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Record W4403019480 · doi:10.1186/s12909-024-06081-y

Coaching to develop leadership of healthcare managers: a mixed-methods systematic review

2024· review· en· W4403019480 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBMC Medical Education · 2024
Typereview
Languageen
FieldPsychology
TopicCoaching Methods and Impact
Canadian institutionsUniversity of Ottawa
FundersScience and Technology Program of Hunan ProvinceOpetushallitusTurun YliopistoCentral South University
KeywordsCoachingMedical educationHealth carePsychologyMedicineNursingPolitical science

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.017
metaresearch head score (Gemma)0.046
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.469
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.046
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.284
GPT teacher head0.583
Teacher spread0.299 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it