women's life strains, social support, coping, and positive and negative affect: cross-sectional...

Journal of Community Psychology Volume 18, July 1990

Women’s Life Strains, Social Support, Coping, and Positive and Negative Affect: Cross-Sectional and Longitudinal Tests of the Tko-Factor Theory of Emotional Wefi-Being

Geoffrey Nelson Wilfred Laurier University

This research examined the relationships between life strains, social support, coping, and positive and negative affect among 90 women at three different interviews over an 18-month period. Predictions were derived from previous research and the two-factor theory of emotional well-being. Two- factor theory asserts that positive affect and negative affect are relatively independent dimensions and that they have distinctly different correlates. It was predicted that life strains would be related to negative affect, but not to positive affect. However, life strains were related to both of these variables. As predicted, enacted support and coping were correlated with positive affect, but not with negative affect. Cross-sectional and longitudinal regression analyses showed that life strains, social support, and coping combined in additive models to predict positive affect, suggesting that support and coping have a “health-enhancing” effect on positive affect. However, life strains interacted with support and coping to predict negative affect. In these analyses, both support and coping buffered the effects of life strains, suggesting that social support has a “health-protecting” effect on negative affect. Overall, the results demonstrated the utility of two-factor theory for research on women’s life strains, support, coping, and affect.

Over the past decade, there has been considerable research demonstrating that the emotional well-being of adults is a function of life events or strains, social support, coping, and the interaction of events or strains and support or coping (Kessler, Price, & Wortman, 1985). It is the thesis of this article that this area of research might profit from the use of the two-factor theory of emotional well-being (Bradburn, 1969; Herz- berg, 1966) in order to understand better how and when stress, social support, and coping influence emotional well-being. The article begins by outlining two-factor theory and indicating its relevance to research on women’s stress, social support, coping, and emotional well-being. Then, data from a longitudinal study of recently separated and married women are presented that bear on hypotheses derived from previous research and two-factor theory.

Two-Factor Theory of Emotional Well-Being

Two-factor theory posits that there are two distinct types of human needs: pain avoidance and growth. Moreover, Herzberg, Mathapo, Wiener, and Wiesen (1974) asserted that satisfaction of pain avoidance needs results in an emotional state that “. . , ranges on a continuum of pain-relief,” whereas satisfaction of growth needs results

This research was funded by a grant from the Atkinson Foundation. 1 am grateful t o the women for their participation in the study; to Marilyn Evers, Adrienne Gehl, and Dee Kalan for conducting the interviews; to De Bryant, Gilles Charbonneau, Rose Colacone, Peter Crocker, Karen Hooper, and John Iwohara for their research assistance; to Mark Pancer for his comments on this article; and to Paul Davock for his help with the graphs.

All correspondence should be addressed to Geoffrey Nelson, Department of Psychology, Wilfrid Laurier University, Waterloo, Ontario, Canada, N2L 3C5.

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240 NELSON

in an emotional state that “. . . ranges along the dimension of emptiness-fulfillment” (p. 41 1). Therefore, two-factor theory holds that failure to meet one’s pain avoidance needs results in negative affect or dissatisfaction, whereas failure to meet one’s growth needs results in a lack of positive affect or satisfaction. Finally, Herzberg et al. (1974) argued that only “hygiene” factors (such as the absence of stressful working conditions) can satisfy pain avoidance needs and only “motivator” factors (such as challenging and interesting work) can satisfy growth needs.

Research has provided some support for two-factor theory. Bradburn (1969) and Herzberg (1966) found that measures of positive affect and negative affect are relatively independent of one another. More recent research has confirmed this finding (Diener, 1984; Diener & Emmons, 1985; Watson, 1988). Research has also suggested that positive affect and negative affect have distinctly different correlates, as predicted by two-factor theory. Bradburn (1969) found positive affect to be associated directly with frequency of socializing and negative affect to be associated directly with symptomatology. Sim- ilarly, it has been found that “hygiene” factors are related to job dissatisfaction, whereas “motivator” factors are related to job satisfaction (Herzberg, 1966; Zautra, Eblen, & Reynolds, 1986).

Application of Two-Factor Theory to Research on Women’s Life Strains, Social Support, Coping, and Emotional Well-Being

Life events and strains. Following from two-factor theory, it stands to reason that negative life events should lead to failure to meet one’s pain avoidance needs, thus producing negative affect. The research appears consistent with this hypothesis, showing that negative events are associated with negative affect, but not with positive affect (Zautra & Reich, 1983).

Recently, there has been a shift away from the study of major life events to the study of more chronic life strains or hassles that are experienced on a daily basis. Research has shown that life strains are better predictors of emotional well-being than are life events (DeLongis, Coyne, Dakof, Folkman, & Lazarus, 1982; Eckenrode, 1984; Kanner, Coyne, Schaefer, & Lazarus, 1981; Monroe, 1983). Moreover, recent studies have found that measures of hassles (Kanner et al., 1981; Zika & Chamberlin, 1987) and daily stress (Watson, 1988) are more strongly related to negative affect than to positive affect, which supports two-factor theory.

There has yet to be a test of the hypothesis that life strains are more related to negative affect than positive affect in the context of women’s stress and well-being. However, there is considerable evidence that strains in various areas of role functioning (e.g., marriage, child-rearing, housework, employment, and finances) are related to measures of depression, self-esteem, and life satisfaction both for married women (Aneshensel, 1986; Kandel, Davies, & Raveis, 1985; Vanfossen, 1986) and for separated/divorced women (Berman & Turk, 1981; D’Ercole, 1988; Kazak & Linney, 1983). Women are entering the work force in ever increasing numbers, but their jobs are typically lower in wages, status, and power than those of men. Thus, it stands to reason that employed women face considerable strains in their occupational and financial roles. Also, working women remain primarily responsible for child-rearing and housework (Spitze, 1986), and women who do not work outside tide home experience isolation in their roles as parent and household manager (Belle, 1912). Given the variety of daily hassles and role strains experienced by women, a test of the two-factor theory should shed light on how these strains have an impact on women’s emotional well-being.

WOMEN’S STRAINS, SUPPORT, COPING, AND AFFECT 24 1

Social support. Researchers have made a distinction between two ways of con- ceptualizing and assessing social support: enacted or received support and perceived support (Barrera, 1986; Cummins, 1988). Enacted support can be defined as the actual receipt of different types of support (e.g., tangible help, emotional support) and can be measured by counting the number of people who provided different types of support or how frequently the support was provided. Perceived support refers to an individual’s perceptions about the adequacy or availability of different types of support. Often, perceived support is measured in terms of one’s satisfaction with different types of support. Several recent studies have found various measures of enacted support, such as receipt of support from family and friends (Zautra, 1983), frequency of support (Earls & Nelson, 1988), and social activity (Watson, 1988), to be associated with positive affect, but not with negative affect. These empirical findings seem consistent with two-factor theory in suggesting that social support can only satisfy one’s growth needs, thereby producing positive affect.

However, measures of perceived support have been found in many studies to be inversely related to negative affect (Barrera, 1986), thus casting some doubt about how social support might fit with two-factor theory. The discrepancy in findings between how measures of enacted support and perceived support relate to positive and negative affect may be explained by the issue of confounding. Barrera (1986) has pointed out that measures of perceived support may be confounded with measures of emotional distress, because the items used in these measures might be quite similar. Also, measures of perceived support demand considerable inference on the part of respondents, and thus they may be more confounded with measures of emotional distress than with measures of enacted support which demand more description (Dohrenwend, Dohren- wend, Dodson, & Shrout, 1984). Thus, the inconsistency of findings on the relationship between perceived support and negative affect with two-factor theory may be due to a methodological problem.

Although there has not been a test of the relationships between different measures of support and women’s positive and negative affect derived from two-factor theory, there is evidence that social support is important for women’s emotional well-being, Measures of perceived support have been found to be inversely related to depression for both married (Aneshensel, 1986) and divorced women (Wilcox, 1986). In a study comparing men and women in the same occupational roles, Rosario, Shinn, Morch, and Huckabee (1988) found that women reported more perceived support from co- workers than did men. Rosario et al. (1988) and Hobfoll (1986) have suggested that women are socialized both to seek and to give intimate support more than men are. Thus, both separated and married women with children who are isolated and cut off from a network of support are likely to be vulnerable to emotional difficulties. In this research, two-factor theory is used to clarify how enacted support and perceived support are related to women’s positive and negative affect.

There have recently been a variety of attempts to conceptualize and assess coping. In most of these approaches, coping is defined as ways that an individual thinks, feels, and behaves in response to environmental demands and challenges (e.g., Pearlin & Schooler, 1978). One approach to the assessment of coping is to identify the coping strategies used by a particular group of people in response to the demands that typically impinge upon that group. Particularly germane to the present investigation is the work of Berman and Turk (1981), who modified an existing coping scale to assess the strategies used by divorced women with children. Several of the subscales of this measure

Coping.

242 NELSON

(autonomy, personal understanding, home and family activities, social activities, learning) were found to be directly related to women’s self-reported mood and life satisfaction.

Within the context of two-factor theory, coping, like social support, can be con- strued as a “motivator” factor. Coping strategies such as developing autonomy, personal understanding, learning, and involvement in family and social activities should help to meet women’s growth needs and therefore should be directly related to their experience of positive affect.

Interactions between life strains and social support and life strains and coping. The research reviewed thus far has considered only the direct relationships between life strains, social support, and coping, on the one hand, and positive and negative affect, on the other hand. An additive model assumes that life strains, social support, and coping have independent and direct effects on the measures of affect. Another model that has received considerable attention in the literature is an interactive model in which it is assumed that social support and coping influence affect indirectly by interacting with life strains. An interactive model permits an examination of the stress-buffering hypothesis, which posits a strong relationship between strains and distress for those who are low in support, and a weak relationship between strains and distress for those who are high in support (Cohen & Wills, 1985; Dean & Lin, 1977; Mitchell, Billings, & Moos, 1981).

Previous research has found stress-buffering effects with measures of perceived support (Cohen, McGowan, Fooskas, & Rose, 1984; Sandler & Barrera, 1984; Wethington & Kessler, 1986) and enacted support (Barrera, 1981; Cummins, 1988; Earls & Nelson, 1988; Sandler & Barrera, 1984). There is also some evidence for the stress-buffering effects of coping (Aldwin & Revenson, 1987; Billings & Moos, 1981; Mitchell, Cronkite, &Moos, 1983). In terms of two-factor theory, Zautra and Reich (1983) refer to the buffering effect as a “cross-domain effect.” That is, enacted support and coping may not be directly related to negative affect, but they may interact with life strains to reduce negative affect. With regard to positive affect, there are neither conceptual reasons nor empirical evidence to suggest that strains should interact with support or coping to predict positive affect.

Research Hypotheses and Overview of the Study The purpose of this research was to examine the relationship between life strains,

social support, coping, and positive and negative affect from the perspective of two- factor theory. Based on the logic of two-factor theory and previous research findings, the following hypotheses were advanced.

1. 2.

3.

4. 5 .

6.

7.

Life strains will be directly related to negative affect, but not to positive affect. Enacted support will be directly related to positive affect, but not to negative affect. Support satisfaction will be directly related to positive affect and inversely related to negative affect. Coping will be directly related to positive affect, but not to negative affect. Life strains and social support (both support satisfaction and enacted support) will combine in additive models, not interactive models, to predict positive affect. Life strains and coping will combine in additive models, not interactive models, to predict positive affect. Life strains and social support (both support satisfaction and enacted support) will combine in interactive models to predict negative affect, thus demonstrating a stress-buffering effect.

WOMEN’S STRAINS, SUPPORT, COPING, AND AFFECT 243

8. Life strains and coping will combine in interactive models to predict negative affect, supporting the stress-buffering hypothesis.

Because the data in this study were collected at three different points in time, these hypotheses were tested both cross-sectionally and longitudinally. That is, at each of the three different time periods, positive and negative affect were related to the strains, support, and coping that were assessed at the same point in time (i.e., concurrently). Also, strains, support, and coping assessed at the first time period were used to predict positive and negative affect assessed at the second and third time periods. Similarly, strains, support, and coping assessed at the second time period were used to predict positive and negative affect at the third time period. Although the cross-sectional data can confirm an association between the variables, the direction of causal influence cannot be deter- mined. The advantage of having a longitudinal design is that predictive relationships can be tested, which can suggest the potential causal influences of strains, support, and coping on affect.

Method Sample Selection and Respondent Characteristics

The study was conducted in the Waterloo region of Ontario, Canada, which has a population of approximately 320,000. Eligible participants were either separated or married women who had at least one child in the age range of 8 to 17. Separated women must have had custody of the child or children and must have been separated for less than 8 months.

The separated women were identified through an examination of divorce petitions and notices of separation filed at the county court. Letters explaining the study were sent to 114 women who met the criteria for inclusion in the study, and 35 women (30%) responded to the letter and agreed to be interviewed for the study. Not all of the separated women had received their final divorce decree at the time of the study, but this was in process for all of these women.

Married women were identified through a survey of 10 public schools spanning grades 3 to 12. Teachers gave letters addressed to “Parents” to randomly selected children and instructed them to take the letter home to their parents. Sixty-six women who met the inclusion criteria responded and agreed to be interviewed. Because more than one letter could have been sent to each family and because many women who did not meet the inclusion criteria responded, it was not possible to calculate accurately the response rate.

To be included in the analyses for this study, the women had to have completed at least the first two of the three interviews. There were 90 women, 30 separated and 60 married, who completed the first two interviews, and 85 women, 27 separated and 58 married, who completed all three interviews.

The average age of the women was 37.6 years, and both the married and separated women had been married for an average of 15.9 years. With regard to education, 43% had not completed high school, 31% had obtained a high school diploma, and 26% had received some education beyond high school. At the time of the initial interview, 53% had a family income of less than $2,000 (gross) per month, whereas the remainder had a family income in excess of that amount. Two-thirds (67%) of the women were employed outside the home at the time of the first interview, 70% were Protestant, and all but one were White.

244 NELSON

These women were coping with a number of different stressful circumstances. At the initial interview, the stressful life event most frequently mentioned by the separated women was the marital separation or problems with their husbands (mentioned by 24 of the 30 separated women); the most frequently mentioned stressful life event for the married women concerned finances or work (mentioned by 29 of the 60 married women). Other stressful life events that were mentioned were child-related concerns, health problems, or the death of a family member.

Measures Life strains. A modified version of Berman and Turk’s (1981) Checklist of Prob-

lems and Concerns (CPC) was used. Women were asked to rate the extent to which the 20 items in the scale were a problem or concern in the past 8 months (or since the last interview on the follow-up interviews) on a 4-point scale ranging from “never” to “always.” Five subscales for the CPC were derived: (1) practical problems (i.e., the role of household manager), (2) social relations (i.e., the role of friend), (3) financial concerns (i.e., the role of provider), (4) parent-child relations (i.e., the role of parent), and ( 5 ) spouse relations (i.e., the role of spouse or ex-spouse). A total score was obtained by summing all of the subscales. Berman and Turk (1981) found that these subscales of the CPC possessed adequate internal consistency and that they were significantly related to measures of mood state and life satisfaction.

Based on Barrera’s (1981) Arizona Social Support Interview Schedule (ASSIS), two measures of network support were employed: enacted support and support satisfaction. The ASSIS assesses six types of support: intimate interaction (discussion of private feelings), material aid (loan of $25 or more), positive feedback (praise, approval or encouragement), guidance (advice), physical assistance (tangible help, such as babysitting, going to the store for the person), and social participation (recreation and relaxation). Two measures of support were derived from the ASSIS. Enacted support refers to the number of people who had provided each type of support during the past 8 months (or since the last interview for follow-up interviews). Support satisfaction refers to how satisfied they were with each type of support (rated on a 3-point scale). Scores for these two measures were obtained by summing the individual scores for each type of support and dividing by six (the number of types of support). In a study of 60 undergraduate psychology students, the following test-retest reliability coefficients were found for a 2-week interval: enacted support, r = .87; and support satisfaction, r = .71.

A modified version of Berman and Turk’s (1981) Coping Strategies and Resources Inventory (CRSI) was used to assess situation-focused strategies the women used to cope with the stressful life events they had experienced over the last 8 months (or since the last interview for the follow-up interviews). The modified scale included items applicable to both divorced and married women with children. Women indicated which coping strategies they had used on a “Yes” or “No” basis. Five subscales of the CSRI were used: (1) social activities (five items), (2) learning (four items), (3) personal understanding (four items), (4) autonomy (five items), and ( 5 ) home and family activities (four items). A total score was obtained by summing all of the subscales. The test-retest reliability over a 2-week period for the CSRI total score was r = .81.

Turner’s (1981) measure of emotional well-being was used. There are three subscales in this measure: anxiety, anger, and depression. Each subscale consists of five items which are rated on a 5-point scale, ranging from

Social support.

Coping strategies.

Positive aflect and negative aflect.


“not at all like me” to “very much like me.” These three scales were summed to yield a measure of negative affect. Additionally, the five items of Bradburn’s (1969) positive affect measure were included and were rated on the same 5-point scale. In the study of university students, the test-retest reliability coefficients were r = .68 for positive affect and r = .71 for negative affect.

Interview Procedure The interviews were conducted in families’ homes and lasted about 2 to 3 hours.

The interviewers were mature women who were selected on the basis of their interper- sonal skills (e.g., warmth and compassion). Most of the interviews were done by three women, all of whom had been married and divorced and who had raised children while on a limited income. Initially, the interviewers were given an orientation and instructions by the author, and, subsequently, the interviewers met with the author on a regular basis to review what happened during the interviews.

At the initial interview, the interviewer explained the nature of the research, the rights of participants, and the requirements for participation to the women. The interview focused on marital and demographic information. With the instructions provided by the interviewer, the women then completed the CPC, ASSIS, CSRI, Positive Affect, and Negative Affect measures. Following the initial interview, the women were interviewed two more times: 6 months after the initial interview and 1% years after the initial interview. The women were paid $15 for each interview in which they participated and were sent a summary of the results at the conclusion of the study.

Results Descriptive Analyses

The means and standard deviations of all variables for all of the women (separated and married women combined) are presented in Table 1. One-way repeated measures ANOVAs showed significant decreases in the CPC total score, F(2,154) = 3.4, p < .05, and enacted support, F(2,166) = 17.6, p < .001, over time, whereas the other variables remained fairly stable. Thus, women reported high levels of strains and support received at the first interview, but these levels dropped significantly by the second interview. This suggests that women’s needs for support were particulary acute at the initial interview.

Correlational Analyses First, the correlations between all of the variables were computed separately for

the separated and married women. The pattern of results was very similar for both groups. The two groups were then combined, and the correlation matrix for the entire sample was computed. (See Table 1 .) Because the first four hypotheses are concerned with the direct relationships of strain, support, and coping variables with positive and negative affect, and not with various combinations of the predictor variables, simple correlations are used to test these hypotheses. Beginning with the first hypothesis, the correlations between the CPC total score and postive affect and negative affect are of interest. The concurrent correlations between CPC total score and positive affect (PA) were - 3 2 (TI), - .31 (T2), and - .37 (T3), and the predictive correlations between CPC total score and positive affect (PA) were - .28 (CPC T1, PA T2), - .25 (CPC TI, PA T3), and - .26 (CPC T2, PA T3). The concurrent correlations between CPC total score and negative affect (NA) were .49 (Tl), .42 (T2), and .49 (T3), and the predic-

246 NELSON

Table 1 Means and SDs of and Intercorrelation Among Variables

Variable 1 2 3 4 5 6

Mean SD

Possible range

41.6 38.7 39.1 6.6 5.0 5.1 9.4 8.7 9.2 3.8 3.6 3.7

20-80 0-30

1. 2. 3. 4. 5. 6. 7. 8. 9.

10. 11. 12. 13. 14. 15. 16. 17. 18.

CPC total (Tl) CPC total (T2) CPC total (T3) Enacted support (Tl) Enacted support (T2) Enacted support (T3) Support satisfaction (Tl) Support satisfaction (T2) Support satisfaction (T3) CSRI total (Tl) CSRI total (T2) CSRI total (T3) Positive affect (Tl) Positive affect (T2) Positive affect (T3) Negative affect (Tl) Negative affect (T2) Negative affect (T3)

.71

.58 .71

.01 .06 .04 -.04 -.05 -.09 -.07 -.15 -.I4 -.14 -.06 -.02 -.27 -.26 - .26 -.27 - . I 8 -.23

.18 .14 .20

.10 .17 .18

.27 .32 .27 -.52 -.34 -.24 -.28 -.3l -.27 -.25 -.26 -.37

.49 .36 .29

.44 .42 .44

.18 .19 .49

.80

.68 .70

.28 .25 . I 8

.10 .14 .07

.20 .19 .I0

.21 .17 .03

.15 .09 .09

.06 .02 .04

.20 .27 . I 8

.20 .25 .34 -.03 -.06 -.07 - . l o -.18 -.13 -.07 -.12 -.09

.07 -.05 .OO

Note. Correlations 2 .19 are significant at the .05 level.

tive correlations were .44 (CPC T1, NA T2), .18 (CPC T1, NA T3), and .19 (CPC T2, NA T3). All but one of these correlations were significant. Thus, the first hypothesis, that life strains would only be related to negative affect, was not supported.

The second hypothesis concerns the relationship between enacted support and positive affect and negative affect. The concurrent correlations between enacted support (ES) and PA were .06 (Tl), .27 (T2), and .34 (T3), while the predictive correlations between these variables were .20 (ES T1, PA T2), .20 (ES T1, PA T3), and .25 (ES T2, PA T3). All but one of these correlations were significant. In contrast, none of the concurrent or predictive correlations between enacted support and negative affect was significant. These results support the second hypothesis that enacted support would only be related to positive affect.

The third hypothesis postulates a relationship between support satisfaction and positive affect and negative affect. The concurrent correlations between support satisfaction (SS) and PA were .12 (Tl), .21 (T2), and .30 (T3) (two of three were significant), while the predictive correlations were .04 ( S S T1, PA T2), .03 (SS TI, PA T3), and .32 ( S S T2, PA T3) (one of three was significant). The concurrent correlations between SS and NA were - .22 (Tl), - .08 (T2), and - .29 (T3) (two of three were significant), while the predictive correlations were - .18 (SS T1, NA T2), - .01 (SS T1, NA T3), and - .08 (SS T2, NA T3) (none of which was significant). The third hypothesis was supported only by the cross-sectional findings.

WOMEN’S STRAINS, SUPPORT, COPING, AND AFFECT

Table 1 (Continued)

247

7 8 9 10 11 12 13 14 15 16 17 18

2.5 2.7 2.6 10.9 10.8 10.5 18.0 17.9 17.8 30.8 29.2 29.7 .4 .4 .4 4.4 4.1 4.6 4.0 3.8 3.8 10.5 9.6 10.5

1-3 0-21 5-25 15-75

.54

.31 .43

.02 .02 .19 3 1 - .04 - .04 .04

-.02 -.11 .12 .66 .63 .12 .09 -.04 .20 .04 .01 .04 .21 .OO .06 .22 .07 .49 .03 .32 .30 .08 .I1 .24 .30 .48

-.22 .03 - . lo .05 .10 .15 -.52 -.37 -.17 .18 -.08 -.14 .05 .05 . l l -.39 -.53 -.39 .71 .Ol -.08 -.29 .18 .13 .10 -.13 -.33 -.43 .42 .64

The fourth hypothesis is that coping would be positively related to positive affect, but not to negative affect. The concurrent correlations between the CSRI and PA were .20 (TI), .22 (T2), and .24 (T3), while the predictive correlations were .06 (CSRI T1, PA T2), .08 (CSRI T1, PA T3), and .l 1 (CSRI T2, PA T3). All of the concurrent correlations were significant, but none of the predictive correlations was significant. None of the concurrent or predictive correlations between the CSRI and NA was significant. Thus, the fourth hypothesis was supported only by the cross-sectional findings.

The concurrent correlations between PA and NA were - 3 2 (Tl), - .53 (T2), and - .43 (T3). These moderately high correlations may have resulted from the rating format, which asked respondents how well the item described them as a person. Similarly, Watson (1988) found a correlation of - .37 between a trait measure of negative affect and a trait measure of positive affect. Much lower correlations between these two variables are found when the measures are state-like (rating the frequency of occurrence of the feeling) as opposed to trait-like (rating how well the feeling describes the respondent’s personality) (Watson, 1988).

Overview of Regression Analyses Both crmectional and longitudinal regression models were fitted to test hypotheses

five to eight. For both the cross-sectional and longitudinal analyses, two types of regression models were used, following the methods used by Cohen, Burt, and Bjork (1987)

248 NELSON

and Holahan and Moos (1987). In the first case, the CPC total score was entered first, followed by the social support (or coping ) measure, and then the interaction term (i.e., CPC x Support or CPC x Coping). In the second case, the scores for the dependent variable at the previous time period were entered first, followed by the CPC total score, social support (or coping) measure, and then the interaction term. In both cases, if the F ratio for the interaction term was significant, then the interaction model was retained; if it was not significant, then the additive model was examined. If the F ratio for the social support (or coping) measure was significant, then the additive model was retained; if it was not significant, then the additive model was dropped.

Regression Analyses with Positive AfSect as the Dependent Variable The cross-sectional analyses with positive affect as the

dependent variable and the CPC, support measures, and the interaction terms as the independent variables are presented in Table 2. The regressions without controls for earlier positive affect are on the lefthand side of the Table. Six cross-sectional regression models were computed: one for enacted support and one for support satisfaction at each of three time periods. Although neither of the models was significant at the first time period, three of the four models were significant at the second and third time periods. In each case, the significant model was additive as opposed to interactive.

Although these analyses have demonstrated an association between the variables, they do not clarify the potential causal role of life strains and social support, because these factors may be influenced by earlier positive affect. The regression models shown on the right side of Table 2 examined the relationship between life strains and social support and “changes” in positive affect by controlling for earlier levels of positive affect. Once again, neither of the models was significant at the first time period, whereas three of the four models were significant at the second and third time periods. Again, all of the significant models were additive.

The cross-sectional regression analyses with positive affect as the dependent variable and CPC, CSRI, and the interaction terms as the independent variables are presented in Table 3. At each of the three time periods, the CPC and CSRI combined in additive models to predict positive affect. The proportion of variance accounted for in the models that did not control for earlier levels of positive affect ranged from 17% to 36070, whereas the models that did control for earlier levels of positive affect accounted for 31% to 38% of the variance.

The longitudinal regression models with positive affect as the dependent variable and the CPC, support measures, and the interaction terms as the independent variables are presented in Table 4. Six regression models were computed: T1 predictors of T2 (two models), T1 predictors of T3 (two models), and T2 predictors of T3 (two models). All six of the regression models that do not control for earlier positive affect (presented on the lefthand side of Table 3) were significant. Four of the significant models were additive, whereas two were interactive.

To interpret the significant interaction models, the level of positive affect predicted by the equation was calculated, given levels of the CPC total score at + 1, 0, and - 1 standard deviations and levels of social support at + 1, 0, and - 1 standard deviations. The results of the calculations for both significant interaction models corresponded with the buffering hypothesis. As can be seen in the illustration in Figure 1, the regression line between CPC total score (Tl) and positive affect (T3) was relatively flat for high

Cross-sectional analyses.

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1,82

)=

8.3"

C

PC to

tal

(T2)

.2

6 F(

1,82

)= 2

.3

Ena

cted

sup

port

(T2

) .1

6 F(

1,82

)=

6.3a

E

nact

ed s

uppo

rt (

T2)

.33

F(1,

82)=

7.

7a

All

pred

icto

rs

F(2,

81)=

7.

7"

All

pred

icto

rs

F(3,

80)=

12.

8"

0

!a Po

sitiv

e af

fect

(T3

) Po

sitiv

e af

fect

(T2

) .2

3 F(

1,81

)= 1

5.8'

* C

PC to

tal

(T3)

.1

4 F(

1,83

)=11

.3"

CPC

tota

l (T

3)

.30

F(1,

81)=

6.2

a 0

E

nact

ed s

uppo

rt (

T3)

.22

F(1,

83)=

8.7

" E

nact

ed s

uppo

rt (

T3)

.35

F(1,

81)=

6.6

" 8

.23

F(1,

79)=

20.3

a Z

CPC

tota

l (T

3)

.14

F(1,

81)=

9.6

a C

PC to

tal

(T3)

.3

0 F(

1,79

)= 4

.1a

U Su

ppor

t sat

isfa

ctio

n (T

3)

.36

F(1,

79)=

7.

3"

%

All

pred

icto

rs (

T3)

F(2,

82) =

1 1.

6"

All

pred

icto

rs

* Po

sitiv

e af

fect

(T3

) Po

sitiv

e af

fect

(T2

)

Supp

ort

satis

fact

ion

(T3)

.1

9 F(

1,81

)= 4

.8a

All

pred

icto

rs

F(2

,80)

= 9.

2a

All

pred

icto

rs

F(3,

77)-

14

.2"

mi

N

P

W

Tabl

e 3

Cro

ss-S

ectio

nal R

egre

ssio

n A

naly

ses

with

Pos

itive

AH

ect a

s th

e D

epen

dent

Var

iabl

e an

d C

PC

Tot

al a

nd C

SRI a

s th

e In

depe

nden

t V

aria

bles

Reg

ress

ions

with

out

cont

rols

for

ear

lier p

ositi

ve a

ffec

t R

egre

ssio

ns w

ith c

ontr

ols

for

earl

ier p

ositi

ve a

ffec

t D

epen

dent

var

iabl

e In

depe

nden

t var

iabl

es

R2

F

Inde

pend

ent v

aria

bles

R

2 F

Posi

tive

affe

ct (

TI)

C

PC to

tal

(Tl)

C

SRI

("1)

All

pred

icto

rs

Posi

tive

affe

ct (

T2)

CPC

tota

l (T

2)

CSR

I (T

2)

All

pred

icto

rs

Posi

tive

affe

ct (

T3)

CPC

tota

l (T3

) C

SRI

(T3)

A

ll pr

edic

tors

.27

F(1,

84) =

41.6

" .3

6 F(

1,84

)= 1

1.3a

F(

2,83

) = 23

.4=

Posi

tive

affe

ct (

Tl)

.2

4 F(

1,79

)= 16.P

.09

F(1,

79) =

11 .

4a

CPC

tota

l (T

2)

.26

F(1,

79)=

4.

2"

CSR

I (T

2)

.31

F(1,

79)=

5.

9"

.17

F(1,

79)=

7.

0"

F(2,

78)=

7.

Y

All

pred

icto

rs

F(3,

77)=

11.

7'

Posi

tive

affe

ct (

T2)

.23

F(1,

78)=

14.

7' .1

4 F

( 1,8

0) =

22.0

" C

PC to

tal

(T3)

.3

0 F(

1,78

)= 1

3.1'

.26

F(1,

80)=

13.

3' C

SRI

(T3)

.3

8 F(

1,78

) = 1

0.6"

F(

2,79

) = 1

4.0"

A

ll pr

edic

tors

F(

3,76

)= 1

5.6'

Tabl

e 4

Long

itudi

nal R

egre

ssio

n A

naly

ses w

ith P

ositi

ve A

ffec

t as t

he D

epen

dent

Var

iabl

e and

CPC

Tot

al an

d So

cial

Net

wor

k M

easu

res a

s the

Inde

pen-

de

nt V

aria

bles

Reg

ress

ions

with

out c

ontr

ols

for

earli

er p

ositi

ve a

ffec

t R

egre

ssio

ns w

ith c

ontr

ols

for

earl

ier p

ositi

ve a

ffec

t

Dep

ende

nt v

aria

ble

Inde

pend

ent v

aria

bles

R2

F

Inde

pend

ent v

aria

bles

R2

F

Posi

tive

affe

ct (

T2)

Posi

tive

affe

ct (

Tl)

.2

4 F(

1,83

)= 1

6.3"

3 B $ 5 $ E

nact

ed s

uppo

rt (

Tl)

.1

0 F(

1,82

)=

3.8

Ena

cted

sup

port

(T

l)

.14

F(1,

82)=

3.3

' "2

CPC

tota

l (T

l)

.08

F(1,

84)=

7.

5"

CPC

tota

l (T

l)

.24

F(1,

83)=

.2

E

nact

ed s

uppo

rt (

Tl)

.1

2 F(

1,84

)=

4.P

E

nact

ed s

uppo

rt (

Tl)

.2

7 F(

1,83

)= 3

.4

All

pred

icto

rs

F(2,

83)=

5.

7' A

ll pr

edic

tors

F(

3,81

j=

9.9"

Posi

tive

affe

ct (

T3)

Posi

tive

affe

ct (

Tl)

.0

9 F(

1,81

)=

7.1'

CPC

tota

l (T

l)

.06

F(1,

81)=

10.

3"

CPC

tota

l (T

l)

.10

F(1,

81)=

13.3

' Su

ppor

t sa

tisfa

ctio

n (T

l)

.06

F(1,

81)=

8.

5'

Supp

ort

satis

fact

ion

(Tl)

.1

0 F(

1,81

)= 1

2.3'

Inte

ract

ion

All

pred

icto

rs

F(3,

79)=

4B

a A

ll pr

edic

tors

F(

4,78

) = 5

.7"

01"

-16

F(1,

81)=

8.7

" In

tera

ctio

n .2

3 F(

1,81

)= 1

2.5"

01

v

Posi

tive

affe

ct (

T3)

Posi

tive

affe

ct (

Tl)

.0

9 F(

1,82

)=

3.2

CPC

tota

l (T

l)

.06

F(1,

82)=

5.7

' C

PC to

tal

(Tl)

.1

0 F(

1,82

)=

1.3

0

All

pred

icto

rs

F(2,

81)=

4.

7"

All

pred

icto

rs

F(3,

80)=

4.3

" CI 4

.24

F(1,

83)=

31.3

' .2

4 F(

1,83

)=25

.4a

CPC

tota

l (T

l)

.08

F(1,

83)=

13.

9a

CPC

tota

l (T

l)

Supp

ort

satis

fact

ion

(Tl)

.0

8 F(

1,83

)= 1

1.4'

Supp

ort s

atis

fact

ion

(Tl)

.2

4 F(

1,83

) = 25

.1"

Posi

tive

affe

ct (

T2)

Posi

tive

affe

ct (

TI)

0 *

Inte

ract

ion

.19

F(1,

83)=

11.

8' In

tera

ctio

n .4

2 F(

1,83

)=25

.4a

z A

ll pr

edic

tors

F(

3,81

)=

6.5'

All

pred

icto

rs

F(4,

80)=

14.

6"

U t Po

sitiv

e af

fect

(T2)

.2

3 F(

1,81

)= 1

5.2'

crl

CPC

tota

l (T

2)

.07

F(1,

81)=

5.4'

C

PC to

tal

(T2)

.2

5 F(

1,81

)=

1.4

CI

M H

Posi

tive

affe

ct (

T3)

Ena

cted

sup

port

(T2

) .1

2 F(

1,81

)=

5.0"

E

nact

ed s

uppo

rt (

T2)

.26

F(1,

81)=

1.

7 AU p

redi

ctor

s F(

2,80

)=

5.5"

A

ll pr

edic

tors

F(

3,79

)= 9

.3'

Posi

tive

affe

ct (

T3)

Posi

tive

affe

ct (T

2)

.23

F(1,

79)=

16.

7"

CPC

tota

l (T

2)

.08

F(1,

79)=

2.8

C

PC to

tal

(T2)

.2

5 F(

1,79

)=

.5

Supp

ort s

atis

fact

ion

(T2)

.1

5 F(

1,79

)= 6

.2"

Supp

ort s

atis

fact

ion

(T2)

.2

9 F(

1,79

)= 4

.6'

All

pred

icto

rs

F(2,

78)=

6.

0"

All

pred

icto

rs

F(3,

77)=

10.

4"

h)

v,

CL

"p

< .0

5.

25 2 NELSON

levels (+ 1 SD) of support satisfaction, but the line for low levels (- 1 SD) of support satisfaction sloped downward sharply.' Thus, at high levels on the CPC total score (Tl), positive affect (T3) was at a low level for those with low levels of support satisfaction (Tl) but at a higher level for those with high levels of support satisfaction (Tl).

support

01) Satisfaction

120' A-- + -1 so X t 1 SD

CPC Total Score (Tl)

FIGURE 1. Relationship Between CPC (Tl) and Positive Affect (T3) at Different Levels of Sup- port Satisfaction (Tl).

The regression models controlling for earlier levels of positive affect are presented on the righthand side of Table 4. The two interaction models remained significant, but only one of the additive models remained significant when earlier positive affect was entered into the equation first.

Three predictive models were fitted with positive affect as the dependent variable and the CPC, CSRI, and interaction terms as the independent variables: (1) TI predictors of T2, (2) T1 predictors of T3, and (3) T2 predictors of T3. Only one of the three models that did not control for earlier levels of positive affect was significant. The CPC and CSRI assessed at T2 combined in an interactive model to predict positive affect at T3, F(3,76) = 5.0, p < .01, R2 = .17. The significant interaction was graphed and the results conformed with a stress-buffering effect. None of the three predictive models controlling for earlier levels of positive affect was significant.

'There were several significant interaction models found in the results. In the interest of conserving space, only a few of the graphs are presented for illustrative purposes.

Tabl

e 5

Cro

ss-S

ectio

nal R

egre

ssio

n A

naly

ses

with

Neg

ativ

e A

ffec

t as

the

Dep

ende

nt V

aria

ble a

nd C

PC

Tot

al a

nd S

ocia

l Net

wor

k M

easu

res

as th

e In

depe

nden

t V

aria

bles

~

~

Reg

ress

ions

with

out c

ontr

ols

for

earli

er n

egat

ive

affe

ct

Dep

ende

nt v

aria

ble

Inde

pend

ent v

aria

bles

Neg

ativ

e af

fect

(T

l)

CPC

tota

l (T

l)

Ena

cted

sup

port

(T

l)

Inte

ract

ion

All

pred

icto

rs

CPC

tota

l (T

l)

Supp

ort

satis

fact

ion

(Tl)

In

tera

ctio

n All

pred

icto

rs

Neg

ativ

e af

fect

(T

l)

R2

F

.24

F(1,

84)=

20.8

' .2

5 F(

1,84

)=

5.0"

.2

9 F(

1,84

)=

5.6'

F(3,

82) =

11.4

"

.24

F(1,

83)=

10.

6'

.27

F(1,

83)=

5.5

' .3

3 F(

1,83

)=

7.2"

F(

3,81

)= 1

3.2'

< In

depe

nden

t var

iabl

es

R2

F

0 5

Reg

ress

ions

with

con

trol

s fo

r ea

rlier

neg

ativ

e af

fect

1: J F -3 5 Vl

e 0

w 1

d 8

Ena

cted

sup

port

(T2)

.2

0 F(

1,82

)=

7.9"

E

nact

ed s

uppo

rt (

T2)

.55

F(1,

82)=

3.

1 -z 5

Neg

ativ

e af

fect

(T

3)

Neg

ativ

e af

fect

(T

2)

.40

F(1,

79)=

35.7

" 6

CPC

tota

l (T

3)

.24

F(1,

81)=

7.5

' C

PC to

tal

(T3)

.46

F(1,

79)=

9.

6"

# Su

ppor

t sa

tisfa

ctio

n (T

3)

.27

F(1,

81)=

3.

2 Su

ppor

t sa

tisfa

ctio

n (T

3)

.49

F(1,

79)=

5.5

' 2

Neg

ativ

e af

fect

(T2

) N

egat

ive

affe

ct (

Tl)

.5

1 F(

1,82

)=54

.4'

CPC

tota

l (T

2)

.17

F(1,

82)=

26.0

" C

PC to

tal

(T2)

.5

4 F(

1,82

)=

9.4'

Inte

ract

ion

.29

F(1,

82)=

10.

4' In

tera

ctio

n .5

8 F(

1,82

)=

4.6"

All

pred

icto

rs

F(3,

80) =

10.9

' All p

redi

ctor

s F(

4,79

) = 27

.2'

U

Inte

ract

ion

.32

F(1,

81)=

4.

P

Inte

ract

ion

.53

F(1,

79)=

7.8'

A

ll pr

edic

tors

F(

3,79

)= 1

2.1"

A

ll pr

edic

tors

F(

4,76

)=21

.8'

'p -c

.05

.

t4

Ih

w

254

U.0,

NELSON

/‘

I Q ’ > i

: - - - - - - - .1 SD X $1 SD

I L O L - - - - - c - - - - - - - t

CDC Total Score ( T l )

FIGURE 2. Relationship Between CPC (Tl) and Negative Affect (Tl) at Different Levels of Sup- port Satisfaction (Tl).

Summary. The fifth hypothesis, that life strains and social support (both support satisfaction and enacted support) would combine in additive models to predict positive affect, received some support from both the cross-sectional and longitudinal analyses. The sixth hypothesis, that life strains and coping would combine in additive models to predict positive affect, was strongly supported by the cross-sectional findings, but was not supported at all by the longitudinal analyses.

Regression Analyses with Negative M e c t as the Dependent Variable Cross-sectional analyses. The cross-sectional regression analyses with negative

affect as the dependent variable and the CPC, support measures, and interaction terms as the independent variables are presented in Table 5. Four of the six models that do not control for earlier levels of negative affect were significant. As predicted, all of the significant models were interactive as opposed to additive. The significant interaction models were graphed, and all of the models showed a buffering effect. As can be seen in the illustration in Figure 2, the regression line between CPC total score (Tl) and negative affect (Tl) was relatively flat at high levels of support satisfaction (Tl), whereas the line rose sharply at low levels of support satisfaction (Tl).

The two regression models shown on the righthand side of Table 5 examined the relationship between life strains and social support and “changes” in negative affect. Both of these models showed significant interaction effects, which is consistent with the analyses that did not control for earlier levels of negative affect.

The cross-sectional regression analyses with negative affect as the dependent variable and the CPC, CSRI, and interaction terms as the independent variables are presented

Tab

le 6

C

ross

-Sec

tiona

l Reg

ress

ion

Ana

lyse

s w

ith N

egat

ive

Afle

ct a

s th

e D

epen

dent

Var

iabl

e and

CP

C a

nd C

SRI as th

e In

depe

nden

t V

aria

bles

e

Dep

ende

nt v

aria

ble

Inde

pend

ent v

aria

bles

R'

F

Inde

pend

ent v

aria

bles

R2

F

rn" 0 B

Reg

ress

ions

with

out c

ontr

ols

for

earli

er n

egat

ive

affe

ct

Reg

ress

ions

with

con

trol

s fo

r ea

rlie

r neg

ativ

e af

fect

Neg

ativ

e aff

ect (

TI)

CPC

tota

l (T

l)

CSR

I (T

l)

Inte

ract

ion

All

pred

icto

rs

Neg

ativ

e af

fect

(T2

) C

PC to

tal

(T2)

C

SRI

(T2)

In

tera

ctio

n A

ll pr

edic

tors

Neg

ativ

e af

fect

(T3)

C

PC to

tal

(T3)

C

SRI

03

) In

tera

ctio

n A

ll pr

edic

tors

.24

F(1,

84) =

20.P

.2

5 F(

1,84

)=

5.3"

.3

0 F(

1,84

)= 6

.2"

F(3,

82)=

11.

6"

.17

F(1,

79)=

47.5

" .1

7 F(

1,79

) = 28

.9"

.41

F(1

,79)

=31

.P

F(3,

77)=

17

9

23

F(1.

80)=

3.

9"

.24

F(1

,80)

=

.O

.24

F(1,

80)=

.O

F(3,

78)=

8.

2"

Neg

ativ

e aff

ect (

Tl)

C

PC to

tal (l-2)

CSR

I (T

2)

Inte

ract

ion

All

pred

icto

rs

Neg

ativ

e af

fect

("2

) C

PC to

tal

(T3)

C

SRI

(T3)

In

tera

ctio

n AU

pre

dict

ors

.51

.54

.54

.64

.40

.46

.46

.46

i F(

1,79

) = 49

.6"

21 F(

1,79

) = 28

.0"

*z F(

1,79

)= 1

9.6"

0

F(1,

79)=

22.P

8

F(4,

76) =

34.3

" z

F(1,

78)=

.8

3

F(1,

78)=

.O

cd

F(1,

78)=

.O

M

F(4,

75)=

16.

P

1

0

F(1,

78) =

30.5

" 9

9

cd

0

256 NELSON

in Table 6. At the first and second time periods, the models that do not control for earlier levels of negative affect are significant; both significant models are interactive; and the models account for 30% and 41% of the variance in the criterion. On the righthand side of the Table, the two models with controls for earlier levels of negative affect are presented. Again, at the second time period, an interactive model predicted negative affect, accounting for 64% of the variance in this variable. There were no significant models for the third time period.

The significant interactions were graphed and it was found that the results of the calculations for both significant interactions conformed with the buffering hypothesis. To conserve space, only one of the significant interactions is presented. (See Figure 3.) The regression line between CPC (T2) and negative affect (T2) was flat for high levels (+ 1 SO) of CSRI, but the line for low levels ( - 1 SO) of CSRI sloped upwards sharply. This pattern is consistent with the buffering hypothesis.

- +1 SD !

I I & I

CPC Total Score (T2) .1 SD X tl SD

FIGURE 3. Relationship Between CPC (T2) and Negative Affect (T2) at Different Levels of CSRI (T2).

Longitudinal analyses. The longitudinal regression analyses with negative affect as the dependent variable and the CPC, support measures, and interaction terms as the independent variables are presented in Table 7. Four of the six models that do not control for earlier levels of negative affect were significant. Moreover, each of the models was interactive as opposed to additive, as predicted. All of the interaction models were graphed, and all were found to show buffering effects. The illustration presented in Figure 4 clearly showed a buffering effect for support satisfaction (Tl) on negative affect (T2).

Tab

le 7

Lo

ngitu

dina

l Reg

ress

ion

Ana

lyse

s w

ith N

egat

ive A

flect

as

the D

epen

dent

Var

iabl

e and

CP

C T

otal

Sco

re a

nd S

ocia

l Net

wor

k M

easu

res as th

e In

depe

nden

t V

aria

bles

Reg

ress

ions

with

out c

ontr

ols

for

earl

ier n

egat

ive

affe

ct

Reg

ress

ions

with

con

trol

s fo

r ea

rlie

r neg

ativ

e af

fect

Dep

ende

nt v

aria

ble

Inde

pend

ent v

aria

bles

R2

F

Inde

pend

ent v

aria

bles

R

2 F

Neg

ativ

e af

fect

(T2

) C

PC to

tal

(Tl)

Su

ppor

t sa

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The longitudinal regression models in which earlier levels of negative affect were entered first into the equation are presented on the righthand side of Table 7. Two of the models were significant, and both were interactive models.

There were three predictive models with negative affect as the dependent variable and the CPC, CSRI, and interaction terms as the independent variables. None of these models reached statistical significance.

Summary. The seventh hypothesis, that life strains and social support (both support satisfaction and enacted support) would combine in interactive models to predict negative affect received some support from both the cross-sectional and the longitudinal analyses. Social support was found to buffer the effects of life strains on negative affect. The eighth hypothesis, that life strains and coping would combine in additive models to predict negative affect, received some support from the cross-sectional analyses, but was not supported at all by the longitudinal analyses. Like social support, coping showed a stress-buffering effect in the cross-sectional analyses.

Discussion The results of this study provide some support for the two-factor theory of emo-

tional well-being. The measure of life strains was directly associated with negative affect. This finding is consistent with both two-factor theory and previous research which has shown that the degree of strain women with children experience in various roles (e.g., marital, financial, child-rearing) is related to their emotional well-being (Aneshensel, 1986; Berman & Turk, 1981; D’Ercole, 1988; Kandel et al., 1985; Kazak & Linney, 1983; Vanfossen, 1986). However, all of the previous research used cross-sectional designs,

WOMEN’S STRAINS, SUPPORT, COPING, AND AYFECT 259

whereas the present study found that life strains at one point in time predicted negative affect 6 months, 1 year, or 1 % years later. Thus, the results of this study go beyond previous research in suggesting a potential causal role for life strains on women’s negative affect.

This research also found that life strains were inversely associated with positive affect, which is contrary to the prediction of two-factor theory. This finding may be due to a confounding of the life strain and positive affect measures. Kessler et al. (1985) pointed out that a problem with measures of life strains is that they evaluate rather than describe strains. Similarly, Dohrenwend et al. (1984) and Dohrenwend and Shrout (1985) have shown that one measure of life strains (Kanner et al.’s, 1981, “daily hassles” scale) is confounded with measures of distress. Thus, if a woman perceives a strain in her relationship with her husband, friends, or children, she might also be likely to report a low level of positive affect and a high level of negative affect. One way around this problem is to use a measure of life strains that describes the occurrence of life strains and that requires little inference on the part of the respondent. In the present context, it may be useful to develop a measure which clearly distinguishes between positive social interactions and negative ones. Two-factor theory would predict that negative interactions would be related only to negative affect, and positive interactions would be related only to positive affect.

The second hypothesis was that enacted support would be directly associated with positive affect and unassociated with negative affect. This hypothesis was supported by both the cross-sectional and longitudinal correlations. This suggests that it is the receipt of supportive behavior that is important for positive affect. Moreover, this finding is consistent with previous research which has shown positive affect to be directly associated with the frequency of social activity and support (Earls & Nelson, 1988; Murrell & Norris, 1984; Watson, 1988; Zautra, 1983). The fact that enacted support predicted positive affect at later time periods again speaks to a potential causal influence of support.

The third hypothesis was that perceived support would be associated with both positive affect and negative affect. This hypothesis was supported only by the cross- sectional correlations. This finding is consistent with numerous studies which have shown that perceived support is inversely related to negative emotional states (Barrera, 1986). The finding that support satisfaction was related to both dimensions of affect, whereas enacted support was related only to positive affect, may be due to the problem of confounding mentioned earlier. Also, the fact that the measure of support satisfaction could not predict positive or negative affect at later time periods casts further doubt on the utility of measures of support satisfaction. Future research applying two-factor theory to the phenomena of life strains, support, and emotional well-being needs to pay particular attention to this issue of confounding and to use measures that require more description than inference on the part of the respondents.

The fourth hypothesis was that coping would be correlated with positive affect, but not with negative affect. The cross-sectional correlations clearly supported this hypothesis derived from two-factor theory. However, none of the correlations between coping and positive affect assessed at later time periods was significant. These findings are in sharp contrast to those regarding the predictive relationship between enacted support and positive affect and suggest that coping does not exert a causal influence on positive affect. However, the number of people available to provide support is likely a much more enduring characteristic of an individual than the strategies a person uses to cope with a particular life strain. It could be that coping is causally related to affect,

260 NELSON

but only over a short time period, as DeLongis, Folkman, and Lazarus (1988) have suggested. To test more adequately the causal influence of coping on affect, the interval between assessments should be no more than a few weeks, not several months or a year as it was in this study.

The fifth and sixth hypotheses were that life strains would combine with social support and coping in additive models to predict positive affect. Both of these hypotheses were supported by the cross-sectional findings. Moreover, cross-sectional analyses with controls for earlier levels of positive affect also revealed support for these hypotheses. The longitudinal analyses also provided consistent support for the fifth hypothesis that social support would predict positive affect independent of life strains when the measure of enacted support was used. When the measure of support satisfaction was used, however, support was found to interact with life strains to predict positive affect in two of three cases. It is difficult to know how to explain this anomaly, especially in light of the previously mentioned problems with measures of support satisfaction.

Regarding the sixth hypothesis, the longitudinal analyses did not show that coping could predict positive affect at later time periods. Although this suggests that coping is not causally related to positive affect, perhaps, as was previously argued, the interval between assessments may simply have been too long to detect an effect for coping.

The seventh and eighth hypotheses were that social support and coping would interact with life strains to predict negative affect consistent with the notion of a stress- buffering effect. Although the cross-sectional findings supported these hypotheses, the longitudinal analyses showed that social support, but not coping, interacted with life strains to predict negative affect at later time periods. Previous research using the ASSIS has consistently found stress-buffering effects for enacted support (Barrera, 1981; Earls & Nelson, 1988; Sandler 8c Barrera, 1984), but only Sandler and Barrera (1984) have reported stress-buffering effects for perceived support.

The findings that life strains combine with social support and coping in different models to predict positive affect and negative affect relates to Gottlieb’s (1987) distinction between the “health protection” and “health enhancement” functions of social support and coping. According to Gottlieb (1987):

. . . Social support can contribute to primary prevention in two ways: by protecting health at times when people are exposed to adversity accompanying stressful life events and role transitions, and by enhancing health and morale in everyday life. Its former contribution is reflected in studies documenting a stress-buffering role of support, while its contribution to health promotion is reflected in studies which find a direct or main effect of support on health. (pp. 53-54)

The findings of this research shed further light on this distinction in suggesting that social support and coping can serve a “health protection” effect with respect to negative affect and a “health enhancement” effect with respect to positive affect.

The question of whether life strains, social support, and coping are causally related to positive and negative affect was examined in two ways. First, cross-sectional regression analyses were performed that controlled for earlier levels of affect. Second, longitudinal regression analyses were performed to determine the predictive power of the strain and support variables. The results of those analyses are consistent with the findings of previous research (Cohen et al., 1984; Cohen et al., 1987; Holahan & Moos, 1987) which has shown that both life events and social support can predict future emotional well-being. On the other hand, there was no evidence for a long-term influence of coping on affect.


It must be kept in mind that these findings can only suggest a possible causal role for life strains, social support, and coping on emotional well-being, since a correlational design was used. Experimental or quasi-experimental evaluations of support or coping skills training interventions are necessary to rule out plausible alternative hypotheses. In this regard, Henninger and Nelson (1984) examined the influence of a social support intervention on young unwed mothers’ self-reported positive and negative affect. Women who participated in a self-help group for 6 months maintained a high level of positive affect from pretest to posttest, while those in a control group showed a significant decline on this variable. However, the intervention did not appear to influence negative affect. Further studies of this type are needed to examine the issue of causality.

In summary, this research examined the relationships between women’s life strains, social support, coping, and positive and negative affect from the perspective of two- factor theory of emotional well-being. Life strains and support satisfaction were related to both positive and negative affect. These findings cast doubt on the value of two-factor theory for understanding the phenomena of life strains, social support, and emotional well-being. However, these findings which do not support two-factor theory may be due to a problem of confounded measures. On the other hand, it was found that enacted support and coping were related to positive affect but not to negative affect, which is consistent with two-factor theory. Also, both cross-sectional and longitudinal regression analyses showed that different models predicted positive affect and negative affect. These latter findings suggest that it is important for future research to differentiate between positive affect and negative affect. Further research using unconfounded measures of life strains, social support, and coping is needed to examine the utility of two-factor theory for this area of research. It must also be kept in mind that this study examined the utility of two-factor theory for women’s strains, support, coping, and affect. Studies of men are also needed to determine the utility of this approach.

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