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DOI 10.1016/j.ijnurstu.2026.105589

Медицинская библиотека · International journal of nursing studies · 2026

Digital health self-management support for stroke patients following discharge: A randomized controlled trial.

Jiang Ning, Feng Ling, Tian Tian, Wu Yating, Wang Rui, Lai Zhenli, Xiao Yuling, Song Rui, Zhou Shisong, Chen Xiangyu, Zhang Ni, Jiang Xiaolian

СтатьяРандомизированное исследованиеПеревод пока не подготовлен

Аннотация

BACKGROUND

Stroke is the leading cause of death and disability among adults in China. Effective self-management after hospital discharge can significantly improve patients' quality of life. However, the current level of self-management among stroke survivors in China remains suboptimal, highlighting an urgent need for innovative support strategies.

OBJECTIVES

To develop an individualized and dynamic self-management support program based on wearable technology and the solution-focused model, evaluate its effectiveness, and provide new insights for advancing post-stroke care models.

METHODS

A total of 183 stroke patients scheduled for discharge were randomly assigned to one of three groups-smartwatch, wristband, or control-with 61 participants per group. Over an 8-week intervention period, participants in the smartwatch intervention group received support through a personalized cloud platform that integrated real-time data from smartwatches, patient-maintained self-management diaries, and semi-structured interviews, to identify dynamic issues and obtain tailored feedback. Outcome measures-including self-management behaviors, resilience, patient activation, social support, Barthel Index, depression, blood pressure, glucose concentration, and stroke recurrence-were assessed at baseline (T0) and at 2 (T1), 3 (T2), and 6 (T3) months post-discharge. Intervention effects were analyzed using linear mixed-effects models.

RESULTS

The cloud platform comprised a smartwatch interface, HMS Core application software, and a WeChat mini-program. The intervention significantly improved: self-management behaviors (T1: β = 27.496, p < 0.001; T2: β = 13.855, p = 0.004; T3: β = 10.649, p = 0.025), resilience (T1: β = 5.361, p < 0.001; T2: β = 3.498, p = 0.01; T3: β = 3.519, p = 0.01), patient activation (T1: β = 17.836, p < 0.001; T2: β = 14.302, p < 0.001; T3: β = 15.13, p < 0.001), and Barthel Index (T1: β = 5.225, p = 0.049; T3: β = 5.594, p = 0.035).

CONCLUSIONS

The individualized and dynamic self-management support program effectively enhanced self- management behaviors, resilience, and patient activation in stroke survivors. It also showed promising trends toward reducing post-stroke depression and recurrence, and may contribute to better control of blood pressure and glucose concentration.

REGISTRATION: Registered at chictr.org.cn, ChiCTR2300070384, on April 11, 2023, https://www.chictr.org.cn/showproj.html?proj=193286. The protocol version is ESC 1.0.

Для цитирования: Jiang Ning, Feng Ling, Tian Tian, Wu Yating, Wang Rui, Lai Zhenli, Xiao Yuling, Song Rui, Zhou Shisong, Chen Xiangyu, Zhang Ni, Jiang Xiaolian. Digital health self-management support for stroke patients following discharge: A randomized controlled trial.. International journal of nursing studies. 2026. DOI: 10.1016/j.ijnurstu.2026.105589.

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