The Use of Technology to Provide Mental Health Services to Youth Experiencing Homelessness: Scoping Review
Bibliographic record
Abstract
BACKGROUND: There is growing interest in using information and communication technologies (ICTs) to improve access to mental health services for youth experiencing homelessness (YEH); however, limited efforts have been made to synthesize this literature. OBJECTIVE: This study aimed to review the research on the use of ICTs to provide mental health services and interventions for YEH. METHODS: We used a scoping review methodology following the Arksey and O'Malley framework and guidelines from the Joanna Briggs Institute Manual for Evidence Synthesis. The results are reported according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews). A systematic search was conducted from 2005 to 2021 in MEDLINE, Embase, CINAHL, PsycInfo, Cochrane, Web of Science, and Maestro and in ProQuest Thesis and Dissertations, Papyrus, Homeless Hub, and Google Scholar for gray literature. Studies were included if participants' mean age was between 13 and 29 years, youth with mental health issues were experiencing homelessness or living in a shelter, ICTs were used as a means of intervention, and the study provided a description of the technology. The exclusion criteria were technology that did not allow for interaction (eg, television) and languages other than French or English. The data were analyzed using descriptive statistics and qualitative approaches. Two reviewers were involved in the screening and data extraction process in consultation with a third reviewer. The data were summarized in tables and by narrative synthesis. RESULTS: From the 2153 abstracts and titles screened, 12 were included in the analysis. The most common types of ICTs used were communication technologies (eg, phone, video, and SMS text messages) and mobile apps. The intervention goals varied widely across studies; the most common goal was reducing risky behaviors, followed by addressing cognitive functioning, providing emotional support, providing vital resources, and reducing anxiety. Most studies (9/11, 82%) focused on the feasibility of interventions. Almost all studies reported high levels of acceptability (8/9, 89%) and moderate to high frequency of use (5/6, 83%). The principal challenges were related to technical problems such as the need to replace phones, issues with data services, and phone charging. CONCLUSIONS: Our results indicate the emerging role of ICTs in the delivery of mental health services to YEH and that there is a high level of acceptability based on early feasibility studies. However, our results should be interpreted cautiously, considering the limited number of studies included in the analysis and the elevated levels of dropout. There is a need to advance efficacy and effectiveness research in this area with larger and longer studies. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2022-061313.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.083 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.024 | 0.020 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".