The Relative Impact of Positive and Negative Social Exchanges on Symptoms of Depression

1. The Relative Impact of Positive and Negative Social Exchanges on Symptoms of Depression Jason T. Newsom Portland State University Portland, OR Acknowledgements: Helpful comments were provided by Karen Rook and David Morgan. Masami Nishishiba provided valuable assistance with data anlaysis.

2. Background • Ongoing debate about whether negative or positive exchanges are more important predictors of mental health outcomes such as depression. • Test of this question is difficult without measures that are comparable in content and reliability. • Many prior studies focusing on this question have been based on small and unrepresentative samples. • The present study is based on a large, representative sample of adults over 65 and uses comparable measures of positive and negative exchanges measured across 4 domains.

3. Background • Impact of exchanges is most likely mediated through subjective reactions to those exchanges. • Social support researchers have argued that support perceptions are more important than actual received support (e.g., Kaplan, Cassel, & Gore, 1977; Krause, 1989). • Support researchers distinguish among embeddedness, enacted, perceived support, and satisfaction (e.g., Barrera, 1986; Sarason, Sarason, & Pierce, 1990). • Not all support attempts are viewed positively (Lehman, Ellard, Wortman, 1986; Newsom, 1998; Pagel, Erdly, & Becker, 1987).

4. Outline • Frequency of positive and negative exchanges • Relative strength of positive and negative exchanges predicting depression symptomatology, using 4 parallel domains of exchanges • Unique effects of specific domains of social exchanges • Subjective appraisals of 4 domains of positive exchanges (i.e., satisfaction) and negative exchanges (i.e., botheredness).

5. Positive Social Exchange Measure • 12-item measure, 4 domains, 3 items each • Frequency in the past month (5-point scale ranging from 0 “never” to 4 “very often”) • Informational (e.g., “… offer helpful advice when you need to make important decisions?”) • Instrumental (e.g., “…do favors and other things for you?”) • Emotional (e.g., “… do or say things that were kind or considerate toward you?”) • Companionship (e.g., “…provide you with good company and companionship?”)

6. Negative Social Exchange Measure • 12-item measure, 4 domains, 3 items each • Frequency of occurrence in the past month (5-point scale ranging from 0 “never” to 4 “very often”) • Informational (e.g., “… give you unwanted advice?”) • Instrumental (e.g., “…let you down when you needed help?”) • Emotional (e.g., “… act unsympathetic or critical about your personal concerns?”) • Companionship (e.g., “…forget or ignore you?”)

7. Depression Measure • Center for Epidemiologic Studies Depression scale (CES-D; Radloff, 1977) • Brief 9-item version developed by Santor and Coyne (1997) • 3 domains (following McCallum, MacKinnon, Simons, & Simons, 1995) : • Positive affect (e.g., “You were happy”), 2 items • Negative Affect (e.g., “You felt sad”), 4 items • Somatic Symptoms (e.g., “Your sleep was restless”), 3 items • 4-point response scale ranging from 0 “None of the time” to 4 “Most of the time”

8. Subjective Appraisal of Positive Exchanges • Satisfied with Positive Exchanges • Degree of satisfaction with each of the four positive exchange domains in the past month • “In general, how satisfied are you with the advice and information that you receive?” • 4-point response scale ranging from 0 “Not at all satisfied” to 3 “Very satisfied” • Only those reporting some occurrence of each domain of positive exchange included

9. Subjective Appraisal of Negative Exchanges • Bothered by Negative Exchanges • Degree to which the respondent was bothered by each of the four negative exchange domains in the past month • “In general, how bothered are you when you receive unwanted advice or opinions?” • 4-point response scale ranging from 0 “Not at all bothered” to 3 “Very bothered” • Those reporting no occurrence in the past month were coded as 0 (“Not at all bothered”)

10. Analyses • Structural equation models using Mplus, version 2.02 (Muthen & Muthen, 1998). • Because of concerns about multivariate nonnormality, ML with Satorra-Bentler correction for chi-square and standard errors (Satorra & Bentler, 1994) • Fit statistics: • Chi-square (affected by model complexity and sample size) • Bollen’s Incremental Fit Index (IFI; Bollen, 1989), .95 and above indicates excellent fit (Hu & Bentler, 1999) • Standardized Root Mean Square Residual (SRMR; Bentler, 1995), .06 and below indicates excellent fit (Hu & Bentler, 1999) • Fit indices computed using Satorra-Bentler adjusted chi-square for the null model

11. Analyses • Measurement models: • Second-order confirmatory factor models of positive exchanges, negative exchanges, depression. • First-order confirmatory factor model of satisfaction and botheredness • Correlated measurement errors between positive and negative exchanges for parallel domains • Correlated disturbances between positive and negative exchanges for parallel domains

12. Analyses • Structural models: • Relative impact of positive and negative exchanges overall • Relative impact of specific domains • Relative impact of subjective appraisals • All models controlled for: • Age, Education, Self-reported Health, IADL/ADLs, Health Conditions

13. Frequency of Social Exchanges

14. Measurement Model for Positive Exchanges Positive Exchanges .663 .608 .654 .863 Informational Instrumental Emotional Companionship .865 .880 .882 .812 .842 .919 .842 .907 .851 .897 .631 .907 Ways to deal with problems Discuss personal matters Provide assistance Helpful advice Useful suggestions Do favors Help important tasks Kind and considerate Cheer you up Provide company Include you Do social activities Model Fit Statistics: N= , χ2(50)= 190.133, p<.001, SRMR=.044, IFI= .975. All loadings significant at p < .001. Correlated errors and disturbances not shown.

15. Measurement Model for Negative Exchanges Negative Exchanges .708 .698 .760 .820 Informational Instrumental Emotional Companionship .870 .757 .791 .815 .657 .886 .803 .915 .802 .845 .879 .756 Interfere in Personal matters Ask for too much help Fail to give assistance Do thoughtless things Act angry or upset with you Act unsympathetic or critical Forget/ ignore you Fail to spend time Unwanted advice Question your decisions Let you down Leave you out Model fit statistic: N= , χ2(50)= 71.696, p=.0238, SRMR=.031, IFI= .991. All loadings significant at p < .001. Correlated errors and disturbances not shown.

16. Measurement Model for Depression Depression (CES-D ) .795a .882a .810a Somatic Symptoms Positive Affect Negative Affect Happy Enjoy Bothered Blues Depressed Sad Mind Effort Sleep Model Fit Statistics: N= 868, χ2(26)= 68.690, p<.001, SRMR=.055, IFI= .976 a Second-order loadings were set equal for empirical identification. All loadings significant at p < .001.

17. Model Comparing the Effects of Positive and Negative Exchanges on Depression Positive Exchanges Depression (CESD) Negative Exchange Age, Education, Self-reported Health, IADL/ADLs, Health Conditions

18. Relative impact of positive and negative exchanges on depression, structural model results

19. The relative effect of individual domains of positive and negative exchanges on depression, structural model results

20. Measurement Model of Subjective Appraisal of Positive and Negative Exchanges on Depression -.460 Satisfaction with Positive Exchanges Bothered by Negative Exchanges .483 .660 .546 .549 .661 .662 .661 .761 Informational Instrumental Emotional Companionship Informational Instrumental Emotional Companionship Model Fit Statistics: N= 624, χ2(19)= 30.387, p<.047, SRMR=.029, IFI= .983 All loadings significant at p < .001.

21. Structural Model Comparing the Effects of the Subjective Appraisal of Positive and Negative Exchanges on Depression Satisfaction Depression (CESD) Bothered Age, Education, Self-reported Health, IADL/ADLs, Health Conditions

22. The effect of subject appraisal of positive and negative exchanges on depression, structural model results

23. Summary and Conclusions • Between 79-92% report one or more positive exchanges. • Positive exchanges in the emotional and companionship domains were the most common. • Fewer (26-43%) reported one or more negative exchanges. • Negative exchanges in the informational domain (e.g., unwanted advice) were the most common. • Negative exchanges have far greater impact on depressive symptoms than positive exchanges when comparable measures are used, after controlling for age, gender, education, and health variables.

24. Summary and Conclusions • When subjective appraisals of exchanges are examined, the impact of positive and negative exchanges is approximately equal. • Positive exchanges may be expected, leading to a lesser impact unless supportive actions are particularly appreciated. • Not all supportive attempts by network members will be viewed positively (e.g., Krause, 1995; Lehman, Ellard, & Wortman, 1986), whereas negative exchanges will rarely be interpreted positively.

25. Future Research • Investigate sources of positive and negative exchanges and number of network members associated with positive and negative exchanges. • Estimate the frequency with which supportive attempts are not positively appraised. • Interaction of frequency and negative appraisals.

26. Future Research • Examine the extent to which satisfaction is affected by presence of negative interactions and, conversely, the extent to which botheredness is affected by the presence of positive exchanges (Krause, 1995). • What factors determine subjective appraisals of positive support? When are supportive attempts viewed negatively (Smith & Goodnow, 1999)? To what extent are appraisals determined by recipient characteristics (e.g., self-esteem) vs. provider characteristics (e.g., social skills), contextual factors (e.g., history of conflict, reciprocity), or situational factors? Are some people more reactive to negative exchanges?