ArticleJMIR mHealth and uHealth2023
Understanding Mobile Health and Youth Mental Health: Scoping Review.
Article in JMIR mHealth and uHealth, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 31 citations in OpenAlex.
- The Preliminary Efficacy and Feasibility of SMILE Serious Game for Adolescents and Young Adults: Protocol for Cluster Randomized Multisite Adaptive Trial Design.JMIR research protocols · 2026Article
- Characteristics of Mobile Health Interventions for Repetitive Negative Thinking: Protocol for a Scoping Review.JMIR research protocols · 2026Article
- "My Day is Already Planned Out Before I Even Get to Choose it": Using Youth-Oriented Research to Understand and Measure What Matters to Youth Aged 12-15 Years and the Implications for Mental Health Services.Child psychiatry and human development · 2025Article
- Perception of AI Use in Youth Mental Health Services: Qualitative Study.Journal of participatory medicine · 2025Article
- mHealth Applications for Childhood Anxiety Disorders: Current Landscape, Challenges, and Future Directions.Current psychiatry reports · 2025Review
- Health-Promoting Effects and Everyday Experiences With a Mental Health App Using Ecological Momentary Assessments and AI-Based Ecological Momentary Interventions Among Young People: Qualitative Interview and Focus Group Study.JMIR mHealth and uHealth · 2025Article
- Reflections of Foster Youth Engaging in the Co-Design of Digital Mental Health Technology: Duoethnography Study.JMIR formative research · 2025Article
- Consensus derived client outcomes and clinician actions for youth online chat mental health services: a Delphi study.Frontiers in digital health · 2025Article
- Young people's participation in their own mental health care: Session-by-session feedback in youth mental health services (headspace).Early intervention in psychiatry · 2025Article
- Mobile Apps for the Personal Safety of At-Risk Children and Youth: Scoping Review.JMIR mHealth and uHealth · 2024Article
- Assessing the Usage and Usability of a Mental Health Advice Telephone Service in Uganda: Mixed Methods Study.Journal of medical Internet research · 2024Article
- Feasibility and utility of mobile health interventions for depression and anxiety in rural populations: A scoping review.Internet interventions · 2024Article
- Development and Validation of a Routine Session-by-Session Experience Measure for Youth Mental Health Services: My Youth Mental Health Session Experience (MySE).Psychology research and behavior management · 2023Article
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Corrections and comments
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Authors and funding
7 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundA total of 75% of people with mental health disorders have an onset of illness between the ages of 12 and 24 years. Many in this age group report substantial obstacles to receiving quality youth-centered mental health care services. With the rapid development of technology and the recent COVID-19 pandemic, mobile health (mHealth) has presented new opportunities for youth mental health research, practice, and policy.
objectiveThe research objectives were to (1) synthesize the current evidence supporting mHealth interventions for youths who experience mental health challenges and (2) identify current gaps in the mHealth field related to youth's access to mental health services and health outcomes.
methodsGuided by the methods of Arksey and O'Malley, we conducted a scoping review of peer-reviewed studies that used mHealth tools to improve youth mental health (January 2016-February 2022). We searched MEDLINE, PubMed, PsycINFO, and Embase databases using the following key terms: (1) mHealth; (2) youth and young adults; and (3) mental health. The current gaps were analyzed using content analysis.
resultsThe search produced 4270 records, of which 151 met inclusion criteria. Included articles highlight the comprehensive aspects of youth mHealth intervention resource allocation for targeted conditions, mHealth delivery methods, measurement tools, evaluation of mHealth intervention, and youth engagement. The median age for participants in all studies is 17 (IQR 14-21) years. Only 3 (2%) studies involved participants who reported their sex or gender outside of the binary option. Many studies (68/151, 45%) were published after the onset of the COVID-19 outbreak. Study types and designs varied, with 60 (40%) identified as randomized controlled trials. Notably, 143 out of 151 (95%) studies came from developed countries, suggesting an evidence shortfall on the feasibility of implementing mHealth services in lower-resourced settings. Additionally, the results highlight concerns related to inadequate resources devoted to self-harm and substance uses, weak study design, expert engagement, and the variety of outcome measures selected to capture impact or changes over time. There is also a lack of standardized regulations and guidelines for researching mHealth technologies for youths and the use of non-youth-centered approaches to implementing results.
conclusionsThis study may be used to inform future work as well as the development of youth-centered mHealth tools that can be implemented and sustained over time for diverse types of youths. Implementation science research that prioritizes youths' engagement is needed to advance the current understanding of mHealth implementation. Moreover, core outcome sets may support a youth-centered measurement strategy to capture outcomes in a systematic way that prioritizes equity, diversity, inclusion, and robust measurement science. Finally, this study suggests that future practice and policy research are needed to ensure the risk of mHealth is minimized and that this innovative health care service is meeting the emerging needs of youths over time.
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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.