Influence of Cultural Norms on Formal Service Engagement Among Survivors of Intimate Partner Violence: A Qualitative Meta-synthesis
Bibliographic record
Abstract
For victim-survivors of intimate partner violence (IPV), receiving help from formal services such as specialist family violence, health, or criminal justice services can be critical for their safety and well-being. Previous research has found cross-cultural differences in the rates of help-seeking behavior, with women from non-Anglo-Saxon communities less likely to seek formal help than Anglo-Saxon populations. This qualitative meta-synthesis has integrated qualitative evidence to examine the relationship between specific cultural norms and formal service engagement for female victim-survivors of IPV from non-Anglo-Saxon communities. A comprehensive search of seven databases was conducted for peer-reviewed articles published between 1985 to May 2021, in addition to searching gray literature. Thirty-five articles met the criteria for inclusion, representing 1,286 participants from 20 cultural groups. Based on a thematic synthesis approach, five key themes that captured specific cultural norms that influence formal service engagement were identified: (1) gender roles and social expectations, (2) community recognition and acceptance of abuse, (3) honor-based society, (4) the role of religion, and (5) cultural beliefs and attitudes toward formal services. These findings have important implications for responses to family violence, particularly concerning family violence education for non-Anglo-Saxon ethnically diverse communities and best-practice strategies to improve the cultural relevancy of formal service providers.
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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 | 0.059 | 0.149 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.009 |
| Bibliometrics | 0.015 | 0.015 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 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".