Dementia Caregiver Quality Profiles from Chinese Hospital Survey

A cross-sectional survey of 213 dyads of people with dementia and their informal caregivers in Wuhan, China, conducted between July 2023 and July 2024. The dataset was created by researcher Chan Cai to identify distinct profiles of care quality and their influencing factors. It includes results from latent profile analysis, multinomial logistic regression, and ROC analysis for determining a cut-off score on the Exemplary Care Scale.

Use Cases

• Classify caregivers into high, moderate, or low quality-of-care profiles using latent profile analysis results.
• Predict care quality profile membership from factors like caregiver monthly income, social support, perceived overload, and pre-illness relationship quality.
• Validate the Exemplary Care Scale cut-off score of 15 for identifying low-quality care using the provided sensitivity (0.993) and specificity (0.955) metrics.
• Analyze associations between patient Activities of Daily Living (ADL) scores and the likelihood of receiving high-quality informal care.

Strengths

• Includes data from 213 patient-caregiver dyads, providing a substantive sample for analysis.
• Clear temporal coverage from a one-year survey period (July 2023 to July 2024).
• Results validated via ROC analysis with high reported sensitivity and specificity.

Limitations

• Limited geographic scope to hospitals and communities in Wuhan, China, reducing generalizability.
• Small sample size of 213 dyads may limit statistical power for subgroup analyses.
• Cross-sectional design prevents analysis of causal relationships or care quality changes over time.

Provenance

Source

Chan Cai via figshare.

Collection Method

Cross-sectional survey conducted in memory, rehabilitation, and neurological clinics and communities.

Time Range

July 15, 2023 to July 14, 2024.

Freshness

Data collected up to July 2024, with platform entry updated in April 2026.

Geography

Wuhan, Hubei, China.