Theory-based practice as plural interpretations: A case of the the integration of the Humanbecoming theory in a palliative care setting
Bibliographic record
Abstract
Nurses and students are generally encouraged to base their practice on nursing grand theories and models. However, the concrete benefits of these models in practice are often debated. Given that past studies were mostly dedicated to documenting the benefits of nursing theories in practice and were conducted by their supporters, their contribution to the debate is questionable. In 2012, we conducted a retrospective case study in a palliative care unit in Canada where caregivers have based their practice on the Humanbecoming theory since two years. We aimed to examine the process of integration and its effects. Data was obtained from individual interviews, direct observation and documents were analyzed using a network analysis method. Results suggest that integrating a grand theory in practice implies plural interpretations of what constitutes good practice, which brings about various effects, including some that are unexpected. The authors challenge the belief that theories and models necessarily have positive effects in practice.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.041 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.029 | 0.085 |
| Scholarly communication | 0.017 | 0.018 |
| Open science | 0.003 | 0.020 |
| Research integrity | 0.009 | 0.014 |
| 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".