Reaching out to those we teach about: a qualitative appreciative inquiry of older persons’ experience as mentors in a bachelor of nursing programme during the Covid-19 pandemic
Bibliographic record
Abstract
Background: This article describes the development and refinement of a component of a first-year nursing course called ‘Theoretical perspectives in nursing care: complexities in seniors care’. Initially developed in 2020 in response to the pandemic restrictions and guided by the philosophy of person- centredness and person-centred practice, a senior mentorship programme called ‘Engaging with your senior mentor in the community’ has become an important element of the broader theoretical course. Aim: To report on the experiences of older persons living in the community who volunteered to be mentors to first-year bachelor of nursing students, and explain how their experiences informed person-centred quality improvements for future courses. Methods: Appreciative inquiry principles guided the study. Qualitative descriptive design methods – online surveys and focus groups – were employed to evaluate the senior mentorship initiative. Thematic analysis was performed to identify themes that described what the experience of participating in the initiative was like from the perspective of the senior mentors themselves. Findings: Our analysis identified five themes: (a) sharing; (b) contributing; (c) listening; (d) self-reflecting; and (e) communicating expectations. Conclusion: Sharing wisdom informed by lived experience can be a rewarding part of ageing. Senior mentors believed they had contributed in a meaningful way to the student nurses’ learning. Implications for practice: This article reaffirms that older persons are keen to participate in education initiatives Insights from the senior mentors will inform educators in health and social sciences who want to incorporate the voices of older persons in their classroom and practice teaching Older persons should be considered potential partners who can help educators develop a culture of person-centredness to help students prepare to appreciate the older persons in their care
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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 | 0.036 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.019 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.004 | 0.014 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".