Understanding Dynamics: A Systematic Review of the Attitudes, Knowledge, and Competencies of European Frontline Professionals Toward Domestic Abuse
Bibliographic record
Abstract
There remains a paucity of European research on attitudes and responses to domestic abuse from frontline workers and professionals who regularly encounter domestic abuse or engage with domestic abuse legislation. This systematic review synthesized qualitative, quantitative, and mixed-method peer-reviewed studies that explored professionals' knowledge, attitudes, and competencies related to domestic abuse. The professionals included medical staff (doctors, nurses, midwives), social care professionals, police officers, and criminal justice practitioners. The review was conducted on current European studies published between 2014 and 2025 and was reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Databases consulted included APA PsycInfo, Scopus, Web of Science, PubMed, Sociological Abstracts, International Bibliography of the Social Sciences, Social Services Abstracts, and Google Scholar. Full-text review was performed on 273 articles, of which 36 were deemed appropriate for inclusion. The review included 8 multi-country studies spanning the United Kingdom (England, Scotland, and Wales), and 28 single-country studies conducted in England, Sweden, Turkey, Portugal, the Republic of Ireland, Wales, Bosnia, Spain, Italy, Slovenia, and Hungary. A narrative and thematic synthesis categorized professional attitudes toward domestic abuse into four emergent themes: attitudes toward engagement and responsibility, attitudes toward victims, knowledge and understanding of domestic abuse, and attitudes as predictors of professional practice. This review addresses a dearth of research and provides recommendations for promoting proactive practice among professionals most likely to receive disclosures of abuse.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".