# Digital Literacy and Heart Failure Self-Care in Older Patients and Their Caregivers: Dyadic Analysis Using the Actor-Partner Interdependence Model

**Authors:** Hokon Kim, Misook L Chung, Yeonsoo Jang, JiYeon Choi, Byung Su Yoo, Sang Hui Chu

PMC · DOI: 10.2196/85976 · JMIR Aging · 2026-03-12

## TL;DR

This study explores how digital literacy affects heart failure self-care in older patients and their caregivers, finding that individual digital skills matter more than shared effects.

## Contribution

The study introduces a dyadic analysis using the Actor-Partner Interdependence Model to examine how digital literacy influences heart failure self-care behaviors in patient-caregiver pairs.

## Key findings

- Patients had significantly lower digital literacy than caregivers.
- Digital literacy was significantly associated with symptom perception in both patients and caregivers.
- No significant cross-partner effects were found in heart failure self-care behaviors.

## Abstract

The population of patients with heart failure (HF) is rapidly aging, and the prevalence of HF continues to rise among older adults. Effective HF self-care is essential for improving survival and reducing hospital readmissions, and the role of family caregivers in supporting and reinforcing these behaviors has become increasingly important. With the growing integration of digital health technologies into HF management, technology-assisted self-care is becoming more common. However, many older adults experience difficulties in adopting and effectively using digital tools, which may limit the potential benefits of digital health interventions. As both patients’ and caregivers’ levels of digital literacy may jointly shape HF self-care behaviors, a dyadic analytic approach is warranted to clarify their interdependent effects.

This study aimed to compare digital literacy between older patients with HF and their caregivers and to examine how digital literacy influences HF self-care behaviors within patient-caregiver dyads.

This cross-sectional study included 102 patients with HF–caregiver dyads recruited from outpatient clinics in South Korea. Digital literacy was measured using the Everyday Digital Literacy Questionnaire. HF self-care, encompassing 3 key dimensions—self-care maintenance, symptom perception, and self-care management—was assessed using the Self-Care of Heart Failure Index (version 7.2) for patients and the Caregiver Contribution to Self-Care of Heart Failure Index (version 2.0) for caregivers. Dyadic associations were analyzed using the Actor-Partner Interdependence Model with maximum likelihood estimation.

Patients (age: mean 79.4, SD 9.1 years) had significantly lower digital literacy than caregivers (age: mean 59.0, SD 13.1 years). Caregivers primarily consisted of adult children (63/102, 61.8%), followed by spouses (33/102, 32.4%). The Actor-Partner Interdependence Model results revealed significant actor effects of digital literacy on symptom perception for both patients (β=0.26; P=.008) and caregivers (β=0.32; P=.002). For self-care management, a significant actor effect was observed only for patients (β=0.24; P=.02). No significant actor effects were found for self-care maintenance, and no partner effects reached statistical significance across any dimension.

Digital literacy significantly influenced individuals’ own HF self-care behaviors, particularly symptom perception, but cross-partner effects were not observed within dyads. These findings suggest that digital health interventions should assess and address patients’ and caregivers’ digital skills as distinct targets rather than assuming spillover effects within dyads. To optimize HF outcomes in aging populations, culturally sensitive and dyad-focused strategies that consider individual digital literacy are essential.

## Linked entities

- **Diseases:** heart failure (MONDO:0005252)

## Full-text entities

- **Diseases:** symptom (MESH:D012816), HF (MESH:D006333)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## References

51 references — full list in the complete paper: https://tomesphere.com/paper/PMC13022548/full.md

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Source: https://tomesphere.com/paper/PMC13022548