Coaching to develop leadership for healthcare managers: a mixed-method systematic review protocol
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.
Bibliographic record
Abstract
BACKGROUND: An increasing number of interventions have focused on leadership development for healthcare managers, among which coaching is a common strategy. The purpose of the present systematic review is to synthesize evidence on the effect of coaching in developing leadership of healthcare managers. METHODS AND ANALYSIS: A literature search will be conducted in six English databases (MEDLINE (Ovid), CINAHL, Embase, Cochrane library, Nursing & Allied Health Premium, and Scopus) and four Chinese databases (Wanfang, CNKI, SinoMed, and VIP) from inception to April 1st, 2022. The titles, abstracts, and full texts of the studies will be screened by two independent researchers to determine their eligibility. The RoB 2, ROBINS-I, CASP, and MMAT will be applied to assess the quality of randomized trials, non-randomized studies, qualitative studies, and mixed-method studies, respectively. We will then extract the study characteristics, participant characteristics, and study outcomes of the reviewed papers. The Aims, Ingredients, Mechanism, and Delivery framework will be used to extract the components of coaching strategies. For quantitative data, a meta-analysis will be performed if sufficient data are available; otherwise, we will conduct a narrative synthesis. Thematic synthesis methods will be used for qualitative data analysis. DISCUSSION: By conducting this systematic review, we expect to synthesize evidence regarding the components of coaching for leadership development among healthcare managers; the influence of coaching on leadership development among managers at the individual, unit-wide, or organizational level; and how managers view coaching as a leadership development strategy. TRIAL REGISTRATION: PROSPERO registration number: CRD42020194290 .
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.063 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it