The Effects of an E-Mental Health Program and Job Coaching on the Risk of Major Depression and Productivity in Canadian Male Workers: Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Major depression (MDE) is prevalent in men and affects men's health and productivity. Because of the stigma against depression and social/gender norms, men are less likely to seek help for emotion and stress-related issues. Therefore, innovative solutions tailored for men are needed. With rapid development of the Internet and information technologies, one promising solution that has drawn considerable attentions is electronic mental (e-mental) health programs and services. OBJECTIVE: The objective of our study is to evaluate the effectiveness of the e-mental health program BroHealth on reducing the risk of having MDE and improving productivity and return to investment. METHODS: The target population is Canadian working men who are at high risk of having MDE (N=1200). Participants will be recruited using the method of random digit dialing across the country and workplace advertisement. Eligible participants will be randomly allocated into the following groups: (1) a control group, (2) a group receiving BroHealth only, and (3) a group receiving BroHealth and telephone-based job coaching service. The groups will be assessed at 6 and 12 months after randomization. The primary outcome is the risk proportion of MDE over 12 months, which will be assessed by the World Health Organization's (WHO's) Composite International Diagnostic Interview-Short Form for Major Depression. Intention-to-treat principle will be used in the analysis. The 12-month proportions of MDE in the groups will be estimated and compared. Logistic regression modeling will be used to examine the effect of the intervention on the outcome, controlling for the effects of baseline confounders. RESULTS: It is anticipated that the randomized controlled trial (RCT) will be completed by 2018. This study has been approved by the Conjoint Health Research Ethics Review Board of the University of Calgary. The trial is funded by a team grant from the Movember Foundation, a global charity for men's health. BroHealth was developed at the Digital Emergency Medicine, University of British Columbia, and the usability testing has been completed. CONCLUSIONS: BroHealth was developed based on men's needs. We hypothesized that BroHealth will be an effective, acceptable, and sustainable product for early prevention of MDE in workplaces. CLINICALTRIAL: Clinicaltrials.gov NCT02777112; https://clinicaltrials.gov/ct2/show/NCT02777112 (Archived by WebCite at http://www.webcitation.org/6lbOQpiCG).
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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 | 0.027 | 0.021 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.014 | 0.007 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.062 | 0.007 |
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".