Men’s anxiety, why it matters, and what is needed to limit its risk for male suicide
Bibliographic record
Abstract
Anxiety disorders are the most prevalent mental health disorder experienced by men. If left untreated, anxiety is predictive of psychiatric disorders including depression and associated suicide risk. Despite the prevalence and impact of men's anxiety, it remains largely overlooked in the field of men's mental health. Globally, men are reported to have lower rates of anxiety disorders compared to women; however, these sex-differences do not reflect the complexity and nuance of men's experiences. There is early evidence to suggest a male-type anxiety phenotype which may go undetected with generic diagnostic classifications. Masculine norms (i.e., stoicism, toughness, invulnerability) appear to be central to men's experiences and expressions of anxiety as well as men's help-seeking and coping behaviours. This is particularly concerning given anxiety increases men's risk of physical and psychological comorbidities and suicide risk. The effective assessment, detection and treatment of men's anxiety is therefore critical to improve mental health outcomes across the male lifespan. We propose three key recommendations for the field of men's anxiety: (i) to develop a theoretical model surrounding men's experiences of anxiety, (ii) broaden mental health resources, interventions and suicide prevention strategies to encompass men's gendered experiences of anxiety (e.g., sentiments of shame, physical symptom manifestation), and (iii) utilise informal supports (i.e., friends and family) as an avenue of intervention to improve men's anxiety outcomes. Without a substantial research agenda in men's anxiety, we will fail to recognise and respond to men's gendered experiences of anxiety and ultimately fail to reduce male suicides.
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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 | 0.006 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".