ArticleHealth expectations : an international journal of public participation in health care and health policy2024
Recruitment and retention of adolescents for an ecological momentary assessment measurement burst mental health study: The MHIM engagement strategy.
Article in Health expectations : an international journal of public participation in health care and health policy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed.
- Real-Time Type 1 Diabetes Self-Management Decision-Making in Adolescents: Protocol for a Longitudinal Mixed Methods Study Using Text Messaging and Continuous Glucose Monitoring.JMIR research protocols · 2026Article
- Mental health in the moment: protocol for an accelerated cohort measurement burst study of adolescent mental health.BMJ open · 2025Article
- Recruitment and retention of adolescents for an ecological momentary assessment measurement burst mental health study: The MHIM engagement strategy.Health expectations : an international journal of public participation in health care and health policy · 2024Article
- Feasibility and Utility of Multimodal Micro Ecological Momentary Assessment on a Smartwatch.Proceedings of the SIGCHI conference on human factors in computing systems. CHI ConferenceArticle
- Development and validation of a multimodal data collection system for adolescent mental health management.Digital healthArticle
Corrections and comments
- Erratum issued
Authors and funding
4 authors.
Funding
Abstract
introductionRecruitment and long-term retention of adolescent participants in longitudinal research are challenging and may be especially so in studies involving remote measurement and biosampling components. The ability to effectively recruit and retain participants can be supported by the use of specific evidence-based engagement strategies that are built in from the earliest stages.
methodsInformed by a review of the evidence on effective engagement strategies and consultations with adolescents (via two Young Person Advisory Groups [YPAGs]; ages 11-13 and 14-17), the current protocol describes the planned participant engagement strategy for the Mental Health in the Moment Study: a multimodal measurement burst study of adolescent mental health across ages 11-19.
resultsThe protocol incorporates engagement strategies in four key domains: consultations/co-design with the target population, incentives, relationship-building and burden/barrier reduction. In addition to describing general engagement strategies in longitudinal studies, we also discuss specific concerns regarding engagement in data collection methods such as biosampling and ecological momentary assessment where a paucity of evidence exists.
conclusionEngagement strategies for adolescent mental health studies should be based on existing evidence and consultations with adolescents. We present our approach in developing the planned engagement strategies and also discuss limitations and future directions in engaging adolescents in longitudinal research. PATIENT OR PUBLIC CONTRIBUTION: The study design for this project places a strong emphasis on the active engagement of adolescents throughout its development. Specifically, the feedback and suggestions provided by the YPAGs have been instrumental in refining our strategies for maximising the recruitment and retention of participants.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.