ESRA 2027 sessions by theme

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A substantial part of every society's population needs care, either in long-term care facilities or at home, often supported by family members and professional care providers. Due to their health-related problems, people in need of care are often underrepresented or excluded from representative surveys, limiting the possibility to make valid inferences from the resulting data. Yet, their inclusion is crucial for understanding social outcomes across different living and care arrangements and for informing policies that address the needs of vulnerable groups.
Surveying people in need of care poses particular methodological and ethical challenges. Reaching and recruiting them may require adapted sampling and fieldwork procedures that vary across care settings. In institutional settings, suitable sampling frames may be difficult to obtain, while panel studies face challenges tracking the transitions into institutionalized living, contributing to sample attrition. Access may also depend on relatives, informal or professional caregivers, or institutions acting as gatekeepers.
Interviewing people with cognitive, sensory, or physical impairments raises further questions concerning informed consent, decision-making capacity, respondent burden, and data quality. Assisted or proxy interviews may facilitate participation, but can affect measurement quality, representativeness and comparability to self-reported data.
Against this background, this session invites contributions that address these challenges and propose solutions for surveying people in need of care. Topics may include, but are not limited to:
• Sampling and recruiting people in need of care across different living and care settings
• Monitoring changes in living and care arrangements in panel studies
• Engaging gatekeepers to support research efforts
• Practical solutions for conducting interviews with people in need of care
• Ethical issues, including consent and vulnerability
• Assisted and proxy interviews and their implications for representativeness, data quality, and comparability