Exploring acute care nurses’ decision‐making in psychotropic PRN use in hospitalised people with dementia
Bibliographic record
Abstract
AIMS AND OBJECTIVES: To understand how acute care nurses make decisions about administering "as-needed" (PRN) psychotropic medications to hospitalised people with dementia (PWD). BACKGROUND: Behavioural and psychological symptoms of dementia occur in approximately 75% of PWD admitted to acute care. Despite this, few studies provide insight into the use and prevalence of psychotropic use in acute care. DESIGN: A qualitative descriptive design was used to explore acute care nurses' decision-making about PRN psychotropic medication administration to PWD. METHODS: Semi-structured interviews were conducted with eight nurses from three acute care medical units in a large tertiary hospital in Western Canada. Conventional content analysis was used to develop three themes that reflect nurses' decision-making related to administering PRNs to hospitalised PWD. COREQ guidelines were followed. RESULTS: Three themes of legitimising control, making the patient fit and future telling were developed. Legitimising control involved medicating undesirable behaviours to promote the nurses' perceptions of safety. Making the patient fit involved maintaining routine and order. Future telling involved pre-emptively medicating to prevent undesirable behaviours from escalating. Nurses provided little to no mention of assessing for physical causes contributing to behaviours. PRNs were seen as a reasonable alternative to physical restraints and were frequently used. Additionally, organisational and unit routines greatly influenced nurses' decision-making. CONCLUSIONS: These findings provide an initial understanding of how nurses make decisions to administer PRN medications to hospitalised older people and may inform prescribing practices. There were novel findings about the lack of assessment prior to PRN administration, and the nurses' collective response in decision-making. More research is needed to better understand the complexities of nurses' decision-making, to assist in the development of interventions for nursing practice.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".