Protocol for a randomized controlled trial of the Men in Mind training for mental health practitioners to enhance their clinical competencies for working with male clients
Bibliographic record
Abstract
BACKGROUND: Although the proportion of men seeking professional mental health care has risen over the past two decades, on average, men continue to attend fewer sessions of psychotherapy and are more likely to drop out of treatment prematurely compared to women. Men account for three-quarters of suicide deaths; furthermore, over half of the males who die by suicide have engaged with mental health care in the 12 months prior to their death. These findings highlight a need to equip mental health practitioners with skills to improve male clients' engagement and mental health outcomes. This article reports the protocol for a randomized controlled trial of Men in Mind, a self-paced online training program purpose-built to advance the clinical competencies of practitioners who provide psychotherapy to male clients. METHODS: A randomized controlled trial with two parallel groups will be conducted. Participating practitioners will be randomly allocated, on a 1:1 basis, to the intervention group (Men in Mind training) or a waitlist control group. The primary outcome, efficacy of the training, will be evaluated by pre- to post-training (T1 to T2) changes in scores on the Engaging Men in Therapy Scale (EMITS) in the intervention group, relative to the control group. DISCUSSION: This trial will provide evidence of the efficacy of Men in Mind training, as an interim step towards adjusting content and delivery of the intervention to maximize the potential for sustaining and scaling. TRIAL REGISTRATION: The trial was registered prospectively with the Australian New Zealand Clinical Trials Registry on 3rd December 2021 (ACTRN12621001669886).
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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 | 0.063 | 0.066 |
| Meta-epidemiology (narrow) | 0.009 | 0.005 |
| Meta-epidemiology (broad) | 0.016 | 0.007 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.014 | 0.016 |
| Insufficient payload (model declined to judge) | 0.137 | 0.029 |
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".