“Heartbreaking, Hardest Part of the Job”: A Qualitative Descriptive Study of Acute Care Nurses’ Work with Patients with Dementia Who Self-Neglect Their Hygiene
Bibliographic record
Abstract
When nurses encounter people in institutional settings who are living with dementia and self-neglecting their hygiene, they are challenged to provide care that respects autonomy while upholding the ethical principles of beneficence and non-maleficence. This study aimed to understand how nurses respond when confronted with patients who decline assistance with personal hygiene and then became physically aggressive. Methods: A qualitative descriptive study employing think-aloud interviewing to explore nurses’ clinical reasoning about how they would proceed with the care of a patient living with dementia who self-neglects their hygiene. Results: Nurses describe many creative ways that they would work with patients to accomplish personal hygiene care in an ideal world. Participants also share the many barriers they experience to providing desired care and instances where they would force care with people who self-neglect their hygiene. Thematic analysis revealed six key themes: non-preferred approaches to care; preferred approaches to care; barriers to actualizing preferred approaches; responding to continued resistance to care; justified use of force; and efforts to minimize harm. Conclusions: This study highlights that ethical nursing practice in dementia care is not simply a matter of following through with best practices. It is an ongoing negotiation, carried out in environments that are often misaligned with nurses’ values.
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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 | 0.020 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.018 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".