Sot. Sci. Med. Vol. 34. No. 7,pp.779-788. 1992 Printedin Great Britain. 0277-9536/92 165.00 f0.00 Pergamon Press plc SOCIAL RELATIONSHIPS AND HEALTH: THE RELATIVE ROLES OF FAMILY FUNCTIONING AND SOCIAL SUPPORT PETER FRANKS,’ THOMAS L. CAMPBELL’.’ and CLEVELAND G. SHIELDS’.* Departments of ‘Family Medicine and 2Psychiatry, University of Rochester, Family Medicine Center, 885 South Avenue, Rochester, NY 14618, U.S.A. Abstract-The associations between social relationships and health have been examined using two major research traditions. Using a social epidemiological approach, much research has shown the beneficial effect of social supports on health and health behaviors. Family interaction research, which has grown out of a more clinical tradition, has shown the complex effects of family functioning on health, particularly mental health. No studies have examined the relative power of these two approaches in explicating the connections between social relationships and health. We hypothesized that social relationships (social support and family functioning) would exert direct and indirect (through depressive symptoms) effects on health behaviors. We also hypothesized that the effects of social relationships on health would be more powerfully explicated by family functioning than by social support. We mailed a pilot survey to a random sample of patients attending a family practice center, including questions on depressive symptoms, cardiovascular health behaviors, demographics, social support using the ISEL scale, and family functioning using the FEICS scale. FEICS is a self-report questionnaire designed to assess family emotional involement and criticism, the media elements of family expressed emotion. Eighty-three useable responses were obtained. Regression analyses and structural modelling showed both direct and indirect statistically significant paths from social relationships to health behaviors. Family criticism was directly associated (standardized coefficient = 0.29) with depressive symptoms, and family emotional involvement was directly associated with both depressive symptoms (coefficient = 0.35) and healthy cardiovascular behaviors (coefficient = 0.32). The results support the primacy of family functioning factors in understand- ing the associations among social relationships, mental health, and health behaviors. The contrasting relationships between emotional involvement and depressive symptoms on the one hand and emotional involvement and health behaviors on the other suggest the need for a more complex model to understand the connections between social relationships and health. Key words-social support, family functioning, depressive symptoms, health behavior INTRODUCTION The social support literature had provided much information on the association between social re- lationships and health [l-3]. Most of this literature has relied on self-report measures of social support, suggesting that it is the perceived level of social support that is assessed. Large epidemiological studies, particularly those examining the relationship between social support and mortality have tended to treat social support as a unitary concept [2]. Other studies have examined components of the concept such as social network composition and size, and emotional and instrumental support [4]. However, there is very little accepted theory about how social support or its components exerts its beneficial effect [2, 5-81. Social support is seen as either directly [9] promoting health and health behaviors or as buffer- ing the adverse effect of stressors [IO]. There is controversy in the social support literature whether the direct effect or the buffering effect is moreimport- ant [l 1, 121. Whether social support is seen as having one or several dimensions, or having a direct or buffering influence on health, most social support theorists view the effects of social support on health as purely beneficial. That is, the worst situation is an absence of social support, and incremental amounts of social support bring incremental health benefits. Social exchange theorists, on the other hand, have emphasized [ 131that social interactions entail costs as well as rewards. In other words social relationships are not necessarily exclusively beneficial. Social ex- change theory posits that humans rationally attempt to maximize their rewards and minimize their losses. Presumably some metric of the relative balance of the rewards and costs of social relationships determines their net effect on health [14]. Consistent with this theory is a small but growing literature that suggests that stressful, negative, or upsetting interactions, though less frequent than positive interactions (or social support), are more important in their effect on psychological well-being [ 15-221. These research findings and social exchange theory have broadened our understanding of the complexity of the effects of social relationships on health. Theories about family functioning are more devel- oped, but have been applied mostly to mental health problems. Understanding the relationship between family functioning and health offers great promise as a model to explain the effects of social relationships 779
Transcript
Sot. Sci. Med. Vol. 34. No. 7, pp. 779-788. 1992 Printed in Great Britain.
0277-9536/92 165.00 f0.00 Pergamon Press plc
SOCIAL RELATIONSHIPS AND HEALTH: THE RELATIVE
ROLES OF FAMILY FUNCTIONING AND SOCIAL
SUPPORT
PETER FRANKS,’ THOMAS L. CAMPBELL’.’ and CLEVELAND G. SHIELDS’.* Departments of ‘Family Medicine and 2Psychiatry, University of Rochester, Family Medicine Center,
885 South Avenue, Rochester, NY 14618, U.S.A.
Abstract-The associations between social relationships and health have been examined using two major research traditions. Using a social epidemiological approach, much research has shown the beneficial effect of social supports on health and health behaviors. Family interaction research, which has grown out of a more clinical tradition, has shown the complex effects of family functioning on health, particularly mental health. No studies have examined the relative power of these two approaches in explicating the connections between social relationships and health. We hypothesized that social relationships (social support and family functioning) would exert direct and indirect (through depressive symptoms) effects on health behaviors. We also hypothesized that the effects of social relationships on health would be more powerfully explicated by family functioning than by social support. We mailed a pilot survey to a random sample of patients attending a family practice center, including questions on depressive symptoms, cardiovascular health behaviors, demographics, social support using the ISEL scale, and family functioning using the FEICS scale. FEICS is a self-report questionnaire designed to assess family emotional involement and criticism, the media elements of family expressed emotion. Eighty-three useable responses were obtained. Regression analyses and structural modelling showed both direct and indirect statistically significant paths from social relationships to health behaviors. Family criticism was directly associated (standardized coefficient = 0.29) with depressive symptoms, and family emotional involvement was directly associated with both depressive symptoms (coefficient = 0.35) and healthy cardiovascular behaviors (coefficient = 0.32). The results support the primacy of family functioning factors in understand- ing the associations among social relationships, mental health, and health behaviors. The contrasting relationships between emotional involvement and depressive symptoms on the one hand and emotional involvement and health behaviors on the other suggest the need for a more complex model to understand the connections between social relationships and health.
Key words-social support, family functioning, depressive symptoms, health behavior
INTRODUCTION
The social support literature had provided much information on the association between social re- lationships and health [l-3]. Most of this literature has relied on self-report measures of social support, suggesting that it is the perceived level of social support that is assessed. Large epidemiological studies, particularly those examining the relationship between social support and mortality have tended to treat social support as a unitary concept [2]. Other studies have examined components of the concept such as social network composition and size, and emotional and instrumental support [4]. However, there is very little accepted theory about how social support or its components exerts its beneficial effect [2, 5-81. Social support is seen as either directly [9] promoting health and health behaviors or as buffer- ing the adverse effect of stressors [IO]. There is controversy in the social support literature whether the direct effect or the buffering effect is moreimport- ant [l 1, 121. Whether social support is seen as having one or several dimensions, or having a direct or buffering influence on health, most social support theorists view the effects of social support on health
as purely beneficial. That is, the worst situation is an absence of social support, and incremental amounts of social support bring incremental health benefits.
Social exchange theorists, on the other hand, have emphasized [ 131 that social interactions entail costs as well as rewards. In other words social relationships are not necessarily exclusively beneficial. Social ex- change theory posits that humans rationally attempt to maximize their rewards and minimize their losses. Presumably some metric of the relative balance of the rewards and costs of social relationships determines their net effect on health [14]. Consistent with this theory is a small but growing literature that suggests that stressful, negative, or upsetting interactions, though less frequent than positive interactions (or social support), are more important in their effect on psychological well-being [ 15-221. These research findings and social exchange theory have broadened our understanding of the complexity of the effects of social relationships on health.
Theories about family functioning are more devel- oped, but have been applied mostly to mental health problems. Understanding the relationship between family functioning and health offers great promise as a model to explain the effects of social relationships
779
780 PETER FRANKSU al.
on health. There are two reasons for this. First, the family contributed the primary and most central experience that we have of social relationships [23, 241. This experience provides a crucial behavioral model that affects all our other social relationships. The family of origin and then subsequent family relationships developed in adult life continue to be our principal experience of social relationships. The hypothesized central role of the family in social relationships derives from intergenerational family systems theory [25,26]. The theory proposes that the influence of the family of origin is sustained whether or not the person continues to interact with the family. The influence is constituted by the individual’s current perceptions of the characteristics and quality of those family relationships. The crucial role of the family is exemplified even in the social support literature by the dominant place given to family related items in many instruments measuring social support and networks. In addition, studies on the relationship between social support and mortality have shown that marital status is the most consistent variable affecting mortality [27-291.
Second, theories about the family have been devel- oped from clinically important features of inter- personal relationships in families. They thus may provide a more complete understanding of the specifi- city and complexity of the effects of social relation- ships on health. For example, the family therapy literature has drawn attention to the adverse effect of family interactions characterized by critical com- ments and emotional overinvolvement (or Expressed Emotion) on patients with depression [30-351 and schizophrenia [36-381.
We report here on some results of a pilot study investigating the connections between social relation-
ships and cardiovascular health. Social relationships are defined as the social connections perceived by the individual. The purpose of this study is to help elucidate how social relationships influence cardio- vascular health. This paper focuses on cardiovascular health behaviors and depression. We were interested in studying depressive symptomology for two reasons. First, depressive symptoms have been shown to influence health behaviors [39-42]. Second, the effects of social relationships on emotional well-being and in turn on neuro-endocrine and psycho- immunologic pathways may be an important mech- anism by which social relationships affect physical health [4345].
We examined three hypotheses. First, we hypoth- esized (Fig. I) that social relationships would exert a direct effect on health behavior through the instru- mental and emotional benefits afforded by social support [46-49] and as a manifestation of social control exerted primarily through the family [X%53].
Second, we hypothesized that there would be an indirect effect because of the impact of social relation- ships on mood states, which in turn affect health behaviors. Specifically, detrimental social interactions would result in depressive symptoms that in turn would adversely affect health behaviors. These path- ways are well documented. Depressive symptoms have been strongly associated both with an adverse family environment (30-35, 541 and with low levels of social support [3,9, 12,55-571. Depressive symptoms also have a detrimental effect on change toward and maintenance of healthy cardiovascular behaviors. especially smoking [39%42].
Finally, as discussed above, we anticipated that family interactions would have a greater effect than general social support on depressive symptoms and
Social Relationshios: Social Support Family Functioning
Fig. I. Hypothesized relationships examined in study.
Social relationships and health 781
health behaviors. The few studies that have compared the relative effects of family and other social support on both depressive symptoms [22,58] and health behaviors [59,60] have shown that the family is the more powerful influence. In other words, and follow- ing intergenerational family systems theory, we view the individual’s perception of social support as a reflection of a more fundamental process; namely, perceived social support reflects the current percep- tion of the character and quality of family relation- ships. Because family interactions characterized by high levels of critical comments and intense emotional involvement (or expressed emotion) have been found to affect profoundly the course of depression [30-351, we chose this domain as our measure of family function.
METHODS
Sample
The population base was comprised of patients receiving primary medical care at the University of Rochester Family Medicine Center. The sample was derived from a database that is being used to monitor cardiovascular health, Patients were eligible for in- clusion in the sample if they had a cholesterol value in the database, had made at least two visits in the 18 months before July 1990, and were at least 40 years of age. In households where two or more eligible patients lived, one household member was randomly selected. These criteria identified 1745 patients. A 10% random sample (182 patients) was selected for this pilot study. To make the results as generalizable as possible, unmarried patients and those living alone were included.
Procedures
We used a modified version of Dillman’s total design method [61] to conduct the survey. The ques- tionnaire with a cover letter was mailed to patients in July 1990; two weeks later a post card reminder was sent to non-responders; and at four weeks a follow-up letter and a replacement copy of the questionnaire was mailed to non-responders. We did not send an additional mailings by certified mail at 7 weeks as suggested by Dillman [61].
Instruments
I. Family Emotional Involvement and Criticism
Scale (FEICS). This scale (see Appendix) measures by self report the important components of Expressed Emotion, namely critical comments and emotional overinvolvement. The instrument comprises 14 items, 7 each measuring the subscales intensity of emotional involvement and perceived criticism. SeparaTe analy- ses showed that the FEICS had adequate psycho- metric properties: Cronbach’s alpha for the perceived criticism subscale was 0.82, and 0.74 for the emotional involvement subscale.
2. Symptom Check List-PO (SCL-90). This ninety item scale [62] measures nine psychiatric symptom constructs. We used the 13 item depressive symptom subscale. Cronbach’s alpha for the depressive symptoms subscale is 0.90 [63].
3. Social support. Orth-Gomer and Unden [4] have pointed out that the choice among the various social support instruments is difficult. In their review they identified two groups of instruments, those measuring quantitative aspects of social network and social interactions, and those describing the functions and quality of social support. The former have uncertain psychometric properties, but have been found to predict health outcomes. Qualitative instruments have been tested for psychometric properties but have been little used in predicting health ourcomes. In addition, some instruments have questions that limit their application to general populations. House et al.
[2] have emphasized the need to explicate the way in which social support influences health. For this reason we chose to use an instrument, the Inter- personal Support Evaluation List (ISEL), that focuses on the function and quality of social support, yet is applicable to a general population. It has excellent reliability and validity, including studies using depressive symptoms [64,65] and health behavior change [46] as measures of criterion related validity. The instrument does not distinguish the sources of social support (family, friends or co- workers). This facilitates assessing the relative contribution of the two methods of evaluating social relationships (social support and family functioning). We chose not to use instruments that have been developed to measure supportive behaviors specific to particular health behaviors [46-48,60] so that the analysis would be more generalizable. ISEL is a 40 item scale measuring four constructs related to social support: tangible, belonging, appraisal, and self- esteem. We omitted the self-esteem subscale, because it seems more a measure of self-esteem than social support.
4. Negative life events. The undesirable life event items from Holmes and Rahe’s scale [66] were used. Respondents were asked to consider only life events occurring in the previous 3 months. Although the scale has undesirable psychometric qualities [67], versions of the scale using equal weight- ing of undesirable events have been shown to have predictive validity [68-701. An additional problem with the life events scale used in a cross-sectional study is that significant losses are reflected in both the life events scale and as losses in social support, and social network. However, the measurement of life events was considered essential in this study since negative life events have such a powerful influence on depressive symptomology. We do not consider that these complex effects confound discernment of the relative influence of social support and family interactions on depressive symptoms or health behaviors.
782 PETER FRANKS er al.
5. Demographic variables. Age, sex, education and income.
6. Index of healthy cardiovascular behatliors. A summary score was created, one point each for not smoking, getting any regular exercise (based on a positive response to the question ‘In your spare time, do you exercise or play sports on a regular basis?‘), not being obese (based on being less than 120% above ideal body weight derived from the patient’s height and weight in the cardiovascular database), and eating a diet low in animal fats and cholesterol. Respondents were asked to indicate how many times per week they consumed each of the following: red meat, fried foods, whole milk, eggs, butter and cheese excluding cottage cheese. A low cholesterol diet was defined as consuming these foods less than 3 times per week averaged over all items.
Analyses
To examine the study hypotheses, variable were grouped as outcome variables (depressive symptom score, and index of healthy cardiovascular behav- iors), social relationship variables (FEICS and ISEL), and background variables, including demographics (age, sex, education and income) and negative life events. Three methods of analyses were used. First, the correlations of each variable with depressive symptom scores and the index of healthy cardio- vascular behaviors were examined. Second, two sets of regression analyses were conducted to correspond to the study hypotheses. The high inter-correlations of the ISEL subscales (all r > 0.65) resulted in the problem of multicollinearity. Because there was no apriori hypothesis about which of the ISEL subscales should be most critical, the analyses determined the subscale or combination of subscales that accounted for most of the variance. Observations with missing data were omitted from the multivariate analyses.
Finally, structural equation modelling was used to examine the hypothesized model expressed in Fig. I and both regression equations. Besides allowing measurement of the relative strengths of the various paths in the model, structural equation modeling provides several measures of goodness-of-fit of the model to the data. Other models with additional constraints also can be examined. We considered other models in an iterative fashion starting with the original hypothesized model. This was done to obtain a more parsimonious model to help interpretation and to improve the model fit. Non-significant (P > 0.05) paths were eliminated in a stepwise man- ner, the least significant remaining path being chosen in turn. The Wald test was used to decide whether elimination of that path contributed to model fit. This process was repeated until the paths of the remaining variables provided an optimum fit OT the data. Paths that were not statistically significant (P > 0.05) were retained if they contributed to the overall fit of the model or their inclusion was justified on substantive grounds. The analysis reported here was implemented
using the CALIS procedure in the SAS system [7l]. Observations with missing data were omitted from this analysis.
RESULTS
Of the 182 questionnaires mailed, IO1 (55%) were completed and returned, 12 additional questionnaires were returned undeliverable, or blank. Those that did not complete the questionnaire did not differ statistically significantly from respondents in age, sex, insurance, blood pressure, or cholesterol. The charac- teristics of the sample are shown in Table 1. This is an older population with the average age of 55.5 years of age. Of note, 42% were married and 35% lived alone.
An additional 18 people did not complete the family items (FEICS). Compared with those who did complete the family items (IV = 83), those who did not (N = 18) were more likely to be unmarried (87% vs 52%), and have smaller family networks (mean 2.4 vs 4.7). There were no other statistically significant psychosocial or demographic differences.
Income and the three social support subscales were inversely correlated (P < 0.05) with depressive symp- toms, whereas perceived criticism and negative life events were directly correlated (P < 0.05) with depressive symptoms (Table 2). None of the other variables exhibited a statistically significant relation- ship with depressive symptoms in this univariate analysis.
When depressive symptom score was regressed on the background variables and the social relationship variables, perceived criticism, emotional involvement, and negative life events all made independent positive contributions (P < 0.05) to the equation (Table 3). There was a non-significant trend (P = 0.09) for appraisal of social support to exert a protective effect. The adjusted R’ for this equation was 41%.
Table I. Summary Statistics of main variables examined
Ps~chorocial and behacioral mriables Depressive symptoms Perceived criticism Emotional involvement Tangible social support Belonging social support Appraisal social support Life events Index of healthy behaviors
Mean
55.50 32 12.75
27 15 17 15 25 42 35
I .97 I .69 3.06 1.64 1.70 I .66 1.00 2.28
SD
12.63
3.56
0.72 0.67 0.92 0.5s 0.56 0.62 I .46 1.01
Social relationships and health 783
Table 2. Correlations of study variables with depressive symptom scores and index of healthv cardiovascular behaviors
Variable
Age (yr) Sex (Female coded I) Income (S) Education (yr) Negative life events Emotional involvement Perceived criticism Appraisal social support Tangible social support Belonging social support Deoression
Depressive symptom (P)
-0.01 (0.96) 0.14(0.16)
-0.32 (0.00) -0.06 (0.55)
0.47 (0.00) 0.09 (0.42) 0.38 (0.00)
-0.28 (0.01) -0.24 (0.02) -0.27 (0.01)
-
Index of CV behavior (P)
-0.08 (0.43) -0.19 (0.05)
0.30 (0.00) 0. I3 (0.20)
-0.27 (0.01) 0.25 (0.02)
-0.14(0.20) 0.04 (0.66) 0.06 (0.56) 0.07 (0.50)
-0.34 (0.00)
Table 3. Regression of depressive symptom scores on social relationship variables, and background variables (N = 83)
Variable
Parameter estimate (95% confidence
interval) Standardized
coefficient (SE) P
Age Female sex Income Education Negative life events Emotional involvement Perceived criticism Appraisal social support
When the index of healthy cardiovascular behav- to the index of healthy cardiovascular behaviors were iors was regressed on all other variables (Table 4), eliminated. Appraisal of social support, sex, age and emotional involvement and increasing age made posi- income were retained though their individual paths tive contributions whereas depressive symptoms were not statistically significant. This was done be- made a negative contribution to the equation. There cause they contributed to overall model fit and was a non-significant trend (P = 0.07) for tangible predictive ability. This restricted model provided social support to exert an adverse effect on cardio- a better fit to the data (adjusted goodness-of-fit vascular behavior. The adjusted R2 for this equation index = 0.98, model x2 = 6.65, df = 6, P = 0.37, and was 25%. Schwa& Bayesian Criterion = - 19.7). The R’s for
Tables 3 and 4 also show the standardized par- dependent variables depressive symptoms and the ameter estimates for the original hypothesized model index of healthy cardiovascular behaviors were 45% obtained using structural equation modelling. The and 24% respectively. goodness-of-fit index adjusted for the degree of free- dom was 0.76 (model x2 = 3.28, df = 2, P = 0.19, and Schwa& Bayesian Criterion = -5.5). The R2 for DISCUSSION
the dependent variables in the model was 46% for depressive symptoms and 32% for the index of All three hypotheses of this study were confirmed. healthy cardiovascular behaviors. Figure 2 illustrates Using three different methods of analysis, we showed the optimal path analysis found on substantive and that social relationships exert direct and indirect goodness of fit grounds. Of note, the direct paths effects (through depressive symptoms) on health from perceived criticism and tangible social support behavior and that family interaction variables have
Table 4. Regression of index of healthy cardiovascular behaviors score on social relationship variables, depressive symptom scores and background variables
(N = 83)
Variable
Parameter estimate (95% confidence
interval) Standardized
coefficient (SE) P
Age Female sex Income Education Negative life events Emotional involvement Perceived criticism Tangible social support Depressive symptoms
study. Numbers of paths indicate standardized coefficients. (*: Pathway statistically significant, P < 0.05.)
more powerful associations with health behaviors than do social support variables. Perceived social connections (social support and family factors) can influence health behaviors by two pathways, either directly (e.g. provision of tangible support or re- sources) or by changing the individual’s psychologi- cal state or mood that results in changes in health behaviors. The results of this study support both pathways, but suggest that perceived social connec- tions primarily affect the individual’s mood state that in turn influences health behaviors.
Patients were more likely to have depressive symp- toms if they were female, poor, experienced many negative life events, or their family was very close and critical. These findings are all consistent with previous research on social factors and depressive symptoms [30-35, 721. Appraisal of social support showed a significant protective effect in the correlation analy- ses, that became statistically non-significant in the multivariate analyses. The attenuation of effect ob- served for appraisal of social support is consistent with our hypothesis that family interactions enable a more cogent analysis of the effect of social relation- ships on depressive symptoms. The concepts of family emotional involvement and criticism were examined because they are the key components of family Expressed Emotion, which has been shown to predict the course of depression [30-351.
Of the social relationship variables, only family emotional involvement had a direct, statistically significant association with healthy cardiovascular behaviors. As expected, depressive symptoms were inversely associated with healthy cardiovascular be- haviors. The small salutary effect of age on health
behaviors is primarily due to significant correlations of age with lower fat and cigarette consumption.
The non-significant negative association between tangible social support and healthy cardiovascular behavior is probably a statistical artefact generated in the regression analysis. The association is counter- intuitive and contradicts other reported studies on the relationship between social support and health be- haviors [4&49, 59,601. Also, tangible social support did not contribute to the overall model fit in the structural equation analysis. The lack of a plausible direct relationship between social supports and health
behaviors may reflect a measurement problem. The instrument (ISEL) used in our study assesses cat- egories of general social support. Some studies have suggested that specific supportive behaviors are necessary to elicit behavior change (46-48,60]. Other studies have shown a beneficial effect of general social support [49, 591. Furthermore, Mermelstein et a/. [46] found evidence for the benefit of both general support using the ISEL instrument and specific support.
Unden er al. [73] have recently demonstrated that social support at work is correlated inversely with heart rate. They found no association with smoking or obesity and suggested that social support may directly influence the cardiovascular system. We be- lieve the inference that social support has a direct influence on the cardiovascular system is premature. The mechanism for a direct social to neural pathway has not been identified. Instead, we think that a more plausible pathway involves the psychological effects of perceived social support. These cognitive and emotional processes are then translated into neuro- endocrine and psycho-immunologic pathways. We
Social relationships and health 785
posit that depressive symptomology is a candidate for one such intervening psychological process, since it has been associated with significant neuro-endocrine and psycho-immunologic changes [43-45].
The absence of a direct effect of perceived criticism of health behaviors was surprising because nagging has been found to adversely affect smoking cessation [74], cholesterol reduction [75], and weight reduction [76]. The absence of effect may be because we measured current health behaviors rather than behav- ior changes. Alternatively, the detrimental effect of nagging observed in other studies may be indirect, adversely affecting mood.
These results show that intense emotional involvement is associated with depressive symptoms, fitting a classical interpretation of the causes and consequences of overinvolvement, or enmeshment [19,24, 37,771. In contrast, intense emotional in- volvement is positively associated with healthy cardiovascular behaviors. The latter finding suggests that family closeness may facilitate social control of health behaviors in the family, exerting a beneficial effect [50]. Individuals in a very close or enmeshed family may experience depressive symptoms but feel they must conform to the family rules regarding health behaviors (e.g. no smoking, eating health foods, etc.).
The contrasting effects of emotional involvement on depressive symptoms and health behaviors challenge the widely held view that high emotional involvement of closeness is bad or unhealthy. Fiske et al. [77] found that emotional closeness is associated with improved health in families with chronic illness. They suggested that the health effects of family closeness may be specific to particular health related phenomena. Grant et al. [78] reported similarly para- doxical findings for the relationships among social support, depressive symptoms and physical illness. They found that men with symptoms of depression perceived reduced social support from relatives, but those with physical illness had more supports from relatives. These studies imply that we need a more complex model for understanding how emotional closeness within families affects physical and psycho- logical health.
It is not surprising that the family has a more powerful influence on health behaviors than overall social support. Most health behaviors are initiated and maintained within the context of the family [79-811. As a result, there is a high concordance of health risk factors, especially for cardiovascular disease within families [81]. A family approach to promoting healthy behaviors is likely to be more effective if it can influence the behavior of several family members simultaneously and can address and change the family dynamics that support tiiihealthy behaviors.
Limitations of this study include its cross-sectional design, small sample size with a low response rate, especially for the family items, and possible
confounding by other variables. Because the study is cross-sectional, we cannot be certain about the causal pathway. Rather than high levels of perceived criticism and intense emotional involvement or low social support causing depressive symptoms, people with depressive symptoms may elicit low social support and critical family response by their behav- ior. There is some evidence that this reverse causal pathway does occur [20,82]. Also health behaviors, particularly exercise, may mitigate depression [83-861.
The low response rate for the family items suggests that these results may not be generalizable, particu- larly to those who are not married. The low response rate was probable due to the wording of the overall instruction to the family items, which was ‘Describe your family now,’ and the option of a ‘does not apply’ response category. Several respondents noted that these items did not apply, because they had no family. We believe that removing the word ‘now’ and the ‘does not apply’ category from the instructions would avoid this problem. There were no significant psycho- social differences between those that did and did not respond to the family items, so that it is unlikely that this response bias would have confounded the observed associations.
The small sample size of this pilot study makes multivariate adjustment for many potential con- founders unreliable. We therefore chose not to report analyses of other potential confounders that did not bear directly on our study hypotheses. We did examine the effects of other possible confounders, including both health status using the MOS short- form general health survey [87] and marital status. We were unable to show any statistically significant confounding by health status. The results observed in unmarried respondents were similar to the overall results. This suggests that the extended family or family of origin remains a powerful influence for those who are unmarried.
Slater and Linder [88] found evidence on methodo- logical grounds to question the validity of summary indices of health behaviors. They noted that these summaries result in the loss of information and biases introduced by ignoring the varying contributions made by the components of the index. Summary indices have been shown to be predictive of health status, morbidity, and mortality [89-921 suggesting some criterion and predictive validity. In addition, other studies have suggested that the tendency to practice preventive cardiovascular behaviors may reflect an underlying unidimensional factor [93,94]. In other words despite methodological and psycho- metric limitations, use of summary health behavior indices have predictive validity. In this study, the construct validity of the index is suggested by its association with both depressive symptoms and social relationships.
The results of this small cross-sectional study are viewed as preliminary. They require confirmation
786 PETER FRANKS et al.
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APPENDIX
Family Emotional Incolcemenr and Criticism Scale (FEICS)
Almost Once in a Almost Never While Some Often Always
1 2 3 4 5
01. I am upset if anyone else in my family is upset. 02. My family approves of most everything I do. 03. My family knows what I am feeling most of the time. 04. My family finds fault with my friends. 05. Family members give me money when I need it. 06. My family complains about the way I handle money. 07. My family knows what I am thinking before I tell them. 08. My family approves of my friends. 09. I often know what my family members are thinking before they tell me. IO. My family complains about what I do for fun. II. If I am upset, people in my family get upset too. 12. My family is always trying to get me to change. 13. If I have no way of getting somewhere my family will take me. 14. I have to be careful what I do or my family will put me down. Perceived Criticism subscale: even numbered items. Emotional Involvement subscale: odd numbered items.
