Exploring Shared Implementation Leadership of Point of Care Nursing Leadership Teams on Inpatient Hospital Units: Protocol for a Collective Case Study
Bibliographic record
Abstract
BACKGROUND: Nursing leadership teams at the point of care (POC), consisting of both formal and informal leaders, are regularly called upon to support the implementation of evidence-based practices (EBPs) in hospital units. However, current conceptualizations of effective leadership for successful implementation typically focus on the behaviors of individual leaders in managerial roles. Little is known about how multiple nursing leaders in formal and informal roles share implementation leadership (IL), representing an important knowledge gap. OBJECTIVE: This study aims to explore shared IL among formal and informal nursing leaders in inpatient hospital units. The central research question is as follows: How is IL shared among members of POC nursing leadership teams on inpatient hospital units? The subquestions are as follows: (1) What IL behaviors are enacted and shared by formal and informal leaders? (2) What social processes enable shared IL by formal and informal leaders? and (3) What factors influence shared IL in nursing leadership teams? METHODS: We will use a collective case study approach to describe and generate an in-depth understanding of shared IL in nursing. We will select nursing leadership teams on 2 inpatient hospital units that have successfully implemented an EBP as instrumental cases. We will construct data through focus groups and individual interviews with key informants (leaders, unit staff, and senior nurse leaders), review of organizational documents, and researcher-generated field notes. We have developed a conceptual framework of shared IL to guide data analysis, which describes effective IL behaviors, formal and informal nursing leaders' roles at the POC, and social processes generating shared leadership and influencing contextual factors. We will use the Framework Method to systematically generate data matrices from deductive and inductive thematic analysis of each case. We will then generate assertions about shared IL following a cross-case analysis. RESULTS: The study protocol received research ethics approval (2022-8408) on February 24, 2022. Data collection began in June 2022, and we have recruited 2 inpatient hospital units and 25 participants. Data collection was completed in December 2023, and data analysis is ongoing. We anticipate findings to be published in a peer-reviewed journal by late 2024. CONCLUSIONS: The anticipated results will shed light on how multiple and diverse members of the POC nursing leadership team enact and share IL. This study addresses calls to advance knowledge in promoting effective implementation of EBPs to ensure high-quality health care delivery by further developing the concept of shared IL in a nursing context. We will identify strategies to strengthen shared IL in nursing leadership teams at the POC, informing future intervention studies. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/54681.
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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 | 0.076 | 0.075 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.026 | 0.005 |
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".