Exploring Nurses’ and Nursing Students' Self- Efficacy and Mindsets in Caring for the Elderly in Canada.
Bibliographic record
Abstract
Background. The elderly population is considered the most significant health care consumers, and caring for them is among the most challenging issue of public health and social care systems. Providing nursing students with the required skills and knowledge related to the senior population's care will promote their self-efficacy and mindsets. Aim. This study explores nurses' and nursing students' self-efficacy and mindsets in caring for the elderly, examines the nursing curriculum's contributions to nurses' self-efficacy and mindsets, and provides suggestions for reconfiguring the nursing curriculum for comprehensive geriatric nursing care. Methods. A mixed-method research design was utilized, and quantitative and qualitative data were collected from 90 nurses and nursing students through an online questionnaire. Data were analyzed via SPSS and NVivo 12 software programs. Results. The results revealed that most nurses had an above-average level of self-efficacy toward caring for geriatric patients. A statistically significant positive correlation between self-efficacy and nurses' attitudes, knowledge level, and years of experience was revealed. This study demonstrated the positive impact of the Canadian nursing curriculum on nurses' self-efficacy. Conclusion. The current study recommends following Bandura's self-efficacy theory's fundamental beliefs such as role modeling, verbal encouragement, and mastery experience to enhance the nursing curriculum by incorporating them into the teaching and learning strategies to improve nursing students' performance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".