Dyadic Health Literacy and Its Association with Care Collaboration and Satisfaction in Heart Failure...

Effective heart failure self-care depends on robust collaboration within patient-caregiver dyads. Health literacy is crucial for illness management, but its patterns and links to dyadic care collaboration and satisfaction are unclear.

This study aimed to identify the latent profiles of health literacy in heart failure patient-caregiver dyads and to examine how these profiles relate to dyadic care collaboration and satisfaction with care type.

A cross-sectional descriptive study was conducted. A total of 231 heart failure patient-caregiver dyads were recruited from four tertiary hospitals in Beijing, China, between September 2023 and August 2024. Health literacy was measured using the Heart Failure-Specific Health Literacy Scale (HFS-HLS), while dyadic collaboration and satisfaction were assessed via the Dyadic Symptom Management Type scale (DSMT). Latent profile analysis was conducted using Mplus 8.3 to identify distinct health literacy profiles. Binary logistic regression analyses were performed to evaluate the associations between dyadic health literacy profiles, dyadic care collaboration, and satisfaction.

Latent profile analysis identified two distinct health literacy profiles: a "Low Dyadic Health Literacy" group and a "High Dyadic Health Literacy" group. Binary logistic regression revealed that patient gender, number of hospitalizations, caregiver gender, and caregiver education level were significant independent predictors of profile membership. Dyads classified in the high health literacy profile were significantly more likely to engage in collaborative care and to report higher levels of caregiver satisfaction.

Heart failure patient-caregiver dyads with higher levels of dyadic health literacy are more inclined to adopt collaborative care approaches and express greater satisfaction with their care arrangements. These findings suggest that routine assessment of dyadic health literacy in clinical settings may help identify at-risk dyads and guide interventions development.