Men’s Experiences of Mental Illness Stigma Across the Lifespan: A Scoping Review
Bibliographic record
Abstract
The stigma of men's mental illness has been described as having wide-reaching and profound consequences beyond the condition[s] itself. Stigma negatively impacts men's mental health help-seeking and the use of services amid impeding disclosures, diminishing social connection and amplifying economic hardship. Although men often face barriers to discussing their struggles with, and help-seeking for mental illness challenges, research focused on men's lived experiences of mental illness stigma is, at best, emergent. This scoping review explores men's mental illness related stigmas synthesizing and discussing the findings drawn from 21 published qualitative articles over the last 10 years. Four thematic findings were derived: (a) the weight of societal stigma, (b) stigma in male-dominated environments, (c) inequity driven stigmas, and (d) de-stigmatizing strategies. Despite evidence that stigma is a common experience for men experiencing diverse mental illness challenges, the field remains underdeveloped. Based on the scoping review findings, research gaps and opportunities for advancing the field are discussed.
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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".