By Deborah Borfitz 

March 9, 2023 | An existing trust-based intervention known to increase minority participation in clinical trials won’t do much to improve the representation of American Indians (AI) and Alaska Natives (AN) in studies, according to Arch G. Mainous III, Ph.D., professor in the department of community health and family medicine as well as health services research, management and policy at the University of Florida. Community engagement is critical when dealing with indigenous populations from a particular tribe or reservation—and they are “not one big monolith.”   

It was only a few years ago that the “trust triangle” dynamic used in the RECRUIT study was found to facilitate minority recruitment to intervention trials by increasing trust between patients, referring physicians, and specialist investigators (Contemporary Clinical Trials, DOI: 10.1016/j.cct.2021.106519). But indigenous populations have proven uniquely difficult to enroll, Mainous says, and still have the lowest representation of all racial and ethnic groups in the United States. 

Mainous has done many studies on trust-building with minorities for trial recruitment purposes and most recently teamed up with Alaskan Native (Athabaskan) Allison Kelleher, M.D., and American Indian (Sioux) Donald Warne, M.D., both with the world-first Department of Indigenous Health at the University of North Dakota, to develop a new “circle of trust” conceptual model. It builds on the trust triangle—patients, referring physicians, and specialist investigators—with a fourth component inclusive of the community to promote inclusion of AI/AN populations in trials to improve health outcomes (Annals of Family Medicine, DOI: 10.1370/afm.2901). 

A Tribe Apart 

The recruitment of minorities in general has been a longstanding problem that the National Institutes of Health (NIH) first sought to address through a 1993 mandate that funded researchers and institutions include women and minorities as participants in clinical trials. This led to the 2006 publication of the Trust in Medical Researchers Scale (Annals of Family Medicine, DOI: 10.1370/afm.541), focused on differentiating African American from white individuals, which Mainous helped develop. 

He was also part of the team testing the trust triangle model for clinical trials where individuals—for example, patients with cancer or Parkinson’s disease—are less inclined to respond to a recruitment ad or event co-led by a trusted community member than the advice of their personal physician. The idea here is to identify site-specific barriers for increasing referrals from local minority-serving physicians by improving their relationship with trial investigators, Mainous says. Minority-serving physicians—even if they are white—tend to be particularly protective of their patients and have low trust in clinical researchers. 

The trust triangle concept was subsequently incorporated into a 2021 research statement by the American Thoracic Society for enhancing recruitment and retention of minority populations (American Journal of Respiratory and Critical Care Medicine, DOI: 10.1164/rccm.202105-1210ST). Researchers and investigative sites frequently claim to be making efforts to build trust with minority groups when in fact they are doing little more than sending out a blast email to everyone, says Mainous.  Historical and current mistrust of scientific research hurts recruitment in ways that take time and effort to remedy with information-sharing and a trusted someone who can vouch for the investigator. 

The circle of trust model introduced in the latest published article is the first effort by Mainous to home in on the recruitment of indigenous populations, which are different than other minority groups in a few key respects. For starters, “actual hard boundaries” define different AI/AN communities, he notes. These geographies also have tribal leaders and councils as well as tribe-specific cultural norms. A Navajo is not the same as a Seminole nor an Athabaskan or any other group of Alaskan Natives. 

‘Too Much Trouble’ 

Central to relationship-building with AI/AN populations is the notion of reciprocity, but in more than a transactional sense (i.e., payment for participation), says Mainous. Reciprocity is an ethical principle that guides indigenous life, highlighted by sharing and the idea that “everyone is sort of in it together,” which isn’t typical of the views of mainstream U.S. culture.   

The problem is that institutional review boards monitoring biomedical research require that study protocols clearly state the benefits to participants, which in some cases don’t exist, he continues. The benefits need to be expressed, and appreciated, more at the community than the individual level and that is not currently the case. 

In lieu of relationship-building, says Mainous, everyone is looking for ways (e.g., artificial intelligence) to speed up clinical trials. Principal investigators don’t take the time to meet with other physicians in the community, leaving that up to study coordinators who may likewise view it as unnecessary and “too much trouble.”  

Pragmatic trials will hopefully now be done to demonstrate that the circle of trust model works better than anything that is currently being done to engage indigenous communities, he says. How to make headway on implementing its principles will be the subject of an upcoming meeting between Mainous and NIH officials. 

In the past, Mainous notes, one of the biggest incentives for embracing change has been the threat of having trials shut down. “We hope that’s not the only incentive we have to get people to do this.”                   

An initiative to increase the number of indigenous people who become physician-investigators would also be useful but could be another uphill battle given the overall pool has been shrinking over the past two decades, says Mainous. For AI/AN populations, investigators of the same ethnicity would have the advantage of already understanding the cultural nuances that can make or break trust and the likelihood to consider clinical trial participation.