Development and Pilot testing of a Leadership Module to Support Quality Improvement Teams in Nursing Homes
Bibliographic record
Abstract
ABSTRACT Background Leadership is a critical lever for supporting implementation of practice change ideas intended to improve care. We need evidence-based leadership programs to help front-line providers meaningfully implement practice change in complex care settings. Part of the SHIFT intervention, this paper describes and pilot tests a leadership program module (LeaderSHIFT) that provides training and implementation coaching to front-line leaders, as one of several integrated facilitated supports designed to help front-line care teams meaningfully enact practice change. Methods The LeaderSHIFT program module was developed based on empirical work, relevant facilitation and transformational leadership theories, and principles of stakeholder co-design and feasible engagement. A pilot implementation study was conducted that examined several of Proctor’s (2011) implementation outcomes. Results LeaderSHIFT includes four interactive workshops plus two one-on-one coaching sessions designed to develop capacity in four areas of implementation leadership: (1) Self-awareness, (2) Motivate and inspire, (3) Facilitate learning capacity, and (4 ) Support ‘team-oriented processes’. Pilot results suggest it can be successfully implemented (it was acceptable, adopted, appropriate, feasible). Fidelity (LeaderSHIFT role enactment) varied across pilot teams. Conclusions With a strong theoretical and empirical base, LeaderSHIFT highlights important, often overlooked, relational and socio-cultural aspects of successful implementation leadership. As such, the LeaderSHIFT program module has the potential to improve implementation of practice change interventions in nursing homes and other institutional care settings. Trial registration Registered at ClinicalTrials.gov (ID NCT03426072 ) on July 18, 2022. KEY MESSAGES REGARDING FEASIBILITY What uncertainties existed regarding the feasibility? While leadership is known to be a critical lever for implementation of evidence-informed practice change, there are few leadership training programs that have a relational focus designed to support broader team-based practice change initiatives; and uncertainty remains regarding implementability (feasibility, acceptability, appropriateness, fidelity) of this type of leadership module in complex care settings What are the key feasibility findings? The LeaderSHIFT module performed well on several key implementation outcomes (module acceptability, feasibility, appropriateness). Fidelity to implementation leadership was successful for managers who were able to enact relational aspects of the role. What are the implications of the feasibility findings for the design of the main study? Findings confirmed the value of one-to-one coaching for enhancing leaders’ relational competencies and prompted training overlap for senior and front-line leaders to ensure there is a common understanding of respective roles in intervention implementation.
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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 | 0.011 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".