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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".