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Record W3194482249 · doi:10.1016/j.eclinm.2021.101108

Building an evidence base on organisational interventions to advance women in healthcare leadership

2021· article· en· W3194482249 on OpenAlexaboutno aff
Pavel V. Ovseiko, Evanthia Kalpazidou Schmidt

Bibliographic record

VenueEClinicalMedicine · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicDiversity and Career in Medicine
Canadian institutionsnot available
FundersNIHR Oxford Biomedical Research CentreNorges ForskningsrådUniversity of OxfordHorizon 2020National Institute for Health and Care Research
KeywordsPsychological interventionHealth careMedicineSystematic reviewHospitalityScopusPublic relationsGovernment (linguistics)Medical educationMEDLINENursingPolitical science

Abstract

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While women remain underrepresented in healthcare leadership, an evidence base on organisational interventions that can help to accelerate their advancement to leadership positions is limited and scattered across different sectors. In an article published in EClinicalMedicine, Helena Teede and colleagues contribute to building such an evidence base by identifying and synthesising organisational interventions that have been shown to measurably advance women in leadership [[1]Mousa M. Boyle J. Skouteris H. et al.Advancing women in healthcare leadership: a systematic review and meta-synthesis of multi-sector evidence on organisational interventions.EClinicalMedicine. 2021; 39101084https://doi.org/10.1016/j.eclinm.2021.101084Summary Full Text Full Text PDF PubMed Scopus (5) Google Scholar]. Teede and colleagues systematically searched the relevant multi-disciplinary databases and identified 91 eligible studies across academia, health, government, sports, hospitality, finance, and information technology sectors, which were published in English in peer-reviewed journals between January 2000 and March 2021. Amongst these studies, there were more studies from academic medicine and healthcare than from any other sector. The authors narratively synthesised the findings from these studies using a meta-synthesis approach with a view to generating insights on the processes that enable women to advance in healthcare leadership. The multi-sector scope of the review and its meta-synthesis approach make a unique and valuable addition to other recent reviews on gender equity in healthcare [[2]Laver K.E. Prichard I.J. Cations M. et al.A systematic review of interventions to support the careers of women in academic medicine and other disciplines.BMJ Open. 2018; 8e020380https://doi.org/10.1136/bmjopen-2017-020380Crossref PubMed Scopus (50) Google Scholar,[3]Tricco A.C. Bourgeault I. Moore A. et al.Advancing gender equity in medicine.Can Med Assoc J. 2021; 193: E244-EE50https://doi.org/10.1503/cmaj.200951Crossref Scopus (11) Google Scholar]. The results of the review have the potential to inform organisational strategies, policies, and practices. Namely, the results indicate that organisational leadership, commitment, and accountability are associated with measurable improvements in women's advancement. The results identify five categories of potentially effective organisational interventions: (i) organisational processes, (ii) awareness and engagement, (iii) mentoring and networking, (iv) leadership development, and (v) support tools. Importantly, the authors acknowledge the shortcomings of isolated interventions and argue for a multifaceted approach including a range of interventions at multiple organisational levels. Moreover, the article poses important implications for the development of the field of diversity interventions. One important implication is the quality of evidence on diversity interventions. The article shows that currently there is a paucity of robust quantitative studies, a varied body of qualitative studies, and a lack of standardised outcome measures across both quantitative and qualitative studies. This is in line with previous research showing that even in the case of mentoring, which is arguably the most common diversity and career advancement intervention, it is impossible to ascertain its effectiveness in reducing gender inequalities due to a lack of standardised approaches and weak evaluation designs [[4]House A. Dracup N. Burkinshaw P. et al.Mentoring as an intervention to promote gender equality in academic medicine: a systematic review.BMJ Open. 2021; 11e040355https://doi.org/10.1136/bmjopen-2020-040355Crossref PubMed Scopus (5) Google Scholar]. Given that research funders, professional associations, and research organisations across the globe commit significant resources and efforts to diversity interventions, there is a need to develop standardised and more rigorous approaches to designing and evaluating diversity interventions. For example, government funding agencies and professional associations in the United Kingdom, Ireland, Australia, the United States, and Canada have been instrumental in the wide-spread adoption by higher education and research institutions of gender equality action plans based on the standardised Athena Swan framework [[5]Ovseiko P.V. Taylor M. Gilligan R.E. et al.Effect of Athena SWAN funding incentives on women’s research leadership.BMJ. 2020; 371: m3975https://doi.org/10.1136/bmj.m3975Crossref PubMed Scopus (9) Google Scholar]. A new European gender equality strategy has made provisions for the European flagship research funding programme to require applicants to have in place gender equality action plans [[6]Kalpazidou Schmidt E. Ovseiko P.V. Link Horizon Europe funding to real steps to gender equality.Nature. 2020; 584: 525https://doi.org/10.1038/d41586-020-02430-1Crossref PubMed Scopus (5) Google Scholar]. The Australian Academy of Science has identified establishing a consistent national evaluation framework across all gender equity initiatives in science, technology, engineering and mathematics as one of the major strategic opportunities of the current decade [[7]Australian Academy of ScienceWomen in STEM decadal plan. Australian Academy of Science, 2019https://www.science.org.au/womeninSTEMplanGoogle Scholar]. Another important implication for the development of the field of diversity interventions posed by the article is the complexity of organisational interventions, which requires continuously adapting interventions to the local contexts and constantly emerging conditions [[8]Kalpazidou Schmidt E. Ovseiko P.V. Henderson L.R. et al.Understanding the Athena SWAN award scheme for gender equality as a complex social intervention in a complex system: analysis of Silver award action plans in a comparative European perspective.Health Res Policy Syst. 2020; 18https://doi.org/10.1186/s12961-020-0527-xCrossref PubMed Scopus (26) Google Scholar,[9]Kalpazidou Schmidt E. Ovseiko P.V. Acknowledging complexity in evaluation of gender equality interventions.EClinicalMedicine. 2020; 28https://doi.org/10.1016/j.eclinm.2020.100623Summary Full Text Full Text PDF PubMed Scopus (1) Google Scholar]. It follows that the effectiveness of interventions will also depend on the capabilities of the local staff in adapting and implementing interventions taking into account their local contexts and emerging conditions. As such, in parallel with standardising and strengthening the design and evaluation of diversity interventions, there is a need to develop implementation science approaches and tools to support the effective implementation of diversity interventions. Yet another important implication for the development of the field of diversity interventions posed by the article is the salience of sector and organisational cultural factors. The authors rightly point out that there is a need for future research to gain greater insight into organisational cultures in the strongly hierarchical healthcare sector. While the hierarchical cultures in the health sector can present barriers to women's career advancement, they can also help to ensure the uptake and effective implementation of gender equity interventions when healthcare leaders commit themselves to advancing gender equity [[5]Ovseiko P.V. Taylor M. Gilligan R.E. et al.Effect of Athena SWAN funding incentives on women’s research leadership.BMJ. 2020; 371: m3975https://doi.org/10.1136/bmj.m3975Crossref PubMed Scopus (9) Google Scholar,[10]Ovseiko P.V. Pololi L.H. Edmunds L.D. et al.Creating a more supportive and inclusive university culture: a mixed-methods interdisciplinary comparative analysis of medical and social sciences at the University of Oxford.Interdiscip. Sci Rev. 2019; 44: 166-191https://doi.org/10.1080/03080188.2019.1603880Crossref Scopus (20) Google Scholar]. The fact that the current review includes more studies from academic medicine and healthcare than from any other sector suggests that the healthcare sector is leading multi-sector efforts in evidence-based gender equality interventions. The evidence synthesis presented in the current article makes a valuable contribution to help accelerate such efforts further. PVO declares an advisory role with the Advance HE Athena Swan Governance Committee. EKS declares no conflicts of interest. PVO is supported by the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre, Grant BRC-1215–20008 to the Oxford University Hospitals NHS Foundation Trust and the University of Oxford, and by the European Union's Horizon 2020 research and innovation programme under grant agreement No. 872396 . EKS is supported by the European Union´s Horizon 2020 research and innovation programme under Grant agreements Nos. 872146, 101006386 , and by the Norwegian Research Council through the Gender, Citizenship and Academic Power (GAP) project. Advancing women in healthcare leadership: A systematic review and meta-synthesis of multi-sector evidence on organisational interventionsThis review provides an evidence base on organisational interventions for advancing women in leadership across diverse settings, with lessons for healthcare. It transcends the focus on the individual to target organisational change, capturing measurable change across intervention categories. This work directly informs a national initiative with international links, to enable women to achieve their career goals in healthcare and moves beyond the focus on barriers to solutions. Full-Text PDF Open Access

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

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)0.005
metaresearch head score (Gemma)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.346
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.343
GPT teacher head0.488
Teacher spread0.145 · 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

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations3
Published2021
Admission routes1
Has abstractyes

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