Abstract 4366392: Comparable Improvement of a Sensor-Controlled Digital Game Intervention and a Sensor-Based Control on Self-Care and Outcomes in Older Adults with Heart Failure: A Randomized Controlled Trial

Introduction: Older adults with heart failure (HF) have well-established barriers to consistent engagement in effective self-care behaviors. Inadequate self-care leads to declines in functional status, diminished quality of life, and increased rates of hospitalization. We evaluated a sensor-controlled digital game (SCDG), Heart Health Mountain, that used data from sensor devices (smart scale and activity tracker) to promote engagement in HF self-care compared to a control group that received only the sensor devices. Hypothesis: A SCDG would improve HF-related outcomes of self-efficacy, knowledge, self-care behaviors, functional status, quality of life, and hospitalizations compared to a sensor control group at weeks 6, 12, and 24. Methods: In this decentralized, 6-month RCT, 200 adults aged >45 years with NYHA Class I-III HF from 20 southern U.S. states were randomized 1:1 to either the intervention group (IG) or control group (CG). Outcome variables were collected at baseline and the 3 timepoints using online surveys. Analyses included descriptive statistics and linear mixed-effects models to assess group, time, and interaction effects. Results: Of 146 participants who completed the 6-month RCT from the 199 enrolled at the time of this abstract (mean age 59.4 years; 65.8% male; 80.8% White, 52.1% with financial hardship), 72 were randomized to the IG and 74 to CG. Linear mixed-effects models showed significant improvements over time in self-care confidence (SCHFI: +14.7 points at 24 weeks, p < .001), self-care behaviors (EHFBS: +8.1, p < .001), functional status (KCCQ: +5.6, p = .003), and quality of life (KCCQ-QoL: +12.9, p < .001), but no significant group-by-time effects. HF knowledge remained stable over time, with no statistically significant change observed (AHFKT: +1.31 at 24 weeks, p = 0.466). HF-related hospitalizations were lower in the IG at 6 weeks (4.2% vs. 18.9%), with smaller differences at later time points (e.g., 24 weeks: 16.7% vs. 17.6%). Conclusion: Although the SCDG (IG) did not result in statistically significant differences in outcomes compared to CG, both groups who received sensor-based digital tools showed significant improvements over time in self-efficacy, self-care behaviors, functional status, and quality of life among older adults with HF. These findings highlight the potential of digital tools to improve HF self-management and underscore the need for future interventions that are more personalized and adapted to individual needs.

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Publication Details

Journal
Circulation
Published
2025-11-03
DOI
https://doi.org/10.1161/circ.152.suppl_3.4366392
Primary Topic
Heart Failure Treatment and Management
Type
article
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article

Abstract 4366392: Comparable Improvement of a Sensor-Controlled Digital Game Intervention and a Sensor-Based Control on Self-Care and Outcomes in Older Adults with Heart Failure: A Randomized Controlled Trial

Kavita Radhakrishnan, Jay Bartroff, Christine Julien, N. Clifford et al.
Circulation
Heart Failure Treatment and Management
article

Abstract 4366392: Comparable Improvement of a Sensor-Controlled Digital Game Intervention and a Sensor-Based Control on Self-Care and Outcomes in Older Adults with Heart Failure: A Randomized Controlled Trial

Kavita Radhakrishnan, Jay Bartroff, Christine Julien, N. Clifford, Jie Zeng, Matthew O’Hair, Rachel Tunis, Tom Baranowski, Grace Lee
article en

Abstract

Introduction: Older adults with heart failure (HF) have well-established barriers to consistent engagement in effective self-care behaviors. Inadequate self-care leads to declines in functional status, diminished quality of life, and increased rates of hospitalization. We evaluated a sensor-controlled digital game (SCDG), Heart Health Mountain, that used data from sensor devices (smart scale and activity tracker) to promote engagement in HF self-care compared to a control group that received only the sensor devices. Hypothesis: A SCDG would improve HF-related outcomes of self-efficacy, knowledge, self-care behaviors, functional status, quality of life, and hospitalizations compared to a sensor control group at weeks 6, 12, and 24. Methods: In this decentralized, 6-month RCT, 200 adults aged >45 years with NYHA Class I-III HF from 20 southern U.S. states were randomized 1:1 to either the intervention group (IG) or control group (CG). Outcome variables were collected at baseline and the 3 timepoints using online surveys. Analyses included descriptive statistics and linear mixed-effects models to assess group, time, and interaction effects. Results: Of 146 participants who completed the 6-month RCT from the 199 enrolled at the time of this abstract (mean age 59.4 years; 65.8% male; 80.8% White, 52.1% with financial hardship), 72 were randomized to the IG and 74 to CG. Linear mixed-effects models showed significant improvements over time in self-care confidence (SCHFI: +14.7 points at 24 weeks, p < .001), self-care behaviors (EHFBS: +8.1, p < .001), functional status (KCCQ: +5.6, p = .003), and quality of life (KCCQ-QoL: +12.9, p < .001), but no significant group-by-time effects. HF knowledge remained stable over time, with no statistically significant change observed (AHFKT: +1.31 at 24 weeks, p = 0.466). HF-related hospitalizations were lower in the IG at 6 weeks (4.2% vs. 18.9%), with smaller differences at later time points (e.g., 24 weeks: 16.7% vs. 17.6%). Conclusion: Although the SCDG (IG) did not result in statistically significant differences in outcomes compared to CG, both groups who received sensor-based digital tools showed significant improvements over time in self-efficacy, self-care behaviors, functional status, and quality of life among older adults with HF. These findings highlight the potential of digital tools to improve HF self-management and underscore the need for future interventions that are more personalized and adapted to individual needs.

CirculationVol. 152(Suppl_3)
Baylor College of Medicine (US), Virginia Tech (US), The University of Texas at Austin (US)
Openalex Percentile: Top 52%
Heart Failure Treatment and Management
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