Evaluating the Relationship Between Intimate Partner Violence-Related Training and Mental Health Professionals’ Assessment of Relationship Problems
Bibliographic record
Abstract
Intimate partner violence (IPV) is a serious public health problem associated with increased risk of developing mental health conditions. Assessment of IPV in mental health settings is important for appropriate treatment planning and referral; however, lack of training in how to identify and respond to IPV presents a significant barrier to assessment. To address this issue, the World Health Organization (WHO) advanced a series of evidence-based recommendations for IPV-related training programs. This study examines the relationship between mental health professionals’ experiences of IPV-related training, including the degree to which their training resembles WHO training recommendations, and their accuracy in correctly identifying relationship problems. Participants were psychologists and psychiatrists ( N = 321) from 24 countries who agreed to participate in an online survey in French, Japanese, or Spanish. They responded to questions regarding their IPV-related training (i.e., components and hours of training) and rated the presence or absence of clinically significant relationship problems and maltreatment (RPM) and mental disorders across four case vignettes. Participants who received IPV-related training, and whose training was more recent and more closely resembled WHO training recommendations, were more likely than those without training to accurately identify RPM when it was present. Clinicians regardless of IPV-related training were equally likely to misclassify normative couple issues as clinically significant RPM. Findings suggest that IPV-related training assists clinicians in making more accurate assessments of patients presenting with clinically significant relationship problems, including IPV. These data inform recommendations for IPV-related training programs and suggest that training should be repeated, multicomponent, and include experiential training exercises, and guidelines for distinguishing normative relationship problems from clinically significant RPM.
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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 | 0.007 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".