Nurses' Knowledge, Attitudes, and Confidence Regarding Preventing and Treating Deconditioning in Older Adults
Bibliographic record
Abstract
BACKGROUND: This article examines nurses' knowledge, beliefs, attitudes, and confidence regarding providing care to prevent and treat deconditioning in hospitalized older adults. METHODS: Data were collected from 157 registered nurses enrolled in a post-registered nurse, bachelor of science in nursing program using a descriptive cross-sectional survey. RESULTS: Nurses' responses reflected substantial gaps in their knowledge and theoretical understanding of deconditioning, and a strong belief in the need for more education on the prevention of it. Levels of confidence in preventing deconditioning in older adults were modest, but participants expressed positive attitudes toward nurses' role in deconditioning care. Barriers to deconditioning care included lack of education, low staffing levels, and a lack of valuing prevention efforts. CONCLUSION: This study suggests that it is important to establish gerontology continuing education programs with a core component on deconditioning treatment and prevention to enhance nurses' knowledge and confidence levels in providing care to older adults.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".