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Background <p>Eligibility criteria are a critical component of a well-designed clinical trial, enhancing trial safety and internal validity. Yet, data suggest that exclusion rates based on these criteria often vary by participant race/ethnicity.</p> Method <p>This study compared the proportion of participants (<i>n</i> = 4235) from seven racial/ethnic groups, who were included versus excluded from participation in a randomized controlled trial (RCT) testing two digital sleep interventions for the prevention of perinatal depression. Eight 2 × 7 chi-squared tests were conducted to compare the proportion of each racial/ethnic group excluded due to each eligibility criterion. Logistic regressions were fitted to estimate the magnitude of the relationship between racial/ethnic group and exclusion based on each eligibility criterion.</p> Results <p>The proportion of excluded participants differed by race/ethnicity across all eight eligibility criteria. For example, Black participants were more likely to be excluded due to comorbid conditions such as sleep apnea <i>X</i><sup>2</sup>&#xa0;(6,&#xa0;<i>N</i> = 4151) = 20.94,&#xa0;<i>p</i> = .002, and Asian participants were more likely to be excluded for reporting subclinical insomnia symptoms <i>X</i><sup>2</sup>&#xa0;(6,&#xa0;<i>N</i> = 4151) = 85.99,&#xa0;<i>p</i> &lt; .001. Logistic regressions showed that compared to White participants, Black participants had significantly higher odds (odds ratios ranging from 1.70 to 6.86) of study exclusion for three of the eight eligibility criteria.</p> Conclusions <p>Eligibility criteria excluded prospective study participants at different rates dependent on their race/ethnicity. Differences in trial exclusion can contribute to the under-enrollment of minoritized pregnant people in RCTs for behavioral health. Quantifying and reporting eligibility disparities enables investigators to more precisely evaluate the trade-offs of specific inclusion criteria against the generalizability of findings to diverse populations.</p>

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Detecting racial and ethnic disparities in study exclusion: screening outcomes from a RCT for pregnant women with insomnia

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月13日

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  • Carolyn Ponting,
  • Candance Sorensen,
  • Bernadette McClelland,
  • Richelle Mah,
  • John Neuhaus,
  • Rachel Manber,
  • Andrew D. Krystal,
  • Patricia Moran,
  • Jennifer N. Felder

摘要

Background

Eligibility criteria are a critical component of a well-designed clinical trial, enhancing trial safety and internal validity. Yet, data suggest that exclusion rates based on these criteria often vary by participant race/ethnicity.

Method

This study compared the proportion of participants (n = 4235) from seven racial/ethnic groups, who were included versus excluded from participation in a randomized controlled trial (RCT) testing two digital sleep interventions for the prevention of perinatal depression. Eight 2 × 7 chi-squared tests were conducted to compare the proportion of each racial/ethnic group excluded due to each eligibility criterion. Logistic regressions were fitted to estimate the magnitude of the relationship between racial/ethnic group and exclusion based on each eligibility criterion.

Results

The proportion of excluded participants differed by race/ethnicity across all eight eligibility criteria. For example, Black participants were more likely to be excluded due to comorbid conditions such as sleep apnea X2 (6, N = 4151) = 20.94, p = .002, and Asian participants were more likely to be excluded for reporting subclinical insomnia symptoms X2 (6, N = 4151) = 85.99, p < .001. Logistic regressions showed that compared to White participants, Black participants had significantly higher odds (odds ratios ranging from 1.70 to 6.86) of study exclusion for three of the eight eligibility criteria.

Conclusions

Eligibility criteria excluded prospective study participants at different rates dependent on their race/ethnicity. Differences in trial exclusion can contribute to the under-enrollment of minoritized pregnant people in RCTs for behavioral health. Quantifying and reporting eligibility disparities enables investigators to more precisely evaluate the trade-offs of specific inclusion criteria against the generalizability of findings to diverse populations.