Understanding healthcare professionals’ self-efficacy to resolve interprofessional conflict
Bibliographic record
Abstract
Conflict within interprofessional healthcare teams, when not effectively resolved, has been linked to detrimental consequences; however, effective conflict resolution has been shown to enhance team performance, increase patient safety, and improve patient outcomes. Alarmingly, knowledge of healthcare professionals' ability to resolve conflict has been limited, largely due to the challenges that arise when researchers attempt to observe a conflict occurring in real time. Research literature has identified three central components that seem to influence healthcare professional's perceived ability to resolve conflict: communication competence, problem-solving ability, and conflict resolution education and training. The purpose of this study was to investigate the impact of communication competence, problem-solving ability, and conflict resolution education and training on healthcare professionals' perceived ability to resolve conflicts. This study employed a cross-sectional survey design. Multiple regression analyses demonstrated that two of the three central components-conflict resolution education and training and communication competence-were found to be statistically significant predictors of healthcare professionals' perceived ability to resolve conflict. Implications include a call to action for clinicians and academicians to recognize the importance of communication competence and conflict resolution education and training as a vital area in interprofessional pre- and post-licensure education and collaborative practice.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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; both teacher heads agree on what is shown here.
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".