Canada’s Student Mental Health Network: Protocol for a Comprehensive Program Evaluation (Preprint)
Bibliographic record
Abstract
BACKGROUND Prevalence estimates for mental health–related problems, including above-average stress, psychological distress, and symptoms of mental illnesses have increased significantly among Canadian postsecondary students. As demand for downstream mental treatment has surpassed many institutions’ abilities to deliver timely care, there is a need for innovative upstream supports that foster mental health promotion and mental illness prevention among this population. OBJECTIVE Supported by an extensive network of student volunteers, Canada's Student Mental Health Network is a virtual, one-stop shop for centralized mental health education and evidence-based resources tailored to postsecondary students. This article describes a protocol for the comprehensive evaluation of the Network. METHODS Development of the Network was developed using a participatory action research framework. Network content is created and curated by students and reviewed by subject matter experts. The proposed program evaluation will include both a formative process evaluation and a summative impact assessment to determine the feasibility, acceptability, and utility of the Network in addition to assessing change in the 3 primary outcomes of interest: mental health literacy, perceived social support, and help-seeking behavior. Participants will be recruited directly from the Network website using a “rolling” recruitment approach to allow for continuous data collection and evaluation. A combination of qualitative (ie, interviews) and quantitative (ie, surveys) methods of data collection will be used. RESULTS The process of evaluation of the Network will begin in September 2022, collecting data for 1 year. In September 2023, the impact evaluation will begin using the same follow-up schedule. Data collection will then remain ongoing to facilitate the continued evaluation of the Network. Reports detailing evaluation data will be released annually. CONCLUSIONS The Network is a novel and innovative method of delivering universal mental health promotion to Canadian postsecondary students by providing centralized and freely accessible mental health education and resources, created by students and validated by subject matter experts. The continued creation and curation of resources for the Network will be ongoing to meet the evolving needs of the target population. INTERNATIONAL REGISTERED REPORT PRR1-10.2196/41521
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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 | 0.101 | 0.112 |
| Meta-epidemiology (narrow) | 0.005 | 0.006 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.248 | 0.040 |
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".