Caring for Hospitalized Older Adults at Risk for Delirium: The Silent, Unspoken Piece of Nursing Practice
Bibliographic record
Abstract
More than half of hospitalized older adults will experience delirium, which--if left untreated--can lead to detrimental outcomes. Despite the prevalence and severity of delirium, nurses recognize less than one third of cases. Because little is known about how nurses manage this problem, a qualitative study was conducted to explore how nurses care for hospitalized older adults at risk for delirium. The data revealed that nurses care for older adults byTaking a Quick Look, Keeping an Eye on Them, and Controlling the Situation. The context in which nurses choose their priorities and interventions was reflected in the themes of the Care Environment and Negative Beliefs and Attitudes about older adults. Nurses are caring for an older population whose care requirements are different than those of younger people and in a context where this challenging work is rarely addressed. To improve care, the older population must be acknowledged, and nurses must possess the knowledge and resources needed to meet this population's unique needs.
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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 | 0.014 | 0.046 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.015 |
| Scholarly communication | 0.005 | 0.010 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.005 | 0.006 |
| 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".