Web-Based Interactive Training for Managers (Managing Minds at Work) to Promote Mental Health at Work: Pilot Feasibility Cluster Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Line managers play a key role in preventing poor mental health but often lack necessary skills and knowledge. Existing interventions typically focus on mental health awareness rather than practical skills. The evidence-based Managing Minds at Work (MMW) web-based training program was developed to address this gap by enhancing line managers' confidence and competence in prevention. OBJECTIVE: This study piloted the MMW intervention to assess its feasibility. Objectives included evaluating (1) uptake potential across small, medium, and large companies; (2) perceived suitability and effectiveness of the intervention; and (3) feasibility of outcome data collection methods. METHODS: We conducted a 2-arm pilot cluster randomized controlled trial of a self-guided, web-based training intervention for line managers. Twenty-four organizations were randomly assigned to the MMW intervention or a 3-month waitlist. A total of 224 line managers completed baseline measures (intervention: n=141, 62.9%; control: n=83, 37.1%), along with 112 of their direct reports (intervention: n=74, 66.1%; control: n=38, 33.9%). Follow-up data were collected at 3 and 6 months. Semistructured interviews with line managers and stakeholders (n=20) explored experiences with the study and intervention, and qualitative data were analyzed thematically. Line managers also completed feedback forms after each of the 5 MMW modules. RESULTS: The recruitment of organizations and line managers exceeded targets, and retention rates of line managers were good at 3 months (161/224, 71.9%) but not at the 6-month follow-up (55/224, 24.6%). Feedback on the intervention was very positive, indicating that line managers and organizational stakeholders found the intervention acceptable, usable, and useful. We observed significant improvements with moderate to large effect sizes for all trial outcomes for line managers in the intervention arm from baseline to the 3-month follow-up. Line managers completed a variety of questionnaires, which showed increased scores for confidence in creating a mentally healthy workplace (intervention group: mean change 3.8, SD 3.2; control group: mean change 0.6, SD 3.2), mental health knowledge (intervention group: mean change 1.9, SD 3.0; control group: mean change 0.2, SD 2.9), psychological well-being (intervention group: mean change 3.6, SD 8.3; control group: mean change -0.7, SD 7.7), and mental health literacy at work (intervention group: mean change 11.8, SD 8.9; control group: mean change 0.8, SD 6.2). Collecting data from direct reports in both study arms was challenging, with results inconclusive regarding observed changes in trial outcomes. Time constraints and workload were commonly cited barriers to completion of the intervention. CONCLUSIONS: This pilot feasibility trial provides strong evidence for the usability and acceptability of the MMW digital training and the research design. MMW shows potential to improve line managers' confidence and competencies in promoting mental health. The study also identified key considerations for future large-scale implementation and evaluation. TRIAL REGISTRATION: ClinicalTrials.gov NCT05154019; https://clinicaltrials.gov/study/NCT05154019.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".