关于数据偏差,卫生专业的学生应该学些什么?

Q2 Social Sciences
Douglas Shenson, Beverley J Sheares, Chelesa Fearce
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引用次数: 0

摘要

在流行病学中,偏倚被定义为系统性地偏离事实,它可能出现在科学调查的不同阶段(例如,数据收集、方法应用和结果分析)。流行病学偏倚可以作为数据偏倚(通常归类为选择偏倚或信息偏倚)或社会偏倚(偏见)的结果出现。这种形式的偏见可能单独发生,也可能同时发生。这篇文章探讨了卫生专业的学生应该学习什么关于数据偏差和社会偏差之间的关系——由种族、民族、性别或其他类型的偏见产生,单独或组合——作为影响患者护理和社区健康的卫生保健实践和政策的伦理和临床关注的来源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
What Should Health Professions Students Learn About Data Bias?

In epidemiology, bias is defined as systematic deviation from the truth, and it can arise at different stages of scientific investigation (eg, data collection, methodological application, and outcomes analysis). Epidemiological bias can appear as a consequence of data bias (usually categorized as selection bias or information bias) or social bias (prejudice). Such forms of bias may occur separately or together. This article explores what health professions students should learn about the relationship between data bias and social bias-generated by racial, ethnic, gender, or other kinds of prejudice, singly or in combination-as a source of ethical and clinical concern in health care practices and policies that influence patient care and community health.

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来源期刊
AMA journal of ethics
AMA journal of ethics Social Sciences-Health (social science)
CiteScore
1.90
自引率
0.00%
发文量
146
期刊介绍: The AMA Journal of Ethics exists to help medical students, physicians and all health care professionals navigate ethical decisions in service to patients and society. The journal publishes cases and expert commentary, medical education articles, policy discussions, peer-reviewed articles for journal-based and audio CME, visuals, and more. Since its inception as an editorially-independent journal, we promote ethics inquiry as a public good.
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