Making connections across silos: intimate partner violence, mental health, and substance use
Bibliographic record
Abstract
BACKGROUND: Untold numbers of women worldwide are survivors of intimate partner violence (IPV) with a substantial number of these experiencing co-occurring mental health and substance use problems. Despite the complex interconnections among these problems, funding mechanisms and organizational structures and mandates have been designed to address just a single, focal problem. One of the challenges for frontline providers is the lack of effective, evidence-informed inter-professional education or training to help them identify and appropriately respond to co-occurring problems. We developed an evidence-informed, competency-based curriculum to address this gap. In this paper we report on its effectiveness in increasing knowledge, changing beliefs and enhancing skills of frontline workers from all three sectors. METHODS: The curriculum consists of multiple elements: a text manual; an interactive, online series of modules; and, an in-person workshop. Frontline workers (n = 1111) in the violence against women (VAW) (n = 499), mental health (n = 229), addiction treatment (n = 167), and associated sectors (n = 149) were recruited to attend the workshop and instructed to read the manual or complete the online modules before attending. Some failed to respond (n = 67). Online pre- and post-tests were used to assess changes in knowledge, beliefs and skills; evaluations of the workshop were also collected. RESULTS: Matched pre- and post-tests were available for over half of the participants (n = 624). Results show statistically significant improvements across all six competency domains from pre to post-test (p <0.0001). Significant changes in participants' knowledge and stigmatizing beliefs were achieved. There was no correlation among differences in sector, age, size of organization, years of experience or prior training. Participant feedback made evident prior misconceptions about women experiencing co-occurring problems, improved understanding about the need to bridge silos, as well as the need for enhanced self-care. CONCLUSIONS: An educational intervention designed to sensitize frontline workers to the realities of women's experiences of co-occurring problems, educate about the challenges of accessing help when there are co-occurring problems, and bridge discipline and practice-based silos, can effectively challenge and alter providers' negative attitudes and stigmatizing beliefs. Decreasing stigmatizing beliefs and increasing knowledge has the potential to help survivors access needed help.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".