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Language Bias in Health Research: External Factors That Influence Latent Language Patterns
Danny Valdez1, Patricia Goodson2
1Department of Applied Health Science, Indiana University School of Public Health, Bloomington, IN, United States.
Frontiers in Research Metrics and Analytics
|April 19, 2021
Summary
Language analysis reveals potential bias in health research. Topic modeling of publication histories showed differences in focus based on time, funding, and country, highlighting the need to scrutinize scientific language alongside data.
Area of Science:
- Health research ethics
- Computational linguistics
- Bibliometrics
Background:
- Problematic research often linked to statistical methods.
- The role of language in shaping research findings and data presentation is under-examined.
- Language analysis is crucial for understanding potential bias in scientific publications.
Purpose of the Study:
- To investigate language as a predictor of potential bias in health research.
- To apply topic modeling to publication histories across different health research areas.
- To identify how factors like time, funding, and origin influence research language.
Main Methods:
- Latent Dirichlet Allocation (LDA) topic models were employed.
- Publication histories were analyzed, disaggregated by time, funding source, and nation of origin.
- Case studies included ADHD pharmacotherapy, sugar consumption, and Pediatric Highly-Active Anti-Retroviral Therapy (P-HAART).
Main Results:
- Significant linguistic differences were observed when publication histories were disaggregated by the studied factors.
- Language in ADHD pharmacotherapy research evolved over time, reflecting new trends.
- Funding source (industry vs. federal) influenced research focus in sugar consumption studies.
- National regulatory differences (US vs. Europe) appeared to shape research direction in P-HAART.
Conclusions:
- Language and its framing warrant careful study, akin to numerical data, in assessing research rigor, reproducibility, and transparency.
- Topic models offer a valuable tool for hypothesis-driven research questions in scientific ethics.
- Integrating linguistic analysis can enhance the evaluation of scientific integrity.
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