Coaching to develop leadership of healthcare managers: a mixed-methods systematic review
Bibliographic record
Abstract
INTRODUCTION: Coaching is commonly used to facilitate leadership development among healthcare managers. However, there is limited knowledge of the components of coaching interventions and their impacts on healthcare managers' leadership development. This mixed-methods systematic review aimed to synthesize evidence of coaching to develop leadership among healthcare managers. METHODS: The authors conducted a mixed-methods systematic review using a convergent synthesis design where quantitative and qualitative evidence was collected and analyzed concurrently using a matrix synthesis method. They reviewed studies published in English or Chinese by searching databases including MEDLINE (Ovid), CINAHL, Embase, Cochrane Library, Nursing & Allied Health Premium, Scopus, Wanfang, CNKI, SinoMed, and VIP databases from their inception to August 10, 2023, and updated the search again on July 9, 2024. Articles were screened and assessed for eligibility. First, from eligible studies, the qualitative data were extracted to describe intervention components, the perceived impact of coaching, and participants' perceptions of being involved in coaching intervention. Second, quantitative data analysis was conducted to describe the impact of coaching interventions and the frequency of each theme evolved in the data. Third, qualitative and quantitative data were synthesized using the matrix synthesis method. RESULTS: A total of 13 studies were included in the analysis. Three qualitative studies were assessed as having 'no or few limitations', three case series studies were scored between five and eight out of 10 points, two quasi-experimental studies showed 'moderate' overall bias, and the five mixed-methods studies scored from 40 to 60% (out of 100%). For Objective 1, which covers the component of coaching (aims, ingredients, mechanism, and delivery), the typical aim of coaching interventions was to develop the leadership skills of middle management managers. The ingredients of coaching encompassed three distinct coaching categories and seven specific procedures. The mechanisms of most coaching interventions were based on theory and empirical evidence. The average delivery time was approximately four months. Overall, coaching positively impacts outcomes for managers, organizations, and staff (Objective 2). Perceptions of the participants toward coaching interventions were divided into six categories: barriers, facilitators, effective components, attitudes, satisfactory aspects, and suggestions for designing high-quality coaching interventions to improve leadership (Objective 3). CONCLUSIONS: The components of coaching interventions varied across different studies. The impact of coaching on leadership development was positive across three levels (manager, organization, and staff). Therefore, we recommend coaching as an intervention for healthcare managers aiming to enhance their leadership level. Future coaching interventions may achieve greater effectiveness if they are specifically aligned with the participants' perceptions identified in our study.
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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 | 0.061 | 0.144 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.011 |
| Bibliometrics | 0.020 | 0.016 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".