可穿戴增强型移动健康干预促进手动轮椅使用者身体活动:单组前后可行性研究。
Wearable-Enhanced mHealth Intervention to Promote Physical Activity in Manual Wheelchair Users: Single-Group Pre-Post Feasibility Study.
作者信息
Huang Zijian, McCoy Dan, Cooper Rosemarie, Crytzer Theresa M, Chi Yueyang, Ding Dan
机构信息
Department of Rehabilitation Science and Technology, School of Health and Rehabilitation Sciences, University of Pittsburgh, 6425 Penn Ave, Suite 401, Pittsburgh, PA, 15206, United States, 1 4126241964.
Department of Veteran Affairs Pittsburgh Healthcare System, Human Engineering Research Laboratories, Pittsburgh, PA, United States.
出版信息
JMIR Rehabil Assist Technol. 2025 Jun 5;12:e70063. doi: 10.2196/70063.
BACKGROUND
With the rapid advancement of technology, using wearable devices and mobile health (mHealth) apps to monitor and promote physical activity (PA) has become increasingly popular among individuals with various chronic conditions. However, such work remains limited among individuals with spinal cord injury (SCI), especially those who use a manual wheelchair for mobility.
OBJECTIVES
The study aims to describe the development of the WheelFit mHealth app for monitoring and promoting PA in manual wheelchair users (MWUs) with SCI and evaluate its feasibility and usability in free-living conditions.
METHODS
The WheelFit app, based on the Fogg Behavioral Model with inputs from stakeholders, including MWUs, physical therapists, and personal trainers, was developed to promote PA in MWUs. It works with two commercial wearable devices, that is, an Android smartwatch and a wheel sensor, which stream users' upper extremity and wheelchair movement to the app to calculate PA variables using custom algorithms. Users can set personal goals, review daily progress and PA history, and access an adaptive workout library within the app. A 4-week single-group pre-post study, consisting of a 1-week baseline and 3-week intervention phase, was conducted to evaluate WheelFit's feasibility and usability. Feasibility was evaluated using the session attendance rate, device and app usage, and implementation of action plans. Usability was assessed using the system usability scale. The preliminary effectiveness was assessed by comparing preintervention and postintervention PA variables and scores from the SCI exercise self-efficacy scale.
RESULTS
A total of 16 participants completed the study protocol with 100% session attendance and maintained 14.2 hours of daily device and app connection. Participants demonstrated varying levels of adherence to their action plans. The excellent usability of WheelFit was indicated by an average system usability scale score of 81.8 (SD 19.2) points. Statistically significant increases between pre-post daily exercise times (preintervention: mean 26.4, SD 16.9 minutes; postintervention: mean 33.3, SD 24.9 minutes; P=.049) and exercise self-efficacy scale scores (preintervention: mean 33.9, SD 4.5 points; postintervention: mean 35.9, SD 3.2 points; P=.043) were observed.
CONCLUSIONS
The WheelFit app demonstrated promising feasibility, usability, and a positive impact on promoting PA in MWUs with SCI. Future investigation exploring the potential integration of the WheelFit app into clinical practice is warranted.
背景
随着技术的飞速发展,使用可穿戴设备和移动健康(mHealth)应用程序来监测和促进身体活动(PA)在患有各种慢性病的人群中越来越受欢迎。然而,在脊髓损伤(SCI)患者中,尤其是那些使用手动轮椅出行的患者中,此类工作仍然有限。
目的
本研究旨在描述用于监测和促进SCI手动轮椅使用者(MWU)身体活动的WheelFit mHealth应用程序的开发过程,并评估其在自由生活条件下的可行性和可用性。
方法
基于福格行为模型,并结合包括MWU、物理治疗师和私人教练在内的利益相关者的意见,开发了WheelFit应用程序,以促进MWU的身体活动。它与两款商业可穿戴设备配合使用,即安卓智能手表和车轮传感器,这些设备将用户的上肢和轮椅运动数据传输到应用程序中,使用自定义算法计算身体活动变量。用户可以设定个人目标,查看每日进展和身体活动历史记录,并访问应用程序内的自适应锻炼库。进行了一项为期4周的单组前后研究,包括1周的基线期和3周的干预期,以评估WheelFit的可行性和可用性。可行性通过课程出席率、设备和应用程序使用情况以及行动计划的实施情况进行评估。可用性使用系统可用性量表进行评估。通过比较干预前和干预后身体活动变量以及SCI运动自我效能量表的得分来评估初步效果。
结果
共有16名参与者完成了研究方案,课程出席率为100%,并且每天保持14.2小时的设备和应用程序连接。参与者对其行动计划的遵守程度各不相同。WheelFit的出色可用性通过系统可用性量表的平均得分为81.8(标准差19.2)分来表明。干预前后每日锻炼时间(干预前:平均26.4,标准差16.9分钟;干预后:平均33.3,标准差24.9分钟;P = 0.049)和运动自我效能量表得分(干预前:平均33.9,标准差4.5分;干预后:平均35.9,标准差3.2分;P = 0.043)在统计学上有显著增加。
结论
WheelFit应用程序在促进SCI的MWU身体活动方面显示出有前景的可行性、可用性和积极影响。未来有必要探索将WheelFit应用程序潜在整合到临床实践中的研究。
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