Developing the Next Generation of Nursing Disciplinary Leaders in Higher Education: Protocol for a Sequential Mixed Methods Study
Bibliographic record
Abstract
BACKGROUND: Leading nurse education and research in the higher education (HE) sector has become increasingly challenging over the last decade with many universities in Australia and New Zealand having undergone academic restructuring. The future of HE faces many challenges including recruitment of suitably qualified staff to lead teaching and research and advance professional disciplines. Increasing cultural diversity of the Nursing workforce and the communities' nurses serve, and the identification of cultural attributes in the context of racial inequities exposed by the pandemic and the climate emergency suggest different forms of leadership may be required in the future by those leading nurse education in the HE sector. Currently, there is a dearth of research evidence that identifies the qualities, behaviors, and characteristics (collectively identified as core attributes) required by nurse academic leaders. OBJECTIVE: This research aims to identify an evidenced based set of core attributes that are required to lead the discipline of Nursing in the Australian and New Zealand HE sectors. METHODS: This research is using a 2-phase sequential mixed methods design incorporating a scoping review; and Delphi technique. In phase 1, a scoping review will be undertaken to identify the qualities, behaviors, and characteristics that can influence the evolution of the next generation of academic nurse leaders. A set of draft statements and questions will be prepared based on analysis of findings from the review. Phase 2 uses Delphi technique consisting of e-survey rounds with experts in leading nursing faculties in Australia and New Zealand. An Expert Advisory Group will consider the initial set of draft statements and questions from phase 1. Consistent with Delphi technique, a series of "rounds" will then occur using an e-survey method. Established leaders (Professors and Associate Professors who are members of the Council of Deans Australia and New Zealand) will rate their level of agreement to statements on the qualities, behaviors, and characteristics required to lead the discipline of nursing in the HE sector in Australia and New Zealand. RESULTS: The findings of the scoping review will identify what is currently known about the qualities, behaviors, and characteristics of academic nurse leaders. Quantitative and qualitative results from the Delphi study will initially be reported in separate manuscripts for publication. It is projected that a final paper will be prepared from aggregated research data and outline how the findings can inform the preparation of future academic nurse leaders. CONCLUSIONS: The generation of an evidenced-based set of core attributes will serve to inform the next generation of academic nurse leaders including informing recruitment processes and postgraduate nurse leadership programs. It is anticipated that the data sets and findings will be transferrable to other disciplines within HE to aid in future-proofing discipline-based expertise and leadership in the context of academic restructure. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/40677.
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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 | 0.111 | 0.092 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.076 | 0.016 |
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".