Unique Considerations for Patient Retention in Decentralized Clinical Trials

Clinical Researcher—February 2023 (Volume 37, Issue 1)


Ingrid Oakley-Girvan, PhD, MPH


As decentralized clinical trials (DCTs) become more prevalent, particularly in the wake of the pandemic, their lower burden approach can make participation more attractive for some. Yet the vexing issue of retaining participants throughout the course of a trial will continue to be problematic without a thoughtful approach to keep them engaged. A three-phase model of engagement, based on proven science and intelligently informed by utilizing data, can make important inroads into solving this long-standing challenge.


While concerns about how to successfully increase access and the pace of enrollment for clinical trials have often kept principal investigators and sponsors up at night, retaining enrolled participants is also critically important to consider. Poor retention rates can lead to increased costs and a loss of useful data for regulatory submission. According to Forte Research, the average dropout rate across all clinical trials is 30% and the average cost to recruit just one participant is $6,533. Retention throughout each phase of a clinical trial plays an important role in a study’s success, both from an economic and scientific point of view.

Despite the enormous impact that poor retention can make, a comprehensive study of more than 5,500 clinical trial participants, conducted by the Center for Information and Study on Clinical Research Participation (CISCRP) in 2019 and again in 2021, concluded that nearly one-quarter of all participants who enroll in clinical trials do not complete them, thus threatening the quality of the data and the integrity of a vast number of studies.{1}

The CISCRP survey results shed some interesting light onto why retention is such a challenge. The data seem to indicate that the burdens that many traditional clinical trial participants face have become more onerous in recent years. For example, in the 2021 survey, 44% of study participants indicated that traveling to a study clinic was “somewhat” or “very burdensome,” up 15% from just two years earlier. Additionally, the length of study visits was cited as “somewhat” or “very burdensome” by 40% of those who were surveyed in 2021, nearly double what respondents indicated in 2019.

These stark shifts in attitude over such a brief period can likely be traced to the repercussions of the pandemic. Participants seem to have appreciated the pivot that clinical trials made to online and digital methods due to COVID. A full one-half of the respondents who were surveyed in 2021 said that they wanted to see telemedicine and virtual clinic visits continue for clinical trials, even after the pandemic. These numbers are even more pronounced for Hispanic and Black respondents, with more than 60% of Hispanic and 56% of Black respondents favoring the digital shift.

The Case for Decentralized Trials, and the Challenges They Must Overcome

This growing discontent among prospective participants at the disruptive nature of traditional clinical trials presents a clear opportunity to do things differently. As the data from the CISCRP survey indicate, prospective clinical trial participants have a clear preference for studies that are more convenient and less demanding on their time. Decentralized trials (which invariably require less travel, less time spent in clinical settings, and incorporate more convenient methods of communication) clearly fit the bill.

Would a shift to participant-preferred DCTs automatically reduce the challenges of retention? First, it is important to recognize that the issue of compliance in healthcare (which for clinical trials is often manifested as dropping out of a study) are as old as medicine itself. Healthcare practitioners have struggled since the beginning of time, with varying degrees of success, to ensure that their patients adhere to their recommendations.

Clinical trials, of course, are not immune to these same challenges. There are countless reasons why noncompliance and poor retention occur in healthcare settings. Even when a participant has every intention of completing a study, there are a myriad of reasons why they might lose their motivation and drop out. Yet, this outcome can be greatly improved through thoughtful and intentional engagement.

Dr. John P. Docherty, adjunct professor of psychiatry at Weill Cornell Medicine in New York City, notes that while digital health applications can be easier and more convenient to use, such benefits alone are not enough to create and sustain the level of engagement required for successful clinical study participants, particularly if they do not feel valued or have confidence using the technology. “Many things can interfere with engagement,” he says. “It requires a much deeper understanding in order for engagement to truly be effective.”

So how can study sponsors traverse these challenges and properly engage their DCT participants in ways that will help them stay enrolled in a study? “As the writer H. L. Mencken famously said, ‘For every complex problem there is an answer that is clear, simple, and wrong,’” Dr. Docherty says. “And this same logic holds true when it comes to healthcare compliance.”

There are no simple solutions. However, a lot can be learned from the extensive body of work across the behavioral, cognitive, and psychosocial sciences. Moreover, understanding how the most successful digital platforms engage their users can also provide some valuable insight.

The process begins by understanding what engagement means. When digital health applications first came to market, the understanding of user engagement was relatively simple. Analysis focused primarily on limited data such as how often users logged into the application or how much time they spent with it. Over time, the understanding of user engagement has become more sophisticated and nuanced. “We are thinking about engagement in a much more subjective way now,” says Dr. Docherty. “And to make a digital health application work, we know now that it has to be an enriched experience that draws on all of the aspects that cause people to be engaged with any activity.”

More advanced and thoughtful analysis of user data is particularly important when it comes to digital healthcare applications because healthcare settings, including those of clinical trials, exist outside most people’s comfort zones and typically increase anxiety. Add to this the fact that, while the digital environment of DCTs can mitigate some challenges, the experience of engaging with the health application will invariably fall short of scrolling through Instagram or TikTok, where the algorithms are carefully designed to serve you more of what you already like. Further, the lack of frequent, in-person engagement with patients in a decentralized trial—while helping to reduce travel and time burdens—can also create a scenario where there is less opportunity to engage in a meaningful way.

A New Solution: The Three-Phase Model of Engagement for DCTs

A framework structured around the three phases of the engagement process (initiation, strengthening, and the maintenance of engagement) can provide a scaffolding that will enable sponsors to better understand how they can leverage technology to their advantage when interacting with trial participants. This three-phase framework enables trials to incorporate an extensive body of knowledge from across the psychosocial, behavioral, and cognitive sciences, and translate it all effectively to the digital health environment. Noteworthy here is that, while it’s not an easy fix, baking proven engagement strategies into decentralized trial platform technology offers a sustainable way to both improve participant access as well as retention throughout the duration of the study.

Phase 1 – Initiation

Initiating engagement is what starts prospective participants on the path toward trial completion. There are several factors that can help facilitate a participant’s initial engagement, starting with thoughtful technology design. An effective user interface is essential to induce participation and reduce early friction and anxiety that can impede participation.

Another initiation component is reflected in the Transtheoretical Model, or Stages of Change,{2} which lays out the process that individuals go through while thinking about making a behavioral change. In addition, Motivational Interviewing,{3} a goal-oriented style of communication, as well as Patient Activation Measure,{4} which can help to measure a prospective subject’s engagement, should be employed. These tested strategies have been used for decades across various specialties with great success, and they can be effectively incorporated into the engagement algorithms used in digital applications to encourage and support engagement.

Ultimately, participants must feel competent and confident about their ability to use the technology in a decentralized trial. It isn’t good enough to simply assume that the application is user friendly. Additionally, health applications have the added layer of requiring users to have a relatively good level of health literacy. They need to understand the information that the application provides and be able to respond accurately and completely. Gently assessing participants for these criteria and providing them with the education necessary to make them comfortable is essential.

Phase 2 – Strengthening Engagement

Next, teams must work to strengthen that initial engagement, which is a central component for achieving what is referred to as “adherence” in the healthcare community. The often-used quote attributed to former U.S. Surgeon General C. Everett Coop, “drugs don’t work in patients who don’t take them,” indicates just how endemic the issue of adherence has been across healthcare over the years. However, digital health applications might offer a unique solution.

“Adherence is a complex and dynamic problem in healthcare delivery that we have never been able to effectively address before because it’s too challenging to do in a face-to-face setting,” says Dr. Docherty.

People’s feelings about healthcare and even their ability to access that care for logistical or financial reasons can change quickly, making it impossible for providers to understand what a patient or subject might be thinking at any given moment. Because of this, it is virtually impossible for providers to react properly to or anticipate how someone’s views or access will evolve over time. “Yet now, thanks to digital applications, we are capable of dealing with this ever-changing variable effectively, in real time, because we can see the participant’s behavior reflected in the data,” explains Dr. Docherty.

Boredom, fatigue, stress, and other demands can create a drag on a participant’s desire and ability to continue with a study. To prevent such attrition, engagement can be strengthened by establishing a collaborative relationship and “therapeutic alliance.”{5} Building a sense of trust and helping participants recognize that you and they are working together toward a collective goal is key. Key to this is to explicitly agree on required tasks and inform the patient about the importance of each task to the study. This signals a collaborative relationship from the start, and when this engagement happens within a digital application, it can be more easily reinforced in an organic, burden-free way.

Phase 3 – Maintaining Engagement

The hard work doesn’t stop after the enrollment. In addition to continuing with tailored, subject-specific communications informed by adherence management data, the Nudge Theory{6} can be deployed. Platform providers should provide systems that guide trial participants to make good choices and stay on task. For instance, some applications might make lifestyle recommendations and send medication reminders as well as include motivational messaging. “If you start to notice from the digital data that a participant’s behavior is changing suddenly, technology makes it easy to adjust certain aspects of how you are engaging to maintain participation motivation,” Dr. Docherty says.

An advantage of a digital application for the maintenance phase is how often these data-driven prompts and changes can be made without having to ask the participant directly. This intuitive responsiveness can often yield better results than one-on-one, in-person questioning that may feel intrusive.

Holistic Patient Engagement in DCTs

A carefully designed framework can help guide the process of combining time-tested theories from the psychosocial, behavioral, and cognitive sciences with the exceptional analytical and intuitive technologies of digital applications. However, in all cases—whether a decentralized trial or hybrid or traditional onsite trial—engagement can only be improved if it is addressed holistically. At each stage of trial participation, changing circumstances, attitudes, and emotions must be considered, as well as those of the participant’s caregivers. Get this right, and the industry will see a real breakthrough in improving the systemic challenge of retention, thereby improving the speed, quality, and integrity of the trial and the generated data.

NOTE: The Interactive Journal of Medical Research published a peer-reviewed study of these considerations – see it here.


  1. The Center for Information and Study on Clinical Research Participation. 2021. Perceptions and Insights Study. www.ciscrp.org/wp-content/uploads/2021/11/2021-PI-Participation-Experience-Report-04NOV2021-FINAL.pdf
  2. Prochaska JO, DiClemente CC. 1983. Stages and processes of self-change of smoking: toward an integrative model of change. J Consult Clin Psychol 51(3):390–5.
  3. Miller WR, Rollnick S. 1992. Motivational Interviewing: Preparing People to Change Addictive Behavior. New York, NY: The Guilford Press.
  4. Hibbard JH, Stockard J, Mahoney ER, Tusler M. 2004. Development of the Patient Activation Measure (PAM): conceptualizing and measuring activation in patients and consumers. Health Serv Res 39(4 Pt 1):1005–26.
  5. Henson P, Wisniewski H, Hollis C, Keshavan M, Torous J. 2019. Digital mental health apps and the therapeutic alliance: initial review. BJPsych Open 5(1):e15.
  6. King P. 2009. Review of Thaler RH, Sunstein CR. 2008. Nudge: Improving Decisions About Health, Wealth and Happiness. London: Yale. J Soc Pol 38(4):726–7.

Ingrid Oakley-Girvan

Ingrid Oakley-Girvan, PhD, MPH, (ingrid@medable.com) is Senior Vice President of Value and Strategy at Medable Inc., where she focuses on modernizing clinical trials, exploring the digital virtual healthcare space, and creating technology and tools to collect precision data.