Bringing Single-Sessions Up to Speed: A Systematic Review of Methods in Youth Mental Health Interventions
Bibliographic record
Abstract
Objective: Single-session interventions (SSIs) offer a promising way to expand youth mental health care, particularly in underserved communities. However, methodological limitations have historically affected the quality and clarity of SSI research. Method: This systematic review examined peer-reviewed English-language studies on SSIs and mental health outcomes for youth (≤18 years) that included at least one control group with quantitative or mixed-methods designs. Grey literature, qualitative research, and case studies were excluded. Of 218 records screened, 22 met the inclusion criteria. Results: The reviewed studies reflect growing use of larger samples, more randomized controlled trials, standardized self-report measures, and immediate follow-ups. Ongoing challenges include limited sample diversity, geographic bias toward high-income countries, limited multimethod measures, inconsistent preregistration, low open science participation, and long-term assessment, with only half of studies following up beyond 2 months. Conclusions: While the field shows signs of methodological progress, continued improvements are needed for clinical reliability and broader applicability.
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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 | 0.025 | 0.076 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.009 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".