A Qualitative Evaluation of the Implementation of an Intimate Partner Violence Education Program in Fracture Clinics
Bibliographic record
Abstract
We developed an intimate partner violence educational program (EDUCATE) for health care providers which was implemented in seven fracture clinics by local IPV champions. The purpose of the program was to provide health care providers with the knowledge and skills required to comfortably identify and assist women experiencing IPV in the fracture clinic. The program consisted of an introductory video, interactive online modules, and an in-person presentation by a local IPV champion. The study aim was to qualitatively evaluate the feasibility, acceptability, and perceived value of the program. We conducted semi-structured interviews with 10 champions and 23 participants and identified themes using a qualitative descriptive approach. Champions and participants expressed a strong satisfaction with the program. Champions also described several barriers and facilitators to program implementation. Additionally, we identified themes through analysis of interview data from champions (champion training, program delivery, and perceptions about program participants' receptiveness to the training) and participants (value of the training experience, useful program content, desire for more education, and suggested program improvements). The program showed promising results, as both champions and program participants had overall positive experiences completing the program. Their suggestions for improvement have been used to refine the program, which is now publically available for educational purposes through www.IPVeducate.com.
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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 | 0.031 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| 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".