Registered nurses’ perception of their professional role regarding medication management in nursing care of the elderly
Bibliographic record
Abstract
Background: The role of the registered nurse (RN) in the municipality regarding medication management in care for the elderly is rarely discussed. Organizational issues related to medication management often contribute more to the management than needs of the patients, nursing skills, and collaboration with the physician in primary care. Objective: The aim of this study was to describe RNs’ perceptions of their professional role, especially regarding medication management in nursing of the elderly. Design: The study is descriptive with a qualitative approach. Interviews with 16 RNs working at nursing homes were analysed by content analysis. Results: The findings can be grouped into seven categories showing the RN in different roles while performing different aspects of her or his work: as controller, executer, messenger, supervisor, initiator, visionary and solitary worker. These themes were identified in the interviews and characterized the nurses’ own judgements and actions taken, especially regarding drug treatment. Overall, the RNs described nursing in elderly care as an undefined profession lacking leadership regarding medication management. Conclusions: The study concludes that medication management ought to be promoted in care for the elderly. To handle the challenge and risks of polypharmacy there must be sufficient and adequate reporting based on the RNs’ nursing and skills to monitor and evaluate the drug treatment in teamwork with the physician. This requires leadership with understanding of the integration of services in care for the elderly, and of the medical processes and nursing skills involved.
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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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".