Reflective Practice: A Comparative Dimensional Analysis of the Concept in Nursing and Education Studies
Bibliographic record
Abstract
AIM: This paper reports on an analysis of the concept of reflective practice. BACKGROUND: Reflective practice, a concept borrowed from the field of education, is widely used in nursing. However, to date, no study has explored whether this appropriation has resulted in a definition of the concept specific to the nursing discipline. DATA SOURCES: A sample comprised of 42 articles in the field of nursing drawn from the CINAHL database and 35 articles in education from the ERIC database (1989-2013) was analyzed. REVIEW METHOD: A concept analysis using the method proposed by Bowers and Schatzman was conducted to explore the differing meanings of reflective practice in nursing and education. RESULTS: In nursing, the dimensions of the concept differ depending on context. In the clinical context, the dimensions may be summarized as theory-practice gap, development, and caring; in training, as learning, guided process, and development; and in research, as knowledge, method, and social change. In education, the concept is also used in the contexts of training (the dimensions being development, deliberate review, emotions, and evaluation) and research (knowledge, temporal distance, and method). The humanist dimension in nursing thus reflects a use of the concept more specific to the discipline. CONCLUSION: The concept analysis helped clarify the meaning of reflective practice in nursing and its specific use in the discipline. This observation leads to a consideration of how the concept has developed since its appropriation by nursing; the adoption of a terminology particular to nursing may well be worth contemplating.
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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 | 0.048 | 0.089 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.018 | 0.018 |
| Science and technology studies | 0.005 | 0.013 |
| Scholarly communication | 0.015 | 0.014 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".