Italian Version of the mHealth App Usability Questionnaire (Ita-MAUQ): Translation and Validation Study in People With Multiple Sclerosis.

IF 2.6 Q2 HEALTH CARE SCIENCES & SERVICES JMIR Human Factors Pub Date : 2024-09-30 DOI:10.2196/58079
Jessica Podda, Erica Grange, Alessia Susini, Andrea Tacchino, Federica Di Antonio, Ludovico Pedullà, Giampaolo Brichetto, Michela Ponzio
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Abstract

Background: Telemedicine and mobile health (mHealth) apps have emerged as powerful tools in health care, offering convenient access to services and empowering participants in managing their health. Among populations with chronic and progressive disease such as multiple sclerosis (MS), mHealth apps hold promise for enhancing self-management and care. To be used in clinical practice, the validity and usability of mHealth tools should be tested. The most commonly used method for assessing the usability of electronic technologies are questionnaires.

Objective: This study aimed to translate and validate the English version of the mHealth App Usability Questionnaire into Italian (ita-MAUQ) in a sample of people with MS.

Methods: The 18-item mHealth App Usability Questionnaire was forward- and back-translated from English into Italian by an expert panel, following scientific guidelines for translation and cross-cultural adaptation. The ita-MAUQ (patient version for stand-alone apps) comprises 3 subscales, which are ease of use, interface and satisfaction, and usefulness. After interacting with DIGICOG-MS (Digital Assessment of Cognitive Impairment in Multiple Sclerosis), a novel mHealth app for cognitive self-assessment in MS, people completed the ita-MAUQ and the System Usability Scale, included to test construct validity of the translated questionnaire. Confirmatory factor analysis, internal consistency, test-retest reliability, and construct validity were assessed. Known-groups validity was examined based on disability levels as indicated by the Expanded Disability Status Scale (EDSS) score and gender.

Results: In total, 116 people with MS (female n=74; mean age 47.2, SD 14 years; mean EDSS 3.32, SD 1.72) were enrolled. The ita-MAUQ demonstrated acceptable model fit, good internal consistency (Cronbach α=0.92), and moderate test-retest reliability (intraclass coefficient correlation 0.84). Spearman coefficients revealed significant correlations between the ita-MAUQ total score; the ease of use (5 items), interface and satisfaction (7 items), and usefulness subscales; and the System Usability Scale (all P values <.05). Known-group analysis found no difference between people with MS with mild and moderate EDSS (all P values >.05), suggesting that ambulation ability, mainly detected by the EDSS, did not affect the ita-MAUQ scores. Interestingly, a statistical difference between female and male participants concerning the ease of use ita-MAUQ subscale was found (P=.02).

Conclusions: The ita-MAUQ demonstrated high reliability and validity and it might be used to evaluate the usability, utility, and acceptability of mHealth apps in people with MS.

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意大利语版移动医疗应用程序可用性问卷(Ita-MAUQ):多发性硬化症患者的翻译和验证研究。
背景:远程医疗和移动医疗(mHealth)应用程序已成为医疗保健领域的有力工具,为人们提供了便捷的服务,并增强了参与者管理自身健康的能力。在患有多发性硬化症(MS)等慢性进展性疾病的人群中,移动医疗应用程序有望加强自我管理和护理。要在临床实践中使用移动医疗工具,必须对其有效性和可用性进行测试。评估电子技术可用性最常用的方法是问卷调查:本研究旨在将英语版的移动医疗应用程序可用性问卷(ita-MAUQ)翻译成意大利语,并在多发性硬化症患者样本中进行验证:由一个专家小组按照翻译和跨文化适应的科学指南,将 18 个项目的移动医疗应用程序可用性问卷从英语正向和反向翻译成意大利语。ita-MAUQ(独立应用程序的患者版本)包括 3 个分量表,分别是易用性、界面和满意度以及实用性。在与用于多发性硬化症认知自我评估的新型移动医疗应用程序 DIGICOG-MS(多发性硬化症认知障碍数字评估)进行互动后,人们填写了 ita-MAUQ 和系统可用性量表,以检验翻译问卷的结构效度。对确认性因子分析、内部一致性、测试-再测可靠性和建构效度进行了评估。根据扩展残疾状况量表(EDSS)的评分和性别对已知群体的有效性进行了检验:共有 116 名多发性硬化症患者(女性 74 人;平均年龄 47.2 岁,标准差 14 岁;平均 EDSS 3.32 分,标准差 1.72 分)参加了研究。ita-MAUQ显示了可接受的模型拟合度、良好的内部一致性(Cronbach α=0.92)和适度的测试-再测可靠性(类内系数相关性0.84)。斯皮尔曼系数显示,ita-MAUQ 总分、易用性分量表(5 个项目)、界面和满意度分量表(7 个项目)、有用性分量表以及系统可用性量表之间存在显著相关性(所有 P 值均为 0.05),这表明主要通过 EDSS 检测的行走能力并不影响 ita-MAUQ 的得分。有趣的是,在ita-MAUQ的易用性分量表中,女性和男性参与者之间存在统计学差异(P=.02):ita-MAUQ具有很高的信度和效度,可用于评估移动医疗应用程序在多发性硬化症患者中的可用性、实用性和可接受性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
JMIR Human Factors
JMIR Human Factors Medicine-Health Informatics
CiteScore
3.40
自引率
3.70%
发文量
123
审稿时长
12 weeks
期刊最新文献
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