Learning from experience: a systematic review of community consultation acceptance data

Study objective: Federal regulations permitting an exception from informed consent for research in emergency settings require community consultation before study approval. Rates of acceptance of exception from informed consent in community consultation are often reported, but predictors of acceptance are not well understood, and investigators and institutional review boards struggle to interpret and use acceptance data.

Methods: We systematically reviewed empirical literature on community consultation for exception from informed consent trials in the PubMed, EMBASE, and Web of Science databases. We included peer-reviewed articles reporting acceptance data from community consultation for US exception from informed consent trials. Questions were categorized by enrollment focus (eg, personal enrollment versus more general exception from informed consent acceptance), and observed acceptance was compared across studies. We also compared potential predictors of acceptance, including demographic factors, consultation method, and target community.

Results: Nine studies (total n=9,036 participants) were included in the final analysis. Personal acceptance of enrollment in the proposed exception from informed consent study ranged from 45% to 93% and clustered in the range of 64% to 80%. Acceptance of the exception from informed consent mechanism in general (without reference to personal inclusion) was lower (35% to 84%) than personal acceptance. The effect of demographic characteristics on acceptance was inconsistent, and meeting-based consultation methods were associated with greater acceptance than survey-based methods. Finally, acceptance rates varied substantially according to the phrasing of the question.

Conclusion: Personal acceptance clustered between 64% and 80%. This range may be informative for institutional review boards and investigators evaluating community consultation results. However, numerous factors affect acceptance, and there is a need for considerable caution against overreliance on acceptance data.