An Exploratory Qualitative Content Analysis of First-Year Veterinary Students’ Perspectives on Conflict
Bibliographic record
Abstract
Teamwork among health professionals is a requirement for the delivery of excellent medical care; effective teamwork leads to improved patient outcomes and greater job satisfaction for health care professionals. A critical component of successful teamwork is effective conflict management. While preliminary evidence suggests that many health care providers have negative perceptions of conflict and conflict-avoidant tendencies, no existing research to-date has explored veterinary students' perspectives on conflict. Understanding the ways in which veterinary students perceive conflict represents an important first step in helping them identify strategies for future conflict management. The purpose of this exploratory study was to describe the first-year veterinary students' perspectives on conflict. Students responded to two open-ended prompts as part of a reflection assignment following an instructional module on conflict. Results from the qualitative content analysis showed that students demonstrated an understanding of (a) the role of feelings and emotions in conflict, (b) the importance of relying on facts and observations as opposed to evaluations and judgment in conflict, (c) the value of competent communication in conflict, and (d) self-awareness of personal factors related to conflict. These findings highlight the power of self-reflection to learners' awareness of default tendencies when faced with conflict, the impact of their attitudes and experiences on conflict behavior, and a willingness to incorporate a collaborative approach to conflict resolution in the future.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".