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Development and testing of study tools and methods to examine ethnic bias and clinical decision-making among medical students in New Zealand: The Bias and Decision-Making in Medicine (BDMM) study

Overview of attention for article published in BMC Medical Education, July 2016
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  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

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Title
Development and testing of study tools and methods to examine ethnic bias and clinical decision-making among medical students in New Zealand: The Bias and Decision-Making in Medicine (BDMM) study
Published in
BMC Medical Education, July 2016
DOI 10.1186/s12909-016-0701-6
Pubmed ID
Authors

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

Abstract

Health provider racial/ethnic bias and its relationship to clinical decision-making is an emerging area of research focus in understanding and addressing ethnic health inequities. Examining potential racial/ethnic bias among medical students may provide important information to inform medical education and training. This paper describes the development, pretesting and piloting of study content, tools and processes for an online study of racial/ethnic bias (comparing Māori and New Zealand European) and clinical decision-making among final year medical students in New Zealand (NZ). The study was developed, pretested and piloted using a staged process (eight stages within five phases). Phase 1 included three stages: 1) scoping and conceptual framework development; 2) literature review and identification of potential measures and items; and, 3) development and adaptation of study content. Three main components were identified to assess different aspects of racial/ethnic bias: (1) implicit racial/ethnic bias using NZ-specific Implicit Association Tests (IATs); (2) explicit racial/ethnic bias using direct questions; and, (3) clinical decision-making, using chronic disease vignettes. Phase 2 (stage 4) comprised expert review and refinement. Formal pretesting (Phase 3) included construct testing using sorting and rating tasks (stage 5) and cognitive interviewing (stage 6). Phase 4 (stage 7) involved content revision and building of the web-based study, followed by pilot testing in Phase 5 (stage 8). Materials identified for potential inclusion performed well in construct testing among six participants. This assisted in the prioritisation and selection of measures that worked best in the New Zealand context and aligned with constructs of interest. Findings from the cognitive interviewing (nine participants) on the clarity, meaning, and acceptability of measures led to changes in the final wording of items and ordering of questions. Piloting (18 participants) confirmed the overall functionality of the web-based questionnaire, with a few minor revisions made to the final study. Robust processes are required in the development of study content to assess racial/ethnic bias in order to optimise the validity of specific measures, ensure acceptability and minimise potential problems. This paper has utility for other researchers in this area by informing potential development approaches and identifying possible measurement tools.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 109 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 109 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 16 15%
Student > Master 15 14%
Student > Ph. D. Student 9 8%
Student > Bachelor 8 7%
Student > Doctoral Student 8 7%
Other 21 19%
Unknown 32 29%
Readers by discipline Count As %
Medicine and Dentistry 20 18%
Social Sciences 17 16%
Nursing and Health Professions 14 13%
Psychology 11 10%
Agricultural and Biological Sciences 1 <1%
Other 8 7%
Unknown 38 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 September 2016.
All research outputs
#6,214,793
of 24,751,485 outputs
Outputs from BMC Medical Education
#1,012
of 3,816 outputs
Outputs of similar age
#97,778
of 362,096 outputs
Outputs of similar age from BMC Medical Education
#17
of 66 outputs
Altmetric has tracked 24,751,485 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 3,816 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.4. This one has gotten more attention than average, scoring higher than 73% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 362,096 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.
We're also able to compare this research output to 66 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.