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使用 Rasch 测量理论开发的用于评估用户对移动健康应用满意度的问卷

A Questionnaire for Assessing User Satisfaction With Mobile Health Apps: Development Using Rasch Measurement Theory.

机构信息

Research Institutes of Sweden AB, Göteborg, Sweden.

Clinical Epidemiology Division, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden.

出版信息

JMIR Mhealth Uhealth. 2020 May 26;8(5):e15909. doi: 10.2196/15909.


DOI:10.2196/15909
PMID:32452817
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7284402/
Abstract

BACKGROUND: Mobile health (mHealth) apps offer great opportunities to deliver large-scale, cost-efficient digital solutions for implementing lifestyle changes. Furthermore, many mHealth apps act as medical devices. Yet, there is little research on how to assess user satisfaction with an mHealth solution. OBJECTIVE: This study presents the development of the mHealth Satisfaction Questionnaire and evaluates its measurement properties. METHODS: Respondents who took part in the Health Integrator Study and were randomized to use the Health Integrator smartphone app for lifestyle changes (n=112), with and without additional telephone coaching, rated their satisfaction with the app using the new 14-item mHealth Satisfaction Questionnaire. The ratings were given on a 5-point Likert scale and measurement properties were evaluated using Rasch measurement theory (RMT). RESULTS: Optimal scoring was reached when response options 2, 3, and 4 were collapsed, giving three response categories. After omitting two items that did not fit into the scale, fit residuals were within, or close to, the recommended range of ±2.5. There was no differential item functioning between intervention group, age group, or sex. The Person Separation Index was 0.79, indicating that the scale's ability to discriminate correctly between person leniency was acceptable for group comparisons but not for individual evaluations. The scale did not meet the criterion of unidimensionality; 16.1% (18/112) of the respondents were outside the desired range of -1.96 to 1.96. In addition, several items showed local dependency and three underlying dimensions emerged: negative experiences, positive experiences, and lifestyle consequences of using the mHealth solution. CONCLUSIONS: In times where mHealth apps and digital solutions are given more attention, the mHealth Satisfaction Questionnaire provides a new possibility to measure user satisfaction to ensure usability and improve development of new apps. Our study is one of only a few cases where RMT has been used to evaluate the usability of such an instrument. There is, though, a need for further development of the mHealth Satisfaction Questionnaire, including the addition of more items and consideration of further response options. The mHealth Satisfaction Questionnaire should also be evaluated in a larger sample and with other mHealth apps and in other contexts. TRIAL REGISTRATION: ClinicalTrials.gov NCT03579342; http://clinicaltrials.gov/ct2/show/NCT03579342.

摘要

背景:移动医疗(mHealth)应用为提供大规模、具有成本效益的数字解决方案以实现生活方式的改变提供了绝佳机会。此外,许多 mHealth 应用可充当医疗器械。然而,对于如何评估用户对 mHealth 解决方案的满意度,相关研究甚少。

目的:本研究提出了 mHealth 满意度问卷的开发方法,并对其测量属性进行了评估。

方法:参加健康整合器研究(Health Integrator Study)并被随机分配使用健康整合器智能手机应用进行生活方式改变的参与者(n=112),无论是否接受额外的电话辅导,均使用新的 14 项 mHealth 满意度问卷对应用的满意度进行评分。评分采用 5 级 Likert 量表,采用 Rasch 测量理论(Rasch measurement theory,RMT)评估测量属性。

结果:当将响应选项 2、3 和 4 合并为 3 个响应类别时,达到了最佳评分。剔除 2 项不符合量表的项目后,拟合残差在推荐范围±2.5 内或接近该范围。干预组、年龄组和性别之间不存在差异项目功能。个体区分指数为 0.79,表明该量表在区分个体宽容度方面的能力可用于组间比较,但不能用于个体评估。该量表不符合单维性标准;16.1%(112 例中的 18 例)的受访者超出了期望范围(-1.96 到 1.96)。此外,有几个项目显示出局部依赖,出现了 3 个潜在维度:负面体验、正面体验以及使用 mHealth 解决方案对生活方式的影响。

结论:在 mHealth 应用和数字解决方案越来越受到关注的时代,mHealth 满意度问卷提供了一种新的测量用户满意度的方法,可确保可用性并改进新应用的开发。我们的研究是为数不多的使用 RMT 评估此类工具可用性的案例之一。然而,需要进一步开发 mHealth 满意度问卷,包括增加更多项目和考虑进一步的响应选项。mHealth 满意度问卷还应在更大的样本中,以及使用其他 mHealth 应用和在其他环境中进行评估。

试验注册:ClinicalTrials.gov NCT03579342;http://clinicaltrials.gov/ct2/show/NCT03579342。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e12/7284402/7acaa456bbc4/mhealth_v8i5e15909_fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e12/7284402/d0059a22feb1/mhealth_v8i5e15909_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e12/7284402/4331c1d0f451/mhealth_v8i5e15909_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e12/7284402/c7acacae4e7f/mhealth_v8i5e15909_fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e12/7284402/7acaa456bbc4/mhealth_v8i5e15909_fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e12/7284402/d0059a22feb1/mhealth_v8i5e15909_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e12/7284402/4331c1d0f451/mhealth_v8i5e15909_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e12/7284402/c7acacae4e7f/mhealth_v8i5e15909_fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e12/7284402/7acaa456bbc4/mhealth_v8i5e15909_fig4.jpg

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