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Record W4385064446 · doi:10.1186/s12913-023-09811-y

Linking leadership development programs for physicians with organization-level outcomes: a realist review

2023· review· en· W4385064446 on OpenAlexaff
Maarten P. M. Debets, Iris Jansen, Kiki M. J. M. H. Lombarts, Wietske Kuijer‐Siebelink, Karen Kruijthof, Yvonne Steinert, Joost G. Daams, Milou Silkens

Bibliographic record

VenueBMC Health Services Research · 2023
Typereview
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsPsycINFOHealth informaticsContext (archaeology)Health administrationNursing researchOrganizational cultureQuality managementPublic relationsQuality (philosophy)MedicineLeadership developmentMEDLINEMedical educationKnowledge managementPsychologyNursingPublic healthBusinessComputer sciencePolitical scienceMarketingService (business)

Abstract

fetched live from OpenAlex

BACKGROUND: Hospitals invest in Leadership Development Programs (LDPs) for physicians, assuming they benefit the organization's performance. Researchers have listed the advantages of LDPs, but knowledge of how and why organization-level outcomes are achieved is missing. OBJECTIVE: To investigate how, why and under which circumstances LDPs for physicians can impact organization-level outcomes. METHODS: We conducted a realist review, following the RAMESES guidelines. Scientific articles and grey literature published between January 2010 and March 2021 evaluating a leadership intervention for physicians in the hospital setting were considered for inclusion. The following databases were searched: Medline, PsycInfo, ERIC, Web of Science, and Academic Search Premier. Based on the included documents, we developed a LDP middle-range program theory (MRPT) consisting of Context-Mechanism-Outcome configurations (CMOs) describing how specific contexts (C) trigger certain mechanisms (M) to generate organization-level outcomes (O). RESULTS: In total, 3904 titles and abstracts and, subsequently, 100 full-text documents were inspected; 38 documents with LDPs from multiple countries informed our MRPT. The MRPT includes five CMOs that describe how LDPs can impact the organization-level outcomes categories 'culture', 'quality improvement', and 'the leadership pipeline': 'Acquiring self-insight and people skills (CMO1)', 'Intentionally building professional networks (CMO2)', 'Supporting quality improvement projects (CMO3)', 'Tailored LDP content prepares physicians (CMO4)', and 'Valuing physician leaders and organizational commitment (CMO5)'. Culture was the outcome of CMO1 and CMO2, quality improvement of CMO2 and CMO3, and the leadership pipeline of CMO2, CMO4, and CMO5. These CMOs operated within an overarching context, the leadership ecosystem, that determined realizing and sustaining organization-level outcomes. CONCLUSIONS: LDPs benefit organization-level outcomes through multiple mechanisms. Creating the contexts to trigger these mechanisms depends on the resources invested in LDPs and adequately supporting physicians. LDP providers can use the presented MRPT to guide the development of LDPs when aiming for specific organization-level outcomes.

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.

How this classification was reachedexpand

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewlow
gptno category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewmedium
models agreeAgreement compares identical category sets and study designs across arms.

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)0.025
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.665
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0250.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.009
Science and technology studies0.0050.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.003

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 head0.917
GPT teacher head0.732
Teacher spread0.185 · 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

Classification

machine, unvalidated

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations17
Published2023
Admission routes1
Has abstractyes

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