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12 Social Networks and Social Support Thomas Ashby Wills Marnie Filer Fegan Ferkauf Graduate School of Psychology and Albert Einstein College of Medicine This chapter considers how soci

12

Social Networks and Social Support

Thomas Ashby Wills Marnie Filer Fegan Ferkauf Graduate School of Psychology and Albert Einstein College of Medicine

This chapter considers how social support is related to physical health, including research on mortality, morbidity, and recovery from illness During the past 10 years there has been a large amount of research showing measures of social network structure, or measures of available supportive functions, to be related to various outcomes (Belle, 1989; S Cohen & Syme, 1985; I G Sarason, B R Sarason, & I G Sarason, 1988; Wills, 199Ob) During this time, there have been substantial advances in recognizing how beneficial social support can be; at the same time, this research has raised intriguing questions about how social support works

The theme of the chapter is how social support works, because at present this question is less understood A number of different mechanisms have been suggested as the basis for which an abstract social variable, social support, is related to objective physiological intermediaries (e.g., blood pressure) and to disease endpoints (e.g., mortality from myocardial

infarction) These suggested mechanisms are most interesting from the standpoint of health psychology because they represent an interface

between psychological theories of stress, coping, and affect, as well as physiological models of disease processes Although a plethora of

mechanisms has been suggested, the current evidence on the mechanism ofsupport effects is mixed and sometimes fragmentary, so at present there is

no consensus for seeing one particular mechanism as most likely Hence the goal here is to survey the range of evidence available on social support and

to suggest the relevance of possible mechanisms where they are indicated

by the evidence

This chapter is organized first by concepts about social support and then by areas of research It first defines basic concepts and discusses conceptual issues where debate is still occurring Then it describes the nature of five groups of mechanisms that have been postulated to account for the

relationship between social support and health, and discusses briefly the approach for testing each mechanism The chapter then covers evidence from several areas of social support research It begins by surveying

epidemiologic studies of morbidity and all-cause mortality, and then

considers research on social support effects for three specific disease conditions: cancer, diabetes, and renal failure The chapter then considers specific topics, such as social support effects among children and

adolescents, social support effects during pregnancy, and social support effects in elderly populations A final section summarizes the current

findings and discusses some questions for further research

CONCEPTS IN SOCIAL SUPPORT

RESEARCH

Social support is broadly defined as resources and interactions provided by others that may be useful for helping a person to cope with a problem

Under this broad definition, however, several different perspectives on socialsupport are encompassed, and these are reflected in different assessment approaches and research designs One point of divergence is whether support is conceptualized as the number of persons an individual knows, or whether support should be conceptualized as the amount of effective resources available to an individual, irrespective of the absolute number of friends and acquaintances Another area of divergence is whether it is adequate to obtain a global assessment of a person's support, or whether it

is necessary to measure specific dimensions of support

-209-provided by persons from different life domains, including spouse, friends, and workmates The broad definition also does not guarantee that social support is only effective for persons with many problems, because it is also possible that support is effective across the board, such that persons with relatively few problems show just as much benefit as persons with many problems Finally, the “may” in the broad definition allows the possibility thatinteractions regarded as supportive by the deliverer may not always be so perceived by the recipient (Coriell & S Cohen, 1995; Rook, 1990) These varying perspectives on social support have produced several different research approaches, each with its own advantages and limitations

Although we see some approaches as more useful than others, attention is given to all of these perspectives in the course of the chapter The following sections discuss some basic terms and concepts in detail

Structural Versus Functional

Measures

First is the distinction between structural and functional aspects of support Structural and functional measures involve different theoretical assumptionsabout the basis for effects of support, with structural measures giving emphasis to the total number of linkages people have in their community Structural measures assume it is the quantity of established, regular social connections that is important, and that the range of connections with different parts of the community may also be informative Structural

measures include items asking about the existence of primary social

relationships, such as being married or having relatives and children who live nearby They also tap frequency of visiting with neighbors and talking with friends, either in person or on the telephone (or, these days, by

Internet) Other items in typical structural measures tap the existence of normative social roles, such as being employed and belonging to communityorganizations These items can be combined to produce indices for the total size of a person's network, the number of different social roles a person occupies, and other indices such as the percent of kin in the network or the number of network members who know each other (Hall & Wellman, 1985) The goal of such indices is to provide a quantitative measure of the number

of social network connections Analyses for structural measures are typicallybased on the total score for social connections, but investigators have sometimes performed separate tests for component indices to determine whether particular types of social connections might be differentially

beneficial for men and women (e.g., Be&man & Syme, 1979; House,

Robbins, & Metzner, 1982) It should be noted that a structural measure does not ask about the quality of the existing relationships, nor does it ask about what resources the network members provide

Functional measures are based on the assumption that it is the quality of available resources that is most important, hence these measures aim to

assess the extent to which supportive functions are available to an individual(Wills, 1985) In contrast to structural inventories, functional measures ask about the availability of a particular function (e.g., ability to confide with somebody about problems and worries) They do not necessarily determine who the support comes from (although some inventories do assess

availability of emotional support from different sources), but rather focus on whether support is available if needed

Functional inventories typically include multi-item scales to assess the perceived availability of each of several supportive functions Scales for emotiond support (also termed appraisal, confiding, ventilation, or esteem support) have items that ask whether there are persons with whom you can share fears and worries, persons with whom you can talk about problems freely, and persons who make you feel understood and accepted Scales for instrumental support (also termed tangible, material, or practical support) ask whether there are persons who could provide assistance with financial problems (i.e., lending money), transportation, repairs, housework, or child care Scales for informational support (also termed advice, guidance, or feedback) include items asking whether there are persons available who canprovide useful information and can make suggestions about relevant

resources and alternative courses of action Scales for companionship support (also termed belonging) include items that ask whether there are persons available for companionship with various kinds of leisure activities, such as going to movies, sporting events, theaters or museums, hiking, or boating From these scales, subjects would receive a total score for

emotional support, for example, based on their cumulative responses to the availability of different aspects of this function It is typical to find scores for the different dimensions of functional support substantially correlated; for example, individuals with higher scores for emotional support also tend to have higher scores for instrumental and informational support Whether this

is attributable to perceptual factors, personality influences, or individual differences in the ability to recruit supporters has not been entirely worked out (see S Cohen, Sherrod, & Clark, 1986; Coble, Gantt, & Mallinckrodt, 1996); for this reason, investigators often test unique effects of different dimensions as well as the total functional support score

There are two interesting facts about structural and functional measures: They are not highly correlated, and they are both related to health

outcomes The first fact is initially puzzling to some, who assume that the more persons an individual knows then the more support they must have available The probable explanation for the low correlation of structural and functional measures is that the existence of a relationship does not provide much information about the quality of that relationship (Wills, 1991); it is possible that people with a relatively small social network may still have available a large amount of esteem support, instrumental support, and so

on, because of the nature of their relationships The fact that both structural and functional measures are related to health outcomes is still not well understood There are reasons to believe that structural and functional support contribute to health status through different mechanisms, but this question has not been entirely explicated

Main Effects Versus Buffering Effects

A second issue in social support research is whether social support is

primarily useful to persons experiencing a high

-210-level of life stress, or whether support is useful irrespective of a person's stress level The issue is a basic one for social support researchers because

it directs attention to the question of what kind of process is involved in the operation of support This question has been examined in studies that include both a measure of social support and a measure of life stress, and therefore can test for whether effects of support are dependent on stress level (S Cohen & Wills, 1985)

The first possibility is usually termed the main eflect model because it is demonstrated by a statistical main effect, indicating that support is equally beneficial to persons with low or high stress The second possibility, termed the bucffering is demonstrated by a Stress x Support interaction effect, indicating that the effect of support is much greater for persons at a high level of stress The terminology derives from the portrayal of support as a buffer that protects a person from the potentially adverse impact of negativeevents Whereas buffering effects have frequently been observed in studies that used good functional measures and sizable samples, main effects are more typical for structural measures, and a main effect model has been observed in some other conditions (S Cohen & Wills, 1985; Wills, 1991; Wills, Mariani, & Filer, 1996)

Matching of Functional Support

to Needs

A theoretical issue that has been prominent in research on functional measures is what is known as the matching hypothesis (S Cohen & McKay, 1984; Cutrona & Russell, 1990) Given the definition that support functions are useful for helping persons to cope with problems, the question arises concerning whether particular functions are best matched with specific needs; if so, then the availability of specific functional dimensions would be particularly helpful for persons who had a specific need For example, a subgroup of persons within the general population might have adequate self- esteem but experience high financial stress because of unemployment, low income, and so on In this case, it might be hypothesized that the availability of instrumental support, including financial aid or in-kind

services, would be the primary (or only) useful function for these persons Situations can be imagined in which functions such as emotional or

informational support would be most useful, and the effectiveness of the available support would depend on the match between the functions

provided by individuals' relationships and the needs evoked by their

problem

The status of the matching hypothesis remains an intriguing question for research There have been some studies showing that buffering effects occur only for situations predicted by the matching hypothesis (e.g., Peirce, Frone, Russell, & Cooper, 1996) However, studies with functional inventoriestypically find emotional support to be a broadly useful function (Wills, 1991),even in situations where it might not be expected to be particularly useful (e.g., Krause, 1987) Current research is trying to extend this work through delineating the support needs evoked by particular kinds of life events, and through developing and testing theory on how functional support actually works

Where support Acts in the Disease

Precess

A question of particular importance is where in the disease process social support acts Does it act primarily to prevent social acts Does it

development of risk factors among those who are healthy? Does it act to retard the onset of a clinical disease episode among persons who have accumulated risk factors? Or, does it reduce disease severity and speed recovery among those who have suffered a disease episode? Each of these models is important from a health standpoint, but would represent quite different modes of operation (Cohen, 1988)

An answer to the question depends on several types of findings If support were strongly related to incident disease (onset of new illness among those initially healthy), this would imply that the protective effect of support occurs early in the disease process If support were more strongly related to prevalent disease (cases of existing illness), this would im- imply that effects

of support occur later in the disease process, ply either through reducing theseverity of disease among those originally affected or by enhancing recoveryfrom disease

The question of where support acts in the disease process is not easily answered, because chronic diseases such as CHD have onset periods that span a decade or more, whereas infec- infectious diseases like as upper respiratory infection have a period tious of a few days from exposure to infection to recovery Long-termterm prospective research and short-term intensive and short-term primarily prevent model, intensive studies each have advantages and disadvantages, and accord- accordingly the question cannot be completely answered by any sin- ingly single study A full

understanding of the question requires gle cumulated findings from many sources, and is only beginning to emerge The most recent evidence has shown social sup- support strongly related to recovery from disease, but there is also port some evidence for protective effects of support at earlier points in disease processes This issue is discussed at several points in the chapter

THEORETICAL MECHANISMS AND

MODELS OF ANALYSIS

How is support related to health? In theory, social support could be related

to physical health through several different mechanisms These are not mutually exclusive but are discussed in terms of three general categories In addition, alternative theoretical mechanisms are appropriately analyzed through different statistical models The following section first describes two statistical issues relevant for testing different types of theoretical

mechanisms, and then discusses theoretical mechanisms through which social support is currently believed to operate

Statistical Models: Buffering Effect

Versus Main Effect

As noted earlier, support could be beneficial to persons irrespective of their stress level, or alternatively, support could be most useful to persons currrently experiencing a high level of stressful events Evaluating these modes of operation requires

-211-a study th-211-at includes reli-211-able me-211-asures of life stress -211-and soci-211-al support, h-211-as

this is sometimes termed a mediated relationship because the effect of social support is transmitted through the mediator ( Fig 12.2 B) Mixed models are possible, in which support has an indirect effect and also a significant direct effect (for more discussion see Wills & Cleary, 1996; Wills, McNamara, & Vaccaro, 1995)

Physiological Mechanisms

Seven mechanisms, which are illustrated graphically in various parts of Fig 12.3, are described with respect to theoretical mechanisms Two variant mechanisms posit that support acts directly on physiological variables One mechanism posits that the presence of other persons has a calming effect that is essentially innate because of evolutionary processes for social species Other things being equal, individuals would be more relaxed and in

a more positive affective state when other persons were around, compared with when they were alone or isolated from others This could be construed

as a direct effect in that relaxed states and positive affect could be related

to a range of physical variables conducive to health ( Fig 12.3 A)

The second mechanism posits that good support is related to better immunesystem functioning (e.g., more proliferative T4 cells or natural killer cells) through reducing levels of depression and anxiety in times of stress This would really be construed as an indirect effect because support acts on anxiety/depression which in turn acts on the immune system To analyze thismechanism it is necessary to show that support is related to lower

depression, which in turn is related to better immune system function, which

in turn is related to lower likelihood of infectious or other disease ( Fig 12.3

B)

Appraisal and Reactivity Mechanisms

For the appraisal mechanism, it is posited that the knowledge that support isavailable to cope with problems makes persons appraise stressors as less severe Because of the less severe threat appraisal, persons then would be less depressed/ anxious when subjected to life stressors This mechanism would be analyzed by measuring individuals' cognitive appraisals of stress and showing that these appraisals were linked to anxiety/depression This would be construed as an indirect effect because the buffering effect of support occurs through altering the cognitive appraisal ( Fig 12.3 C)

For the reactivity mechanism, it is posited that having support available makes persons less physiologically reactive (i.e., less change in heart rate and blood pressure) when subjected to acute stressors, and hence makes them less prone to disease conditions that are linked to cardiovascular reactivity, such as hypertension Unlike the direct calming effect, this mechanism should be relevant only in times of stress, and would be

analyzed by showing physiological reactivity was moderated by the

availability of social support ( Fig 12.3 D)

mediated effect

-213-to lower levels of harmful behaviors that are relevant for health risk ( Fig 12.3 E) For example, persons with high support could be less likely to smokecigarettes, or less likely to engage in heavy alcohol consumption and/or binge drinking (Wills, 1990a) In analyzing this mechanism it would be shownthat support is related to lower levels of smoking and alcohol use, and that substance use is the primary causal factor in relation to subsequent adverse health outcomes

Linkage to More Protective Behaviors Two variant mechanisms posit that social support is linked to patterns of behavior that lead to better health outcomes In one mechanism ( Fig 12.3 F), it is posited that support is related to more help seeking in times of stress and greater access to

preventive services in the community (e.g., cancer screening, regular physician visits) This would be expected to reduce mortality rates In analyzing this mechanism it would be shown that support was related to more help seeking and medical service utilization, and the latter was related

to physical health status (Wills & DePaulo, 1991) The second mechanism (

Fig 12.3 G) posits that having good social support enables persons to cope more effectively with problems and hence reduces anxiety/ depression in times of stress (Thoits, 1986) This mechanism would be analyzed by

showing that support is related to patterns of coping with problems, and coping in turn was related to less anxiety/depression and better physical health

has an indirect effect on immune function, mediated through

anxiety/depression (C) Support has an indirect effect on anxiety/depression,mediated through cognitive appraisal of stressors; anxiety/depression isthen related to health outcome (ID) Support reduces physiological reactivitywhen a stressor is encountered; reactivity is then related to health outcome.(E) Support is indirectly related to health status through a relation to health-harmful behavior, which is then related to the health outcome (F) Support isindirectly related to health status through a relation to preventive behavior,which is then related to the health outcome (G) Support is indirectly relatedthrough influencing coping, which then affects level of anxiety/depression

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These studies are discussed in some detail because they are essential for understanding the epidemiologic evidence on social support and health (House, Landis, & Umberson, 1988) The focus is on prospective studies in which a sample of participants is examined at a baseline measurement; the sample is then followed for a period of several years, and the health status

of the participants at the follow-up point is determined The studies typically include measures for demographics and baseline health status, used as

control variables to test the possibility that low support at baseline is attributable to a demographic third factor (e.g., low income) or is a

consequence of preexisting illness Significant effects of social support are commonly found with control for possible confounders, so all this evidence isnot discussed in detail This section first discusses studies of prevalent disease conducted with general population samples and samples of elderly persons, and then discusses studies on incident disease and recovery from illness

Social Networks and Mortality

in General Populations

A number of prospective studies using social network measures have been conducted, with follow-up periods ranging from 5 to 9 years (Berkman & Syme, 1979; Blazer, 1982; B S Hanson, J T Isacsson, Janzon, & Lindell, 1989; House et al., 1982; G A Kaplan et al., 1988; Orth-Gomer & Johnson, 1987; Schoenbach, B H Kaplan, Fredman, & Kleinbaum, 1986; Welin et al., 1985; Welin, Larsson, Svtirdsudd, Tibblin, & G Tibblin, 1992) The social network measures indexed the existence of a range of social connections as described previously The outcome was mortality status at follow- up as verified through death certificates, usually with close to 100%

ascertainment The results consistently showed number of social

connections to be inversely related to mortality rate, and although results tend to be stronger for men than for women, significant effects have been observed for both genders In some cases, the investigators analyzed the network measure as a total scale (e.g., G A Kaplan et al., 1988; Orth-Gomer

& Johnson, 1987), whereas in other studies analyses were performed both for the total network score and for each of the component items (Berkman &Syme, 1979; House et al., 1982) Most component items show significant relationships to mortality, indicating that effects are not simply driven by a particular aspect of social networks

Researchers have examined the question of whether the effect of social networks represents a gradient effect, with progressive reduction in

mortality for each higher level of social connections, or a threshold efict, such that elevated mortality is found only for persons with few social connections and no effects are observed at higher levels The studies are somewhat divided on this, with some investigators reporting results that resemble a threshold effect (e.g., House et al., 1982) However, other studies have shown a clear gradient effect, with a continous reduction in mortality rates across increasing levels of social connections (e.g., Berkman

& Syme, 1979; G A Kaplan et al., 1988; Welin et al., 1985), and some studies have found gradient effects for specific causes of death (e.g., cardiovascular disease) occurring together with threshold effects for

mortality from cancer (Welin et al., 1992) The repeated findings of gradient effects suggest that the protective effect of social network does not occur just for a small group of socially isolated persons

Functional Support and Mortality

Although the initial research in the area predominantly used structural measures, some studies have tested whether functional measures have value for predicting mortality Blazer's (1982) study of a U.S elderly sample included both structural and functional measures; results indicated that a measure of perceived support (e.g., availability of a confidant, availability of instrumental assistance) was a strong inverse predictor of mortality,

independent of a variety of demographic and biomedical controls Here the

structural measures were nonsignificant when tested with the functional measure, suggestive of an indirect effect, with social connections

contributing to greater emotional and instrumental support and the latter being proximal protective factors These findings were extended in Europeanstudies B S Hanson, J T Isacsson, Janzon, and Lindell (1989) included scales for the perceived availability and adequacy of emotional support and

of instrumental/informational support They found a significant effect for the former measure: Men with low emotional support had 2.5 times the risk of mortality over the study period, controlling for demographic status and a variety of biomedical variables

Buffering effects were analyzed with data for male participants from the Malmii study (Falk, B S Hanson, Isacsson, & Ostergren, 1992) Both

structural and functional measures were tested as possible buffers in

relation to a measure of stress from job strain The job stress measure itself showed a significant relationship to higher risk of mortality Results for the support measures showed a relative risk of 3.6 for men with high stress and low emotional support, and I 2 for those with high stress and high emotionalsupport; thus a buffering effect was demonstrated An analogous effect was found for the structural measure (termed social participation; from B S Hanson et al., 1989), with risks of 2.6 and 1.3, respectively Hence, in this study, both the structural measure and the functional measure showed evidence of buffering effects, although the measures were not analyzed together

A recent analysis from the Gothenburg study also tested for buffering effectswith an all-male sample (Rosengren, Orth-Gomer, Wedel, & Wilhelmsen, 1993) A measure of 10 negative life events was obtained at a baseline assessment together with an interview designed to assess the availability of emotional support from close relationships and from a variety of peripheral social relationships (termed social integration, but not directly analogous to

a social network measure) Over four levels of life events the range of mortality rates was 15.1 for men with low emotional support and 1.2 for menwith high emotional support; hence these data indicate a buffering effect of emotional support with respect to mortality For the social integration measure, no buffering effect was found

of social network measures for the health status of elderly persons For example, Seeman, G A Kaplan, Knusden, R Cohen, and Guralnik (1987) analyzed data from a 17.5 year follow-up of subjects from the Alameda County study who were age 38 or older at baseline They found that the overall social network index was inversely related to morality for both men and women A study conducted in an urban area in Finland (Jylha & Are, 1989) followed an urban sample and obtained multi-item scales for social contacts (Le., frequency of visiting) and outside- home social participation (similar to Welin's scale for outside-home activities) in addition to single-itemmeasures for marriage, children, and loneliness A continuous score for social participation was inversely related to mortality, again with significant

results for both men and women A study with a U.S national sample (Steinbach, 1992) found a social participation index prospectively related to lower likelihood of both institutionalization and mortality, and these findings were obtained with control for demographic characteristics and health status

at baseline Persons with higher social participation were half as likely to experience an adverse outcome Another study focusing on a sample of ruralelderly in France (Grand, Grosclaude, Bucquet, Pous, & Albarede, 1990) observed protective effects for a social network scale indexing membership

in community groups; a scale for close relationships (marriage and children) was marginally significant, but this was probably attributable to a sample size that was relatively small in comparison to other studies

Beneficial effects of social support have also been indicated in research conducted with Asian populations For example, Ho (1991) conducted a 2-year follow-up with a sample in Hong Kong age 70 or older Measures were obtained for marital status, social contacts, community integration,

participation in family and community events, and instrumental support All

of the social network indices were inversely related to mortality, but the instrumental support measure was nonsignificant A study based on a representative national sample of Japanese elderly (Sugisawa, Liang, & Liu, 1994) is of interest because the investigators tested for both direct and indirect effects of support This study used structural measures, including scales termed social contact (average frequency of visiting with children, relatives, and friends) and social participation (organizational membership and attendance), and also obtained a brief functional scale indexing the availability of caring and confiding The investigators tested whether supportmeasures were related to health status through intermediate variables including functional disability and cigarette smoking Some evidence for indirect effects was observed; for example, social contacts and social participation were inversely related to functional disability, and being married was inversely related to cigarette smoking The social participation scale showed a direct effect, that is, it was inversely related to mortality independent of all the intermediate variables (and of demographic and biomedical controls) These analyses suggest indirect effects for marriage and social contacts, operating through different pathways than the direct effect for social participation

Social Support and Incident Disease

The previous section covered studies that showed a relation between social support and prevalent disease (i.e., mortality from cardiovascular disease, cancer, or other causes) What evidence is there that social support is relevant for disease onset? This question is addressed by studies of incident disease, examining (in longitudinal research) whether social support predictsonset of new disease among those who were initially healthy

The number of studies on incident disease is still relatively small One is a study conducted in Honolulu, Hawaii, in which a cohort of males of Japanese ancestry was followed over 7 years (Reed, McGee, Yano, & Feinlieb, 1983) A nine-item structural scale assessed social connections with relatives,

coworkers, and religious and social organizations The social network score was significantly inversely related to existing disease at baseline (i.e., prevalent disease) and this was true for several types of disease including myocardial infarction and angina Analyses for 7-year onset of heart disease among those initially disease free showed social network to be inversely related to new disease, but analyses with biomedical controls reduced this effect to nonsignificance In contrast to this are findings from a study in

Gothenburg, Sweden (Orth-Gomer, Rosengren, & Wilhelmsen, 1993), where the study group was 736 men who were ascentained to be disease free at baseline and were followed up 6 years later Both a score for emotional support and a score for social integration were significantly inversely related

to incident heart disease, analyzed with biomedical controls The marginal results in the Honolulu study may have been attributable to the fact that heart disease is less common in Japanese populations, so the lower rates make it difficult to detect the smaller number of disease onset events

A study examining both prevalence, incidence, and survival from illness was conducted by Vogt, Mullooly, Ernst, Pope, and Hollis (1992), who followed a sample of HMO members over a 15-year interval and used medical records

to determine both prevalent and incident disease, including cardiovascular disease (ischemic heart disease, hypertension, stroke) and cancer A 26-iteminventory administered at baseline assessed social connections with family, friend, and community networks, and was scored for three indices termed network size, network scope, and frequency of interaction Health measures and outcomes were assessed through search of HMO records and state vital statistics The network scores were independent predictors of 15-year mortality; the strongest effect was for network scope, with a relative risk of 6.7 for those in the lower versus upper thirds of the distribution However, incidence analyses, predicting 15-year disease hazard among those disease free at baseline, were largely nonsignificant; only network scope was related

to significantly lower incidence for one disease These investigators

-216-were also able to analyze predictors of survival through examining the subsequent experience of persons with a new disease episode Findings indicated that higher network scores predicted increased survival; this was found for heart disease, cancer, and stroke The contrast between results forincidence and survival analyses drew attention to a possible role of social support for enhancing recovery from illness

Support and Recovery from

Illness

Because evidence showing social support inversely related to mortality is strikingly consistent but evidence for a relation of support to disease onset isminimal, the question of social support and recovery from illness assumes particular theoretical importance for understanding the way support

operates Evidence on this question is available from several previous studies and has been a focus of recent research In studies of recovery, the participants typically are patients recruited at the time of hospitalization for

a disease episode; the criterion variable is degree of recovery from disease

or survival time after an initial disease episode The available studies vary considerably in characteristics such as sample size, length of follow-up, and nature of the support measures Here emphasis is given to studies with larger samples and longer follow-up times, although some attention is given

to other studies that illustrate interesting points

A study with strong design characteristics was conducted by Williams et al (1992) The investigators followed a large sample of patients for an average

of 9 years after intake At intake all the participants had significant coronary artery disease, as indicated by angiography findings showing greater than 75% stenosis of at least one major mistery The support indices included being married, having a confidant, with friends and relatives The predictive

analyses focused on survival time after intake and included a medical risk score composed from 10 physical variables measured at intake and shown empirically to be significant predictors of survival Results showed that patients who were unmarried and without a confidant had a significantly lower survival rate (50%) compared with those having high support (82%); control analyses showed this result was independent of medical risk and of the patient's economic resources The findings of Williams et al (1992) were consistent with a study of an all-male sample followed for 3 years

(Ruberman, Weinblatt, Goldberg, & Chaudhry, 1984), which found elevated mortality for persons with a high score on life stress and a low score for social networks (based on visiting friends and relatives, and belonging to a social club, fraternal organization, church, or temple) This latter result suggests a stress buffering effect for social networks, but Ruberman et al (1984) did not conduct a formal test for interactions Other studies have used

a specific indicator, marital status, and have indicated that survival times after myocardial infarction are longer for married individuals (Chandra, Szklo, Goldberg, & Tonascia, 1983; Wiklund et al., 1988) It is noteworthy that several of these studies found significant protective effects of support for both men and women

A report by Berkman, Leo-Summers, and Horwi (1992) from their study of elderly persons is of interest because it is based on a community sample followed over time (as in Vogt et al., 1992) These investigators focused on agroup of 165 participants who were hospitalized for acute myocardial infarction during the ongoing study A noteworthy aspect is that the support measures were from an interview conducted prior to the illness episode, unlike other studies where support measures were typically obtained after hospitalization; so these data are truly prospective Support measures included a social network index and a three-level functional index reflecting the number of persons who were available to talk about problems Results showed that persons with greater emotional support were more likely to survive over a 6-month period, and emotional support was related to

survival at all points during the follow-up interval Persons with high support times as likely to survive compared to those with low support, an effect size comparable to effects for several medical risk factors measured in the study

A similar trend was noted for the social network index but was not

significant

Several studies have obtained criterion measures directly assessing the patient's extent of recovery from heart disease, such as physical activity limitations and recurrent symptomatology King, Reis, Porter, and Norsen (1993) measured different aspects of functional support in a sample of coronary artery surgery patients followed for 1 year after the operation Predictive analyses showed esteem and companionship support most consistently related to outcomes (i.e., greater well-being, less functional disability, fewer angina symptoms); some effects were also observed for instrumental support Helgeson (1991) obtained structural and functional measures with a sample of myocardial infarction patients followed for 3 months to 1 year after the illness A functional measure (emotional support from spouse) was inversely related to angina symptoms and

rehospitalization and positively related to perceived health; the structural measure was not significantly related to any criterion A series of reports by Kulik and Mahler (1987, 1989, 1993) was based on a sample of patients recovering from coronary bypass surgery The investigators obtained a measure of general emotional support from spouse through a rating of marital satisfaction and a recording of the proportion of days the spouse visited the patient in the hospital Results showed that the combination of good marital relationship and high visiting was related to less pain

medication usage after surgery and faster release from the hospital Data

from 13-month follow-up indicated emotional support predicted better quality of life, more ambulation, and less cigarette smoking at follow-up Marital status was not significant in these analyses when its correlation with emotional support was statistically controlled, suggesting an indirect effect

It should be noted that functional support is also related to recovery from mental illness, with or without concomitant psychotherapy (see, e.g., killings

& Moos, 1985; Cross, Sheehan, & Khan, 1980; Dadds & McHugh, 1992; Moos, Finney, & Cronkite, 1990), but there is relatively little research on this topic

Research on social support and recovery from cancer is more complex (see Helgeson, S Cohen, & Fritz, 1998; Reifman, 1995) The epidemiologic research in this area has been dominated by studies of marital status, which

is at best a

-217-

proxy for functional support The literature includes a study of 1, 262

persons followed for a lo-year period, which found marriage related to longersurvival time for breast cancer (Neale, Tilley, & Vernon, 1986), and a study

of 25, 706 cases with various types of cancers (J= S Goodwin, Hunt, Key, & Samet, 1987), which found a survival advantage for married persons, controlling for the fact that married persons were likely to be diagnosed at

an earlier stage of cancer (which suggests a behavioral mechanism)

However, several studies have found no significant survival effect for maritalstatus (e.g., Cassileth et al., 1985; LeMarchand, Kolonel, & Nomura, 1984), and although these tend to be with smaller samples with more severe disease and shorter follow-ups, they indicate some inconsistency in the literature

Marital status is only one index of social connections, so it is important to discuss studies that have obtained more extensive measures of social networks Two studies have found social network measures related to longer survival time, one with a sample of 208 patients followed for 20 years (Funch

& Marshall, 1983) and one with a community-based sample of 339 cancer cases followed for 17 years (Reynolds & G A Kaplan, 1990) This research isaugmented by evidence from studies with smaller samples and follow-ups, which show cancer survival time related to measures of social participation (Hislop et al., 1987), contacts with friends (Waxler-Morrison, Hislop, Mears, &Kan, 1991), and social integration (Ell, Nishimoto, Mediansky, Mantell, & Hamovitch, 1992) These studies found social network measures predicted survival time with control for demographics and for medical variables such

as stage at diagnosis The minimal evidence for support effects on cancer incidence (Helgeson & Cohen, 1996) contrasts with the general robustness

of findings on survival time, and indicates this as a promising area for investigation

SPECIFIC AREAS OF RESEARCH

The following sections discuss some specific areas of research on social support The aim of this section is both to show the scope of research effortsand to give consideration to the mechanisms of how support works

Specific Disease Conditions

Social Support and Adjustment tu Cancer The potential role of social support

for helping persons with cancer has been a significant focus of research Thishas been true both because of the severity of the disease and because adjustment involves both issues of coping with emotional distress and of dealing with interpersonal relationships Research on how social support facilitates adjustment to cancer has included studies on specific support functions as well as several intervention studies with peer support groups (see Helgeson & S Cohen, 1996)

Several studies have examined how supportive functions from family members and medical professionals may be relevant for persons with cancer These studies concur in finding that emotional support is the

function desired from family members, particularly with respect to

discussing fears and concerns about the disease (Dakof & Taylor, 1990; Dunkel-Schetter, 1984; Rose, 1990) In contrast, patients want informational support from medical professionals but do not want it from family members

An important aspect of this research has been the finding that emotional support may be inhibited in family settings through a reluctance of family members to talk about the disease, because of fear that it will be upsetting

to the patient; but it is exactly this aspect of support that patients

themselves say they find most helpful Probably for this reason, the patients

in these studies rate emotional support from family members as helpful but sometimes inadequate, and report they may keep their thoughts and feelings to themselves because other people do not want to hear them

Social support has been shown related to indices of better adjustment to illness, such as reduced anxiety, increased self-esteem, or better functional ability Emotional support has been found related to better adjustment in breast cancer patients in both concurrent studies (e.g., Zemore & Shepel, 1989) and longitudinal research (e.g., Northouse, 1988) In the few studies that compared different support functions, emotional support is typically shown to be related to adjustment but effects for instrumental support are sometimes nonsignificant (e.g., Primomo, Yates, & Woods, 1990) It should

be noted that there has been little research using multidimensional

functional inventories with good psychometric properties, and conclusions about the differential effects of support functions accordingly are somewhat qualified Investigators have suggested that effects of emotional support on adjustment to illness are mediated through reduced emotional distress and improved coping (cf Ell et al., 1992) Although this inference is plausible, explicit mediation tests of these mechanisms have not been conducted The evidence showing support measures related to reduced emotional distress and increased survival has motivated several intervention studies designed to enhance the well-being of cancer patients Methodological characteristics in this literature are quite variable and several studies used brief interventions or lacked reasonable control groups (see Helgeson & S Cohen, 1996) Two studies with true randomized designs and intensive interventions have shown positive results A notable study by Spiegel, Bloom, Kramer, and Gottheil(1989) involved a peer support group conductedover a 1-year period for patients with advanced breast cancer The group sessions were facilitated by a professional leader and were intended to provide emotional support through frank sharing of feelings and

experiences, as well as expressions of reassurance and caring A lo-year follow-up of the sample found that support group participants had

significantly increased survival time compared with control participants Analyses were conducted to test whether the survival advantage was attributable to reduced emotional distress, but these results were

inconclusive

A randomized study by F I Fawzy et al (1990, 1993) was conducted for patients with melanoma The patients received education about the disease,received instruction from staff members about stress reduction and coping strategies, and

-218-participated in group discussion withother patients and a group facilitator Results indicated that patien ts who received the intervention showed reduced psychological distress, enhanced immune system function (e.g., natural killer cell activity), and increased survival at 6 years Similar to the Spiegel et al (1989) study, this research involved a true randomized design, and the results of these two studies together have been provocative

This discussion is not meant to minimize the impact of educational

interventions, which focus on providing information about the disease and its treatment These have been shown to have a significant effect on

treatment compliance and survival time in cancer patients (e.g., Richardson

et al., 1987; Richardson, Shelton, Krailo, & Levine, 1990) Some studies included group educational experiences (Helgeson & S Cohen, 1996) and a study by Helgeson, Cohen, Schulz, and Yasko (1999) found a group

education condition had more beneficial effects than a peer support

condition

Social Support and Adjustment to Arthritis Arthritis is a chronic disease that involves unpredictability and interference with daily activities as well as recurrent pain Supportive relationships, particularly with spouses, may be relevant for facilitating adjustment to the disease (Melamed & Brenner, 1990; Revenson, 1994) As in studies of cancer patients, investigators have examined what types of interactions with spouses or friends are perceived

as supportive or nonsupportive For example, Lanza, Cameron, and

Revenson (1995) interviewed arthritis patients about perceptions of recent support episodes Coding of responses indicated that instrumental support was most frequently reported as helpful (e.g., “friend came and cleaned my whole house”); emotional support was second (e.g., “Spouse understood how I felt”) In the category of unhelpful episodes, lack of instrumental support was mentioned most often (e.g., “Husband expected me to do the laundry which I couldn't”), whereas critical remarks and lack of

understanding were mentioned less often Comparable to other studies, spouses were mentioned as most often providing helpful emotional support and physicians as providing helpful instrumental support

Studies of the contributions of support to adjustment among arthritis

patients have included several types of outcomes Functional measures are shown to be related to higher self-esteem (Fitzpatrick, Newman, Lamb, & Shipley, 1988), more positive affect (Affleck, Pfeiffer, Tennen, & Fifield, 1988), and greater life satisfaction (Smith, Dobbins, & Wallston, 1991) In addition, longitudinal studies have shown social support related to

decreased depression over time (Brown, Wallston, & Nicassio, 1989;

Fitzpatrick, Newman, Archer, & Shipley, 1991; Smith & Wallston, 1992) Goodenow, Reisine, and Grady (1990) compared a social network measure with a composite functional measure for predicting several outcomes They found that the functional measure was related to better adjustment in home and family domains For predicting depression, the social network index was inversely related to depression in zero-order correlations, but this effect disappeared when the functional measure was added; this implies that the effect for the structural was mediated through greater functional support

In a somewhat different design, Revenson and Majerovitz (199 I) studied spouses of arthritis patients, comparing a measure of received support from the spouse with a measure of received support from network members The study tested buffering effects of support measures for the stressor of disease severity Results showed a buffering effect for network support but not for spouse support In this case, the measures were for received support (not perceived availability of support) and the support provider was ill, so it

is not clear whether these data are contradictory to the other study A related study (Revenson, Schiaffino, Majerovitz, & Gibofsky, 1991) showed independent, opposite effects for supportive behaviors (positively related to adjustment) and problematic interaction behaviors, negatively related to adjustment This study also found an interaction, with depressive symptoms particularly elevated among persons receiving less supportive behaviors andmore problematic behaviors

Indirect effects were tested by Manne and Zautra (1989), who investigated mediational effects for different aspects of support These investigators obtained a measure for a lo-item composite of emotional and instrumental responses presumed to be helpful for persons with arthritis, together with anindex of responses predicted to be unhelpful, namely, the number of critical remarks made by the spouse during an interview Analyses indicated

independent and opposite contributions for the two scales; support was related to better adjustment and criticism was related to worse adjustment The authors tested for mediation and found that the support score was related to more cognitive coping (which was related to better adjustment) whereas criticism was related to more avoidant coping (which was related toworse adjustment) Thus mediation of support effects through coping was demonstrated and different pathways were demonstrated for supportive andunsupportive behaviors

Social Support and Adjustment to Diabetes Diabetes is a chronic illness in which extensive self-care efforts are necessary, and failure to comply with the daily preventive regimen may lead to adverse physical complications Because glucose metabolism may be upset by negative emotional states and the preventive regimen for diabetes involves continued interactions withother persons, social support may be of considerable relevance for

adjustment to this disease condition

A study by Littlefield, Rodin, Murray, and Craven (1990) examined buffering effects of social support on depression among a sample of individuals with Type I diabetes, using a measure of stress from disease-related disability Marital status was used as the structural measure A functional index was obtained through an inventory for emotional and instrumental support; this was analyzed as a difference score assessing the discrepancy between the amount of support patients desired and the amount of support they

received The majority of respondents (70%) thought they received as much support as they needed, or more; hence the discrepancy score distribution was cut into a group with a positive discrepancy score (labeled as adequate support) and a group with a negative discrepancy

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score (labeled as inadequate support) Multiple regression analysis indicated

a Support x Disability interaction effect: Disability was strongly related to depression among persons with inadequate support, but the effect of disability was considerably reduced for persons with adequate support These results show a buffering effect of functional support