Conflict management styles in academic and hospital pharmacy practice areas in affiliated tertiary institutions in Lagos, Nigeria
Bibliographic record
Abstract
Background/Objective: Types of conflicts in pharmacy organizations were discussed and conflict management styles by pharmacists in academia and hospital pharmacists in two affiliate tertiary institutions in Lagos, Nigeria were assessed. Methods: An adapted questionnaire of 20-item inventory for conflict management scale (CMS) for pharmacy was used to obtain responses from hospital pharmacists and pharmacists in academia in the practice areas. The multistage inventory item comprising questions that used four graded scales and appropriate alphabets A to D against each column was used in line with the described explanatory model. Scales of A, B, C, and D represent: imposing, settling, avoiding and thwarting respectively. Some items were rephrased and content-validated for clarity to respondents, while the last item (number 20) was introduced to reflect a pertinent issue in conflict management. The instrument was administered in voluntary situation over a period of two weeks; the results were collated and analyzed. Results: Thirty-one full-time pharmacist lecturers (14 males, 17 females) and 29 registered hospital pharmacists (6 males, 23 females) in the respective institutions completed the questionnaires. The summed scores of dominant and secondary conflict management styles for the two respective groups show that pharmacists in the two practice areas have different approaches to conflict management in workplace. A substantial number of respondents in both settings are either dominantly settling or avoiding in their style. Conclusion: Training in conflict management and reflective practice is highly recommended for pharmacists, to attain the skills that enhance their interpersonal environment, aimed at making pharmacy practice a very fulfilling and rewarding profession.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".