An explanatory sequential mixed method study of nursing students’ self-efficacy in caring for older adults in Ghana
Bibliographic record
Abstract
BACKGROUND: There is considerable evidence indicating that nursing students demonstrate inadequate knowledge and negative attitudes toward working with older adults. This suggests nursing student's unpreparedness to provide care for the expanding older adult population. Feelings of unpreparedness can negatively impact their motivation and confidence. However, limited evidence exists about how nursing students' knowledge and attitudes influence their self-efficacy in caring for older adults. Knowing this can help to identify gaps and opportunities to facilitate nursing students' confidence in caring for older adults in acute care settings. AIM: To examine nursing students' knowledge, attitudes, and self-efficacy and how these variables impact nursing student self-efficacy in caring for older adults in acute care settings in Ghana. METHODS: We employed explanatory sequential mixed method approach. In Phase I, we used a cross-sectional design and collected quantitative data about students' knowledge, attitudes, and self-efficacy. Data were collected from 170 second and third-year nursing students between December 2019--March 2020. We analyzed the data using descriptive and multiple-variable linear regression. Survey results informed the selection of students for Phase II based on their scores. In Phase II, 17 nursing students were purposively selected for semi-structured interviews between November and December 2020. Interviews were transcribed and analyzed using thematic analysis. Both results were integrated and presented. RESULTS: Students' mean age was 21 years (SD = 3.73). Just over half were female (54%). The majority had lived with/were currently living with older adults (83.0%). Many had low knowledge scores (71%) and a majority had positive attitudes (91%) and high self-efficacy scores (97%). Nursing students' ages and attitudes were significantly positively associated with their self-efficacy. There was no significant association between students' gerontology knowledge and self-efficacy. Qualitative findings showed that low knowledge scores were due to limited attention to gerontology education in the curriculum and heavy course load. Sociocultural norms in caring for older adults influenced students' positive attitudes. This facilitated students' interactions with older adults and increased their confidence. Higher self-efficacy scores were associated with the impact of the general nursing program, students' perceived familiarity with the needs of older adults and routine procedural knowledge. Younger students perceived that their age and competencies were questioned by older adults, impacting their self-efficacy. Both datasets converged at integration. CONCLUSION: It is imperative to enhance students' knowledge and leverage their self-efficacy to advance gerontological nursing education and practice in Ghana.
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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 | 0.010 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".