Men’s Help-Seeking for Depression: Attitudinal and Structural Barriers in Symptomatic Men
Bibliographic record
Abstract
Objective: Men with depression are known to have significant challenges with health service engagement. The current study sought to better understand attitudinal and structural mental health care barriers among those men identified as symptomatic for symptoms of major depression. Design: Cross-sectional study with data provided by Canadian men via a nationally representative online survey. Outcomes examined depression, suicide risk, and barriers to mental health services. Participants: A total of 117 men (mean age = 42.36 years) reporting symptoms of major depression consistent with moderate severity as identified by the Patient Health Questionnaire–Depression Module (PHQ-9). Results: In all, 51.3% of the sample reported previously receiving counselling or psychotherapy for mental health concerns. The majority (63.2%) reported past 2-week suicide or self-harm ideation; however, only a small proportion (8.5%) were currently engaged with professional mental health support. Logistic regression indicated that men’s attitudinal barriers to mental health help-seeking had a greater predictive effect than structural barriers (33% vs 0% of items, respectively). In particular, lower likelihood of help-seeking was associated with men’s reluctance to disclose mood-related symptoms to their physician/family doctor (adjusted odds ratio [AOR] = 0.37), a tendency for self-reliance and solving one’s own problems (AOR = 0.34), and uncertainly about the process of psychotherapy (AOR = 0.29). Conclusion: Gender-transformative approaches to primary health care may be key to improving men’s rates of disclosure and increasing detection for depression and suicide risk.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".