Behavioral science in clinical trials: Key concepts
Behavioral barriers: The real reasons patients decline or drop out often include fear, mistrust, cognitive load, and practical constraints, not simply lack of awareness or interest.
Co-design: Involving patients and site staff in protocol and process design before decisions are finalized reduces friction and prevents costly delays later.
The movable middle: Underrepresented populations often fall into a group that is neither firmly pro-trial nor firmly opposed. Targeted behavioral strategies are most effective at improving reach within this segment.
Service design: Mapping the full patient and site journey identifies high-impact friction points that standard operational metrics, like screening and enrollment rates, rarely capture until problems have already accumulated.
Slow recruitment, high dropout, and persistent underrepresentation are among the most costly and enduring challenges in clinical research. Behavioral science offers a framework for addressing them not as isolated operational problems, but as predictable consequences of how trials are designed, sites are selected, and patients are engaged.
The insights from behavioral science are not abstract. Applied systematically across trial design, site selection, technology implementation, and diversity planning, they offer sponsors a practical path to faster, more inclusive, and more operationally resilient studies.
Here are 10 questions addressing what behavioral science means for clinical trial design and execution.
1. What is behavioral science and why is it relevant to clinical trials?
Behavioral science draws on psychology, decision-making research, and human-centered design to understand why people act the way they do. In clinical trials, it provides tools to identify the real reasons patients decline to participate, drop out, or fail to complete procedures, and why site staff disengage or adopt workflows inconsistently. Rather than relying on assumptions, behavioral science grounds trial design in evidence about how people actually think, decide, and behave under real-world conditions.
2. Why do recruitment problems so often trace back to trial design rather than recruitment itself?
By the time a trial opens to enrollment, many of its most significant barriers are already locked in. Overly restrictive eligibility criteria, invasive procedures, unrealistic visit schedules, and sites without adequate capacity are all design-phase decisions that constrain recruitment before it begins. Applying behavioral science research during protocol development, including direct input from patients and clinicians, allows teams to identify and resolve these barriers while changes are still feasible and inexpensive to make.
3. How should sites be evaluated during feasibility assessments?
Traditional feasibility questions focus on surface-level factors like site location and investigator experience. A behavioral science approach asks more operationally meaningful questions: Are clinic hours compatible with working patients? Is the site geographically accessible to the target population? Do coordinators have the actual capacity to screen and enroll patients, or are they already overloaded? Observing real workflows rather than relying on survey responses uncovers the friction points that predict poor performance before they affect timelines.
4. What are the most common sources of burden for patients and sites during trial execution?
Technology is a consistently underappreciated source of friction. Trials routinely require sites to manage multiple disconnected software systems, each with separate access credentials and training requirements. Poor usability, unreliable functionality, and inadequate support create administrative burden that compounds over time. For patients, technology failures during eligibility screening or ongoing participation can result in missed enrollment or dropout. These are largely preventable problems that basic user testing and co-design could identify before a trial goes live.
5. Why is the Study Participant Feedback Questionnaire insufficient on its own?
The questionnaire relies entirely on quantitative, fixed-response items that can flag where problems exist but rarely explain why. When a patient reports that they did not receive adequate information before joining a trial, the response gives no insight into whether the information was unclear, too long, or missing entirely. Qualitative feedback, collected through open-ended interviews or structured observation, provides the contextual understanding necessary to develop solutions that actually address the underlying issue rather than treating symptoms.
6. How can sponsors use behavioral science to improve digital tool performance in trials?
The starting point is visibility. Many sponsors do not know how often their tools fail, where failures occur, or how they affect patient and site behavior. Systematically collecting mixed-method feedback, quantitative metrics alongside qualitative accounts, creates the evidence base needed to justify change and prioritize improvements. Once problems are understood, behavioral science provides frameworks for redesigning how people interact with information and technology, replacing guesswork with strategies grounded in how people actually process complexity and make decisions.
7. How does improving patient and site experience create a strategic advantage?
Sites operating under resource pressure increasingly select trials based on practical feasibility alongside scientific value. A sponsor with a reputation for reliable technology, manageable protocols, and responsive support is more likely to attract high-performing sites and retain them across studies. Patient-centered design similarly influences investigator willingness to enroll. Trials that demonstrably reduce burden stand out in a competitive landscape, and the evidence base for what works can be built through low-risk pilots on a single study before scaling.
8. Why does clinical trial diversity remain so limited despite years of attention?
A study published in Nature examining 341 approved drugs found that only 6% of pivotal phase III trials achieved enrollment reflecting the racial and ethnic makeup of the US population. The core problem is structural: trials have historically been designed around academic medical centers, standard business hours, and eligibility criteria that inadvertently exclude underserved communities. Late-stage recruitment fixes, such as translated flyers or revised advertisements, do not address these root causes and can reinforce mistrust when they rest on untested assumptions about community needs.
9. What does a behaviorally informed approach to diversity actually require?
It requires treating representativeness as a design constraint from the earliest stages of protocol development, not a recruitment target to pursue after enrollment opens. That means selecting sites in communities where underrepresented patients already receive care, offering flexible scheduling, childcare support, and transportation reimbursement, and building trust through investigators and coordinators who reflect the communities being recruited. Co-designing recruitment strategies with community members, rather than assuming what will resonate, is consistently more effective than surface-level adaptations.
10. How should sponsors begin incorporating behavioral science into their trial programs?
The lowest-risk entry point is a single study, either one that is already struggling with recruitment or retention, or one selected specifically to pilot the approach. Starting with structured research into patient and site experiences, mapping the data journey against real behavioral barriers, and running co-design sessions before protocol finalization generates actionable insight with limited overhead. The evidence produced can build internal confidence, justify broader investment, and create organizational knowledge that carries forward across the portfolio.
Recruitment delays, site disengagement, and underrepresentation are predictable consequences of designing trials without sufficient understanding of how patients and site staff actually experience them. Sponsors who build behavioral science capability systematically will find themselves with faster studies, stronger site relationships, and a more representative evidence base.
This FAQ is based on a recent three-part series by Olga Elizarova, DDS, MPH, MBA, senior consultant behavioral science, S3 Connected Health:
Part 1 — Why Recruitment Problems Start Before Recruitment
Part 2 — How Patient and Site Experience Shapes Trial Success
Part 3 — Why Diversity Must Be Built Into Trial Design
