Can education change attitudes toward aging? A quasi-experimental design with a comparison group
Bibliographic record
Abstract
Background : Widespread negative attitudes toward aging in the U.S. are obstacles to training care providers and providing high quality care. Studies identifying educational effects on attitudes toward older people are still inconclusive. Objective: To examine the impact of learning experiences on university student attitudes toward older people. Methods : Design: A quasi-experimental design with a comparison group study. A total of 147 students registered in nursing and non-nursing programs completed three instruments measuring attitudes toward aging at three month intervals. All nursing students in the study were undertaking gerontology nursing course. Results : All participants expressed more positive attitudes in direct measures than indirect measures. Nursing students taking this gerontology course had significantly lower negative attitudes and negative feelings toward older adults, lower anti-age bias, and improvement in pro-age bias over time as compared to non-nursing students. Conclusions : The findings suggest that: 1) improved knowledge and clinical experience of aging reduce negative attitudes and are fundamental steps in developing positive attitudes for caring for older adults; and 2) comparative research using multiple measures provides a better understanding of attitudes toward older people.
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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 | 0.011 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 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".