The Wellness Quest: A health literacy and self‐advocacy tool developed by youth for youth mental health
Bibliographic record
Abstract
BACKGROUND: Less than 20% of youth who experience mental health difficulties access and receive appropriate treatment. This is exacerbated by barriers such as stigma, confidentiality concerns and lack of mental health literacy. A youth team developed the Wellness Quest: a health literacy tool to enable help-seeking youth to advocate for themselves. OBJECTIVE: To evaluate the content, presentation and utility of the Wellness Quest tool among youth. PARTICIPANTS: Participants aged 14 to 26. METHODS: A youth research team conducted five focus groups and one online survey to evaluate the Wellness Quest tool. Thematic analysis was used to analyse the qualitative data, and descriptive statistics were used to explore the survey results. MAIN RESULTS: Overall evaluations of the Wellness Quest were positive: participants felt it would be useful during their mental health help-seeking journey. Participants expressed the need for information about services for specific populations, such as Indigenous, immigrants, refugees and 2SLGBTQ + youth. They expressed that the tool should be available in complementary online and print versions. DISCUSSION: Improving mental health literacy may improve mental health by enabling youth and those who support them to recognize and respond to signs of distress and understanding where and how to get help. The Wellness Quest tool may equip youth with the knowledge to make informed decisions and advocate for their own mental health, thereby facilitating help-seeking among youth. PATIENT OR PUBLIC CONTRIBUTION: Youth as service users led all stages of the project, from designing and conducting the study and analysing the data to writing the manuscript.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".