The Role of Reflection for Continuing Professional Development of In-Service Health Care Professionals: A Narrative Inquiry in Four Health Professions
Bibliographic record
Abstract
INTRODUCTION: Health care providers (HCPs) use reflection to intervene in complex, ambiguous clinical situations. Yet, there is scant evidence about the circumstances when HCPs use reflection and how they perceive reflection within their continuing professional development. We selected a narrative inquiry approach to study how HCPs perceive reflection's role in learning in four health professions. METHODS: We invited 26 health professionals to a narrative interview conducted by a student in one of the four selected professions: medicine, nursing, occupational therapy, and speech-language pathology. The narrative events that make up the stories were analyzed and interpreted using structural analysis based on the narratives' historic-empirical and psycho-semantic dimensions. RESULTS: Physicians told us that reflection bolsters their clinical performance and confidence. Nurses told us that reflection allowed them to develop resilience as they sought to integrate their work setting and gain autonomy. Occupational therapists spoke of how reflection spurred them to innovate and extend the scope of their practice to advocate for their patients' health better. Speech-language pathologists described how they reflect on "educating" other HCPs about their profession and enhancing their communication skills with patients. DISCUSSION: The communicative power of storytelling allowed us to fathom what is hard to describe in words: how reflection builds clinical and psychosocial skills and introspective capacity. Hence, findings provide empirical evidence of reflection's perceived role in maintaining professional skills that make HCPs effective in complex, ambiguous situations.
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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 | 0.021 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.017 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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".