Supporting Clinical Competencies in Men’s Mental Health Using the Men in Mind Practitioner Training Program: User Experience Study
Bibliographic record
Abstract
BACKGROUND: Engaging men in psychotherapy is essential in male suicide prevention efforts, yet to date, efforts to upskill mental health practitioners in delivering gender-sensitized therapy for men have been lacking. To address this, we developed Men in Mind, an e-learning training program designed to upskill mental health practitioners in engaging men in therapy. OBJECTIVE: This study involves an in-depth analysis of the user experience of the Men in Mind intervention, assessed as part of a randomized controlled trial of the efficacy of the intervention. METHODS: Following completion of the intervention, participants provided qualitative (n=392) and quantitative (n=395) user experience feedback, focused on successes and suggested improvements to the intervention and improvements to their confidence in delivering therapy with specific subpopulations of male clients. We also assessed practitioner learning goals (n=242) and explored the extent to which participants had achieved these goals at follow-up. RESULTS: Participants valued the inclusion of video demonstrations of skills in action alongside the range of evidence-based content dedicated to improving their insight into the engagement of men in therapy. Suggested improvements most commonly reflected the desire for more or more diverse content, alongside the necessary adaptations to improve the learning and user experience. Participants also commonly reported improved confidence in assisting men with difficulty articulating their emotions in therapy and suicidal men. CONCLUSIONS: The evidence obtained from this study aids in plans to scale Men in Mind and informs the future development of practitioner training interventions in men's mental health. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1186/s40359-022-00875-9.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".