Exploring Mental Health Professionals’ Experiences of Intimate Partner Violence–Related Training: Results From a Global Survey
Bibliographic record
Abstract
Intimate partner violence (IPV) is a global public health problem that has been shown to lead to serious mental health consequences. Due to its frequent co-occurrence with psychiatric disorders, it is important to assess for IPV in mental health settings to improve treatment planning and referral. However, lack of training in how to identify and respond to IPV has been identified as a barrier for the assessment of IPV. The present study seeks to better understand this IPV-related training gap by assessing global mental health professionals’ experiences of IPV-related training and factors that contribute to their likelihood of receiving training. Participants were French-, Spanish-, and Japanese-speaking psychologists and psychiatrists ( N = 321) from 24 nations differing on variables related to IPV, including IPV prevalence, IPV-related norms, and IPV-related laws. Participants responded to an online survey asking them to describe their experiences of IPV-related training (i.e., components and hours of training) and were asked to rate the frequency with which they encountered IPV in clinical practice and their level of knowledge and experience related to relationship problems; 53.1% of participants indicated that they had received IPV-related training. Clinicians from countries with relatively better implemented laws addressing IPV and those who encountered IPV more often in their regular practice were more likely to have received training. Participants who had received IPV-related training, relative to those without training, were more likely to report greater knowledge and experience related to relationship problems. Findings suggest that clinicians’ awareness of IPV and the institutional context in which they practice are related to training. Training, in turn, is associated with subjective appraisals of knowledge and experience related to relationship problems. Increasing institutional efforts to address IPV (e.g., implementing IPV legislation) may contribute to improved practices with regard to IPV in mental health settings.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".