Journal of Youth and Adolescence, VoL 14, No. 1, 1985
Differentiating Specialists and Generalists within College Students' Social Support Networks G. A n n e Bogat, ''z Robert A . Caldwell, + Fred A . R o g o s c h , ~ and Julie A n n Kriegler ~ Received September 6, 1984; accepted March 5, 1985
In order to examine the relationships among social network structure, types o f social support, and determinants o f support satisfaction, an alternative method was used to score the Social Support Questionnaire (SSQ). Factor analysis procedures suggested that college students" (N = 198) social networks consisted of four groups: nuclear family, other family, friends, and others. Satisfaction with support was positively related to the proportion of the network occupied by nuclear family and negatively related to the proportion of friends in the network. Evidence was found for the presence o f both support specialists and support generalists in the networks of the college students. These results are discussed from a developmental perspective with attention to the implications for interventions.
INTRODUCTION Psychologists and other health care professionals who are interested in the prevention of psychopathology have turned their attention to the stress-
'Michigan State University, East Lansing, Michigan 48824. Wo whom correspondence should be addressed at Department of Psychology, Michigan State University, East Lansing, Michigan 48824. 23 0047-2891/85/0200-0023504.50/0 © 1985 Plenum Publishing Corporation
24
Bogat, Caldwell, Rogosch, and Kriegler
buffering effects of social support. Social support has been shown to buffer the deleterious effects of accumulated life stress (Leavy, 1983) as well as the specific stresses of individual life events (Caldwell and Bloom, 1982; Wilcox, 1981). It also has been demonstrated that social support maintains and enhances both physical (Broadhead et al., 1983; DiMatteo and Hayes, 1981) and psychological (Leavy, 1983) health. In the light of such research findings, attempts have been made to marshall the protective forces of social support in order to help individuals and populations in need. Gottlieb (1981) points out, however, that much of the basic research that underlies these preventive programs is not conducted in ways that could "inform the design of preventive programs involving the mobilization of social support" (p. 205). Ideally, basic social support research should provide clear guidance for those health care professionals responsible for restoring, maintaining, or enhancing the health of any specified population. To date, the basic research has not been up to the task. This is due, in large measure, to the lack of a clear conceptualization of social support. For instance, social support typically has been measured quantitatively (e.g., the total number of individuals available to the subject) even though recent literature has suggested that the health-enhancing aspects of social support may be a function of the quality of support. Further, our knowledge of social support networks across the life span is inadequate. Researchers cannot assume that the characteristics of adult networks will necessarily parallel those of other age groups. Thoits (1982) provides a compelling argument that social support is a multidimensional concept that is often inadequately operationalized and measured. She reminds us that "Not only is the a m o u n t of support important, but the types of support (e.g., socioemotional and instrumental) and the s o u r c e s of support (e.g., spouse, friends, kin, coworkers) are also important dimensions." (p. 147, emphasis in the original). For the most part, the different components of social support have been treated independently by researchers; however, a few investigations have suggested that various types of support (Lin et al., 1981) and alternative sources of support (Billings and Moos, 1982; Colletta, 1981; Conner et al., 1979) are differentially related to a variety of outcome variables. What the research rarely addresses (and what the program planners may need to know) centers on the interaction between source and type of support. Social network analysis suggests that there are important interactions between source and type of support. Walker et al., (1977) offer an analysis of how different social network characteristics may increase the availability of certain kinds of support. Similarly, Hirsch (1980) has demonstrated that different support is available from high-density and low-density social networks.
Differentiating Social Support
25
One aspect of this type-by-source interaction is the importance that either "support specialists" or "support generalists" assume in social networks. A support specialist is a person who provides a unique, limited kind of support to the focal individual. Gottlieb (1981) and Granovetter (1982) both indicate the importance of such specialists as potential sources of ideas and information that would otherwise be difficult to obtain from one's network. The contrasting position is that networks are composed, either primarily or exclusively, of support generalists- "core" network members able to supply an individual with all or many types of support. There is research to indicate that such generalists are present in support networks and that they offer effective support in a wide variety of situations (Caplan, 1976; Lowenthal and Haven, 1968; Miller and Ingham, 1976). Another important concern of program planners should be the developmental stage of program recipients. Preliminary research on young children has shown the importance of familial social support. For example, Sandler (1980) found that adjustment of elementary school children was enhanced by living with two parents and an older sibling. Nair and Jason (1984) found that networks predominated by family members were the most satisfying to children. Recent research by Kriegler (1985) suggests that family members function as support generalists in the networks of young children, whereas peers and professionals provide more specialized support functions. Future research needs to delineate whether adolescents and children share similar support network characteristics. College students provide an easily accessible late-adolescent population in which to study this question. The college studlent is faced with challenges and stresses quite different from earlier life stages. Not only are some of these experiences stressful in their own right, but the stress is compounded by changes in the student's social networks that occur during this time. The major developmental task of establishing a more secure and mature ego identity (Erikson, 1950) in part entails adolescent separation and individuation from parents. Recent research has demonstrated that adolescents do not terminate strong relationships with their parents, even as they turn toward other adults and peers during this period. Rather, a cognitive restructuring of the parent-adolescent relationship takes place (Youniss, 1983). As students develop new networks in college, it is not known to what extent specific aspects of parental social support is shared with or shifted to friends in the college network. In the present research, college students were studied in order to examine the effect that a normal, developmental transition exerted on social networks. We were particularly interested in the relative importance of suppcrt specialists and support generalists present in college students' social networks, as well as which types of individuals provided these different supportive roles.
26
Bogat, Caldwell, Rogosch, and Kriegler
The Social Support Questionnaire (SSQ) developed by Sarason et aL, (1983) provided one strategy for investigating support in a variety o f life situations. This questionnaire seems especially appropriate for use with college students since it was initially developed with college student populations. The SSQ contains 27 items that seem to assess four areas of social support: emotional support (e.g., "Whom can you really count on to listen to you when you need to talk?"), advice and information (e.g., "Whom can you really count on to give you useful suggestions that help you to avoid making mistakes?"), socialization (e.g., "Whom can you really count on to distract you from your worries when you feel under stress?"), and tangible aid (e.g., "Whom could you really count on to help you out in a crisis situation, even though they would have to go out o f their way to do so?"). Sarason et al. (1983) operationalize social support by calculating the mean number of network members nominated on each of the 27 items of their questionnaire. Although this method of scoring the SSQ is simple and efficient, it provides only a macroscopic, quantitative view of an individual's support network and therefore disallows the investigation of qualitative dimensions of social support such as the presence o f support specialists and support generalists. We therefore coded the SSQ using relationship categories (e.g., nuclear family, friends) that would be likely to detect the presence o f support specialists or generalists. Also, social support profiles were developed for 20 randomly chosen individuals in our study in order to further delineate the specialist-generalist dimension,
METHOD Subjects
Subjects were 198 undergraduate students at a large midwestern university. Participation was voluntary and all students received extra credit in their introductory psychology course for their involvement. The sample consisted of 122 females and 76 males. The mean age of the sample was 19.5 years. Tests and Materials
The Social Support Questionnaire (SSQ; Sarason et aL, 1983) presents 27 situations for which people might need support. Subjects are asked to list those people on whom they can rely for support, their relationship to those people, and their rating o f satisfaction with the support they receive. Sarason et aL developed two separate social support scores for each subject: (1)
27
Differentiating Social Support
average number of network members noted for each question (SSQN), and (2) average satisfaction ratings (SSQS). Preliminary research with the SSQ suggests that it is a reliable and valid measure of social support (Sarason and Sarason, 1982; Sarason et al., 1983). Procedure
The present researchers scored the SSQ in two separate ways. The first method of scoring was identical to that reported by Sarason et al. (1983). For the second method of scoring, network members nominated by our subjects were coded according to their relationship to the focal individual. The seven relationship categories were nuclear family, other family, friend, helping professional, acquaintance, teacher/employer, and other. In a final procedure, researchers randomly selected 20 subject protocols and plotted support network profiles for these individuals. These profiles depicted graphically which network members were nominated for each of the support questions on the SSQ. RESULTS A factor analysis of the 27 variables representing the mean number of network members nominated for each of the SSQ items revealed a one-factor solution consistent with the results obtained by Sarason et al. (1983). Further, when we computed both the average number of network members per question (SSQN) and the average satisfaction rating (SSQS), our data indicated a positive and significant correlation between SSQN and SSQS (r = 0.35; p < 0.001) that was virtually identical to the results obtained by Sarason et al. (r = 0.34). These results suggest that the subjects and data obtained by the present investigators could be compared reliably to the previous research by Sarason et al. (1983). The second scoring method (responses to each item were scored according to the number of network members in each of seven relationship categories) was employed in order to delineate further the characteristics of the supportive networks of our subjects. Examination of the tow frequency with which the relationship categories of helping professional, acquaintance, and teacher/employer were used necessitated merging these categories into a global other category. The original other category was eliminated because it was rarely used and often included unusual responses (e.g., Jack Daniel's whiskey). The four remaining relationship categories were: nuclear family, other family, friend, and other (acquaintances, teachers/employers, and helping professionals).
28
Bogat, Caldwell, Rogosch, and Kriegler
The number of individuals in each of the four relationship categories for each of the 27 items in the SSQ comprised 108 variables that were subjected to a principal components factor analysis with subsequent varimax rotation. Four factors, corresponding to the four relationship categories, emerged from the factor analysis and accounted for 10%0, 9070, 10070, and 10070 of the variance, respectively. Each factor had relatively low correlations with the other factors (range,-0.19 to 0.16). Examination of the variables loading on each factor indicated the factor analysis was clustering the relationship categories irrespective of the SSQ item content. As might be predicted, the average number of responses per question (SSQN) was positively correlated with the average number of responses in each o f the four relationship categories, with the highest correlations occurring for average nuclear family responses and average friend responses. These correlations are presented in Table I. The calculation of SSQN includes support group members who might be listed more than once; therefore, an additional score was derived. This score represents the total number of unique individuals Listed throughout the SSQ. The number of unique individuals ranged from 3 to 36 (M = 14.7; SD = 5.52). The correlations between this new score and the average number o f responses in each of the four relationship categories were low (see Table I). Friends evidenced the highest correlation with unique individuals. This indicated that the friends relationship group had the largest representation in the support network. We next investigated several factors that predicted satisfaction with support. As reported earlier, average support satisfaction (SSQS) was moderately related (1" = 0.35) to the average number of network members (SSQN). In contrast, the correlation of SSQS and the number of unique individuals was marginally negative (r = - 0 . 1 0 , p < 0.08). Partialling out the effect of SSQN revealed a more strongly negative relationship between unique individuals and SSQS (r = -0.31, p < 0.001). Using SSQN and the number of unique individuals in a regression equation to predict SSQS indicated that entering the number of unique individuals added an additional 9°-/0 to the variance accounted for by SSQN alone (12%).
Table I. CorrelationsbetweenSSQN, Total UniqueNetwork Members and Average Number of Nominations for Each Relationship Category SSQN Total unique Average nuclear family 0.61 0.18 Average other family 0.14 0.14 Average friend 0.74 0.39 Average other 0.42 0.15
Differentiating Social Support
29
The extent to which each of the four relationship groups (average relationship category scores) was related to support satisfaction indicated a differential influence for each category (nuclear family, r = 0.34; friend, r = 0.17; other r = 0.14; and other family, r = 0.03). Entering these variables into a regression equation to predict SSQS revealed that average nuclear family responses accounted for 11%0 of the variance, with average friend responses contributing an additional 3%. The other family and other categories did not make an additional significant contribution. Determining the average nuclear family and average friend support allowed for slightly more control of the variance than SSQN alone, while also giving a better understanding of the patterning of network relationship structure and support satisfaction. Finally, ratio scores (i.e., average number of nuclear family responses/SSQN) were also related to SSQS. There were significant relationships between SSQS and the nuclear family ratio (r = 0.16, p < 0.05) and SSQS and the friends ratio (r = - 0 . 1 6 , p < 0.05). This indicated that a greater percentage of family members in a college student's social network, as compared to a greater percentage of friends, was marginally related to greater support satisfaction. In order to determine whether soical support profiles would yield other information regarding the presence or absence of support specialists and generalists, a final set of analyses was conducted. Twenty questionnaires were randomly chosen and hand scored in order to yield a profile of a subject's social support network. The 27 SSQ items were listed across the top of the page and each unique individual was listed along the left-hand margin. We then placed hatch marks in the resulting grid to indicate the various questions for which each supportive individual was listed. On these 20 profiles, subjects listed an average of 15.35 supporters (range, 6 to 29, SD = 5.75). On the average, subjects nominated each supporter 8.83 times (SD = 2.73) with means for each supporter ranging from 2.7 to 14.5. Across profiles, the frequency with which individual supporters were nominated ranged from 1 to 27 times. The 20 hand-scored profiles indicated that there were obvious support specialists and support generalists present in our subjects' networks. ~
3The authors are aware that a computer program could have been employed to calculate the number of nominations for each network member. Such a procedure would have allowed us to determine whether certain persons functioned as support specialists or generalists. For our purposes, we felt that a visual representation would be sufficient for a preliminary article on this subject. Now that we have determined the presence of specialist status supporters, future research will be required to examine more closely the characteristics of these supporters.
30
Bogat, Caldwell, Rogosch, and Kriegler
DISCUSSION When developing the Soical Support Questionnaire (SSQ), Sarason et al. (1983) explored several possible scoring methods, including two methods employed in the present research (i.e., the number of supportive people listed within various relationship categories and the number of unique individuals in the subject's network). They opted for the simplest scoring procedure (the mean number of responses for each question, SSQN) because the intercorrelations between the various scoring methods were generally greater than 0.70. Although the different methods of analyzing supportive networks may be highly correlated, our investigation found that the method of assessing and quantifying subjects' social networks significantly influenced the number of distinct factors found in the SSQ. The mean-number-of-responses scoring procedure resulted in Sarason et al. (1983) and the present researchers finding only one major factor when analyzing the SSQ. Alternatively, the use of a relationship-category scoring system indicated that there were four independent factors, each accounting for about 10°70 of the variance. This second factor analysis clustered relationship categories regardless of item content on the SSQ. A primary goal of this research was to delineate the specialist-generalist dimensions of support present in the social networks of college students. Our data indicate that both specialists and generalists are present in the networks of these subjects. A comparison between correlations of relationship categories and SSQN and correlations of relationship categories and the unique number of supporters (see Table I) was crucial to our understanding of the specialist or generalist functions of different relationship categories. While the data in Table I may seem obvious at first, the two colums of correlations show an interesting pattern. Consider a hypothetical situation. If a subject were to nominate each network member only once throughout the entire questionnaire, SSQN would be exactly equal to the number of unique individuals divided by the number of questions (27). If this were the case, the two columns of correlations in Table I would be identical. To the degree that network members are nominated more than once, the correlations in the rifht-hand column of Table I will be smaller than the correlations in the left-hand column. The degree of difference between the rightand left-hand columns can, therefore, be interpreted as the degree to which network members are nominated more than once. Moving from the hypothetical to the actual, our data indicate that students have at least one category of persons whom they rely upon to provide specialist function(s). Persons belonging to the category "other family members" (i.e., aunts, uncles, cousins, etc.) each seem to be nominated as support group members on only one question (r = 0.14 in both columns).
Differentiating Social Support
31
However, we know that each of these individuals was not nominated on the s a m e one question because the factor analysis did not reveal any factor de-
fined by item-relationship category pairings. Evidence for the presence of support specialists was also found when examining the social support profiles for a random group of 20 subjects. In order to highlight this point, we have reproduced two very different subject grids (see Table II). Subject A's social network consists mainly of support specialists. Although this subject has a large social network (29 individuals), each member of the network is mentioned, on average, only 2.7 times. In contrast, subject B has a truncated, generalist-dominated social network consisting of only six individuals. However, network members of subject B are mentioned, on average, 9.0 times. Although college students clearly have support specialists in their support networks, the presence of strong support generalists was also found. Table I indicates that nuclear family members (r = 0.61 vs. r = 0.18) are nominated many times throughout the questionnaire. The satisfaction ratings also emphasize the importance of the nuclear family in the lives o f these students. While average support satisfaction (SSQS) was moderately related to SSQN, the partial correlation of SSQS and the number of unique individuals was moderately negative. The contrast between these two correlations may indicate that the size of one's support network has less influence on satisfaction than does the consistency with which individuals are relied upon for support (i.e., the support generalist). The most consistent individuals in our students' networks were nuclear family members. Developmentally, as these late-adolescent students separate from their families and form new relationships with peers at college, it is still a supportive relationship with the nuclear family, more so than with friends, that is related to support satisfaction. Our results were consistent with previous research on the social networks of children. Those adolescents with networks dominated by nuclear family members were more satisfied than adolescents with fewer nuclear family members in their networks (cf. Nair and Jason, 1984). Furthermore, in our study nuclear family supporters served as support generalists f o r t h e college students, a finding consistent with the function of family members in the networks of younger children (cf. Kriegler, 1985). Differentiating support generalists and support specialists is an important task for researchers interested in developing preventive interventions in the realm o f social support. Gottlieb (1981) discussed two types of preventive interventions: those attempting to influence the t y p e of support offered by support sources already in the individual's network (e.g., Conter et al., 1980; Wiesenfeld and Weis, 1979); and those designed to increase the number o f potential s o u r c e s o f support available to an individual (e.g., Pilisuk and Minkler, 1980; Weiss, 1976). Findings from the present research inves-
X
X
X
X X X X
X
X X X
Mother Father Sister Brother Uncle Grand mot her Cousin Brother-in-law Aunt Friend 1 Friend 2 Friend 3 Friend 4 Friend 5 Friend 6 Friend 7
3
4
X
X
X X X X X X
1 2
Relationship
X
5
X X
6
7
8
X
9
X
10
X
11
SSQ question 13
X
X X X X
Subject A
12
14
15
16
Table II, Social Support Profiles
17
X
X X X X
18
19
X X
20
X
21
X
X
22
23
X X X X X
24
X
X
X
25
26
27
,,,I
e,c
O
O
.=
e~
o
Mother Father Friend 1 Friend 2 Friend 3 Friend 4
Friend 8 Friend 9 Friend 10 Friend 11 Friend 12 Friend t3 Friend 14 Friend 15 Friend 16 Friend 17 Friend 18 High school teacher High school counselor
XX X X X
X
X X
X X X X X
X X
X X X X X X X X X X
X X
X
X X X X
X X
X
X
X
X
X
X X X
X
Subject B
X
X X
X
X
X
X
X
X
X
X
X X X
X
X
X
X X
X X X
X
X X X
X
X
X
X X
X X X
X
X
X
t~
O
fro
34
Bogat, Caldweil, Rogosch, and Kriegler
t i g a t i o n i n d i c a t e t h a t p r o g r a m p l a n n e r s w h o w o r k w i t h college s t u d e n t p o p u lations might focus their interventions on bolstering the support these young p e o p l e n e e d to r e c e i v e f r o m n u c l e a r f a m i l y m e m b e r s . I f s u c h s u p p o r t is una v a i l a b l e , it m a y be t h a t s t u d e n t s n e e d t o c u l t i v a t e o t h e r s u p p o r t e r s to p r o vide the generalist functions of nuclear family members. Further research s h o u l d f o c u s o n d e l i n e a t i n g w h i c h types o f p e o p l e u n d e r w h i c h c i r c u m s t a n c e s w o u l d benefit m o s t f r o m the skills o f s u p p o r t specialists o r s u p p o r t generalists.
ACKNOWLEDGMENT W e w o u l d like to t h a n k R o g e r M i t c h e l l f o r his h e l p f u l s u g g e s t i o n s o n an e a r l i e r d r a f t o f this p a p e r ,
REFERENCES Billings, A. G., and Moos, R. H. (1982). Work stress and the stress buffering roles of work and family resources..L Occupational Behav. 3: 215-232. Broadhead, W. E., Kaplan, B. H., James, S. A., Wagner, E. H., Schoenbach, V. J., Grimson, R., Heyden, S., Tibblin, G., and Gehlbach, S. H. (1983). The epidemiologic evidence for a relationship between social support and health. Am. J. Epidemiol. 117: 521-537. Caldwell, R. A., and Bloom, B. L. (1982). Social support: Its structure and impact on marital disruption. Am. J. Community Psychol. 10, 647-667. Caplan, G. (1976). The family as a support system. In Caplan, G., and Kitlilea., M. (eds.), Support Systems and Mutual Help: Multidisciplinary Explorations, Grune & Stratton, San Francisco, pp. 19-36. Colletta, N. D. (1981). Social support and the risk of maternal rejection by adolescent mothers. J. PsychoL l09: 191-197. Conner, K. A., Powers, E. A., and Bultena, G. L. (1979). Social interaction and life satisfaction: An empirical assessment of late-life patterns. J. GerontoL 34:116-121. Conter, K. R,, Hatch, C. L., and D'Augelli, A. R. (1980). Enhancing the skills of Cub Scout den leaders: Training, generalization, and maintenance. Am. J. Community Psychol. 8: 77-85. DiMatteo, M. R., and Hayes, R. (1981). Social support and serious illness. In Gottlieb, B. H. (ed.), Social Networks and Social Support, Sage, Beverly Hills, Calif. pp. 117-148. Erikson, E. H. (1950). Childhood and SocieO,, Norton and Company, New York. Gottlieb, B. H. (1981). Preventive interventions involving social networks and social support. In Gottlieb, B. H. (ed.), Social Networks and Social Support, Sage, Beverly Hills, Calif., pp. 201-232. Granoveuer, M. (1982). The strength of weak ties: A network theory revisited. In Marsden, P. V., and Lin, N. (eds.), Social Structure and Network Analysis, Sage, Beverly Hills, Calif., pp. 105-I30. Hirsch, B. J. (1980). Natural support systems and coping with major life changes. Am. J. Community PsychoL 8: 159-172. Kriegler, J. A. (1985). Developmental aspects of social support: A multidimensional analysis of children's social networks. Unpublished master's thesis, Michigan State University, East Lansing, Mich. Leavy, R. L. (1983). Social support and psychological disorder: A review. J. Community Psychol. 1I: 3-21. Lin, N., Dean, A., and Ensel, W. M. (1981). Social support scales: A methodological note. Schizophrenia Bull. 7: 73-89.
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35
Lowenthal, M. F. and Haven, C. (1968). Interaction and adaptation: Intimacy as a critical variable. Am. SocioL Rev. 33: 20-30. Miller, P., and Ingham, J. G. (1976). Friends, confidants, and symptoms. Social Psychiatry. I1: 51-58. Nair, D., and Jason, L. A. (1984). An investigation and analysis of social networks among children. Poster session presented at the Midwestern Psychological Association annual convention, Chicago, Illinois. Pilisuk, M., and Minkler, M. (1980). Supportive networks: Life ties for the elderly. J. Soc. Issues 36: 95-I 16. Sandier, 1. N. (1980). Social support resources, stress, and maladjustment of poor children. Am. J. Community Psychol. 8: 41-52. Sarason, I. G., and Sarason, B. R. (1982). Concomitants of social support: Attitudes, personality characteristics, and life experiences. J. Personal. 50: 331-344. Sarason, 1. G., Levine, H. M., Basham, R. B., and Sarason, B. R. (1983). Assessing social support: The social support questionnaire. J. Personal. Soc. Psychol. 44: 127-139. Thoits, P. A. (1982). Conceptual, methodological, and theoretical problems in studying social support as a buffer against life stress. J. Health Soc. Behav. 23: 145-159. Walker, K. N., MacBride, A., and Vachon, M. L. S. (1977). Social support networks and the crisis of bereavement. Soc. Sci. Ailed. I1: 35-41. Weiss, R. S. (1976). Transition states and other stressful situations: Their nature and programs for their management. In Caplan, G., and Killilea, M. (eds.), Support Systems and Mutual Help: Multidisciplinary Explorations, Grune & Stratton, San Francisco (pp. 213-232). Wiesenfeld, A. R., and Weis, H. M. (1979). Hairdressers and helping: Influencing the behavior of informal caregivers. Prof. Psychol. 7: 786-792. Wilcox, B. L. (1981). Social support in adjusting to marital disruption: A network analysis. In Gottlieh, B. H. (ed.), Social Networks and Social Support, Sage, Beverly Hills, Calif., pp. 97-115. Youniss, J. (1983). Social construction of adolescence by adolescents and parents. In Groterant, H. D. and Cooper, C. R. (eds.), Adolescent Development in the Family. New Directions in Child Development (Vol. 22), Jossey-Bass, San Francisco, pp. 91-109.
Differentiating Specialists and Generalists within College Students' Social Support Networks G. A n n e Bogat, ''z Robert A . Caldwell, + Fred A . R o g o s c h , ~ and Julie A n n Kriegler ~ Received September 6, 1984; accepted March 5, 1985
In order to examine the relationships among social network structure, types o f social support, and determinants o f support satisfaction, an alternative method was used to score the Social Support Questionnaire (SSQ). Factor analysis procedures suggested that college students" (N = 198) social networks consisted of four groups: nuclear family, other family, friends, and others. Satisfaction with support was positively related to the proportion of the network occupied by nuclear family and negatively related to the proportion of friends in the network. Evidence was found for the presence o f both support specialists and support generalists in the networks of the college students. These results are discussed from a developmental perspective with attention to the implications for interventions.
INTRODUCTION Psychologists and other health care professionals who are interested in the prevention of psychopathology have turned their attention to the stress-
'Michigan State University, East Lansing, Michigan 48824. Wo whom correspondence should be addressed at Department of Psychology, Michigan State University, East Lansing, Michigan 48824. 23 0047-2891/85/0200-0023504.50/0 © 1985 Plenum Publishing Corporation
24
Bogat, Caldwell, Rogosch, and Kriegler
buffering effects of social support. Social support has been shown to buffer the deleterious effects of accumulated life stress (Leavy, 1983) as well as the specific stresses of individual life events (Caldwell and Bloom, 1982; Wilcox, 1981). It also has been demonstrated that social support maintains and enhances both physical (Broadhead et al., 1983; DiMatteo and Hayes, 1981) and psychological (Leavy, 1983) health. In the light of such research findings, attempts have been made to marshall the protective forces of social support in order to help individuals and populations in need. Gottlieb (1981) points out, however, that much of the basic research that underlies these preventive programs is not conducted in ways that could "inform the design of preventive programs involving the mobilization of social support" (p. 205). Ideally, basic social support research should provide clear guidance for those health care professionals responsible for restoring, maintaining, or enhancing the health of any specified population. To date, the basic research has not been up to the task. This is due, in large measure, to the lack of a clear conceptualization of social support. For instance, social support typically has been measured quantitatively (e.g., the total number of individuals available to the subject) even though recent literature has suggested that the health-enhancing aspects of social support may be a function of the quality of support. Further, our knowledge of social support networks across the life span is inadequate. Researchers cannot assume that the characteristics of adult networks will necessarily parallel those of other age groups. Thoits (1982) provides a compelling argument that social support is a multidimensional concept that is often inadequately operationalized and measured. She reminds us that "Not only is the a m o u n t of support important, but the types of support (e.g., socioemotional and instrumental) and the s o u r c e s of support (e.g., spouse, friends, kin, coworkers) are also important dimensions." (p. 147, emphasis in the original). For the most part, the different components of social support have been treated independently by researchers; however, a few investigations have suggested that various types of support (Lin et al., 1981) and alternative sources of support (Billings and Moos, 1982; Colletta, 1981; Conner et al., 1979) are differentially related to a variety of outcome variables. What the research rarely addresses (and what the program planners may need to know) centers on the interaction between source and type of support. Social network analysis suggests that there are important interactions between source and type of support. Walker et al., (1977) offer an analysis of how different social network characteristics may increase the availability of certain kinds of support. Similarly, Hirsch (1980) has demonstrated that different support is available from high-density and low-density social networks.
Differentiating Social Support
25
One aspect of this type-by-source interaction is the importance that either "support specialists" or "support generalists" assume in social networks. A support specialist is a person who provides a unique, limited kind of support to the focal individual. Gottlieb (1981) and Granovetter (1982) both indicate the importance of such specialists as potential sources of ideas and information that would otherwise be difficult to obtain from one's network. The contrasting position is that networks are composed, either primarily or exclusively, of support generalists- "core" network members able to supply an individual with all or many types of support. There is research to indicate that such generalists are present in support networks and that they offer effective support in a wide variety of situations (Caplan, 1976; Lowenthal and Haven, 1968; Miller and Ingham, 1976). Another important concern of program planners should be the developmental stage of program recipients. Preliminary research on young children has shown the importance of familial social support. For example, Sandler (1980) found that adjustment of elementary school children was enhanced by living with two parents and an older sibling. Nair and Jason (1984) found that networks predominated by family members were the most satisfying to children. Recent research by Kriegler (1985) suggests that family members function as support generalists in the networks of young children, whereas peers and professionals provide more specialized support functions. Future research needs to delineate whether adolescents and children share similar support network characteristics. College students provide an easily accessible late-adolescent population in which to study this question. The college studlent is faced with challenges and stresses quite different from earlier life stages. Not only are some of these experiences stressful in their own right, but the stress is compounded by changes in the student's social networks that occur during this time. The major developmental task of establishing a more secure and mature ego identity (Erikson, 1950) in part entails adolescent separation and individuation from parents. Recent research has demonstrated that adolescents do not terminate strong relationships with their parents, even as they turn toward other adults and peers during this period. Rather, a cognitive restructuring of the parent-adolescent relationship takes place (Youniss, 1983). As students develop new networks in college, it is not known to what extent specific aspects of parental social support is shared with or shifted to friends in the college network. In the present research, college students were studied in order to examine the effect that a normal, developmental transition exerted on social networks. We were particularly interested in the relative importance of suppcrt specialists and support generalists present in college students' social networks, as well as which types of individuals provided these different supportive roles.
26
Bogat, Caldwell, Rogosch, and Kriegler
The Social Support Questionnaire (SSQ) developed by Sarason et aL, (1983) provided one strategy for investigating support in a variety o f life situations. This questionnaire seems especially appropriate for use with college students since it was initially developed with college student populations. The SSQ contains 27 items that seem to assess four areas of social support: emotional support (e.g., "Whom can you really count on to listen to you when you need to talk?"), advice and information (e.g., "Whom can you really count on to give you useful suggestions that help you to avoid making mistakes?"), socialization (e.g., "Whom can you really count on to distract you from your worries when you feel under stress?"), and tangible aid (e.g., "Whom could you really count on to help you out in a crisis situation, even though they would have to go out o f their way to do so?"). Sarason et al. (1983) operationalize social support by calculating the mean number of network members nominated on each of the 27 items of their questionnaire. Although this method of scoring the SSQ is simple and efficient, it provides only a macroscopic, quantitative view of an individual's support network and therefore disallows the investigation of qualitative dimensions of social support such as the presence o f support specialists and support generalists. We therefore coded the SSQ using relationship categories (e.g., nuclear family, friends) that would be likely to detect the presence o f support specialists or generalists. Also, social support profiles were developed for 20 randomly chosen individuals in our study in order to further delineate the specialist-generalist dimension,
METHOD Subjects
Subjects were 198 undergraduate students at a large midwestern university. Participation was voluntary and all students received extra credit in their introductory psychology course for their involvement. The sample consisted of 122 females and 76 males. The mean age of the sample was 19.5 years. Tests and Materials
The Social Support Questionnaire (SSQ; Sarason et aL, 1983) presents 27 situations for which people might need support. Subjects are asked to list those people on whom they can rely for support, their relationship to those people, and their rating o f satisfaction with the support they receive. Sarason et aL developed two separate social support scores for each subject: (1)
27
Differentiating Social Support
average number of network members noted for each question (SSQN), and (2) average satisfaction ratings (SSQS). Preliminary research with the SSQ suggests that it is a reliable and valid measure of social support (Sarason and Sarason, 1982; Sarason et al., 1983). Procedure
The present researchers scored the SSQ in two separate ways. The first method of scoring was identical to that reported by Sarason et al. (1983). For the second method of scoring, network members nominated by our subjects were coded according to their relationship to the focal individual. The seven relationship categories were nuclear family, other family, friend, helping professional, acquaintance, teacher/employer, and other. In a final procedure, researchers randomly selected 20 subject protocols and plotted support network profiles for these individuals. These profiles depicted graphically which network members were nominated for each of the support questions on the SSQ. RESULTS A factor analysis of the 27 variables representing the mean number of network members nominated for each of the SSQ items revealed a one-factor solution consistent with the results obtained by Sarason et al. (1983). Further, when we computed both the average number of network members per question (SSQN) and the average satisfaction rating (SSQS), our data indicated a positive and significant correlation between SSQN and SSQS (r = 0.35; p < 0.001) that was virtually identical to the results obtained by Sarason et al. (r = 0.34). These results suggest that the subjects and data obtained by the present investigators could be compared reliably to the previous research by Sarason et al. (1983). The second scoring method (responses to each item were scored according to the number of network members in each of seven relationship categories) was employed in order to delineate further the characteristics of the supportive networks of our subjects. Examination of the tow frequency with which the relationship categories of helping professional, acquaintance, and teacher/employer were used necessitated merging these categories into a global other category. The original other category was eliminated because it was rarely used and often included unusual responses (e.g., Jack Daniel's whiskey). The four remaining relationship categories were: nuclear family, other family, friend, and other (acquaintances, teachers/employers, and helping professionals).
28
Bogat, Caldwell, Rogosch, and Kriegler
The number of individuals in each of the four relationship categories for each of the 27 items in the SSQ comprised 108 variables that were subjected to a principal components factor analysis with subsequent varimax rotation. Four factors, corresponding to the four relationship categories, emerged from the factor analysis and accounted for 10%0, 9070, 10070, and 10070 of the variance, respectively. Each factor had relatively low correlations with the other factors (range,-0.19 to 0.16). Examination of the variables loading on each factor indicated the factor analysis was clustering the relationship categories irrespective of the SSQ item content. As might be predicted, the average number of responses per question (SSQN) was positively correlated with the average number of responses in each o f the four relationship categories, with the highest correlations occurring for average nuclear family responses and average friend responses. These correlations are presented in Table I. The calculation of SSQN includes support group members who might be listed more than once; therefore, an additional score was derived. This score represents the total number of unique individuals Listed throughout the SSQ. The number of unique individuals ranged from 3 to 36 (M = 14.7; SD = 5.52). The correlations between this new score and the average number o f responses in each of the four relationship categories were low (see Table I). Friends evidenced the highest correlation with unique individuals. This indicated that the friends relationship group had the largest representation in the support network. We next investigated several factors that predicted satisfaction with support. As reported earlier, average support satisfaction (SSQS) was moderately related (1" = 0.35) to the average number of network members (SSQN). In contrast, the correlation of SSQS and the number of unique individuals was marginally negative (r = - 0 . 1 0 , p < 0.08). Partialling out the effect of SSQN revealed a more strongly negative relationship between unique individuals and SSQS (r = -0.31, p < 0.001). Using SSQN and the number of unique individuals in a regression equation to predict SSQS indicated that entering the number of unique individuals added an additional 9°-/0 to the variance accounted for by SSQN alone (12%).
Table I. CorrelationsbetweenSSQN, Total UniqueNetwork Members and Average Number of Nominations for Each Relationship Category SSQN Total unique Average nuclear family 0.61 0.18 Average other family 0.14 0.14 Average friend 0.74 0.39 Average other 0.42 0.15
Differentiating Social Support
29
The extent to which each of the four relationship groups (average relationship category scores) was related to support satisfaction indicated a differential influence for each category (nuclear family, r = 0.34; friend, r = 0.17; other r = 0.14; and other family, r = 0.03). Entering these variables into a regression equation to predict SSQS revealed that average nuclear family responses accounted for 11%0 of the variance, with average friend responses contributing an additional 3%. The other family and other categories did not make an additional significant contribution. Determining the average nuclear family and average friend support allowed for slightly more control of the variance than SSQN alone, while also giving a better understanding of the patterning of network relationship structure and support satisfaction. Finally, ratio scores (i.e., average number of nuclear family responses/SSQN) were also related to SSQS. There were significant relationships between SSQS and the nuclear family ratio (r = 0.16, p < 0.05) and SSQS and the friends ratio (r = - 0 . 1 6 , p < 0.05). This indicated that a greater percentage of family members in a college student's social network, as compared to a greater percentage of friends, was marginally related to greater support satisfaction. In order to determine whether soical support profiles would yield other information regarding the presence or absence of support specialists and generalists, a final set of analyses was conducted. Twenty questionnaires were randomly chosen and hand scored in order to yield a profile of a subject's social support network. The 27 SSQ items were listed across the top of the page and each unique individual was listed along the left-hand margin. We then placed hatch marks in the resulting grid to indicate the various questions for which each supportive individual was listed. On these 20 profiles, subjects listed an average of 15.35 supporters (range, 6 to 29, SD = 5.75). On the average, subjects nominated each supporter 8.83 times (SD = 2.73) with means for each supporter ranging from 2.7 to 14.5. Across profiles, the frequency with which individual supporters were nominated ranged from 1 to 27 times. The 20 hand-scored profiles indicated that there were obvious support specialists and support generalists present in our subjects' networks. ~
3The authors are aware that a computer program could have been employed to calculate the number of nominations for each network member. Such a procedure would have allowed us to determine whether certain persons functioned as support specialists or generalists. For our purposes, we felt that a visual representation would be sufficient for a preliminary article on this subject. Now that we have determined the presence of specialist status supporters, future research will be required to examine more closely the characteristics of these supporters.
30
Bogat, Caldwell, Rogosch, and Kriegler
DISCUSSION When developing the Soical Support Questionnaire (SSQ), Sarason et al. (1983) explored several possible scoring methods, including two methods employed in the present research (i.e., the number of supportive people listed within various relationship categories and the number of unique individuals in the subject's network). They opted for the simplest scoring procedure (the mean number of responses for each question, SSQN) because the intercorrelations between the various scoring methods were generally greater than 0.70. Although the different methods of analyzing supportive networks may be highly correlated, our investigation found that the method of assessing and quantifying subjects' social networks significantly influenced the number of distinct factors found in the SSQ. The mean-number-of-responses scoring procedure resulted in Sarason et al. (1983) and the present researchers finding only one major factor when analyzing the SSQ. Alternatively, the use of a relationship-category scoring system indicated that there were four independent factors, each accounting for about 10°70 of the variance. This second factor analysis clustered relationship categories regardless of item content on the SSQ. A primary goal of this research was to delineate the specialist-generalist dimensions of support present in the social networks of college students. Our data indicate that both specialists and generalists are present in the networks of these subjects. A comparison between correlations of relationship categories and SSQN and correlations of relationship categories and the unique number of supporters (see Table I) was crucial to our understanding of the specialist or generalist functions of different relationship categories. While the data in Table I may seem obvious at first, the two colums of correlations show an interesting pattern. Consider a hypothetical situation. If a subject were to nominate each network member only once throughout the entire questionnaire, SSQN would be exactly equal to the number of unique individuals divided by the number of questions (27). If this were the case, the two columns of correlations in Table I would be identical. To the degree that network members are nominated more than once, the correlations in the rifht-hand column of Table I will be smaller than the correlations in the left-hand column. The degree of difference between the rightand left-hand columns can, therefore, be interpreted as the degree to which network members are nominated more than once. Moving from the hypothetical to the actual, our data indicate that students have at least one category of persons whom they rely upon to provide specialist function(s). Persons belonging to the category "other family members" (i.e., aunts, uncles, cousins, etc.) each seem to be nominated as support group members on only one question (r = 0.14 in both columns).
Differentiating Social Support
31
However, we know that each of these individuals was not nominated on the s a m e one question because the factor analysis did not reveal any factor de-
fined by item-relationship category pairings. Evidence for the presence of support specialists was also found when examining the social support profiles for a random group of 20 subjects. In order to highlight this point, we have reproduced two very different subject grids (see Table II). Subject A's social network consists mainly of support specialists. Although this subject has a large social network (29 individuals), each member of the network is mentioned, on average, only 2.7 times. In contrast, subject B has a truncated, generalist-dominated social network consisting of only six individuals. However, network members of subject B are mentioned, on average, 9.0 times. Although college students clearly have support specialists in their support networks, the presence of strong support generalists was also found. Table I indicates that nuclear family members (r = 0.61 vs. r = 0.18) are nominated many times throughout the questionnaire. The satisfaction ratings also emphasize the importance of the nuclear family in the lives o f these students. While average support satisfaction (SSQS) was moderately related to SSQN, the partial correlation of SSQS and the number of unique individuals was moderately negative. The contrast between these two correlations may indicate that the size of one's support network has less influence on satisfaction than does the consistency with which individuals are relied upon for support (i.e., the support generalist). The most consistent individuals in our students' networks were nuclear family members. Developmentally, as these late-adolescent students separate from their families and form new relationships with peers at college, it is still a supportive relationship with the nuclear family, more so than with friends, that is related to support satisfaction. Our results were consistent with previous research on the social networks of children. Those adolescents with networks dominated by nuclear family members were more satisfied than adolescents with fewer nuclear family members in their networks (cf. Nair and Jason, 1984). Furthermore, in our study nuclear family supporters served as support generalists f o r t h e college students, a finding consistent with the function of family members in the networks of younger children (cf. Kriegler, 1985). Differentiating support generalists and support specialists is an important task for researchers interested in developing preventive interventions in the realm o f social support. Gottlieb (1981) discussed two types of preventive interventions: those attempting to influence the t y p e of support offered by support sources already in the individual's network (e.g., Conter et al., 1980; Wiesenfeld and Weis, 1979); and those designed to increase the number o f potential s o u r c e s o f support available to an individual (e.g., Pilisuk and Minkler, 1980; Weiss, 1976). Findings from the present research inves-
X
X
X
X X X X
X
X X X
Mother Father Sister Brother Uncle Grand mot her Cousin Brother-in-law Aunt Friend 1 Friend 2 Friend 3 Friend 4 Friend 5 Friend 6 Friend 7
3
4
X
X
X X X X X X
1 2
Relationship
X
5
X X
6
7
8
X
9
X
10
X
11
SSQ question 13
X
X X X X
Subject A
12
14
15
16
Table II, Social Support Profiles
17
X
X X X X
18
19
X X
20
X
21
X
X
22
23
X X X X X
24
X
X
X
25
26
27
,,,I
e,c
O
O
.=
e~
o
Mother Father Friend 1 Friend 2 Friend 3 Friend 4
Friend 8 Friend 9 Friend 10 Friend 11 Friend 12 Friend t3 Friend 14 Friend 15 Friend 16 Friend 17 Friend 18 High school teacher High school counselor
XX X X X
X
X X
X X X X X
X X
X X X X X X X X X X
X X
X
X X X X
X X
X
X
X
X
X
X X X
X
Subject B
X
X X
X
X
X
X
X
X
X
X
X X X
X
X
X
X X
X X X
X
X X X
X
X
X
X X
X X X
X
X
X
t~
O
fro
34
Bogat, Caldweil, Rogosch, and Kriegler
t i g a t i o n i n d i c a t e t h a t p r o g r a m p l a n n e r s w h o w o r k w i t h college s t u d e n t p o p u lations might focus their interventions on bolstering the support these young p e o p l e n e e d to r e c e i v e f r o m n u c l e a r f a m i l y m e m b e r s . I f s u c h s u p p o r t is una v a i l a b l e , it m a y be t h a t s t u d e n t s n e e d t o c u l t i v a t e o t h e r s u p p o r t e r s to p r o vide the generalist functions of nuclear family members. Further research s h o u l d f o c u s o n d e l i n e a t i n g w h i c h types o f p e o p l e u n d e r w h i c h c i r c u m s t a n c e s w o u l d benefit m o s t f r o m the skills o f s u p p o r t specialists o r s u p p o r t generalists.
ACKNOWLEDGMENT W e w o u l d like to t h a n k R o g e r M i t c h e l l f o r his h e l p f u l s u g g e s t i o n s o n an e a r l i e r d r a f t o f this p a p e r ,
REFERENCES Billings, A. G., and Moos, R. H. (1982). Work stress and the stress buffering roles of work and family resources..L Occupational Behav. 3: 215-232. Broadhead, W. E., Kaplan, B. H., James, S. A., Wagner, E. H., Schoenbach, V. J., Grimson, R., Heyden, S., Tibblin, G., and Gehlbach, S. H. (1983). The epidemiologic evidence for a relationship between social support and health. Am. J. Epidemiol. 117: 521-537. Caldwell, R. A., and Bloom, B. L. (1982). Social support: Its structure and impact on marital disruption. Am. J. Community Psychol. 10, 647-667. Caplan, G. (1976). The family as a support system. In Caplan, G., and Kitlilea., M. (eds.), Support Systems and Mutual Help: Multidisciplinary Explorations, Grune & Stratton, San Francisco, pp. 19-36. Colletta, N. D. (1981). Social support and the risk of maternal rejection by adolescent mothers. J. PsychoL l09: 191-197. Conner, K. A., Powers, E. A., and Bultena, G. L. (1979). Social interaction and life satisfaction: An empirical assessment of late-life patterns. J. GerontoL 34:116-121. Conter, K. R,, Hatch, C. L., and D'Augelli, A. R. (1980). Enhancing the skills of Cub Scout den leaders: Training, generalization, and maintenance. Am. J. Community Psychol. 8: 77-85. DiMatteo, M. R., and Hayes, R. (1981). Social support and serious illness. In Gottlieb, B. H. (ed.), Social Networks and Social Support, Sage, Beverly Hills, Calif. pp. 117-148. Erikson, E. H. (1950). Childhood and SocieO,, Norton and Company, New York. Gottlieb, B. H. (1981). Preventive interventions involving social networks and social support. In Gottlieb, B. H. (ed.), Social Networks and Social Support, Sage, Beverly Hills, Calif., pp. 201-232. Granoveuer, M. (1982). The strength of weak ties: A network theory revisited. In Marsden, P. V., and Lin, N. (eds.), Social Structure and Network Analysis, Sage, Beverly Hills, Calif., pp. 105-I30. Hirsch, B. J. (1980). Natural support systems and coping with major life changes. Am. J. Community PsychoL 8: 159-172. Kriegler, J. A. (1985). Developmental aspects of social support: A multidimensional analysis of children's social networks. Unpublished master's thesis, Michigan State University, East Lansing, Mich. Leavy, R. L. (1983). Social support and psychological disorder: A review. J. Community Psychol. 1I: 3-21. Lin, N., Dean, A., and Ensel, W. M. (1981). Social support scales: A methodological note. Schizophrenia Bull. 7: 73-89.
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Lowenthal, M. F. and Haven, C. (1968). Interaction and adaptation: Intimacy as a critical variable. Am. SocioL Rev. 33: 20-30. Miller, P., and Ingham, J. G. (1976). Friends, confidants, and symptoms. Social Psychiatry. I1: 51-58. Nair, D., and Jason, L. A. (1984). An investigation and analysis of social networks among children. Poster session presented at the Midwestern Psychological Association annual convention, Chicago, Illinois. Pilisuk, M., and Minkler, M. (1980). Supportive networks: Life ties for the elderly. J. Soc. Issues 36: 95-I 16. Sandier, 1. N. (1980). Social support resources, stress, and maladjustment of poor children. Am. J. Community Psychol. 8: 41-52. Sarason, I. G., and Sarason, B. R. (1982). Concomitants of social support: Attitudes, personality characteristics, and life experiences. J. Personal. 50: 331-344. Sarason, 1. G., Levine, H. M., Basham, R. B., and Sarason, B. R. (1983). Assessing social support: The social support questionnaire. J. Personal. Soc. Psychol. 44: 127-139. Thoits, P. A. (1982). Conceptual, methodological, and theoretical problems in studying social support as a buffer against life stress. J. Health Soc. Behav. 23: 145-159. Walker, K. N., MacBride, A., and Vachon, M. L. S. (1977). Social support networks and the crisis of bereavement. Soc. Sci. Ailed. I1: 35-41. Weiss, R. S. (1976). Transition states and other stressful situations: Their nature and programs for their management. In Caplan, G., and Killilea, M. (eds.), Support Systems and Mutual Help: Multidisciplinary Explorations, Grune & Stratton, San Francisco (pp. 213-232). Wiesenfeld, A. R., and Weis, H. M. (1979). Hairdressers and helping: Influencing the behavior of informal caregivers. Prof. Psychol. 7: 786-792. Wilcox, B. L. (1981). Social support in adjusting to marital disruption: A network analysis. In Gottlieh, B. H. (ed.), Social Networks and Social Support, Sage, Beverly Hills, Calif., pp. 97-115. Youniss, J. (1983). Social construction of adolescence by adolescents and parents. In Groterant, H. D. and Cooper, C. R. (eds.), Adolescent Development in the Family. New Directions in Child Development (Vol. 22), Jossey-Bass, San Francisco, pp. 91-109.
