Racial, Gender, and Size Bias in a Medical Graphical Abstract Gallery: A Content Analysis
Introduction: Graphical abstracts may enhance dissemination of scientific and medical research but are also prone to reductionism and bias. We conducted a systematic content analysis of the Journal of Internal Medicine (JIM) Graphical Abstract Gallery to assess for evidence of bias. Materials and Me...
| Format: | Article |
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| Language: | English |
| Published: |
Mary Ann Liebert
2023-09-01
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| Series: | Health Equity |
| Online Access: | https://www.liebertpub.com/doi/full/10.1089/HEQ.2023.0026 |
| _version_ | 1797402302415372288 |
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| collection | DOAJ |
| description | Introduction: Graphical abstracts may enhance dissemination of scientific and medical research but are also prone to reductionism and bias. We conducted a systematic content analysis of the Journal of Internal Medicine (JIM) Graphical Abstract Gallery to assess for evidence of bias.
Materials and Methods: We analyzed 140 graphical abstracts published by JIM between February 2019 and May 2020. Using a combination of inductive and deductive approaches, we developed a set of codes and code definitions for thematic, mixed-methods analysis.
Results: We found that JIM graphical abstracts disproportionately emphasized male (59.5%) and light-skinned (91.3%) bodies, stigmatized large body size, and overstated genetic and behavioral causes of disease, even relative to the articles they purportedly represented. Whereas 50.7% of the graphical surface area was coded as representing genetic factors, just 0.4% represented the social environment.
Discussion: Our analysis suggests evidence of bias and reductionism promoting normative white male bodies, linking large bodies with disease and death, conflating race with genetics, and overrepresenting genes while underrepresenting the environment as a driver of health and illness. These findings suggest that uncritical use of graphical abstracts may distort rather than enhance our understanding of disease; harm patients who are minoritized by race, gender, or body size; and direct attention away from dismantling the structural barriers to health equity.
Conclusion: We recommend that journals develop standards for mitigating bias in the publication of graphical abstracts that (1) ensure diverse skin tone and gender representation, (2) mitigate weight bias, (3) avoid racial or ethnic essentialism, and (4) attend to sociostructural contributors to disease. |
| first_indexed | 2024-03-09T02:22:23Z |
| format | Article |
| id | doaj.art-0a7f82ed4dec4c0f8a5be054181fb688 |
| institution | Directory Open Access Journal |
| issn | 2473-1242 |
| language | English |
| last_indexed | 2024-03-09T02:22:23Z |
| publishDate | 2023-09-01 |
| publisher | Mary Ann Liebert |
| record_format | Article |
| series | Health Equity |
| spelling | doaj.art-0a7f82ed4dec4c0f8a5be054181fb6882023-12-06T16:24:16ZengMary Ann LiebertHealth Equity2473-12422023-09-0110.1089/HEQ.2023.0026Racial, Gender, and Size Bias in a Medical Graphical Abstract Gallery: A Content AnalysisIntroduction: Graphical abstracts may enhance dissemination of scientific and medical research but are also prone to reductionism and bias. We conducted a systematic content analysis of the Journal of Internal Medicine (JIM) Graphical Abstract Gallery to assess for evidence of bias. Materials and Methods: We analyzed 140 graphical abstracts published by JIM between February 2019 and May 2020. Using a combination of inductive and deductive approaches, we developed a set of codes and code definitions for thematic, mixed-methods analysis. Results: We found that JIM graphical abstracts disproportionately emphasized male (59.5%) and light-skinned (91.3%) bodies, stigmatized large body size, and overstated genetic and behavioral causes of disease, even relative to the articles they purportedly represented. Whereas 50.7% of the graphical surface area was coded as representing genetic factors, just 0.4% represented the social environment. Discussion: Our analysis suggests evidence of bias and reductionism promoting normative white male bodies, linking large bodies with disease and death, conflating race with genetics, and overrepresenting genes while underrepresenting the environment as a driver of health and illness. These findings suggest that uncritical use of graphical abstracts may distort rather than enhance our understanding of disease; harm patients who are minoritized by race, gender, or body size; and direct attention away from dismantling the structural barriers to health equity. Conclusion: We recommend that journals develop standards for mitigating bias in the publication of graphical abstracts that (1) ensure diverse skin tone and gender representation, (2) mitigate weight bias, (3) avoid racial or ethnic essentialism, and (4) attend to sociostructural contributors to disease.https://www.liebertpub.com/doi/full/10.1089/HEQ.2023.0026 |
| spellingShingle | Racial, Gender, and Size Bias in a Medical Graphical Abstract Gallery: A Content Analysis Health Equity |
| title | Racial, Gender, and Size Bias in a Medical Graphical Abstract Gallery: A Content Analysis |
| title_full | Racial, Gender, and Size Bias in a Medical Graphical Abstract Gallery: A Content Analysis |
| title_fullStr | Racial, Gender, and Size Bias in a Medical Graphical Abstract Gallery: A Content Analysis |
| title_full_unstemmed | Racial, Gender, and Size Bias in a Medical Graphical Abstract Gallery: A Content Analysis |
| title_short | Racial, Gender, and Size Bias in a Medical Graphical Abstract Gallery: A Content Analysis |
| title_sort | racial gender and size bias in a medical graphical abstract gallery a content analysis |
| url | https://www.liebertpub.com/doi/full/10.1089/HEQ.2023.0026 |