Meaningful Text: Total Hip Replacement Patients’ Lived Experience of a Nursing Care Plan Written in Lay Language
Bibliographic record
Abstract
Background: Person-centred care involves respecting patients’ experiences, preferences, and needs, as well as sharing information with them and involving them in care planning. Scant research has been conducted on how it influences patients to have direct access to their care planning when it has been established through the use of standardised care plans or pathways. In the orthopaedic ward in which this study was conducted, a standardised nursing care plan for total hip replacement patients (THR), which was originally written in professional language, was rewritten in lay language and used as peri-operative teaching material for this patient group. Study Aim: To explore the meaning THR patients ascribe to the lived experience of reading and retaining their standardised nursing care plan in lay language during their hospital stay. Methods: The data collection and analysis followed a method adapted by the Vancouver School of Doing Phenomenology. Data were collected through 12 in-depth interviews with six THR patients. Results: The main finding was that the participants acquired knowledge from the text of the care plan that was understandable and meaningful, as evidenced by the empowering impact it had on them. This impact included improved psychological wellbeing, more open communication, and the provision of a tool to keep track of care. Some revisions of the care plan were recommended. Conclusion: The study suggests that a patient version of standardised care plans can act as an important educational tool for THR patients that can empower them to manage their health 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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".