Undergraduate Nursing Students' Knowledge of and Attitudes Toward Aging: Comparison of Context-Based Learning and a Traditional Program
Bibliographic record
Abstract
The purpose of this study was to investigate nursing students' knowledge of and attitudes toward older adults in the first and fourth years of a baccalaureate program, following the introduction of a context-based learning (CBL) curriculum, and to compare the fourth-year CBL student findings to those of fourth-year students in the final year of the traditional, lecture-based baccalaureate program. The Facts on Aging Questionnaire was used to assess knowledge, and the Aging Semantic Differential was used to assess attitudes toward aging related to societal influences. Although there were differences in knowledge and attitudes between fourth-year CBL and fourth-year traditional students, the differences were not significant. These findings support earlier work that an integrated curriculum may not significantly improve knowledge of age-related changes nor positively influence attitudes that are already positive. The Reactions to Ageing Questionnaire was used to examine students' attitudes toward personal aging. There was a significant positive increase in CBL students' attitudes toward personal aging from the first to fourth years of the program. This suggests that CBL learning fosters an inner maturity toward personal aging.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".