‘Connecting with Young Men’: The Impact of Training in Ireland.
Bibliographic record
Abstract
‘Connecting with Young Men’, Unit 6 in ENGAGE, Ireland’s National Men’s Health Training programme was developed to support service providers to engage young in mental health and related services. This study evaluated the impact of Unit 6 on front line service providers’ knowledge, skills, capacity, and practice pre and immediately post-training via questionnaire (n=206). At 1-month post-training interviews were conducted with youth workers (n=11), SPHE (social and emotional health curriculum) teachers (n=3), and sports personnel (n=3) (12-40 mins) to explore their experience of the training and its impact on practice. Overall, feedback regarding training satisfaction was largely positive (8.43±1.43/10). Participants selfreported level of knowledge (p=0.000), skills (p=0.000), capacity to engage (p<0.003) and identify priorities for young men (p<0.001), and success at convincing other service providers within (p<0.001) and beyond (p<0.000) their organization to prioritize engaging young men increased immediately post-training. Notably, 57.3% of service providers said that they would integrate the training into their work practice. Critical components of Unit 6 included (a) the focus on understanding gender as a dynamic construct, (b) the use of experiential and interactive sessions, and (c) the integration of ongoing reflective practice. The provision of more practical tips on ‘how’ to initiate and build relationships with young men as well as including young men’s voices would strengthen the training. Unit 6 has been effective in building capacity among service providers to engage young men. While assessing the longer-term impact of the training on practice is recommended, these findings have implications for those who wish to develop gender-sensitive services for young men elsewhere.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".