Experiences of Irish Mentors and Mentees Engaged in a National Nursing and Midwifery Mentorship Programme: Mixed Methods Study With a Qualitative Focus on Mentors' Views
Bibliographic record
Abstract
AIM: To gain an understanding of the experiences of mentors and mentees engaging in a national mentoring programme within nursing and midwifery in Ireland. DESIGN: A two-phased convergent parallel mixed methods study was undertaken. METHODS: The first phase was a quantitative non-experimental descriptive study using an online survey with mentors (n = 12) and mentees (n = 6). The second phase was a qualitative descriptive study and involved focus group discussions with mentors (n = 5). No mentees took part in the focus group discussions. There was a disproportionate representation of mentors versus mentees in the total sample across both phases of this study. Data were collected between December 2023 and April 2024. RESULTS: Mentorship has a positive impact on professional growth, job satisfaction and career development for both mentors and mentees in nursing and midwifery professions. Significant challenges to effective nursing and midwifery mentorship include time constraints, irregular work patterns and a need for additional managerial and structural support. Areas identified for improvement in programme implementation include clearly defined roles, dedicated time and space for mentorship meetings and tailored support systems to address cultural diversity. CONCLUSION: This study highlights the significant benefits of a national formal mentorship programme; however, substantial barriers continue to underscore the need for strategic improvements. Addressing these challenges through clearer role definitions, dedicated protected mentorship time and culturally responsive support systems may enhance mentorship programme effectiveness and ensure long-term sustainability. PATIENT OR PUBLIC CONTRIBUTION: None.
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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 | 0.013 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| 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".