Preferred Features of E-Mental Health Programs for Prevention of Major Depression in Male Workers: Results From a Canadian National Survey
Bibliographic record
Abstract
BACKGROUND: Major depression is a prevalent mental disorder and imposes considerable burden on health and productivity. Men are not immune to major depression, yet they often delay seeking help because of perceived stigma and gender norms. E-mental health programs hold potential for early prevention of major depression. However, we have little knowledge about men's preferences for design features of e-mental health programs. OBJECTIVES: The objective of this study was to (1) estimate and compare the proportions of Internet use for medical information, preferred design features, and likely use of e-mental health programs; (2) examine factors associated with the likely use of e-mental health programs; and (3) understand potential barriers to the use of e-mental health programs among Canadian working men, who were at high risk of a major depressive episode (MDE). METHODS: A cross-sectional survey in 10 Canadian provinces was conducted between March and December 2015. Random digit dialing method was used through household landlines and cell phones to collect data from 511 working men who were at high risk of having an MDE and 330 working men who were at low risk of having an MDE. RESULTS: High-risk men were more likely to endorse the importance of accessing health resources on the Internet than low-risk men (83.4% vs 75.0%, respectively; P=.01). Of the 17 different features assessed, the top three features 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%). Compared with men at low risk for MDE, men at high risk for MDE were much more likely to consider using almost every one of the different design features. Differences in preferences for the design features by age among men at high risk of MDE were found only for 3 of 17 features. Differences in preferences for design features between English- and French-speaking participants were found only for 4 out of the 17 features. Analysis of qualitative data revealed that privacy issues, perceived stigma, ease of navigation, personal relevance, and lack of personal interaction, time, and knowledge were identified as barriers to the use of e-mental health programs in working men who were at high risk of MDE. CONCLUSION: 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 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 | 0.010 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".