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Five-year trajectories of social networks and social support in older adults with major depression

Published online by Cambridge University Press:  16 April 2007

Corrine I. Voils ,
Jason C. Allaire ,
Maren K. Olsen ,
David C. Steffens ,
Rick H. Hoyle  and
Hayden B. Bosworth
Corrine I. Voils*
Affiliation:
Durham Veterans Affairs Medical Center, Duke University Medical Center, North Carolina, U.S.A.
Jason C. Allaire
Affiliation:
Department of Psychology, North Carolina State University, U.S.A.
Maren K. Olsen
Affiliation:
Durham Veterans Affairs Medical Center, Duke University Medical Center, North Carolina, U.S.A.
David C. Steffens
Affiliation:
Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, North Carolina, U.S.A.
Rick H. Hoyle
Affiliation:
Duke University, Durham, North Carolina, U.S.A.
Hayden B. Bosworth
Affiliation:
Durham Veterans Affairs Medical Center, Duke University Medical Center, North Carolina, U.S.A.
*
Correspondence should be addressed to: Corrine I. Voils, Health Services Research & Development, VA Medical Center (152), 508 Fulton St., Durham, NC 27705. Phone: +1 (919) 286 0411 ext 5196; Fax: +1 (919) 416–5836. Email: voils001@mc.duke.edu.
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Abstract

Background: Research with nondepressed adults suggests that social networks and social support are stable over the life course until very late age. This may not hold true for older adults with depression. We examined baseline status and trajectories of social networks and social support at the group and individual levels over five years.

Methods: The sample consisted of 339 initially depressed adults aged 59 or older (M = 69 years) enrolled in a naturalistic study of depression. Measures of social ties, including social network size, frequency of interaction, instrumental support, and subjective support, were administered at baseline and yearly for five years.

Results: Latent growth curve models were estimated for each aspect of social ties. On average, social network size and frequency of interaction were low at baseline and remained stable over time, whereas subjective and instrumental support were high at baseline yet increased over time. There was significant variation in the direction and rate of change over time, which was not predicted by demographic or clinical factors.

Conclusions: Because increasing social networks may be ineffective and may not be possible for a portion of people who already receive maximal support, interventions to increase social support may only work for a portion of older depressed adults.

Keywords

structural equation modelinglatent growth curve analysissocial supportsocial relationssocial networks
Type
Research Article
Information
International Psychogeriatrics , Volume 19 , Issue 6 , December 2007 , pp. 1110 - 1124
Copyright
Copyright © International Psychogeriatric Association 2007

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References

Antonucci, T. C. 2001. Social relations: an examination of social networks, social support, and sense of control. In Schaie, K. W. (eds.), Handbook of the Psychology of Aging (pp. 427–453). San Diego, CA: Academic Press.Google Scholar
Bentler, P. 1990. Comparative fit indices in structural models. Psychological Bulletin, 107, 238–246. DOI: 10.1037/0033-2909.107.2.238.CrossRefGoogle Scholar
Berkman, L. F. 1995. The role of social relations in health promotion. Psychosomatic Medicine, 57, 245–254.CrossRefGoogle ScholarPubMed
Blazer, D. G. 2003. Depression in late life: review and commentary. Journals of Gerontology Series A: Biological Sciences and Medical Sciences, 58, 249–265.CrossRefGoogle Scholar
Bosworth, H. B., Hays, J. C., George, L. K. and Steffens, D. C. 2002. Psychosocial and clinical predictors of unipolar depression outcome in older adults. International Journal of Geriatric Psychiatry, 17, 238–246. DOI: 10.1002/gps.590.CrossRefGoogle ScholarPubMed
Brissette, I., Cohen, S. and Seeman, T. E. 2000. Measuring social integration and social networks. In Cohen, S., Underwood, L. G. and Gottlieb, B. H. (eds.), Social Support Measurement and Intervention: A Guide for Health and Social Scientists (pp. 53–85). New York: Oxford University Press.CrossRefGoogle Scholar
Browne, M. W. and Cudeck, R. 1993. Alternative ways of assessing model fit. In Bollen, K. A. and Long, J. S. (eds.), Testing Structural Equation Models. Newbury Park, CA: Sage.Google Scholar
Carstensen, L. L., Isaacowitz, D. M. and Charles, S. T. 1999. Taking time seriously: a theory of socioemotional selectivity. American Psychologist, 54, 165–181. DOI: 10.1037/0003-066X.54.3.165.CrossRefGoogle ScholarPubMed
Coyne, J. C. 1976. Depression and the response of others. Journal of Abnormal Psychology, 85, 186–193. DOI: 10.1037/0021-843X.85.2.186.CrossRefGoogle ScholarPubMed
Davidson, J., Turnbull, C. D., Strickland, R., Miller, R. and Graves, K. 1986. The Montgomery-Åsberg Depression Scale: reliability and validity. Acta Psychiatrica Scandinavica, 73, 544–548.CrossRefGoogle ScholarPubMed
Duncan, T. E., Duncan, S. C., Strycker, L. A., Li, F. and Alpert, A. 1999. An Introduction to Latent Variable Growth Curve Modeling: Concepts, Issues, and Applications. Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
George, L. K., Blazer, D. G., Hughes, D. C. and Fowler, N. 1989. Social support and the outcome of major depression. British Journal of Psychiatry, 154, 478–485.CrossRefGoogle ScholarPubMed
Hogan, D. P. and Spencer, L. J. 1993. Kin structure and assistance in aging societies. Annual Review of Gerontology and Geriatrics, 13, 169–186.Google Scholar
Hu, L. and Bentler, P. M. 1999. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1–55.CrossRefGoogle Scholar
Kaplan, R. M., Patterson, T. L., Kerner, D. N., Atkinson, J. H., Heaton, R. K. and Grant, I. 1997. The Quality of Well-Being Scale in asymptomatic HIV-infected patients. Quality of Life Research, 6, 507–514. DOI: 10.1023/A:1018456031659.CrossRefGoogle ScholarPubMed
Krause, N. 1999. Assessing change in social support during late life. Research on Aging, 21, 539–569.CrossRefGoogle Scholar
Landerman, R., George, L. K., Campbell, R. T. and Blazer, D. G. 1989. Alternative models of the stress buffering hypothesis. American Journal of Community Psychology, 17, 625–642. DOI: 10.1007/BF00922639.CrossRefGoogle ScholarPubMed
Morgan, D. L., Neal, M. B. and Carder, P. 1996. The stability of core and peripheral networks over time. Social Networks, 19, 9–25. DOI: 10.1016/S0378-8733(96)00288-2.CrossRefGoogle Scholar
Newsom, J. T. 1999. Another side to caregiving: negative reactions to being helped. Current Directions in Psychological Science, 8, 183–187. DOI: 10.1111/1467-8721.00043.CrossRefGoogle Scholar
Ogilvie, A. D., Morant, N. and Goodwin, G. M. 2005. The burden on informal caregivers of people with bipolar disorder. Bipolar Disorders, 7, 25–32. DOI: 10.1111/j.1399-5618.2005.00191.x.CrossRefGoogle ScholarPubMed
Radloff, L. 1977. The CES-D scale: a self-report depression scale for research in the general population. Applied Psychological Measurement, 3, 385–401.CrossRefGoogle Scholar
Reynolds, C. F. III et al. 2006. Maintenance treatment of major depression in old age. New England Journal of Medicine, 354, 1130–1138. DOI: 10.1056/NEJMoa052619.CrossRefGoogle ScholarPubMed
Steiger, J. H. and Lind, J. C. 1980. Statistically Based Tests for the Number of Common Factors. Iowa City, IA: Psychometric Society.Google Scholar
Stroebe, W., Stroebe, M., Abakoumkin, G. and Shut, H. 1996. The role of loneliness and social support in adjustment to loss: a test of attachment versus stress theory. Journal of Personality and Social Psychology, 70, 1241–1249. DOI: 10.1037/0022-3514.70.6.1241.CrossRefGoogle Scholar
Sultan, S., Fisher, D. A., Voils, C. I., Kinney, A. Y., Sandler, R. S. and Provenzale, D. 2004. Impact of functional support on health-related quality of life in patients with colorectal cancer. Cancer, 101, 2737–2743. DOI: 10.1002/cncr.20699.CrossRefGoogle ScholarPubMed
Vanderhorst, R. K. and McLaren, S. 2005. Social relationships as predictors of depression and suicidal ideation in older adults. Aging and Mental Health, 9, 517–525. DOI: 10.1080/13607860500193062.CrossRefGoogle ScholarPubMed
Voils, C. I., Steffens, D. C., Flint, E. P. and Bosworth, H. B. 2005. Social support and locus of control as predictors of adherence to antidepressant medication in an elderly population. American Journal of Geriatric Psychiatry, 13, 157–165. DOI: 10.1176/appi.ajgp.13.2.157.CrossRefGoogle Scholar
Watanabe, C., Okumura, J., Chiu, T. Y. and Wakai, S. 2004. Social support and depressive symptoms among displaced older adults following the 1999 Taiwan earthquake. Journal of Traumatic Stress, 17, 63–67. DOI: 10.1023/B:JOTS.0000014678.79875.30.CrossRefGoogle ScholarPubMed
Wittink, M. N., Oslin, D., Knott, K. A., Coyne, J. C., Gallo, J. J. and Zubritsky, C. 2005. Personal characteristics and depression-related attitudes of older adults and participation in stages of implementation of a multi-site effectiveness trial (PRISM-E). International Journal of Geriatric Psychiatry, 20, 927–937. DOI: 10.1002/gps.1386.CrossRefGoogle ScholarPubMed
Wothke, W. 2000. Longitudinal and multigroup modeling with missing data. In Little, T. D., Schnabel and, K. U. Baumert, J. (eds.), Modeling Longitudinal and Multiple Group Data: Practical Issues, Applied Approaches and Specific Examples (pp. 219–240). Mahwah, NJ: Lawrence Erlbaum.Google Scholar