Identifying trajectories of depressive symptoms for women caring for their husbands with dementia.
Journal Article (Journal Article)
OBJECTIVES: To use an innovative statistical method, Latent Class Trajectory Analysis (LCTA), to identify and describe subgroups (called trajectories) of caregiver depressive symptoms in a national sample of wives providing informal care for their husbands with dementia. DESIGN: Longitudinal. SETTING: Community. PARTICIPANTS: Respondents to the National Longitudinal Caregiver Survey were wife caregivers of veterans with dementia who were identified through Veterans Affairs hospitals nationally. MEASUREMENTS: Mean number of depressive symptoms as measured using the Center for Epidemiologic Studies Depression scale (CES-D, 20-item scale). RESULTS: Overall mean depressive symptoms of wife caregivers were 6.2 of 20, below the cutpoint (8 or 9/20) associated with clinical depression. Four distinct trajectories of caregiver depressive symptoms were identified. The trajectory with the highest number of symptoms (11.9 of 20), contained one-third of the sample. Another third had mean depressive symptoms virtually identical to the overall sample mean. The final third were divided between two trajectories, low depressive symptoms (mean CES-D, 3.0/20, 22% of sample) and very low (mean CES-D, 0.8/20, 14% of sample). Approximately two-thirds of the sample members were in a depressive symptom trajectory, with substantially higher or lower numbers of symptoms than the overall mean. Two subjective measures asked of wife caregivers (desire for more help, life satisfaction) were significantly associated with membership in the highest depressive symptom trajectory. CONCLUSION: LCTA identified important depressive symptom subgroups of wife caregivers. A population-averaging method identified a mean effect that was similar to the effect in one-third of the cases but substantially different from that in two-thirds of the cases.
- Taylor, DH; Ezell, M; Kuchibhatla, M; Østbye, T; Clipp, EC
- February 2008
Volume / Issue
- 56 / 2
Start / End Page
- 322 - 327
Pubmed Central ID
Electronic International Standard Serial Number (EISSN)
Digital Object Identifier (DOI)
- United States