Conceptualising nursing theory and practice within a local cultural and professional context: a methodological example to inform theory development
Bibliographic record
Abstract
Background: Nursing theories are crucial toward orienting the development of knowledge and practice. However, there is a persistent debate in the literature regarding the gap between theory and practice. Theories and conceptual models developed in Anglo-Saxon countries are often proposed within diverse educational and clinical contexts in other countries, generating challenges in their application in practice. Aim: This study aimed to develop and propose a methodology to promote the advancement of nursing theorising, considering local cultural and professional contexts. Methods: This analysis was conducted within Italy, which served as a local cultural and professional context exemplar for this investigation. A Scoping Review was used to map local nursing knowledge related to nursing practice. Fawcett's metaparadigm was used as a general orienting frame for the literature analysis. Results: In light of the analysis conducted, the four disciplinary concepts related to the local (Italian) cultural and professional context were described (person, environment, health, nursing). Conclusion: This investigation aimed to present an example of how an inductive reflective approach can be used as a way to map nursing practice and define disciplinary concepts that can guide conceptual/theory development. The knowledge that was generated can orient initiatives to promote local nursing theory development.
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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 | 0.053 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.008 | 0.017 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".