Men’s Health Promotion in Waiting Rooms: An Observational Study
Bibliographic record
Abstract
Issue addressed Currently, in Australia, male health outcomes are poorer than that of females, with males experiencing a lower life expectancy, accounting for 62% of the premature deaths. Exploring male-specific health promotional material in health facility waiting rooms provides an opportunity to examine available health information. There are few studies on health-related education for patients, families and carers in general practitioner (GP) waiting rooms, and no studies on male-specific health material content in waiting rooms. Methods This prospective observational study audited all printed health promotional materials in all health facility waiting rooms within a single local government area. A total of 24 sites were surveyed, which included general practice centres, community health centres and hospitals. The surveyed health literature included posters, brochures and booklets. Results There were 1143 health materials audited across the sites. Of these, 3.15% (n = 36) were male-specific literature, 15.31% (n = 175) were female-specific health literature and 81.54% (n = 932) were neutral/others. Overwhelmingly, the audited health literature evidenced a 5:1 ratio favouring female-specific literature versus male-specific literature. Conclusions This research highlighted that despite the known outcomes of lower male life expectancy and higher burden of disease, male-specific literature was observed to be significantly under-represented within the audited health facility waiting room spaces. There remains potential for health clinicians to provide targeted male health education and thereby improve male health literacy.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".