Web-Based Interactive Training for Managers (Managing Minds at Work) to Promote Mental Health at Work: Pilot Feasibility Cluster Randomized Controlled Trial
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,002 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,011 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».