Relationship between personality traits and pharmacist performance in a pharmacy practice research trial
Bibliographic record
Abstract
BACKGROUND: Pharmacy practice research is one avenue through which new pharmacy services can be integrated into daily pharmacy practice. However, pharmacists' participation in this research has not been well characterized. Drawing from the literature on work performance and personality traits, 4 hypotheses were developed to gain insight into pharmacists' performance in a pharmacy practice research trial. METHODS: This study was an observational, cross-sectional survey of pharmacists participating in a research trial. All pharmacists were asked to complete the Big Five Inventory (BFI), a validated, reliable instrument of personality traits. These results were then compared with measures of pharmacists' performance in the trial. RESULTS: Thirty pharmacists expressed interest in participating in the trial; 23 completed the BFI and 14 actively participated in the pharmacy practice research trial. No statistically significant differences were identified in the examination of the predetermined hypotheses. Exploratory analyses revealed significant relationships between the BFI trait of extroversion and pharmacists' participation in the study, obtaining prescribing authority for the study and the number of patients lost to follow-up. DISCUSSION: In addition to identifying a number of personality traits that have been shared by other samples of pharmacists, this work suggests the possibility of an interaction between pharmacists' personality traits and their performance in a pharmacy practice research trial. CONCLUSION: Future research should better characterize the relationship between pharmacists' personality traits and participation in pharmacy practice research trials to gain insight into the context of pharmacy practice and how pharmacists are integrating this research into their practices.
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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 | 0.071 | 0.190 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".