An international portrait of pharmacists' professional role identities: A Q-methodology innovative study
Bibliographic record
Abstract
Background: Professional identities shape who pharmacists are, what they do, and what they stand for as professionals. Novel research methodologies have potential to illuminate pharmacists' professional identity and roles in new and innovative ways. This study aimed to explore international pharmacists' identity through reflection on their professional roles. Methods: Q Methodology, which uses quantitative techniques to systematically study subjectivity, was used to allow for an in-depth analysis of professional identity. The participants were self-identified pharmacists working in patient-facing roles who attended the International Pharmaceutical Federation (FIP) Congress in Brisbane, Australia, from September 24-28, 2023. They completed Q methodology online activities to sort the Q-Set within a fixed quasi-normal distribution grid. Results: Twenty participants completed the Q-Sort activity. Participants came from 10 countries (five of the six World Health Organization regions), two thirds identified as women and approximately one third practiced in hospital and community pharmacy settings, respectively. Three factor arrays are described, which explain 52 % of the variance; Factor 1: Pharmacists as autonomous healthcare providers AND clinical team members; Factor 2: Pharmacists as healthcare providers for individual patients; and Factor 3: Pharmacists as managers first, then healthcare providers. Conclusion: This study offers a new perspective, revealing how various roles may converge to form a pharmacist's professional role identity: for example, autonomous healthcare providers AND clinical team members AND patient-focused practitioners AND leaders mindful of management responsibilities. Viewing the Q Methodology with a systems thinking lens illuminates pharmacists' professional identities as neither a mere sum of the roles and services they provide, nor represented by a singular aspect of their professional work. Recognizing the complexity of the pharmacists' identities as individuals helps to break free from the cognitive dissonance that has plagued the profession suggesting that professional identity is represented by singular or often competing roles as the scope of pharmacy practice evolves.
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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 | 0.068 | 0.046 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| 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".