Codesigning a user-centred digital psychoeducational tool for youth mental well-being with families in Canada: study protocol for a sequential exploratory mixed methods study
Bibliographic record
Abstract
INTRODUCTION: On 11 March 2020, WHO declared the novel coronavirus (COVID-19) disease a global pandemic. Governments globally implemented physical distancing measures and closure of public institutions that resulted in varying implications to youth mental well-being (eg, social isolation, reduced extracurricular activities). These impacts may have detrimental short-term and long-term effects on youth mental well-being; care for youth with mental health disorders was already overstretched, underfunded and fragmented before the pandemic and youth are not often considered in mental health initiatives. There is a pressing need to partner with youth and families to target and improve youth mental well-being prior to the onset of a mental health disorder, as well as to conduct research on youth mental well-being needs related to pandemic recovery. Here we present a protocol for partnering with youth and families to codesign a user-centred digital tool for youth mental well-being. METHODS AND ANALYSIS: We will conduct a national research study to develop a catalogue of recommendations specific to supporting youth mental well-being, and a digital tool to support youth mental well-being through three phases of work: (1) expert consultation on data related to supporting youth mental well-being existing within our Pandemic Preparedness Research Program; (2) codesign of an innovative digital tool for youth mental well-being; and (3) assessment of the tool's usability and acceptability. ETHICS AND DISSEMINATION: This study has been approved by the Dalhousie Research Ethics Board (2023-6538) and the Conjoint Health Research Ethics Board (23-0039). This study will complement ongoing foundational research in youth conducted by our team that involves partnering with youth and families to understand the unique implications of the pandemic on this population.
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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 | 0.051 | 0.048 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.013 | 0.005 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.045 | 0.006 |
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".