An approach to develop a continuing professional development workshop for nurses to differentiate, delirium, dementia and depression among older adults
Bibliographic record
Abstract
Delirium, dementia, and depression challenge nurses in acute care settings. They negatively impact older adult's health, well-being, and quality of life. Misdiagnosis of delirium, dementia, and depression is associated with higher mortality rate, functional decline, increased length of stay, higher admission and institutionalization rates, and higher health care expenditures. Nurses in acute care settings have a lack of knowledge about delirium, dementia, and depression. This lack of knowledge could have implication as necessary referrals to physicians is needed in order to ensure initiating of appropriate treatment. Continuing professional development is necessary to keep nurses abreast of the rapid changes in knowledge and technology needed to provide safe and high quality services. Providing an opportunity to participate in continuing professional development on this particular subject would go a long way to facilitate knowledge translation. As a result nurses will be equipped with the adequate knowledge and skills to meet the overall goal of providing quality care for older adults in different care settings.
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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 | 0.024 | 0.032 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.005 | 0.013 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.016 | 0.008 |
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".