether anybody relies on participant to do something for them each day 2.5 1.05Frequency of friends and relatives listening to participant’s worries 2.5 1.47Frequency of being able to count on friends and relatives for help with dailytasks 2.5 1.47Frequency of friends and relatives making participant feel loved and caredfor 2.5 1.67Frequency of spouse making too many demands 2 . 0 0.63Satisfaction with availability of support related to being helped to feelrelaxed when under pressure 2 . 0 0.75

Note. Ratings were made on a 1-5 scale. * Item was retained in category.

48


Table 2 (cont’d.)

Item Median SDFrequency of children making too many demands 2 . 0 0.75Frequency of spouse being critical 2 . 0 0.75Frequency of children being critical 2 . 0 0.75Frequency of friends and relatives being critical 2 . 0 0.75Frequency of helping others with tasks 2 . 0 0.84Satisfaction with availability of support related to being cared about 2 . 0 0.89Satisfaction with availability of support related to being consoled when veryupset 2 . 0 0.89Frequency of friends and relatives making too many demands 2 . 0 0.98Frequency of being able to count on spouse to help with daily tasks 2 . 0 1.03Satisfaction with availability of support related to being accepted 2 . 0 1 .1

Satisfaction with availability of support related to being distracted fromworries 2 . 0 1.17Satisfaction with availability of support related to being helped to feel betterwhen feeling down-in-the-dumps 2 . 0 1.17Frequency of being able to count on children to help with daily tasks 2 . 0 1.17Frequency of spouse giving advice 2 . 0 1.17Frequency of children giving advice 2 . 0 1.17Frequency of spouse listening to participant’s worries 2 . 0 1 . 2 1

Frequency of children listening to participant’s worries 2 . 0 1 . 2 1

Frequency of spouse making participant feel loved and cared for 2 . 0 1.38Frequency of children making participant feel loved and cared for 2 . 0 1.38Frequency of friends and relatives giving advice 2 . 0 1.51


49


Table 3

Means and Standard Deviations ofJudges ’ Ratings o f Items ’ Fit with PerceivedAvailable Support Category

Item Median SDNumber of relatives with whom participant feels at ease* 5.0 .82Number of close friends* 5.0 .84Frequency of being able to count on spouse to help with daily tasks* 5.0 .84Frequency of being able to count on children to help with daily tasks* 5.0 .84Frequency of being able to count on friends and relatives for help with dailytasks* 5.0 .84Number of friends with whom participant feels at ease* 5.0 1 . 2 2

Number of close relatives* 5.0 1 . 6

Number of friends whom participant can call on for help0 4.5 .82Number of relatives whom participant can call on for help0 4.5 .82Frequency of spouse giving advice* 4.5 .82Frequency of children giving advice* 4.5 .82Frequency of friends and relatives giving advice* 4.5 .82Frequency of having someone to talk to when participant has an importantdecision to make* 4.5 .98Number of people participant can count on to distract from worries* 4.5 1.47Number of people participant can count on to help him/her feel morerelaxed when under pressure* 4.5 1.47Number of people participant can count on to console him/her when veryupset* 4.5 1.47Frequency of spouse listening to participant’s worries* 4.0 .75Frequency of friends and relatives listening to participant’s worries* 4.0 .75Frequency of children listening to participant’s worries* 4.0 .89Number of people who accept participant totally* 4.0 1.03Frequency of spouse making participant feel loved and cared for* 4.0 1.33Frequency of children making participant feel loved and cared for* 4.0 1.33Frequency of friends and relatives making participant feel loved and caredfor* 4.0 1.33Number of people participant can count on to care about him or her* 4.0 1.37Number of people participant can count on when feeling generally down-in-the-dumps* 4.0 1.37Number of friends heard from at least once a month* 3.5 1.17Satisfaction with availability of support related to being accepted0 3.5 1.26Number of friends or relatives seen or talked to at least once a month0 3.5 1.37Satisfaction with availability of support related to being cared about0 3.5 1.47

Note. Ratings were made on a 1-5 scale.* Item was retained in category.0 Item received higher median rating in another category.* Item received equal median rating but lower standard deviation in another category.

50


Table 3 (cont’d.)

Item Median SDSatisfaction with availability of support related to being helped to feel betterwhen feeling down-in-the-dumps° 3.5 1.47Frequency of communication with friend with whom participant has mostcontact* 3.5 1.47Satisfaction with availability of support related to being distracted fromworries0 3.5 1.63Satisfaction with availability of support related to being helped to feelrelaxed when under pressure0 3.5 1.63Satisfaction with availability of support related to being consoled when veryupset0 3.5 1.63Number of relatives seen or heard from at least once a month 3.0 1.26Frequency of attendance at religious services 3.0 1.72Summary of six dichotomous items assessing group membership 2.5 1.47Frequency of participation in group meetings or activities 2.5 1 . 8 6

Frequency of spouse making too many demands 2 . 0 1.17Frequency of children making too many demands 2 . 0 1.17Frequency of friends and relatives making too many demands 2 . 0 1.17Frequency of spouse being critical 2 . 0 1.17Frequency of children being critical 2 . 0 1.17Frequency of friends and relatives being critical 2 . 0 1.17Summary of four dichotomous items assessing frequency of helping friends,neighbors, or relatives with tasks and one dichotomous item measuringwhether anybody relies on participant to do something for them each day 1.5 .82Frequency of others talking to participant about important decisions theyneed to make 1.5 1 . 6

Frequency of helping others with tasks 1 . 0 .84

Note. Ratings were made on a 1-5 scale.* Item was retained in category.0 Item received higher median rating in another category.1’ Item received equal median rating but lower standard deviation in another category.

51


Table 4

Means and Standard Deviations ofJudges ’ Ratings o f Items ’ Fit with Satisfaction withSupport Category

Item Median SDSatisfaction with availability of support related to being distracted fromworries* 5.0 0

Satisfaction with availability of support related to being helped to feelrelaxed when under pressure* 5.0 0

Satisfaction with availability of support related to being cared about* 5.0 0

Satisfaction with availability of support related to being helped to feel betterwhen feeling down-in-the-dumps* 5.0 0

Satisfaction with availability of support related to being consoled when veryupset* 5.0 0

Satisfaction with availability of support related to being accepted* 5.0 .41Number of friends whom participant can call on for help 2.5 .98Number of relatives whom participant can call on for help 2.5 .98Frequency of friends and relatives making participant feel loved and caredfor 2.5 1.38Number of relatives whom participant can call on for help 2 . 0 .89Number of friends with whom participant feels at ease 2 . 0 .89Frequency of communication with friend with whom participant has mostcontact 2 . 0 .89Number of friends heard from at least once a month 2 . 0 1 . 1 0

Number of people participant can count on to distract from worries 2 . 0 1.17Number of people who accept participant totally 2 . 0 1.17Number of people participant can count on to care about him or her 2 . 0 1.17Number of friends or relatives seen or talked to at least once a month 2 . 0 1.17Number of people participant can count on to help him/her feel morerelaxed when under pressure 2 . 0 1.34Number of people participant can count on when feeling generally down-in-the-dumps 2 . 0 1.34Number of people participant can count on to console him/her when veryupset 2 . 0 1.34Frequency of spouse making participant feel loved and cared for 2 . 0 1.51Frequency of children making participant feel loved and cared for 2 . 0 1.51Number of close friends 1.5 .98Number of close relatives 1.5 .98Frequency of having someone to talk to when participant has an importantdecision to make 1.5 .98Frequency of spouse giving advice 1.5 1.26Frequency of children giving advice 1.5 1.26Frequency of friends and relatives giving advice 1.5 1.26


52


Table 4 (cont’d.)

Item Median SDFrequency of friends and relatives listening to participant’s worries 1.5 1.47Frequency of helping others with tasks 1 . 0 0

Summary of six dichotomous items assessing group membership 1 . 0 .41Summary of four dichotomous items assessing frequency of helping friends,neighbors, or relatives with tasks and one dichotomous item measuringwhether anybody relies on participant to do something for them each day 1 . 0 .41Frequency of participation in group meetings or activities 1 . 0 .52Frequency of attendance at religious services 1 . 0 .52Frequency of others talking to participant about important decisions theyneed to make 1 . 0 .52Number of relatives seen or heard from at least once a month 1 . 0 .84Frequency of being able to count on children to help with daily tasks 1 . 0 1.33Frequency of spouse listening to participant’s worries 1 . 0 1.55Frequency of children listening to participant’s worries 1 . 0 1.55Frequency of spouse making too many demands 1 . 0 1.55Frequency of children making too many demands 1 . 0 1.55Frequency of friends and relatives making too many demands 1 . 0 1.55Frequency of being able to count on spouse to help with daily tasks 1 . 0 1.83Frequency of being able to count on friends and relatives for help with dailytasks 1 . 0 1.83Frequency of spouse being critical 1 . 0 1.83Frequency of children being critical 1 . 0 1.83Frequency of friends and relatives being critical 1 . 0 1.83


53


Table 5

Means and Standard Deviations ofJudges ’ Ratings o f Items ’ Fit with Providing SupportCategory

Item Median SDFrequency of others talking to participant about important decisions theyneed to make* 5.0 .52Summary of four dichotomous items assessing frequency of helping friends,neighbors, or relatives with tasks and one dichotomous item measuringwhether anybody relies on participant to do something for them each day* 5.0 .82Frequency of helping others with tasks* 5.0 .84Frequency of attendance at religious services 3.0 1.03Frequency of participation in group meetings or activities 2.5 1.05Frequency of spouse making too many demands 2 . 0 .41Frequency of children making too many demands 2 . 0 .41Frequency of friends and relatives making too many demands 2 . 0 .41Number of relatives seen or heard from at least once a month 2 . 0 .42Frequency of communication with friend with whom participant has mostcontact 2 . 0 .52Number of friends heard from at least once a month 2 . 0 .75Summary of six dichotomous items assessing group membership 2 . 0 1.17Number of friends or relatives seen or talked to at least once a month 1.5 .55Number of relatives with whom participant feels at ease 1.5 .82Number of friends with whom participant feels at ease 1.5 1.47Satisfaction with availability of support related to being distracted fromworries 1 . 0 .41Satisfaction with availability of support related to being helped to feelrelaxed when under pressure 1 . 0 .41Satisfaction with availability of support related to being accepted 1 . 0 .41Satisfaction with availability of support related to being cared about 1 . 0 .41Satisfaction with availability of support related to being helped to feel betterwhen feeling down-in-the-dumps 1 . 0 .41Satisfaction with availability of support related to being consoled when veryupset 1 . 0 .41Frequency of spouse being critical 1 . 0 .41Frequency of children being critical 1 . 0 .41Frequency of friends and relatives being critical 1 . 0 .41Frequency of having someone to talk to when participant has an importantdecision to make 1 . 0 .55Number of people who accept participant totally 1 . 0 .82Number of people participant can count on to distract from worries 1 . 0 .84Number of people participant can count on to help him/her feel morerelaxed when under pressure 1 . 0 .84

Note. Ratings were made on a 1-5 scale. * Item was retained in category

54


Table 5 (cont’d.)

Item Median SDNumber of people participant can count on to care about him or her Number of people participant can count on when feeling generally down-in-

1 . 0 1.03

the-dumpsNumber of people participant can count on to console him/her when very

1 . 0 1.03

upset 1 . 0 1.03Number of friends whom participant can call on for help 1 . 0 1.03Number of relatives whom participant can call on for help 1 . 0 1.03Number of close friends 1 . 0 1 . 2 1

Number of close relatives 1 . 0 1 . 2 1

Frequency of spouse making participant feel loved and cared for 1 . 0 1 .2 1

Frequency of children making participant feel loved and cared for Frequency of friends and relatives making participant feel loved and cared

1 . 0 1 . 2 1

for 1 . 0 1 . 2 1

Frequency of being able to count on spouse to help with daily tasks 1 . 0 1 . 2 1

Frequency of being able to count on children to help with daily tasks Frequency of being able to count on friends and relatives for help with daily

1 . 0 1 . 2 1

tasks 1 . 0 1 . 2 1

Frequency of spouse listening to participant’s worries 1 . 0 1 . 2 2

Frequency of children listening to participant’s worries 1 . 0 1 . 2 2

Frequency of friends and relatives listening to participant’s worries 1 . 0 1 . 2 2

Frequency of spouse giving advice 1 . 0 1 . 2 2

Frequency of children giving advice 1 . 0 1 . 2 2

Frequency of friends and relatives giving advice 1 . 0 1 . 2 2


55


Table 6

Means and Standard Deviations ofJudges ’ Ratings o f Items ’ Fit with NegativeInteractions Category

Item Median SDFrequency of spouse making too many demands* 5.0 .82Frequency of children making too many demands* 5.0 .82Frequency of friends and relatives making too many demands* 5.0 .82Frequency of spouse being critical* 5.0 .82Frequency of children being critical* 5.0 .82Frequency of friends and relatives being critical* 5.0 .82Frequency of others talking to participant about important decisions theyneed to make 2 . 0 1 . 1 0

Summary of four dichotomous items assessing frequency of helping friends,neighbors, or relatives with tasks and one dichotomous item measuringwhether anybody relies on participant to do something for them each day 2 . 0 1.17Frequency of helping others with tasks 2 . 0 1.33Frequency of participation in group meetings or activities 1.5 .82Frequency of having someone to talk to when participant has an importantdecision to make 1.5 .82Frequency of spouse making participant feel loved and cared for 1.5 .82Frequency of children making participant feel loved and cared for 1.5 .82Frequency of friends and relatives making participant feel loved and caredfor 1.5 .82Frequency of spouse listening to participant’s worries 1.5 1.17Frequency of children listening to participant’s worries 1.5 1.17Frequency of friends and relatives listening to participant’s worries 1.5 1.17Frequency of spouse giving advice 1.5 1.47Frequency of children giving advice 1.5 1.47Frequency of friends and relatives giving advice 1.5 1.47Satisfaction with availability of support related to being distracted fromworries 1 . 0 0

Satisfaction with availability of support related to being helped to feelrelaxed when under pressure 1 . 0 0

Satisfaction with availability of support related to being accepted 1 . 0 0

Number of relatives seen or heard from at least once a month 1 . 0 0

Number of friends heard from at least once a month 1 . 0 0

Number of close friends 1 . 0 .41Number of close relatives 1 . 0 .41Number of people participant can count on to distract from worries 1 . 0 .41


56


Table 6 (cont’d.)

Item Median SDNumber of people participant can count on to help him/her feel morerelaxed when under pressure 1 . 0 .41Number of people who accept participant totally 1 . 0 .41Number of people participant can count on to care about him or her 1 . 0 .41Satisfaction with availability of support related to being cared about 1 . 0 .41Number of friends or relatives seen or talked to at least once a month 1 . 0 .41Frequency of attendance at religious services 1 . 0 .41Number of relatives with whom participant feels at ease 1 . 0 .41Number of friends with whom participant feels at ease 1 . 0 .41Frequency of communication with friend with whom participant has mostcontact 1 . 0 .41Summary of six dichotomous items assessing group membership 1 . 0 .52Satisfaction with availability of support related to being helped to feel betterwhen feeling down-in-the-dumps 1 . 0 .84Satisfaction with availability of support related to being consoled when veryupset 1 . 0 .84Number of people participant can count on when feeling generally down-in-the-dumps 1 . 0 1 . 2 1

Number of people participant can count on to console him/her when veryupset 1 . 0 1 . 2 1

Number of friends whom participant can call on for help 1 . 0 1 . 2 2

Number of relatives whom participant can call on for help 1 . 0 1 . 2 2

Frequency of being able to count on spouse to help with daily tasks 1 . 0 1.55Frequency of being able to count on children to help with daily tasks 1 . 0 1.55Frequency of being able to count on friends and relatives for help with dailytasks 1 . 0 1.55


57


Table 7

Factor Loadings o f Items within Social Network Category

Item Factor 1 Factor 2 Factor 3Number of friends with whom participant feels at ease .834 .275 .105Number of friends heard from at least once a month .800 .281 .068Number of friends whom participant can call on for help .679 .180 .298Number of close friends .654 .335 .165Number of relatives with whom participant feels at ease .280 .735 .153Number of close relatives .253 .716 .254Number of relatives whom participant can call on for help .253 .593 .281Number of relatives seen or heard from at least once a month .131 .674 .027Number of friends or relatives seen or talked to at least once a .511 .532 .157monthFrequency of participation in group meetings or activities .181 .069 .609Frequency of attendance at religious services -.028 .074 .474Summary of six dichotomous items assessing group .254 .190 .530membership

Note. N = 253.

58


Table 8

Factor Loadings o f Items within Perceived Available Support Category

Item Factor 1 Factor 2 Factor 3 Factor 4Number of people participant can count on when feeling generally down-in-the-dumps

.823 .077 .081 .204

Number of people who accept participant totally .822 .050 .074 .097Number of people participant can count on to care about him or her

.810 .074 .032 .096

Number of people participant can count on to help him/her feel more relaxed when under pressure

.781 .064 .066 .280

Number of people participant can count on to console him/her when very upset

.778 .041 .117 . 2 1 2

Number of people participant can count on to distract from worries

.751 -.004 .056 .254

Frequency of spouse making participant feel loved and cared for

.090 .958 .023 -.041

Frequency of spouse listening to participant’s worries

.071 .932 .025 .005

Frequency of being able to count on spouse to help with daily tasks

.036 .916 . 0 2 0 - . 0 2 1

Frequency of spouse giving advice .045 .865 .117 -.051Frequency of children listening to participant’s worries

.027 . 0 1 0 .714 .216

Frequency of children giving advice .028 -.024 .691 .138Frequency of being able to count on children to help with daily tasks

.042 .038 .658 .174

Frequency of children making participant feel loved and cared for

.115 .111 .576 .026

Frequency of friends and relatives listening to participant’s worries

.240 -.170 .267 .630

Frequency of friends and relatives giving advice .172 -.119 .248 .583Frequency of communication with friend with whom participant has most contact

.160 -.114 -.048 .503

Frequency of friends and relatives making participant feel loved and cared for

.223 .068 .289 .493

Frequency of having someone to talk to when participant has an important decision to make

.182 .228 .124 .453

Frequency of being able to count on friends and relatives for help with daily tasks

. 1 2 1 .086 .378 .445

Note. N = 246.

59


Table 9

Factor Loadings o f Items within Satisfaction with Support Category

Item Factor 1 Factor 2Satisfaction with availability of support related to being accepted

.799 .458

Satisfaction with availability of support related to being cared about

.791 .498

Satisfaction with availability of support related to being helped to feel better when feeling down-in-the-dumps

.707 .647

Satisfaction with availability of support related to being helped to feel relaxed when under pressure

.502 .779

Satisfaction with availability of support related to being distracted from worries

.430 .748

Satisfaction with availability of support related to being consoled when very upset

.627 .642

Note. N = 240.

60


Table 10

Factor Loadings o f Items within Negative Interactions Category

Item Factor 1 Factor 2Frequency of children being critical . 1 0 1 .602Frequency of friends and relatives making too many demands .063 .590Frequency of children making too many demands .196 .563Frequency of friends and relatives being critical . 0 0 1 .482Frequency of spouse making too many demands .812 .107Frequency of spouse being critical .802 .116

Note. N = 264.

61


Table 11

Items in Multidimensional Parcels Representing Social Networks

Parcel 11 . Number of relatives with whom participant feels at ease2 . Number of friends whom participant can call on for help3. Number of close friends4. Frequency of participation in group meetings or activities

Parcel 21 . Number of relatives seen or heard from at least once a month2 . Number of friends or relatives seen or talked to at least once a month3. Number of friends with whom participant feels at ease4. Frequency of attendance at religious services

Parcel 31 . Number of close relatives2 . Number of relatives whom participant can call on for help3. Number of friends heard from at least once a month4. Summary of six dichotomous items assessing group membership

62


Table 12

Items in Multidimensional Parcels Representing Perceived Available Support

Parcel 11. Number of people participant can count on when feeling generally down-in-the-dumps2. Frequency of children listening to participant’s worries3. Frequency of spouse making participant feel loved and cared for4. Frequency of communication with friend with whom participant has most contact5. Frequency of being able to count on friends and relatives for help with daily tasks_____

Parcel 21. Number of people participant can count on to care about him or her2. Number of people participant can count on to distract from worries3. Frequency of children giving advice4. Frequency of spouse listening to participant’s worries5. Frequency of friends and relatives listening to participant’s worries________________

Parcel 31 .6 . Number of people who accept participant totally2. Frequency of being able to count on children to help with daily tasks3. Frequency of being able to count on spouse to help with daily tasks4. Frequency of having someone to talk to when participant has an important decision to

make5. Frequency of friends and relatives giving advice______________________________

Parcel 41. Number of people participant can count on to help him/her feel more relaxed when under

pressure2. Number of people participant can count on to console him/her when very upset3. Frequency of children making participant feel loved and cared for4. Frequency of spouse giving advice5. Frequency of friends and relatives making participant feel loved and cared for________

63


Table 13

Items in Multidimensional Parcels Representing Satisfaction with Support

Parcel 11 . Satisfaction with availability of support related to being accepted2 . Satisfaction with availability of support related to being helped to feel relaxed when

under pressureParcel 2

1 . Satisfaction with availability of support related to being cared about2 . Satisfaction with availability of support related to being distracted from worries

Parcel 31 . Satisfaction with availability of support related to being helped to feel better when feeling

down-in-the-dumps2 . Satisfaction with availability of support related to being consoled when very upset

64


Table 14

Items in Multidimensional Parcels Representing Providing Support

Parcel 11. Summary of four dichotomous items assessing frequency of helping friends, neighbors,

or relatives with tasks and one dichotomous item measuring whether anybody relies on______participant to do something for them each day______________________________Parcel 2

1. Frequency of others talking to participant about important decisions they need to make Parcel 3

1. Frequency of helping others with tasks___________________________________

65


Table 15

Items in Multidimensional Parcels Representing Negative Interactions

Parcel 11. Frequency of children making too many demands2. Frequency of friends and relatives being critical__________

Parcel 21. Frequency of children being critical2. Frequency of spouse making too many demands__________

Parcel 31. Frequency of friends and relatives making too many demands2. Frequency of spouse being critical____________________

66


Table 16

Model-Fitting Results for Contemporary Social Support Items in Contemporary Sample

Model x2 df P AIC NFI TLI RMSEANull 2,663.08 1 2 0 0 . 0 0 2,423.08 — — 0.301 -factor 1,469.45 104 0 . 0 0 1,261.45 0.45 0.38 0.244-factor 363.99 98 0 . 0 0 167.99 0 . 8 6 0.87 0 . 1 1

5-factor 172.43 94 0 . 0 0 -15.57 0.94 0.96 0.06

Note. N = 237

67


Table 17

Model-Fitting Results for Archival Social Support Items in Archival Sample

Model .....................T df P AIC NFI TLI RMSEANull 1886.38 153 0 . 0 0 1580.381 — — 0.1551 -factor 1018.942 135 0 . 0 0 748.942 0.460 0.422 0.1184-factor 601.052 129 0 . 0 0 343.052 0.681 0.677 0.088

Note. N = 471.

68


Table 18

Model-Fitting Results for Archival Social Support Items in Contemporary Sample

Model df P AIC NFI TLI RMSEANull 1319.264 153 0 . 0 0 1013.264 — — 0.1711 -factor 756.200 135 0 . 0 0 486.200 0.427 0.396 0.1334-factor 484.751 129 0 . 0 0 226.751 0.633 0.638 0.103

Note. N = 263.

69


Table 19

Model-Fitting Results for Establishing Measurement Invariance

Model 3C* df AIC RMSEA (Cl) Comparison to Free

Fully free 1069.914 258 553.914 0.087 (0.082, 0.093) —Fully equated 1133.018 300 533.018 0.083 (0.078, 0.088) p = .0192Error terms and 1116.212 276 564.212 0.086 (0.081,0.092) p =.0003correlations freeSatisfaction free 1098.398 291 516.398 0.083 (0.077, 0.088) p = .6916

Note. Standardized solution.

70


Table 20

Correlations among Archival and Contemporary Social Support Items within Contemporary Sample

Contemporary Items

ArchivalNetworks Perceived

AvailableProviding

Items Networks 5 4 **** 5 3 **** 31****Perceived Available 4 4 **** 3 4 **** .26****Providing 52**** 48**** 4 9 ****

Note. N = 269. 0001.

71


Table 21

Correlations among Archival and Contemporary Social Support Items within Contemporary Sample, Adjusting for Reliability

Contemporary Items

ArchivalSocial Network

SizePerceivedAvailable

ProvidingSupport

ItemsSocial Network Size 0.73

Support0.72 0.47

Perceived Available 0.71 0.60 0.48SupportProviding Support 0.65 0.52 0.63

Note. N = 262.

72


Table 22

Means ofJudges ’ Ratings ofItems in Archival Factors ’ Fit with Factors Resulting from Factor Analysis o f Contemporary Social Support Items

Contemporary FactorArchival Factor Social Network Size Perceived Available

SupportProviding Support

Social Network Size 2.83 2.13 2.46Perceived Available 3.97 4.47 1.90SupportProviding Support 2.47 1.69 4.39

Note. Higher scores indicate higher perceived fit.

73


Table 23

Proportional Hazards Regressions Predicting Mortality Risk as o f2005 from Factors o f Social Support

Variable Total Men WomenSocial Networks

n 533 283 250rh 0.94* 0.96 0.94b -0.06 -0.04 -0.06x2 4.36 1.03 1.84P 0.04 0.31 0.17

Perceived Available Supportn 368 185 183rh 1.00 1.00 1.00b -0.003 -0.004 -0.0002x2 0.10 0.16 0.00P 0.75 0.69 0.98

Providing Supportn 672 357 315rh 0.99 0.99 0.99b -0.001 -0.01 -0.01x2 1.40 0.47 0.45P 0.24 0.49 0.50

* p < .05.

74


Table 24

Simultaneous Proportional Hazards Regressions Predicting Mortality Risk as o f2005 from Factors o f Social Support

Variable Total Men WomenSocial Networks

n 301 158 143rh 1.00 1.02 1.01b 0.001 0.02 0.01x2 0.00 0.07 0.01P 0.99 0.79 0.93

Perceived Available Supportn 301 158 143rh 1.00 1.00 1.00b -0.0003 -0.001 0.002x2 0.00 0.00 0.01P 0.97 0.94 0.91

Providing Supportn 301 158 143rh 0.94** 0.93* 0.95tb -0.07 -0.07 -0.06x2 8.82 5.95 2.79P 0.003 0.01 0.09

p < .10. * p < .05. **p < .01.

75


Reproduced with

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Figure 1. Hypothesized model of social support.

OsSocial Networks Peraeived Available >atisfactior Negative Interactions Providing Support

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without permission.

Figure 2. Model estimates for the final 5-factor model of items from contemporary social support scales in contemporary sample.

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Figure 3. Model estimates for 4-factor model of archival items in archival sample.

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