Conducting a National, Longitudinal Examination of Dual-Role Caregiving and Developing Reusable Analytical Tools to Facilitate Research using CLSA Data.

Abstract

Background
Family caregivers experience substantial burden and distress, yet longitudinal evidence is scarce, particularly for individuals concurrently providing and receiving care (“dual-role caregivers”) who may face compounded vulnerability. The Canadian Longitudinal Study on Aging (CLSA) offers a population-based opportunity which we leveraged to conduct a longitudinal study of dual-role caregiving. In parallel, we developed an R package to improve efficiency and transparency of all CLSA-based research.

Method
We classified CLSA participants at each study cycle as caregivers-only, care-recipients-only, dual-role caregivers, or neither caregiving/care-receiving, and visualized role transitions using a Sankey diagram. We compared socio-demographics, caregiving activities, health measures, and satisfaction with life (SWL) between caregivers-only and dual-role caregivers. The R package contains three core components: 1) harmonization of missing/invalid values across cycles; 2) automated data quality assessments; 3) creation of derived variables (e.g., caregiving/care-receiving flags; composite outcome measures).

Results
At baseline, 19,551/51,169 participants provided care, of whom 13.9% were dual-role caregivers – this increased to 19.5% by Follow-Up2. Compared with caregivers-only, dual-role caregivers were more often female, had lower income, poorer health, lower SWL, and greater functional impairments. While providing substantial care, dual-role caregivers also required considerable support, including informal and professional personal care (22% and 11%, respectively) and medical care (15% and 30%, respectively). Functional decline at subsequent cycle was more common among dual-role caregivers (14.5%) than caregivers-only (7.5%).

Discussion
Our study highlights that dual-role caregivers are increasingly prevalent and experience heightened vulnerabilities. The accompanying R package provides a scalable, transparent resource to support future CLSA research.