Nursing management and leadership approaches from the perspective of registered nurses in Portugal
Bibliographic record
Abstract
Background: The leadership role in nursing reflects the complexity and rapid transformations which take place in healthcare. The influences of this catalyst of change are important for nurses’ identity and professional development, as well as for evolving and innovating nursing practices.Objective: This study is part of a larger research project on doctoral Leadership in Nursing, aims to identify nurses’ perceptions regarding their similarities and differences compared to nurses in manager roles, in order to understand and recognise the influences and barriers to leadership in the nursing hierarchy.Methods: A descriptive cross-sectional study of a qualitative nature, involved the participation of 19 registered nurses (RNs), based on the Zavalloni Ego-Ecological Theory.Results: From the dimension of identification emerged two major themes - the vision of the profession and the competency skills required. The major theme of competency skills includes subthemes of relational, technical/scientific, leadership and management competencies. From the dimension of differentiation emerged two major themes - the vision of the profession and the competency skills. The major theme competency skills included two subthemes - the deficit of relational and management competency skills.Conclusions: Nurse-managers may choose to distance or influence nurses; influence can be achieved through not only a combination of leadership and management competencies but also on the nurse-managers’ evidence-based expertise and relational skills alongside a vision to support team unity in order to create a positive environment which encourages the nurses to be involved in high quality and innovative practices.Implications for nursing management: This study may help to understand the approaches undertaken by leaders in nursing and subsequently enhance their performance. It may also inform future leadership training for nurses.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".