What if you were asked to solve a problem without naming it? In clinical research, gaps in representation among specific patient populations can compromise both the accuracy and applicability of findings. However, the vocabulary traditionally used to describe and address these imbalances has increasingly become a subject of controversy. In such an environment, achieving meaningful progress requires precision, not just in research methods but also in language.
To navigate this complexity, researchers must rely on data-driven, clinically relevant terminology that avoids politicized framing while still addressing the core issue: enhancing representation to ensure scientific validity and improved health outcomes. Below is a structured framework to guide this approach, along with effective substitute phrasing that prioritizes clarity over controversy.
Why Representation Matters
In many areas of clinical research, large segments of the population remain consistently underrepresented. These gaps are not always the result of deliberate exclusion; instead, they often arise from entrenched norms in study design, enrollment criteria, and data collection protocols that favor a narrow participant profile. The result is a limited evidence base that may not be fully applicable to the broader patient population.1
Correcting this pattern is not about ideology — it is about enhancing clinical accuracy. Without comprehensive sampling, significant differences in treatment response, safety, or dosing may go unnoticed. For example, variations in drug metabolism and side effect profiles across different physiological groups underscore the need for enrollment strategies that account for real-world variation.
By adopting methodologies that integrate a wider range of biological and demographic indicators, researchers can improve the generalizability and reliability of trial results. This enhances the scientific foundation of studies and ensures that new therapies are relevant to the full spectrum of patient needs.2
Safe phrasing examples:
“Certain demographic subsets remain consistently under-enrolled in clinical trials.”
“Historical imbalances in research populations limit the generalizability of findings.”
“Some cohorts have been systematically overlooked in data collection.”
“Ensuring clinically relevant populations are reflected in study design.”
“Stratified data supports stronger predictive validity across the full patient spectrum.”
Rethinking Study Design
Conventional trial designs often depend on restrictive eligibility criteria and recruitment practices that unintentionally limit participation. To improve the relevance and reach of clinical findings, researchers are starting to modify these aspects by considering physiologic variation, life stage, and environmental context.3
This evolution in trial design emphasizes flexible protocols, the integration of real-world data, and stratified analyses from the outset. It enables more nuanced insights into how treatments perform across a broader set of patient conditions without requiring explicit categorization based on identity. The goal is scientific: to enhance signal detection, minimize variability, and generate data that more accurately reflect treatment performance across the care continuum.
Safe phrasing examples:
“Segmenting enrollment criteria by physiological variables and life stage markers.”
“Expanding eligibility beyond historical defaults improves applicability.”
“Integrating life-course variables and anatomical variation into endpoints.”
Measuring Impact Without Making It Political
Efforts to expand the clinical trial participant pool are already yielding valuable outcomes. Studies with more comprehensive sampling often reveal findings, such as subgroup-specific safety signals or differential efficacy, that would otherwise remain hidden.4 These insights enable more accurate interventions, tailored treatment pathways, and enhanced post-market performance.
Crucially, the success of such efforts should be assessed through the lens of scientific merit, rather than social messaging. Broader participation enhances the predictive power of trials, bolsters regulatory rigor, and minimizes downstream risks. It is a strategy grounded in methodological robustness, not rhetoric.
Safe phrasing examples:
“Trial adaptations resulted in a more representative cross-section of patient types.”
“Post hoc analyses showed improved therapeutic response rates in newly incorporated sub-cohorts.”
“Greater variance detection was observed across enrollment strata.”
Moving Forward
The future of credible, high-impact clinical research depends on continually refining the structure of studies and the definition of eligibility criteria. As patient care becomes increasingly personalized and outcomes are subject to greater scrutiny, trials must evolve to consider the full range of physiological and environmental factors that shape responses to treatment.
Expanding the scope of study populations is not about meeting arbitrary benchmarks; it’s about aligning with the complexity of modern medicine. By embracing comprehensive, data-informed trial design, the field can ensure that medical advances are both scientifically sound and widely applicable.5
You can find the complete list of known flagged terms here.
Safe phrasing examples:
“Science advances when trial populations reflect the range of real-world patients.”
“Broader recruitment strategies are a matter of rigor, not rhetoric.”
“Capturing a complete clinical picture requires attention to all physiologic trajectories.”
References
1. Improving Representation in Clinical Trials and Research: Building Research Equity for Women and Underrepresented Groups. National Academies of Sciences, Engineering, and Medicine. National Academies Press, 2022.
2. Clark, Lisa T., et al. “Increasing Diversity in Clinical Trials: Overcoming Critical Barriers.” Current Problems in Cardiology. 44: 148–172 (2019).
3. Improving Clinical Trial Design and Conduct for Successful Women's Health Research: Proceedings of a Workshop. National Academies of Sciences, Engineering, and Medicine. National Academies Press, 2022.
4. Eshera, Nicole, et al. “Filling the Gaps: Increasing Participation of Underrepresented Populations in Clinical Research.” Journal of Clinical and Translational Science. 7: e109 (2023).
5. FDA Offers Guidance to Enhance Diversity in Clinical Trials and Encourage Inclusivity in Medical Product Development. U.S. Food and Drug Administration. 13 Apr. 2022.