Nursing students’ knowledge about Alzheimer’s disease
Bibliographic record
Abstract
Objective: Every 66 seconds a U.S. resident develops Alzheimer’s disease (AD). Future nurses will be caring for the rapidly escalating number of adults turning 65, yet information regarding nursing students’ knowledge about the age-related disease of Alzheimer’s is limited. The purpose of this study was to examine 102 Florida baccalaureate nursing students’ basic and advanced AD knowledge.Methods: A descriptive design using two AD knowledge measures and analysis using paired samples t-test were employed.Results: Although the setting was a region of the U.S. with the highest percentage of older adults, knowledge deficits regarding age-related Alzheimer’s disease were striking. Students’ basic knowledge was significantly higher than their advanced AD knowledge (t(101) = 2.28, p = .027). Only 31% of students identified that high cholesterol may increase risk. Just 20% of students correctly answered that exercise does not prevent AD. About 25% correctly responded that the average life expectancy after the onset of AD is 6-12 years. Only 2% of nursing students correctly identified that persons with AD experience stress from disease-related symptoms. Overall, less than 50% of students correctly answered any item on the measure designed for use among health care providers.Conclusions: To better prepare nursing students to care for the increasing numbers of older adults facing risk of AD, updated curricula targeting dementia-related illnesses are essential. Information is offered regarding current state of the science resources of benefit to faculty, students, and practicing nurses, such as experiential learning and Hartford Institute of Geriatric Nursing collaborative programs.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".