Participant Engagement in Microrandomized Trials of mHealth Interventions: Scoping Review

被引:3
|
作者
Leong, Utek [1 ]
Chakraborty, Bibhas [2 ,3 ,4 ,5 ,6 ,7 ]
机构
[1] Natl Univ Singapore, Dept Psychol, Singapore, Singapore
[2] Natl Univ Singapore, Ctr Quantitat Med, Duke NUS Med Sch, Singapore, Singapore
[3] Natl Univ Singapore, Duke NUS Med Sch, Program Hlth Serv & Syst Res, Singapore, Singapore
[4] Natl Univ Singapore, Dept Stat & Data Sci, Singapore, Singapore
[5] Duke Univ, Dept Biostat & Bioinformat, Durham, NC USA
[6] Natl Univ Singapore, Ctr Quantitat Med, Duke NUS Med Sch, 8 Coll Rd, 06-31, Singapore 169857, Singapore
[7] Natl Univ Singapore, Duke NUS Med Sch, Program Hlth Serv & Syst Res, 8 Coll Rd, 06-31, Singapore 169857, Singapore
来源
JMIR MHEALTH AND UHEALTH | 2023年 / 11卷
关键词
microrandomized trials; engagement; adherence; mobile health; mHealth interventions; mobile phone; CONSCIENTIOUSNESS; APP;
D O I
10.2196/44685
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Background: Microrandomized trials (MRTs) have emerged as the gold standard for the development and evaluation of multicomponent, adaptive mobile health (mHealth) interventions. However, not much is known about the state of participant engagement measurement in MRTs of mHealth interventions. Objective: In this scoping review, we aimed to quantify the proportion of existing or planned MRTs of mHealth interventions to date that have assessed (or have planned to assess) engagement. In addition, for the trials that have explicitly assessed (or have planned to assess) engagement, we aimed to investigate how engagement has been operationalized and to identify the factors that have been studied as determinants of engagement in MRTs of mHealth interventions.Methods: We conducted a broad search for MRTs of mHealth interventions in 5 databases and manually searched preprint servers and trial registries. Study characteristics of each included evidence source were extracted. We coded and categorized these data to identify how engagement has been operationalized and which determinants, moderators, and covariates have been assessed in existing MRTs.Results: Our database and manual search yielded 22 eligible evidence sources. Most of these studies (14/22, 64%) were designed to evaluate the effects of intervention components. The median sample size of the included MRTs was 110.5. At least 1 explicit measure of engagement was included in 91% (20/22) of the included MRTs. We found that objective measures such as system usage data (16/20, 80%) and sensor data (7/20, 35%) are the most common methods of measuring engagement. All studies included at least 1 measure of the physical facet of engagement, but the affective and cognitive facets of engagement have largely been neglected (only measured by 1 study each). Most studies measured engagement with the mHealth intervention (Little e) and not with the health behavior of interest (Big E). Only 6 (30%) of the 20 studies that measured engagement assessed the determinants of engagement in MRTs of mHealth interventions; notification-related variables were the most common determinants of engagement assessed (4/6, 67% studies). Of the 6 studies, 3 (50%) examined the moderators of participant engagement-2 studies investigated time-related moderators exclusively, and 1 study planned to investigate a comprehensive set of physiological and psychosocial moderators in addition to time-related moderators.Conclusions: Although the measurement of participant engagement in MRTs of mHealth interventions is prevalent, there is a need for future trials to diversify the measurement of engagement. There is also a need for researchers to address the lack of attention to how engagement is determined and moderated. We hope that by mapping the state of engagement measurement in existing MRTs of mHealth interventions, this review will encourage researchers to pay more attention to these issues when planning for engagement measurement in future trials.
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页数:17
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