Predicting gains in dementia caregiving

Dement Geriatr Cogn Disord. 2010;29(2):115-22. doi: 10.1159/000275569. Epub 2010 Feb 11.

Abstract

Background: Caregiver gain is an important yet less-explored phenomenon. Being conceptually distinct from burden, factors associated with burden and gain can differ. This study aims to explore factors associated with the experience of gains in dementia caregiving.

Method: Cross-sectional study involving caregivers recruited from a tertiary hospital dementia clinic and the local Alzheimer's Association. Caregivers completed a questionnaire containing the following scales: gain in Alzheimer's care Instrument (GAIN), General Health Questionnaire (GHQ-28), Dementia Management Strategies Scale (DMSS), Revised Memory and Behavioral Problems Checklist (RMBPC) and Zarit Burden Interview (ZBI). Demographic information for the person with dementia (PWD) and the caregiver was also recorded. Initial screening with univariate analyses (t tests, ANOVAs, Pearson's correlations) was performed to identify significant (p < 0.05) variables, which were then entered into a multiple regression model to identify variables associated with gain.

Result: The final sample comprised 334 caregivers with a mean age of 51.5 years (SD = 10.9, range = 22-85), the majority of whom where Chinese (94.6%) females (71%). Mean GAIN score was 30 (SD = 6.6, range = 7-40). Regression analysis identified 3 factors significantly associated with gains (adjusted R(2) 32.3%): mental well-being of the caregiver, use of active management as a caregiving strategy, and participation in caregiver educational and support group programmes.

Conclusion: The results have important implications for caregiver interventions. Interventions should target maintaining mental well-being, encouraging participation in educational and support programmes, and teaching appropriate coping and dementia specific management strategies to derive good outcomes.

MeSH terms

  • Age Factors
  • Aged
  • Caregivers / psychology*
  • Caregivers / statistics & numerical data
  • Cost of Illness
  • Data Collection
  • Dementia / epidemiology
  • Dementia / psychology*
  • Female
  • Forecasting
  • Health
  • Humans
  • Linear Models
  • Male
  • Memory / physiology
  • Neuropsychological Tests
  • Patient Education as Topic*
  • Quality of Life
  • Sex Factors
  • Singapore / epidemiology
  • Social Support
  • Socioeconomic Factors
  • Surveys and Questionnaires