Understanding the mental health and recovery needs of Canadian youth with mental health disorders: a Strategy for Patient-Oriented Research (SPOR) collaboration protocol
Bibliographic record
Abstract
BACKGROUND: While considerable progress is being made to understand the health and self-management needs of youth with mental health disorders, little attention has focused on the mental health and recovery needs that the youth themselves identify-this despite a national priority to incorporate patient-oriented research into the development and assessment of mental health services. To address this gap, estimates of the extent to which existing patient-reported outcome measures (PROMs)-originally developed for use amongst adult populations-are clinically meaningful and psychometrically fit for use among youth are needed. In tandem, a recovery profile for youth can be constructed incorporating the youth perspective of the services provided within a community mental health setting. METHODS/DESIGN: This study will utilize a mixed methods design incorporating qualitative focus group interviews and cross-sectional survey. Our process will begin with the hiring of a youth peer research partner who will provide lived experience expertise through all phases of the study. We will advertise, recruit, and conduct four focus groups with youth who receive services from the Foundry Vancouver Granville located in British Columbia, Canada. In the first two focus groups, we will recruit youth aged 15-18 years (n = 10). In the second two focus groups, we will recruit young adults aged 19-24 years (n = 10). In parallel, we will conduct a cross-sectional survey of the recovery and mental health needs of youth, informed by ten widely used and validated PROM. Thematic analysis techniques will guide the identification of predominant thematic trends in the qualitative focus group data. We will use Classical and Rasch measurement methods to test and analyze the reliability and validity of selected PROM measures for youth populations. DISCUSSION: The proposed study has the potential to produce a preliminary conceptual and measurement model for understanding the mental health and recovery needs of youth with mental health disorders. This evidence will inform how youth mental health services can grow, support, and sustain the capacity for a collaborative, interdisciplinary and innovative patient-oriented research environment. Findings will also contribute much needed evidence to improve the standard of care for youth who experience mental health disorders in Canada and beyond.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".