Repository logo
  • Log In
    Log in via Symplectic to deposit your publication(s).
Repository logo
  • Communities & Collections
  • Research Outputs
  • Statistics
  • Log In
    Log in via Symplectic to deposit your publication(s).
  1. Home
  2. Faculty of Medicine
  3. Faculty of Medicine
  4. Measuring the bias against low-income country research: an Implicit Association Test
 
  • Details
Measuring the bias against low-income country research: an Implicit Association Test
File(s)
s12992-017-0304-y.pdf (422.32 KB)
Published version
Author(s)
Harris, MJ
macinko, J
jimenez, G
mullachery, P
Type
Journal Article
Abstract
Background
With an increasing array of innovations and research emerging from low-income countries there is a growing recognition that even high-income countries could learn from these contexts. It is well known that the source of a product influences perception of that product, but little research has examined whether this applies also in evidence-based medicine and decision-making. In order to examine likely barriers to learning from low-income countries, this study uses established methods in cognitive psychology to explore whether healthcare professionals and researchers implicitly associate good research with rich countries more so than with poor countries.

Methods
Computer-based Implicit Association Test (IAT) distributed to healthcare professionals and researchers. Stimuli representing Rich Countries were chosen from OECD members in the top ten (>$36,000 per capita) World Bank rankings and Poor Countries were chosen from the bottom thirty (<$1000 per capita) countries by GDP per capita, in both cases giving attention to regional representation. Stimuli representing Research were descriptors of the motivation (objective/biased), value (useful/worthless), clarity (precise/vague), process (transparent/dishonest), and trustworthiness (credible/unreliable) of research. IAT results are presented as a Cohen’s d statistic. Quantile regression was used to assess the contribution of covariates (e.g. age, sex, country of origin) to different values of IAT responses that correspond to different levels of implicit bias. Poisson regression was used to model dichotomized responses to the explicit bias item.

Results
Three hundred twenty one tests were completed in a four-week period between March and April 2015. The mean Implicit Association Test result (a standardized mean relative latency between congruent and non-congruent categories) for the sample was 0.57 (95% CI 0.52 to 0.61) indicating that on average our sample exhibited moderately strong implicit associations between Rich Countries and Good Research. People over 40 years of age were less likely to exhibit pro-poor implicit associations, and being a peer reviewer contributes to a more pro-poor association.

Conclusions
The majority of our participants associate Good Research with Rich Countries, compared to Poor Countries. Implicit associations such as these might disfavor research from poor countries in research evaluation, evidence-based medicine and diffusion of innovations.
Date Issued
2017-11-06
Date Acceptance
2017-10-13
Citation
Globalization and Health, 2017, 13
URI
http://hdl.handle.net/10044/1/51852
DOI
https://www.dx.doi.org/10.1186/s12992-017-0304-y
ISSN
1744-8603
Publisher
BioMed Central
Journal / Book Title
Globalization and Health
Volume
13
Copyright Statement
© The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
License URL
http://creativecommons.org/licenses/by/4.0/
Sponsor
Commonwealth Fund
Grant Number
Harkness Fellowship in Healthcare Policy and Practice
Subjects
Bias
Implicit association test
Research evaluation
Reverse innovation
Stereotypes
1117 Public Health And Health Services
General & Internal Medicine
Publication Status
Published
Article Number
80
About
Spiral Depositing with Spiral Publishing with Spiral Symplectic
Contact us
Open access team Report an issue
Other Services
Scholarly Communications Library Services
logo

Imperial College London

South Kensington Campus

London SW7 2AZ, UK

tel: +44 (0)20 7589 5111

Accessibility Modern slavery statement Cookie Policy

Built with DSpace-CRIS software - Extension maintained and optimized by 4Science

  • Cookie settings
  • Privacy policy
  • End User Agreement
  • Send Feedback