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Updated: Jun 17, 2025

A Novel Digital Platform for a Monitored Home-based Cardiac Rehabilitation Program
Published on: April 19, 2019
Effects of Social Isolation and Loneliness on Heart Failure Self-care: A Cross-sectional Analysis
Background:
Patients with heart failure (HF) who engage in effective HF self-care have better quality of life, and lower risks of all-cause and HF-related hospital readmission and mortality. It is unclear whether social isolation and loneliness, which are prevalent among patients with HF and known to affect other self-care behaviors, can predict HF self-care.
Objective:
The aim was to explore the relationship between social isolation, loneliness, and HF self-care.
Methods:
This was a cross-sectional secondary analysis (n = 49) of the GEtting iNTo Light Exercise for HF randomized controlled trial, a 6-month home-based live group gentle exercise intervention for patients with HF. Measures included the following: 6-item Lubben Social Network Scale for social isolation, Patient-Reported Outcomes Measurement Information System Social Isolation survey for loneliness, Self-Care of Heart Failure Index, and Patient-Reported Outcomes Measurement Information System Depression survey. Multiple linear regression modeling was used to examine the relationships of 4 HF self-care processes to social isolation and loneliness, adjusting for depression and grouping (control group or intervention group).
Results:
Scores indicating less social isolation predicted higher self-care maintenance ( B = 0.937, P = .015), monitoring ( B = 0.799, P = .041), and management ( B = 1.812, P < .001). Loneliness did not predict HF self-care.
Conclusions:
To our knowledge, this is the first study to predict HF self-care using distinct measures for social isolation and loneliness. Patients who were less socially isolated engaged in better HF self-care; loneliness had no relationship with HF self-care. Prospective studies are needed to investigate causal relationships between social isolation and HF-self-care engagement to determine the effect on outcomes such as hospital readmission and mortality.
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