Abstract WP307: Digital Health Tools and Wearable Technologies for Secondary Stroke Prevention: Effects on Physical Activity and Weight Outcomes

Introduction: Digital health interventions might help improve modifiable vascular risk factors such as physical activity and weight. However, their effectiveness in improving health behavior and secondary prevention after stroke or transient ischemic attack (TIA) remain uncertain. We systematically reviewed studies assessing the impact of digital health tools or devices on physical activity and body weight outcomes in this population. Methods: We searched MEDLINE, Embase, and Cochrane (inception–Feb 2025) using terms related to stroke, TIA, secondary prevention, and digital health tools or devices. Studies reporting physical activity, weight or body mass index (BMI) outcomes after stroke or TIA were included. A meta-analysis was planned if ≥3 studies reported the same outcome with comparable measures; where possible, weighted demographics were calculated. Risk of bias was assessed using RoB-2 for randomized clinical trials (RCTs) and ROBIN-1 for non-randomized studies. Results: Seven studies reported on physical activity (n=551 total; intervention N=351, mean age=59 years, 35% female; control N=200, mean age=59 years, 33% female) and 6 weight management studies (n=511 total; intervention N=325, mean age=44 years, 40% female; control N=186, mean age=43 years, 38.2% female). Interventions included using mobile apps and wearable activity trackers for self-monitoring with goal setting and sometimes tele-coaching. Five studies that reported on physical activity demonstrated 26%-167% increases in steps/day, active minutes, or self-reported activity versus baseline or control (Figure 1). With regards to weight management studies, reported effects were mixed; Four short-duration studies showed minimal or no change, while two observed modest weight loss (Figure 2). Risk of bias assessment found most RCTs to be at low-moderate risk (physical activity: 4/5; weight: 4/4), with one study rated high risk of bias. All non-randomized studies were at serious risk of bias. There was heterogeneity in intervention content, outcome measures, and follow-up that precluded meta-analysis for most outcomes. So we present descriptive pooled summaries of relative improvements. Conclusions: Digital health tools and devices can improve physical activity among stroke and TIA survivors, but evidence for weight reduction is limited. Future research should address longer follow-up, standardized outcome reporting, and diverse populations to clarify generalizability and sustained benefits.

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Journal
Stroke
Published
2026-01-29
DOI
https://doi.org/10.1161/str.57.suppl_1.wp307
Primary Topic
Stroke Rehabilitation and Recovery
Type
article
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article

Abstract WP307: Digital Health Tools and Wearable Technologies for Secondary Stroke Prevention: Effects on Physical Activity and Weight Outcomes

Shumei Man, Margarita Fedorova, Ken Uchino, Neil Nero
Stroke
Stroke Rehabilitation and Recovery
article

Abstract WP307: Digital Health Tools and Wearable Technologies for Secondary Stroke Prevention: Effects on Physical Activity and Weight Outcomes

Shumei Man, Margarita Fedorova, Ken Uchino, Neil Nero
article en

Abstract

Introduction: Digital health interventions might help improve modifiable vascular risk factors such as physical activity and weight. However, their effectiveness in improving health behavior and secondary prevention after stroke or transient ischemic attack (TIA) remain uncertain. We systematically reviewed studies assessing the impact of digital health tools or devices on physical activity and body weight outcomes in this population. Methods: We searched MEDLINE, Embase, and Cochrane (inception–Feb 2025) using terms related to stroke, TIA, secondary prevention, and digital health tools or devices. Studies reporting physical activity, weight or body mass index (BMI) outcomes after stroke or TIA were included. A meta-analysis was planned if ≥3 studies reported the same outcome with comparable measures; where possible, weighted demographics were calculated. Risk of bias was assessed using RoB-2 for randomized clinical trials (RCTs) and ROBIN-1 for non-randomized studies. Results: Seven studies reported on physical activity (n=551 total; intervention N=351, mean age=59 years, 35% female; control N=200, mean age=59 years, 33% female) and 6 weight management studies (n=511 total; intervention N=325, mean age=44 years, 40% female; control N=186, mean age=43 years, 38.2% female). Interventions included using mobile apps and wearable activity trackers for self-monitoring with goal setting and sometimes tele-coaching. Five studies that reported on physical activity demonstrated 26%-167% increases in steps/day, active minutes, or self-reported activity versus baseline or control (Figure 1). With regards to weight management studies, reported effects were mixed; Four short-duration studies showed minimal or no change, while two observed modest weight loss (Figure 2). Risk of bias assessment found most RCTs to be at low-moderate risk (physical activity: 4/5; weight: 4/4), with one study rated high risk of bias. All non-randomized studies were at serious risk of bias. There was heterogeneity in intervention content, outcome measures, and follow-up that precluded meta-analysis for most outcomes. So we present descriptive pooled summaries of relative improvements. Conclusions: Digital health tools and devices can improve physical activity among stroke and TIA survivors, but evidence for weight reduction is limited. Future research should address longer follow-up, standardized outcome reporting, and diverse populations to clarify generalizability and sustained benefits.

StrokeVol. 57(Suppl_1)
Cleveland Clinic (US)
Openalex Percentile: Top 74%
Stroke Rehabilitation and Recovery
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