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衡量对低收入国家研究的偏见:一项内隐联想测验。

Measuring the bias against low-income country research: an Implicit Association Test.

作者信息

Harris Matthew, Macinko James, Jimenez Geronimo, Mullachery Pricila

机构信息

Institute of Global Health Innovation, Imperial College London, 10th Floor, QEQM building, St. Mary's Campus, Praed Street, London, W2 1NY, England.

UCLA Fielding School of Public Health, Center for Health Sciences, 650 Charles E. Young Dr. South, Room 31-235B, Los Angeles, CA, 90095-1772, USA.

出版信息

Global Health. 2017 Nov 6;13(1):80. doi: 10.1186/s12992-017-0304-y.

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.

摘要

背景

随着低收入国家涌现出越来越多的创新成果和研究,人们越来越认识到,即使是高收入国家也能从这些环境中学习。众所周知,产品的来源会影响对该产品的认知,但很少有研究探讨这是否也适用于循证医学和决策制定。为了研究从低收入国家学习可能存在的障碍,本研究采用认知心理学中的既定方法,探讨医疗保健专业人员和研究人员是否更倾向于将高质量研究与富裕国家而非贫穷国家隐含地联系在一起。

方法

向医疗保健专业人员和研究人员发放基于计算机的内隐联想测验(IAT)。代表富裕国家的刺激物选自世界银行排名前十(人均>36,000美元)的经合组织成员国,代表贫穷国家的刺激物选自人均国内生产总值排名垫底的三十个国家(人均<1000美元),两种情况都考虑了区域代表性。代表研究的刺激物是对研究动机(客观/有偏见)、价值(有用/无价值)、清晰度(精确/模糊)、过程(透明/不诚实)和可信度(可信/不可靠)的描述。IAT结果以科恩d统计量表示。分位数回归用于评估协变量(如年龄、性别、原籍国)对与不同程度内隐偏见相对应的IAT反应不同值的贡献。泊松回归用于对明确偏见项目的二分反应进行建模。

结果

在2015年3月至4月的四周内共完成了321次测试。样本的平均内隐联想测验结果(一致和不一致类别之间的标准化平均相对潜伏期)为0.57(95%可信区间0.52至0.61),表明平均而言,我们的样本在富裕国家和高质量研究之间表现出中等强度的内隐关联。40岁以上的人表现出扶贫内隐关联的可能性较小,而作为同行评审员则有助于形成更扶贫的关联。

结论

与贫穷国家相比,我们的大多数参与者将高质量研究与富裕国家联系在一起。这种内隐关联可能会在研究评估、循证医学和创新传播中不利于来自贫穷国家的研究。

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