Preferred Features of E-Mental Health Programs for Prevention of Major Depression in Male Workers: Results from a Canadian National Survey
Bibliographic record
Abstract
The purpose of this study was to estimate and compare the proportions of preferred design features and likely use of e-mental health programs and understand potential barriers to the use of e-mental health programs in working men who were at high risk of a major depressive episode. A cross-sectional survey in 10 provinces in Canada was conducted between March and December 2015 (n = 511). Of the 17 different features assessed, the top three features that were most likely to be used by high-risk men were: "information about improving sleep hygiene" (61.3%), "practice and exercise to help reduce symptoms of stress and depression" (59.5%) and "having access to quality information and resources about work stress issues" (57.8%). E-mental health programs may be a promising strategy for prevention of depression in working men. Development of e-mental health programs should consider men's preferences and perceived barriers to enhance the acceptability of this approach.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".