Potentially eligible patients reporting nonwhite race, lower levels of education, and who had less continuity with one physician, fewer preventive visits, less use of recommended screening tests, and were current or past smokers were more likely to not participate in the trial. The majority of English-speaking subjects that were contacted had never received any type of CRC testing, with nonparticipants being more than 1.5 times more likely to report this.
The most common reason for nonparticipation was passive, not engaging in the telephone interview. Additionally, 10% of eligible participants refused when they were asked to provide verbal consent, which included permission to review their medical data and Health Insurance Portability and Accountability Act (HIPAA) language (a requirement that has been associated with refusal in other studies19
). Thus, more people might have participated if CRC screening interventions were offered as part of a quality improvement initiative and not research.
Systematic reviews provide evidence that factors related to study enrollment are complex and understudied. 7
Wendler and colleagues6
reviewed more than 1600 clinical intervention trials, and found that only 17 trials reported consent rates by race and ethnic groups, with minority racial groups being as likely to enroll. However, there was significant heterogeneity among studies, suggesting that willingness to participate may be mediated by a variety of factors. Interventions most successful at enrolling minority groups20
have used targeted strategies such as recruiting from community centers or faith-based organizations or limited enrollment to specific groups, which might lead to effective strategies for specific subgroups, but are not necessarily inclusive of diverse study populations.
Study designs not requiring individual consent could potentially increase the representativeness of the study population. Methods such as cluster RCTs and interrupted time-series make it possible in some cases to avoid individual consent and assess overall effectiveness of interventions on defined populations.21,22
However, these designs have practical and scientific limitations, particularly in comparative effectiveness studies such as the current one with four comparison groups. Additionally, in cluster RCTs and time-series studies, it may be more difficult to collect data on and adjust for population differences, 23
resulting in potential over- and under-estimates of effect size.24
Interrupted time-series studies attempt to account for temporal trends, but as CRC screening rates have been steadily increasing,4
it might be difficult to distinguish temporal trends from intervention effects. Comparing CRC screening outcomes in participants to those eligible but not invited to participate could potentially be used to improve assessment of external validity.25,26
However, because those not invited were not surveyed, eligibility based on self-reported CRC tests would be unknown.
Glasgow and others as part of the Reach, Effectiveness, Adoption, Implementation, and Maintenance Framework (RE-AIM)27
have called for increased reporting of participation rates and representativeness of study populations. 28,29
Reach, defined as the percentage of those invited and representativeness of those who agree to participate in a trial or program, can be used to quantify the potential impact of a study in other settings. Participation rates vary using different definitions of eligibility (). Similar to Glasgow, the authors favor defining participation rates as including those who are potentially, but not confirmed, eligible.28
Thus, the population-based impact of the SOS intervention could be estimated as reach (acceptance rate of 41%) times effectiveness, and if there are differential effects of the intervention across by subgroups, a correction coefficient for under-represented populations could be applied. 30,31
However, such calculations are estimates only, because some nonparticipants would be found to be ineligible if they had been interviewed (which we conservatively did not correct for) and others who were eligible might complete CRC screening offered as part of a quality initiative.
This study has several limitations. It cannot be assumed that all subjects up-to-date for CRC testing received those tests for screening, and patients receiving diagnostic tests might differ from those screened. There are also limited data on nonparticipants without self-reported data; however, imputed race and education (Appendix B
, available online at www.ajpmonline.org
) revealed trends similar to self-reports. Automated data are presented in aggregate only, as nonparticipants did not consent to have their EMR data reviewed, and adjusted relative risks could only be estimated for self-reported data.
Additionally, patients were recruited from an insured population in the Pacific Northwest; individuals without insurance or who receive care in other healthcare settings might respond differently to being invited to participate in a CRC screening study. Further, the ability to speak English was an eligibility requirement. Because Group Health did not collect data on race at the time of the study, it was not feasible to tailor materials or interviews to specific ethnic subgroups. Inclusion of non-English speakers and provision of culturally tailored interviews might have increased minority participation.
This study, however, has notable strengths, including the ability to characterize the entire age-eligible population from which the patients were recruited. Lamerato et al.,32
in a report of recruitment to the Prostate, Lung, Colorectal, and Ovarian Cancer Screening (PLCO) Trial, described demographic and socioeconomic characteristics of the recruitment cohort within a defined population, the Henry Ford Health System, with minority populations being less likely to participate; however, other PLCO sites that used recruitment strategies such as advertisements or referral were not able to provide similar data. The present study adds additional information on the health care and lifestyle behaviors of the recruitment pool and their relationship to participation in a trial to increase CRC screening rates.