Preceptorship and interpersonal conflict: a multidisciplinary study
Bibliographic record
Abstract
BACKGROUND: The impetus for the study was the concern of teachers about the potentially deleterious effects of conflict in the preceptee-preceptor relationship. Preceptorship, in which students work alongside designated professionals in clinical settings, can provide opportunities to integrate theoretical and practice knowledge, and can play a part in professional development. However, students may experience communications and interpersonal problems with their preceptors and, if the conflict thereby generated is not challenged and resolved, negative outcomes can occur for students, preceptors and teachers. AIM: The purpose of the study was to explore the nature of conflict in preceptorship experiences. METHODS: A modified, simultaneous quantitative/qualitative triangulated method was used, with the quantitative results reported in this paper. A total of 548 questionnaires were mailed to students and preceptors in the final clinical experience of undergraduate programmes in four disciplines. The return rate was 42.7% (234 questionnaires). FINDINGS: Data revealed the prevalence of conflict, the degree to which this affected preceptorship relationships, factors occurring in the practicum that may contribute to conflict, the degree to which the conflict was resolved, and the outcomes of conflict. CONCLUSIONS: It is only through an understanding of the dynamics involved in conflict, and its negative effects on students, that teachers, preceptors and students alike can respond proactively to conflicts and become adept at seeking and implementing effective solutions.
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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 | 0.011 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".