Evidence map›Paper›PMID 29361958›Full record

Observational studyBMC medical education2018

Ethnic bias and clinical decision-making among New Zealand medical students: an observational study.

Ricci Harris, Donna Cormack, James Stanley, Elana Curtis, Rhys Jones, Cameron Lacey

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in BMC medical education, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
5.9field-weighted citation impact, top 4% of its field
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

11 citing papers in PubMed, 43 citations in OpenAlex.

  1. A Brief Online Implicit Bias Intervention for School Mental Health Clinicians.International journal of environmental research and public health · 2022
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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

6 authors at 2 institutions in 1 country.

Ricci HarrisTe Kupenga Hauora Māori, Faculty of Medical and Health Sciences, University of Auckland, Private Bag 92019, Auckland, 1142, New Zealand.
Donna CormackTe Kupenga Hauora Māori, Faculty of Medical and Health Sciences, University of Auckland, Private Bag 92019, Auckland, 1142, New Zealand.
James StanleyBiostatistics Group, Dean's Department, University of Otago Wellington, PO Box 7343, Wellington, 6242, New Zealand.
Elana CurtisTe Kupenga Hauora Māori, Faculty of Medical and Health Sciences, University of Auckland, Private Bag 92019, Auckland, 1142, New Zealand. e.curtis@auckland.ac.nz.
Rhys JonesTe Kupenga Hauora Māori, Faculty of Medical and Health Sciences, University of Auckland, Private Bag 92019, Auckland, 1142, New Zealand.
Cameron LaceyMāori/Indigenous Health Institute (MIHI), University of Otago Christchurch, PO Box 4345, Christchurch, 8140, New Zealand.
University of Auckland · NZUniversity of Otago · NZ

Funding

Health Research Council of New Zealand 09/643b
6 · The paper itself

Abstract

backgroundHealth professional racial/ethnic bias may impact on clinical decision-making and contribute to subsequent ethnic health inequities. However, limited research has been undertaken among medical students. This paper presents findings from the Bias and Decision-Making in Medicine (BDMM) study, which sought to examine ethnic bias (Māori (indigenous peoples) compared with New Zealand European) among medical students and associations with clinical decision-making.

methodsAll final year New Zealand (NZ) medical students in 2014 and 2015 (n = 888) were invited to participate in a cross-sectional online study. Key components included: two chronic disease vignettes (cardiovascular disease (CVD) and depression) with randomized patient ethnicity (Māori or NZ European) and questions on patient management; implicit bias measures (an ethnicity preference Implicit Association Test (IAT) and an ethnicity and compliant patient IAT); and, explicit ethnic bias questions. Associations between ethnic bias and clinical decision-making responses to vignettes were tested using linear regression.

resultsThree hundred and two students participated (34% response rate). Implicit and explicit ethnic bias favoring NZ Europeans was apparent among medical students. In the CVD vignette, no significant differences in clinical decision-making by patient ethnicity were observed. There were also no differential associations by patient ethnicity between any measures of ethnic bias (implicit or explicit) and patient management responses in the CVD vignette. In the depression vignette, some differences in the ranking of recommended treatment options were observed by patient ethnicity and explicit preference for NZ Europeans was associated with increased reporting that NZ European patients would benefit from treatment but not Māori (slope difference 0.34, 95% CI 0.08, 0.60; p = 0.011), although this was the only significant finding in these analyses.

conclusionsNZ medical students demonstrated ethnic bias, although overall this was not associated with clinical decision-making. This study both adds to the small body of literature internationally on racial/ethnic bias among medical students and provides relevant and important information for medical education on indigenous health and ethnic health inequities in New Zealand.

Indexed as

Clinical Decision-MakingEthnicityAttitude of Health PersonnelCardiovascular DiseasesCross-Sectional StudiesDepressionFemaleHealthcare DisparitiesHumansMaleNew ZealandPhysiciansRacismSocial ClassSocial DesirabilityStudents, MedicalBias and Decision-Making in Medicine (BDMM) studyClinical decision-makingImplicit association testMāoriMedical studentsNew ZealandRacial/ethnic biasVignettes

Identifiers

PMID29361958
PMCPMC5782368
OpenAlexW2797521412

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.