Quality versus Risk-of-Bias assessment in clinical research
Open accessAbstract
Assessment of internal validity safeguards implemented by researchers has been used to examine the potential reliability of evidence generated within a study. These safeguards protect against systematic error, and such an assessment has traditionally been called a quality assessment. When the results of a quality assessment are translated through some empirical construct to the potential risk of bias, this has been termed a risk of bias assessment. The latter has gained popularity and is commonly used interchangeably with the term quality assessment. This key concept paper clarifies the differences between these assessments and how they may be used and interpreted when assessing clinical evidence for internal validity.
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Methodological quality depends primarily on the degree to which a study's design, conduct, and analysis meet the highest possible standards and reduce multiple potential biases.
“Methodological quality depends primarily on the degree to which a study’s design, conduct, and analysis meet the highest possible standards and reduce multiple potential biases 34 .”
From Global mapping of randomized controlled trials in dentistry (2024) · cites this paper as [34]
Risk of bias was assessed using the RoB 2 tool at the individual outcome measure level.
“The RoB 2 tool, which requires that the risk of bias is always assessed at the individual outcome measure, was used, thereby ensuring a methodological safeguard (Furuya-Kanamori et al., 2021).”
From Current trends and future implications in the utilization of ChatGPT in nursing: a rapid review (2024) · cites this paper as Furuya-Kanamori et al., 2021
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InfluentialTools to assess the risk of bias in clinical research
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In reply to “Bias assessment: mQ or RoB?”
Barker, T. H., Aromataris, E., Ritskes-Hoitinga, M. J., Sears, K., Klugar, M., Leonardi‐Bee, J., & Munn, Z. (2023) · JBI Evidence Synthesis · doi:10.11124/jbies-23-00213
Ortiz, H. A. D. L. B., Arias, M., & Liebano, R. E. (2023) · Physiotherapy · doi:10.1016/j.physio.2023.09.005
Introduzione all’approccio critico alla decisione clinica
Casazza, G., & Costantino, G. (2024) · doi:10.54103/milanoup.164
Are aquatic exercises feasible post stroke? What do we know after an overview of systematic reviews?
Paixão, L., Obara, K., Silva, C. T., Nampo, D. B., Munaro, G. R., & Cardoso, J. R. (2024) · Neurorehabilitation · doi:10.1177/10538135241289775
“For the evaluation of the non-random controlled trial, the ROBINS-1 is the most indicated, because its critical evaluation is based on the various domains separately, and its use is suggested by the AMSTAR-2 (Armijo-Olivo et al., 2015; Furuya-Kanamori et al., 2021; Shea et al., 2017).”
Bohang, S. A. M., & Lai, J. H. (2024) · Journal of Health and Quality of Life · doi:10.37934/jhqol.4.1.3354
“To eliminate this risk, a risk of bias assessment must be done by reviewing the analysis, conduct and design affecting the results of study [7].”
Research Note: Systematic reviews versus scoping reviews in physiotherapy
Smith‐Turchyn, J., Macedo, L. G., & Kho, M. E. (2025) · Journal of physiotherapy · doi:10.1016/j.jphys.2025.09.011
Matterne, U., Theurich, M. A., Proebstl, S., Pieper, D., Wang, J., Xu, A., & Apfelbacher, C. (2024) · Figshare · doi:10.6084/m9.figshare.26580269
Bias-adjusted meta-analysis using the quality effects model: a Stata tutorial
Stone, J., Stern, C., Jia, R. M., Whitehorn, A., Ho, H. T., & Doi, S. A. R. (2026) · JBI Evidence Synthesis · doi:10.11124/jbies-25-00083
Declerck, L., Ginis, K. M., Cheung, A., Jeng, B., Zheng, P., Huynh, T. L. T., Brunskill, A., & Motl, R. W. (2026) · Systematic Reviews · doi:10.1186/s13643-026-03095-z · Cited by 1 · see citing works
“…quality refers to how well a study is conducted and reported according to established standards and principles of research methodology [29], risk of bias represents the likelihood that flaws in study design, conduct, or analysis have introduced systematic errors that distort the results [29].”
Elmakaty, I., Abdo, R., Ouda, A., Elmarasi, M., Elahtem, M., Khamis, Y. A., & Malki, M. I. (2026) · AI · doi:10.3390/ai7030107
Drowning in Evidence: The Meta‐Analysis Boom and the Rigor It Demands
Impellizzeri, F. M., & Shrier, I. (2026) · Scandinavian Journal of Medicine and Science in Sports · doi:10.1111/sms.70353
Transportation-related factors, cancer screening, and stage at diagnosis: A scoping review
Pohl, A. L., Cohen-Tigor, L. A., Aderonmu, A. A., Doan, A. E., Horton, L., Ko, B., Shideler, B. L., & Morris, A. M. (2026) · PLoS ONE · doi:10.1371/journal.pone.0354856
“A strength of the current study is its inclusion of a true risk-of-bias assessment, rather than a comprehensiveness-of-reporting assessment [123].”
Responding to the challenges of evidence synthesis
Bastounis, A., Kundakci, B., & Booth, A. (2026) · Research methods in applied linguistics · doi:10.1075/rmal.17.18bas
Nguyen, C., Steinberg, O., Scandiffio, J., Lewczuk, M., Matheson, F. I., Colantonio, A., & Chan, V. (2026) · BMJ Open · doi:10.1136/bmjopen-2026-118951
Maleki, M. M., Vaziri–Amjad, S., & Shahbazi, F. (2026) · Avicenna journal of dental research · doi:10.34172/ajdr.4429
“This process allowed us to apply a bias-adjusted meta-analysis model through a quantitative approach (27, 28).”
Selecting the optimal study design!
Albabtain, M. A., AlRasheed, M. M., Arafat, A. A., Breitinger, H., Breitinger, U., Elsisi, G. H., Gaber, A., Gumaa, M., Hozien, M., Abdelghany, R. M., et al. (2026) · Elsevier eBooks · doi:10.1016/b978-0-443-45595-7.00015-7
- Authors
- Furuya-Kanamori, L., Xu, C., Hasan, S. S., & Doi, S. A.
- Affiliations
- Qatar University (QA)
- University of Huddersfield (GB)
- Corresponding author
- Doi, Suhail A.
- Venue
- Journal of Clinical Epidemiology
- Publisher
- Elsevier BV
- Published
- 2021-01
- Volume
- 129
- Pages
- 172-175
- ISSN
- 0895-4356 (ISSN-L)
- OpenAlex
- W3119142291
- Cited by
- 88
- References
- 9
- Citations by year
- 2026: 14 · 2025: 14 · 2024: 22 · 2023: 20 · 2022: 11 · 2021: 7
- FWCI
- 8.67
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal of Clinical Epidemiology (publishedVersion, cc-by)
- PubMed (publishedVersion)
- ANU Open Research (Australian National University) (submittedVersion, cc-by)
- Figshare (submittedVersion, cc-by)
- Huddersfield Research Portal (University of Huddersfield) (submittedVersion, cc-by)
- Qatar University QSpace (Qatar University) (submittedVersion, cc-by)
- Funders
- Qatar National Research Fund
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Keywords
- risk of bias assessment, quality assessment, internal validity, systematic errors, clinical research evidence, reliability of evidence, methodological quality
- MeSH terms
- Public Reporting of Healthcare Data, Humans, Quality Assurance, Health Care, Reproducibility of Results, Bias, Risk Assessment, Evidence-Based Medicine, Biomedical Research
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