Why physicians and nurses ask (or don’t) about partner violence: a qualitative analysis
Bibliographic record
Abstract
BACKGROUND: Intimate partner violence (IPV) against women is a serious public health issue and is associated with significant adverse health outcomes. The current study was undertaken to: 1) explore physicians' and nurses' experiences, both professional and personal, when asking about IPV; 2) determine the variations by discipline; and 3) identify implications for practice, workplace policy and curriculum development. METHODS: Physicians and nurses working in Ontario, Canada were randomly selected from recognized discipline-specific professional directories to complete a 43-item mailed survey about IPV, which included two open-ended questions about barriers and facilitators to asking about IPV. Text from the open-ended questions was transcribed and analyzed using inductive content analysis. In addition, frequencies were calculated for commonly described categories and the Fisher's Exact Test was performed to determine statistical significance when examining nurse/physician differences. RESULTS: Of the 931 respondents who completed the survey, 769 (527 nurses, 238 physicians, four whose discipline was not stated) provided written responses to the open-ended questions. Overall, the top barriers to asking about IPV were lack of time, behaviours attributed to women living with abuse, lack of training, language/cultural practices and partner presence. The most frequently reported facilitators were training, community resources and professional tools/protocols/policies. The need for additional training was a concern described by both groups, yet more so by nurses. There were statistically significant differences between nurses and physicians regarding both barriers and facilitators, most likely related to differences in role expectations and work environments. CONCLUSIONS: This research provides new insights into the complexities of IPV inquiry and the inter-relationships among barriers and facilitators faced by physicians and nurses. The experiences of these nurses and physicians suggest that more supports (e.g., supportive work environments, training, mentors, consultations, community resources, etc.) are needed by practitioners. These findings reflect the results of previous research yet offer perspectives on why barriers persist. Multifaceted and intersectoral approaches that address individual, interpersonal, workplace and systemic issues faced by nurses and physicians when inquiring about IPV are required. Comprehensive frameworks are needed to further explore the many issues associated with IPV inquiry and the interplay across these issues.
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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 | 0.016 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".