What makes mental health and substance use services youth friendly? A scoping review of literature
Bibliographic record
Abstract
BACKGROUND: There are increasing calls to make mental health and substance use services youth friendly, with hopes of improving service uptake, engagement and satisfaction. However, youth-friendliness in this area has not been clearly defined and there is a lack of information about the characteristics that make such services youth friendly. The purpose of this scoping review was to examine the literature available on youth-friendly mental health and substance use services in order to identify the characteristics, outline the expected impacts, and establish a definition. METHODS: A scoping review of seven databases and grey literature sources was conducted. Twenty-eight documents were retained as relevant to the research questions. Relevant data from these documents was extracted, analyzed and presented to stakeholders, including youth, caregivers and service providers to validate and refine the results. RESULTS: Youth-friendly mental health and substance use services include integrated, inclusive, confidential and safe organization and policy characteristics; bright, comfortable, environment with informational materials; welcoming and genuine service providers with appropriate communication and counselling skills; an accessible location; minimal wait times; and individualized and innovative approaches. All areas in which youth friendliness should be implemented in a mental health and substance use service organization had a core value of youth voice. CONCLUSION: Improving the youth friendliness of mental health and substance use services includes incorporating youth voice in organization, policy, environment, service providers, and treatment services, and has implications for treatment uptake, engagement and satisfaction. Further research is required to determine the impact of youth friendliness in such services.
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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 | 0.026 | 0.103 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.029 | 0.026 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".