What Should Health Professions Students Learn About Data Bias

Dados Bibliográficos

ID15744625
AutoresDouglas Shenson (Yale University, autor correspondente), Beverley J Sheares (0000-0001-6138-0033, Yale University), Chelesa Fearce (Yale University)
Ano2025
Volume27
Fascículo1
PáginasE14-20
Data de publicação2025-01-01
Open AccessSim
TipoARTICLE
PeriódicoThe AMA Journal of Ethic (JOURNAL)
Identificadores do periódicoISSN: 2376-6980 • E-ISSN: 2376-6980
EditoraAmerican Medical Association (PUBLISHER • US)
DOI10.1001/amajethics.2025.14
PMID39745910
OpenAlexW4405979692
IdiomaEN
Referências citadas6

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

Data collection · Ethnic group · Gender bias · Health care · Implicit bias · Information bias · MEDLINE · Non-response bias · Political science · Prejudice (legal term · Publication bias · Racial bias · Racism · Selection bias · Social science · Sociology · Food Security and Health in Diverse Populations · Health and Conflict Studies · Healthcare cost, quality, practices · Medicine · Psychology · Social Psychology

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