Leading on the frontlines with passion and persistence: a necessary condition for <scp>B</scp> reastfeeding <scp>B</scp> est <scp>P</scp> ractice <scp>G</scp> uideline uptake
Bibliographic record
Abstract
AIMS AND OBJECTIVES: The research question explored was what are the processes and strategies used by frontline leaders to support the uptake of the Breastfeeding Best Practice Guideline by nurses in maternity care practice settings? BACKGROUND: Best Practice Guidelines have been shown to enhance client care and outcomes. Leadership is known to have a key role in moving Best Practice Guidelines into nursing practice yet how this happens is poorly understood. This insight is needed to consistently and efficiently facilitate Best Practice Guideline uptake into clinical practice. DESIGN: Constructivist grounded theory was used to explore the social processes and strategies involved in facilitating Best Practice Guideline uptake. METHODS: Purposive, criterion-based, theoretical and negative case sampling were used recruiting 58 health professionals and 54 clients. Triangulation and constant comparison of data sources and types (interviews, documents and field notes) were used for analysis and rigour. RESULTS: Passionate, persistent, respected frontline leaders using tailored, multifaceted strategies aimed at three groups of nurse adopters effectively support the uptake of the Breastfeeding Best Practice Guideline in nursing practice. Successful uptake strategies used by frontline leaders that are new or underdeveloped in the previous literature are presented. CONCLUSIONS: The study findings illuminated multidimensional, tailored strategies that frontline leaders use to facilitate the uptake of Best Practice Guidelines. Attention to individual attitudes and beliefs, as well as organisational, interorganisational and interprofessional partnerships are vital to uptake. Organisations that aspire to foster Best Practice Guideline uptake must invest in frontline leaders to 'make it happen' and sustain Best Practice Guideline uptake in practice. RELEVANCE TO CLINICAL PRACTICE: Understanding how frontline leaders facilitate Best Practice Guideline uptake is essential to selecting, educating and supporting them to foster desired practice changes. Strategies are explicated that frontline leaders can adopt and tailor to their own practice contexts.
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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 | 0.005 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".