Professional Fulfillment and Burnout in Fourth-Year Pharmacy Students and Risk Factors for the Future: A Mixed Methods Study
Bibliographic record
Abstract
OBJECTIVE: Many factors shape the professional identity of pharmacy students; however, little is known about the influence of well-being. Two aspects of well-being explored in this study include professional fulfillment and burnout. We describe the current levels of each among fourth-year pharmacy students, identify possible predictors, and uncover themes. METHODS: The Stanford Professional Fulfillment Index was used to measure professional fulfillment and burnout among students in the prior 2 weeks. Multivariable linear regressions were conducted to identify individual characteristics and activities as predictors of professional fulfillment and burnout. Upon completion of activities to foster personal wellness, student self-reflections were analyzed using thematic analysis to describe student-perceived barriers and facilitators of professional fulfillment and burnout. RESULTS: In total 54 students completed the Professional Fulfillment Index, wellness activities, and self-reflection. Having already completed the jurisprudence examination required for licensure and having a job upon graduation were statistically significantly associated with higher professional fulfillment scores. We identified that working in a non-pharmacy-related job, while completing practicums, was statistically significantly associated with higher work exhaustion scores. Themes uncovered from student self-reflections included a definition of wellness, how doing what you are supposed to be doing and working in a psychologically and physically safe environment contributes to professional fulfillment, and system-level factors leading to burnout. CONCLUSION: This study provides evidence of the importance of supporting pharmacy students in the completion of the steps to licensure, the value of exposure to a variety of pharmacist-related activities through experiential education, and well-being as foundational to professional identity.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".