Beyond silence: protocol for a randomized parallel-group trial comparing two approaches to workplace mental health education for healthcare employees
Bibliographic record
Abstract
BACKGROUND: Mental illness is a significant and growing problem in Canadian healthcare organizations, leading to tremendous personal, social and financial costs for individuals, their colleagues, their employers and their patients. Early and appropriate intervention is needed, but unfortunately, few workers get the help that they need in a timely way due to barriers related to poor mental health literacy, stigma, and inadequate access to mental health services. Workplace education and training is one promising approach to early identification and support for workers who are struggling. Little is known, however, about what approach is most effective, particularly in the context of healthcare work. The purpose of this study is to compare the impact of a customized, contact-based education approach with standard mental health literacy training on the mental health knowledge, stigmatized beliefs and help-seeking/help-outreach behaviors of healthcare employees. METHODS/DESIGN: A multi-centre, randomized, two-group parallel group trial design will be adopted. Two hundred healthcare employees will be randomly assigned to one of two educational interventions: Beyond Silence, a peer-led program customized to the healthcare workplace, and Mental Health First Aid, a standardized literacy based training program. Pre, post and 3-month follow-up surveys will track changes in knowledge (mental health literacy), attitudes towards mental illness, and help-seeking/help-outreach behavior. An intent-to-treat, repeated measures analysis will be conducted to compare changes in the two groups over time in terms of the primary outcome of behavior change. Linear regression modeling will be used to explore the extent to which knowledge, and attitudes predict behavior change. Qualitative interviews with participants and leaders will also be conducted to examine process and implementation of the programs. DISCUSSION: This is one of the first experimental studies to compare outcomes of standard mental health literacy training to an intervention with an added anti-stigma component (using best-practices of contact-based education). Study findings will inform recommendations for designing workplace mental health education to promote early intervention for employees with mental health issues in the context of healthcare work. TRIAL REGISTRATION: May 2014 - ClinicalTrials.gov: NCT02158871.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".