Reducing intimate partner violence: a pilot evaluation of an intervention program
Bibliographic record
Abstract
The current study describes a 20-week community-based intimate partner violence (IPV) intervention program delivered in British Columbia, Canada, and provides a preliminary evaluation of program impacts. The Men in Healthy Relationships program targets men who have perpetrated IPV and who voluntarily choose to participate in a program to learn healthy intimate partner relationship strategies. The intervention was evaluated across three program cycles in a pretest–posttest single group design, with a total of 46 participants enrolled. Twenty-eight men completed the pretest survey; analyses focus on the subset of 17 participants who reported having a current intimate partner and who completed the Abusive Behavior Inventory, and the 14–21 participants who completed pretest and posttest questions regarding knowledge and skills learned in the program. Results from the pilot evaluation suggest that the Men in Healthy Relationships program is a promising approach to decreasing abusive behavior, with participants showing significant decreases in both physical and psychological abuse. In addition, participants increased their knowledge and use of calming techniques and “time-outs” to reduce feelings of anger. Limitations and future research are discussed, along with implications for IPV intervention programing for voluntary participants.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".