Managerial leadership for research use in nursing and allied health care professions: a systematic review
Bibliographic record
Abstract
BACKGROUND: Leadership by point-of-care and senior managers is increasingly recognized as critical to the acceptance and use of research evidence in practice. The purpose of this systematic review was to identify the leadership behaviours of managers that are associated with research use by clinical staff in nursing and allied health professionals. METHODS: A mixed methods systematic review was performed. Eight electronic bibliographic databases were searched. Studies examining the association between leadership behaviours and nurses and allied health professionals' use of research were eligible for inclusion. Studies were excluded if leadership could not be clearly attributed to someone in a management position. Two reviewers independently screened abstracts, reviewed full-text articles, extracted data and performed quality assessments. Narrative synthesis was conducted. RESULTS: The search yielded 7019 unique titles and abstracts after duplicates were removed. Three hundred five full-text articles were reviewed, and 31 studies reported in 34 articles were included. Methods used were qualitative (n = 19), cross-sectional survey (n = 9), and mixed methods (n = 3). All studies included nurses, and six also included allied health professionals. Twelve leadership behaviours were extracted from the data for point-of-care managers and ten for senior managers. Findings indicated that managers performed a diverse range of leadership behaviours that encompassed change-oriented, relation-oriented and task-oriented behaviours. The most commonly described behavior was support for the change, which involved demonstrating conceptual and operational commitment to research-based practices. CONCLUSIONS: This systematic review adds to the growing body of evidence that indicates that manager-staff dyads are influential in translating research evidence into action. Findings also reveal that leadership for research use involves change and task-oriented behaviours that influence the environmental milieu and the organisational infrastructure that supports clinical care. While findings explain how managers enact leadership for research use, we now require robust methodological studies to determine which behaviours are effective in enabling research use with nurses and allied health professionals for high-quality evidence-based care. TRIAL REGISTRATION: PROSPERO CRD42014007660.
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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 | 0.043 | 0.156 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.021 | 0.020 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".