Centre for Sports & Exercise Medicine, William Harvey Research Institute, Queen Mary University of London, London, United Kingdom.
Risk and Information Systems Research Group, School of Electronic Engineering and Computer Science, Queen Mary University of London, London, United Kingdom.
J Med Internet Res. 2022 Aug 30;24(8):e38352. doi: 10.2196/38352.
Musculoskeletal disorders negatively affect millions of patients worldwide, placing significant demand on health care systems. Digital technologies that improve clinical outcomes and efficiency across the care pathway are development priorities. We developed the musculoskeletal Digital Assessment Routing Tool (DART) to enable self-assessment and immediate direction to the right care.
We aimed to assess and resolve all serious DART usability issues to create a positive user experience and enhance system adoption before conducting randomized controlled trials for the integration of DART into musculoskeletal management pathways.
An iterative, convergent mixed methods design was used, with 22 adult participants assessing 50 different clinical presentations over 5 testing rounds across 4 DART iterations. Participants were recruited using purposive sampling, with quotas for age, habitual internet use, and English-language ability. Quantitative data collection was defined by the constructs within the International Organization for Standardization 9241-210-2019 standard, with user satisfaction measured by the System Usability Scale. Study end points were resolution of all grade 1 and 2 usability problems and a mean System Usability Scale score of ≥80 across a minimum of 3 user group sessions.
All participants (mean age 48.6, SD 15.2; range 20-77 years) completed the study. Every assessment resulted in a recommendation with no DART system errors and a mean completion time of 5.2 (SD 4.44, range 1-18) minutes. Usability problems were reduced from 12 to 0, with trust and intention to act improving during the study. The relationship between eHealth literacy and age, as explored with a scatter plot and calculation of the Pearson correlation coefficient, was performed for all participants (r=-0.2; 20/22, 91%) and repeated with a potential outlier removed (r=-0.23), with no meaningful relationships observed or found for either. The mean satisfaction for daily internet users was highest (19/22, 86%; mean 86.5, SD 4.48; 90% confidence level [CL] 1.78 or -1.78), with nonnative English speakers (6/22, 27%; mean 78.1, SD 4.60; 90% CL 3.79 or -3.79) and infrequent internet users scoring the lowest (3/22, 14%; mean 70.8, SD 5.44; 90% CL 9.17 or -9.17), although the CIs overlap. The mean score across all groups was 84.3 (SD 4.67), corresponding to an excellent system, with qualitative data from all participants confirming that DART was simple to use.
All serious DART usability issues were resolved, and a good level of satisfaction, trust, and willingness to act on the DART recommendation was demonstrated, thus allowing progression to randomized controlled trials that assess safety and effectiveness against usual care comparators. The iterative, convergent mixed methods design proved highly effective in fully evaluating DART from a user perspective and could provide a blueprint for other researchers of mobile health systems.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/27205.
肌肉骨骼疾病对全球数以百万计的患者产生负面影响,给医疗保健系统带来了巨大的压力。开发能够改善整个护理路径临床效果和效率的数字技术是优先发展事项。我们开发了肌肉骨骼数字评估路由工具(DART),以实现自我评估,并立即将患者引导至合适的护理。
在将 DART 整合到肌肉骨骼管理路径中进行随机对照试验之前,我们旨在解决所有严重的 DART 可用性问题,以创造积极的用户体验并提高系统的采用率。
我们使用迭代、收敛的混合方法设计,在 4 个 DART 迭代中,22 名成年参与者在 5 个测试轮次中评估了 50 种不同的临床表现。参与者通过目的性抽样招募,年龄、习惯性互联网使用和英语能力有配额限制。定量数据收集由国际标准化组织 9241-210-2019 标准中的结构定义,使用系统可用性量表衡量用户满意度。研究终点是解决所有 1 级和 2 级可用性问题,以及至少 3 个用户组会话的系统可用性量表平均得分为≥80。
所有参与者(平均年龄 48.6,标准差 15.2;范围 20-77 岁)均完成了研究。每次评估都得出了建议,没有 DART 系统错误,平均完成时间为 5.2(标准差 4.44,范围 1-18)分钟。可用性问题从 12 个减少到 0 个,信任度和实施意愿在研究过程中有所提高。电子健康素养与年龄之间的关系,通过散点图和皮尔逊相关系数的计算进行了探索,对所有参与者(r=-0.2;20/22,91%)进行了探索,并在剔除一个潜在异常值后(r=-0.23)进行了重复,未观察到或发现有任何有意义的关系。日常互联网用户的满意度最高(22 人中有 19 人,86%;平均 86.5,标准差 4.48;90%置信区间[CL]为 1.78 或-1.78),非母语英语使用者(22 人中有 6 人,27%;平均 78.1,标准差 4.60;90%CL 为 3.79 或-3.79)和不常使用互联网的用户得分最低(22 人中有 3 人,14%;平均 70.8,标准差 5.44;90%CL 为 9.17 或-9.17),尽管置信区间重叠。所有组别的平均得分为 84.3(标准差 4.67),对应于一个极好的系统,所有参与者的定性数据都证实 DART 易于使用。
所有严重的 DART 可用性问题都已解决,对 DART 建议的满意度、信任度和实施意愿均表现良好,从而允许进行安全性和有效性评估的随机对照试验,与常规护理比较。迭代、收敛的混合方法设计从用户角度对 DART 进行了全面评估,可为其他移动健康系统研究人员提供蓝图。
国际注册报告标识符(IRRID):RR2-10.2196/27205。