Young Men’s Anxiety Presentations to Australian Ambulance Services
Bibliographic record
Abstract
Young men experiencing anxiety risk traversing traditional norms of masculinity, a tension that risks under-diagnosis – and by extension under-treatment. Within this context young men frequently present to ambulance services with acute psychosomatic anxiety symptoms implicating extensive, and resource exhaustive diagnostic tests to differentially diagnose and clinically manage potentially life-threatening conditions (i.e., myocardial infarction, dyspnoea, asthma, and stroke). This four-phase mixed-methods study developed and tested a coding framework to describe and interpret clusters within data from the Victorian arm of the Australian National Ambulance Surveillance System (NASS). Six-hundred-and ninety-four young men aged 15-25 years, with an anxiety-related ambulance attendance in 2019 were analysed in the present analyses. Study findings revealed that the most common clinical characteristics in young men’s anxiety presentations were psychosomatic symptoms, alcohol and drug use, and situational stressors. Three typologies for young men’s anxiety presentations, 1) ‘Psychosomatic-Anxiety,’ 2) ‘Anxious-Substance Use’ and 3) ‘Complex-Anxiety’ were evident across severities. Findings highlight the need for tailored assessments to effectively triage young men experiencing anxiety and engage them with appropriate mental health services.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".