Barriers to Men’s Help Seeking for Intimate Partner Violence
Bibliographic record
Abstract
Evidence suggests that male victims of intimate partner violence (IPV) are less likely to seek help for their victimization than female victims. Studies exploring barriers to help seeking are relatively scarce in the United Kingdom (UK) and those that have been undertaken across Europe, United States, Canada, and Australia have tended to rely on small samples of help-seeking men who have self-identified as victims of IPV. With a view to include more male victim voices in the literature, an anonymous qualitative questionnaire was distributed via social media. In total, 147 men (85% from the UK) who self-identified as being subject to abuse from their female partners, completed the questionnaire. The data was subjected to a deductive thematic analysis and one superordinate and two overarching themes were identified. The superordinate theme was stigmatized gender and the two overarching themes (subthemes in parentheses) were barriers prohibiting help seeking (status and credibility, health and well-being) and responses to initial help seeking (discreditation, exclusion/isolation, and helpfulness). The findings are discussed in the context of Overstreet and Quinn's (2013) interpersonal violence and stigma model and findings from previous research. The conclusions and recommendations promote education and training and advocate a radical change to policy.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".