Australian men's initial pathways into mental health services
Bibliographic record
Abstract
ISSUE ADDRESSED: Many men are challenged by barriers to mental health help-seeking and engagement. For men who do access care, their pathways to engaging services can offer important insights to what might constitute gender-specific care. METHODS: Data were drawn from an online cross-sectional survey of N = 2009 Australian men (aged 16-85; M = 43.5) reflecting on their initial pathways to mental health services, including their reasons for help-seeking, how they first located a therapist and the source of any initial recommendation for engaging with services. Respondents were recruited with targeted advertisements via Movember's Facebook page. RESULTS: A relatively even age distribution was observed, with most respondents residing in metropolitan areas (60.4%), a majority employed full time (47.7%), and 25.7% identifying as gay or bisexual. Participants tended to be self-motivated to seek help, with referrals by general practitioners to specialist mental health services. The most common underpinning precipitant for seeking help was anxiety, particularly for younger men, whereas older men tended to have sought help more commonly for familial, relationship or work-related factors. Older men were also more likely to report self-motivated help-seeking, whereas younger men more commonly sought help on the recommendation of a family member. CONCLUSIONS: There are varied pathways for men's initial mental health help-seeking journeys that require an ongoing examination to ensure health promotion efforts are appropriately tailored and responding to men's needs. SO WHAT: As more men access mental health services, having a nuanced understanding of their likely pathways to care can inform the help-seeking efforts of other men as well as guide improved services and systems to reduce barriers.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".