Methodological Challenges in Randomized Controlled Trials of mHealth Interventions: Cross-Sectional Survey Study and Consensus-Based Recommendations.

IF 6 2区 医学 Q1 HEALTH CARE SCIENCES & SERVICES Journal of Medical Internet Research Pub Date : 2024-12-19 DOI:10.2196/53187
Jesus Lopez-Alcalde, L Susan Wieland, Yuqian Yan, Jürgen Barth, Mohammad Reza Khami, Siddharudha Shivalli, Cynthia Lokker, Harleen Kaur Rai, Paul Macharia, Sergi Yun, Elvira Lang, Agnes Bwanika Naggirinya, Concepción Campos-Asensio, Leila Ahmadian, Claudia M Witt
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Abstract

Background: Mobile health (mHealth) refers to using mobile communication devices such as smartphones to support health, health care, and public health. mHealth interventions have their own nature and characteristics that distinguish them from traditional health care interventions, including drug interventions. Thus, randomized controlled trials (RCTs) of mHealth interventions present specific methodological challenges. Identifying and overcoming those challenges is essential to determine whether mHealth interventions improve health outcomes.

Objective: We aimed to identify specific methodological challenges in RCTs testing mHealth interventions' effects and develop consensus-based recommendations to address selected challenges.

Methods: A 2-phase participatory research project was conducted. First, we sent a web-based survey to authors of mHealth RCTs. Survey respondents rated on a 5-point scale how challenging they found 21 methodological aspects in mHealth RCTs compared to non-mHealth RCTs. Nonsystematic searches until June 2022 informed the selection of the methodological challenges listed in the survey. Second, a subset of survey respondents participated in an online workshop to discuss recommendations to address selected methodological aspects identified in the survey. Finally, consensus-based recommendations were developed based on the workshop discussion and email interaction.

Results: We contacted 1535 authors of mHealth intervention RCTs, of whom 80 (5.21%) completed the survey. Most respondents (74/80, 92%) identified at least one methodological aspect as more or much more challenging in mHealth RCTs. The aspects most frequently reported as more or much more challenging were those related to mHealth intervention integrity, that is, the degree to which the study intervention was implemented as intended, in particular managing low adherence to the mHealth intervention (43/77, 56%), defining adherence (39/79, 49%), measuring adherence (33/78, 42%), and determining which mHealth intervention components are used or received by the participant (31/75, 41%). Other challenges were also frequent, such as analyzing passive data (eg, data collected from smartphone sensors; 24/58, 41%) and verifying the participants' identity during recruitment (28/68, 41%). In total, 11 survey respondents participated in the subsequent workshop (n=8, 73% had been involved in at least 2 mHealth RCTs). We developed 17 consensus-based recommendations related to the following four categories: (1) how to measure adherence to the mHealth intervention (7 recommendations), (2) defining adequate adherence (2 recommendations), (3) dealing with low adherence rates (3 recommendations), and (4) addressing mHealth intervention components (5 recommendations).

Conclusions: RCTs of mHealth interventions have specific methodological challenges compared to those of non-mHealth interventions, particularly those related to intervention integrity. Following our recommendations for addressing these challenges can lead to more reliable assessments of the effects of mHealth interventions on health outcomes.

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移动医疗干预随机对照试验的方法学挑战:横断面调查研究和基于共识的建议。
背景:移动医疗(mHealth)是指使用智能手机等移动通信设备来支持健康、医疗保健和公共卫生。移动医疗干预措施有其自身的性质和特点,有别于传统的医疗保健干预措施,包括药物干预措施。因此,移动医疗干预的随机对照试验(RCT)在方法论上面临特殊的挑战。确定并克服这些挑战对于确定移动医疗干预是否能改善健康结果至关重要:我们旨在确定测试移动医疗干预效果的 RCT 在方法学方面的具体挑战,并制定基于共识的建议来应对选定的挑战:我们分两个阶段开展了参与式研究项目。首先,我们向移动医疗 RCT 的作者发送了一份网络调查。调查对象对移动医疗 RCT 与非移动医疗 RCT 相比在 21 个方法学方面的挑战性进行了 5 级评分。截至 2022 年 6 月的非系统性搜索为调查中列出的方法学挑战的选择提供了依据。其次,一部分调查对象参加了在线研讨会,讨论针对调查中发现的某些方法学问题提出的建议。最后,在研讨会讨论和电子邮件互动的基础上提出了基于共识的建议:我们联系了 1535 位移动医疗干预 RCT 的作者,其中 80 位(5.21%)完成了调查。大多数受访者(74/80,92%)认为至少有一个方法论方面在移动医疗干预研究中更具挑战性或更具挑战性。最常被报告为更具挑战性或更具挑战性的方面是与移动医疗干预完整性相关的方面,即研究干预按预期实施的程度,特别是管理移动医疗干预的低依从性(43/77,56%)、定义依从性(39/79,49%)、测量依从性(33/78,42%)以及确定参与者使用或接受了哪些移动医疗干预成分(31/75,41%)。其他挑战也屡见不鲜,如分析被动数据(如从智能手机传感器收集的数据;24/58,41%)和在招募过程中验证参与者身份(28/68,41%)。共有 11 名调查对象参加了随后的研讨会(8 人,73% 参与过至少 2 项移动医疗 RCT)。我们制定了 17 项基于共识的建议,涉及以下四类:(1)如何衡量移动医疗干预的依从性(7 项建议);(2)定义适当的依从性(2 项建议);(3)处理依从率低的问题(3 项建议);(4)处理移动医疗干预的组成部分(5 项建议):与非移动医疗干预相比,移动医疗干预的 RCT 在方法学方面存在特殊挑战,尤其是与干预完整性相关的挑战。按照我们的建议应对这些挑战,可以更可靠地评估移动医疗干预对健康结果的影响。
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来源期刊
CiteScore
14.40
自引率
5.40%
发文量
654
审稿时长
1 months
期刊介绍: The Journal of Medical Internet Research (JMIR) is a highly respected publication in the field of health informatics and health services. With a founding date in 1999, JMIR has been a pioneer in the field for over two decades. As a leader in the industry, the journal focuses on digital health, data science, health informatics, and emerging technologies for health, medicine, and biomedical research. It is recognized as a top publication in these disciplines, ranking in the first quartile (Q1) by Impact Factor. Notably, JMIR holds the prestigious position of being ranked #1 on Google Scholar within the "Medical Informatics" discipline.
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