Nurses' knowledge and beliefs on pain management practices with hospitalised persons living with dementia: A qualitative descriptive study
Bibliographic record
Abstract
AIM: To understand nurses' knowledge, beliefs and experiences affect pain management practices in hospitalised persons living with dementia (PLWD). DESIGN: Naturalistic inquiry using qualitative descriptive design. METHODS: Semi-structured interviews were conducted with 12 registered nurses who worked in one acute care hospital in Southern California from October to November 2022. Data were analysed using content analysis to identify themes. RESULTS: Two themes were developed: improvising pain assessment, which included how pain was documented, and administration hesitancy referring to nurse's concerns about PLWD's confusion. Nurses described the challenges of assessing pain in hospitalised PLWD particularly if they were non-verbal and/or demonstrating responsive behaviours. Nurse's years of experience, dementia stigma, and their unconscious biases affected nurses' pain management practices. CONCLUSIONS: The study findings highlight the complex challenges of pain management in hospitalised PLWD that are exacerbated by nurses' knowledge deficits, negative stereotypical beliefs, dementia stigma and unconscious biases towards older people that contributes to undermanaged pain in hospitalised PLWD. IMPLICATIONS: A comprehensive strategy using an implementation framework is needed to address nurse's knowledge gaps, unconscious bias, dementia stigma and techniques that enhance communication skills is suggested. Building a foundation in these areas would improve pain management in hospitalised PLWD. IMPACT: Improving pain management in hospitalised PLWD would improve the quality of life, decrease hospital length of stay, prevent readmissions, and improve nurse satisfaction. REPORTING METHOD: The study adhered to the Consolidated Criteria for Reporting Qualitative Research (COREQ). PATIENT CONTRIBUTIONS: Improving pain management in hospitalised PLWD would prevent long term confusion, episodes of delirium and improve quality of life as they recover from their acute illness for which they required hospital care.
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".