Developing Leadership in Managers to Facilitate the Implementation of National Guideline Recommendations: A Process Evaluation of Feasibility and Usefulness
Bibliographic record
Abstract
BACKGROUND: Previous research supports the claim that managers are vital players in the implementation of clinical practice guidelines (CPGs), yet little is known about interventions aiming to develop managers' leadership in facilitating implementation. In this pilot study, process evaluation was employed to study the feasibility and usefulness of a leadership intervention by exploring the intervention's potential to support managers in the implementation of national guideline recommendations for stroke care in outpatient rehabilitation. METHODS: Eleven senior and frontline managers from five outpatient stroke rehabilitation centers participated in a four-month leadership intervention that included workshops, seminars, and teleconferences. The focus was on developing knowledge and skills to enhance the implementation of CPG recommendations, with a particular focus on leadership behaviors. Each dyad of managers was assigned to develop a leadership plan with specific goals and leadership behaviors for implementing three rehabilitation recommendations. Feasibility and usefulness were explored through observations and interviews with the managers and staff members prior to the intervention, and then one month and one year after the intervention. RESULTS: Managers considered the intervention beneficial, particularly the participation of both senior and frontline managers and the focus on leadership knowledge and skills for implementing CPG recommendations. All the managers developed a leadership plan, but only two units identified goals specific to implementing the three stroke rehabilitation recommendations. Of these, only one identified leadership behaviors that support implementation. CONCLUSION: Managers found that the intervention was delivered in a feasible way and appreciated the focus on leadership to facilitate implementation. However, the intervention appeared to have limited impact on managers' behaviors or clinical practice at the units. Future interventions directed towards managers should have a stronger focus on developing leadership skills and behaviors to tailor implementation plans and support implementation of CPG recommendations.
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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 | 0.121 | 0.127 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".