Evidence map›Paper›PMID 34429084›Full record

SynthesisBMC medical education2021

Systematic review of specialist selection methods with implications for diversity in the medical workforce.

Andrew James Amos, Kyungmi Lee, Tarun Sen Gupta, Bunmi S Malau-Aduli

Abstract readSystematic Review
In one paragraph

Synthesis in BMC medical education, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Observational
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Andrew James AmosDirector of Training in Psychiatry for North Queensland, Queensland Health, Townsville, Australia. Andrew.Amos@jcu.edu.au.ORCID https://orcid.org/0000-0002-9145-0212
Kyungmi LeeCollege of Science and Engineering, James Cook University, Cairns, Australia.
Tarun Sen GuptaCollege of Medicine and Dentistry, James Cook University, Townsville, Australia.ORCID https://orcid.org/0000-0001-7698-1413
Bunmi S Malau-AduliCollege of Medicine and Dentistry, James Cook University, Townsville, Australia.ORCID https://orcid.org/0000-0001-6054-8498

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThere is growing concern that inequities in methods of selection into medical specialties reduce specialist cohort diversity, particularly where measures designed for another purpose are adapted for specialist selection, prioritising reliability over validity. This review examined how empirical measures affect the diversity of specialist selection. The goals were to summarise the groups for which evidence is available, evaluate evidence that measures prioritising reliability over validity contribute to under-representation, and identify novel measures or processes that address under-representation, in order to make recommendations on selection into medical specialties and research required to support diversity.

methodIn 2020-1, the authors implemented a comprehensive search strategy across 4 electronic databases (Medline, PsychINFO, Scopus, ERIC) covering years 2000-2020, supplemented with hand-search of key journals and reference lists from identified studies. Articles were screened using explicit inclusion and exclusion criteria designed to focus on empirical measures used in medical specialty selection decisions.

resultsThirty-five articles were included from 1344 retrieved from databases and hand-searches. In order of prevalence these papers addressed the under-representation of women (21/35), international medical graduates (10/35), and race/ethnicity (9/35). Apart from well-powered studies of selection into general practice training in the UK, the literature was exploratory, retrospective, and relied upon convenience samples with limited follow-up. There was preliminary evidence that bias in the measures used for selection into training might contribute to under-representation of some groups.

conclusionsThe review did not find convincing evidence that measures prioritising reliability drive under-representation of some groups in medical specialties, although this may be due to limited power analyses. In addition, the review did not identify novel specialist selection methods likely to improve diversity. Nevertheless, significant and divergent efforts are being made to promote the evolution of selection processes that draw on all the diverse qualities required for specialist practice serving diverse populations. More rigorous prospective research across different national frameworks will be needed to clarify whether eliminating or reducing the weighting of reliable pre-selection academic results in selection decisions will increase or decrease diversity, and whether drawing on a broader range of assessments can achieve both reliable and socially desirable outcomes.

Indexed as

SpecializationWorkforceFemaleHumansProspective StudiesReproducibility of ResultsRetrospective StudiesApplicationBiasDiversityEquityEthnicityGenderJusticeMatchingResidencySpecialist selection

Identifiers

PMID34429084
PMCPMC8385860

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.