Behavioral Science in Clinical Trials: Part 2 — How Patient and Site Experience Shapes Trial Success

Clinical trials often struggle because they become overly complex, resulting in a poor experience for both patients and sites, making participation and study execution difficult.

Challenges such as confusing information, unreliable technology, and inefficient processes can quietly accumulate, ultimately affecting site engagement and patient willingness to continue. Standard trial operational outcomes, such as screening and enrollment rates, are lagging and act only as surface-level indicators. They offer insights only after issues have accumulated, and they fail to reveal the underlying patient and site-level experiences that frequently drive these poor outcomes.

This article—the second of our three-part series on applying behavioral science and service design to improve clinical trials—examines how a lack of understanding of the importance of patient and site experiences, and the role they play in successfully delivering a clinical trial, leads to inefficiencies. It discusses common sources of burden, especially those related to digital tools, that are often neglected, and explores how research, behavioral science, and service design can help reduce these obstacles in a practical, low-risk manner. Additionally, it considers how enhancing patient and site experiences can transcend mere problem-solving and evolve into a strategic advantage in the increasingly competitive landscape of clinical research.

The current system for collecting feedback—and its limitations

The Study Participant Feedback Questionnaire is currently the sole tool for measuring patient experiences in clinical trials, but it has significant limitations and is used only sporadically. It relies entirely on quantitative data, asking patients to select fixed options without allowing for detailed feedback. While this can highlight issues, it lacks the qualitative insights necessary to understand the underlying reasons and to understand what kind of solutions could be effective at improving it.

For example, when patients are asked if they received all the information they needed before joining a trial, a simple disagreement gives no context on the issue, whether it was unclear, too lengthy, or missing entirely.

This is why qualitative feedback is so important. It tells us both what is happening and why, allowing clinical teams to leverage these research insights to develop solutions that address real needs.

Despite its importance, a mixed-method approach is often overlooked due to assumptions about the complexity of setting it up, a lack of experience in this approach, beliefs that it will add burden to the patient and to the site’s practical challenges in vendor selection and additional consent process, and fears that additional conversations may overwhelm participants.

What the lack of insight looks like in practice: pain points for sites and patients

Anything that improves or worsens the experience of sites and patients in clinical trials can have a serious impact on recruitment, retention, and overall trial success. As discussed in Part 1 of this series, these remain some of the biggest challenges in clinical research. Against that backdrop, any avoidable source of friction deserves close attention.

Technology is a clear example. Although intended to facilitate clinical trials, it often causes significant frustration for both sites and participants.

Most trials use a range of digital tools, often requiring sites to manage multiple software systems within a single trial. Each tool has its own access requirements and training, even if teams are familiar with the technology from other trials. The lack of integration between systems leads to inefficiency, increased cognitive load, and additional administrative work. Basic tasks like logging in or switching between platforms can disrupt daily operations.

This challenge is compounded by the fact that many tools are not designed with end users in mind. Poor usability, unintuitive workflows, and fragile functionality are common. Issues that could be identified and resolved through basic user testing are often not discovered until the trial is active, with a significantly more severe impact downstream. The result is a buildup of preventable challenges: too many separate software systems, excessive training, software and equipment technical issues, and a lack of high-quality, timely customer support. Although the intent of these technologies is positive, their design and implementation often complicate rather than simplify.

For patients, these issues have real consequences. In some studies, proper use of digital tools is required for eligibility screening or ongoing trial participation. When technology fails, rather than the patient, people fail to be enrolled onto trials or discontinue their participation in the trial entirely due to the technological challenges. During long procedure-intensive visits, a single technical problem can waste hours of effort, leading to repeated procedures or rescheduled visits. Many patients simply decide not to continue.

How research, behavioral science, and service design can reduce the burden

Many pharma companies and CROs don’t fully understand why their tools fail, how often they fail, or where the issues lie. Without that visibility, it is difficult to justify change, and the same problems repeat from trial to trial.

The first step is to begin measuring the appropriate metrics. It’s important to collect data on patient satisfaction with the screening process, their understanding of the study and what is expected from them, patients experience with the site staff, convenience of the visits timing, impact on their daily activities, screen failures due to technical issues with digital tools and equipment, and many others. While quantitative research can show where issues arise, qualitative open-ended feedback helps explain the reasons behind them. Together, these insights reveal what’s going wrong and why. However, gathering feedback is only helpful if it’s shared. Feedback from patients and sites needs to reach everyone involved in designing protocols and choosing vendors, or else the same issues will keep happening in future studies.

Once problems are understood, applying behavioral science can help create effective solutions. It provides evidence-based methods for improving how people interact with trial information, tools, and tasks. For example, when patients report that trial information is confusing or overwhelming, behavioral science helps identify the cognitive barriers involved and guides redesigns that improve comprehension and engagement. This approach replaces guesswork with strategies grounded in how people actually process information and make decisions.

Service design complements this by improving efficiency across the trial journey. Even without rebuilding digital tools, service design can reduce predictable points of failure by reorganizing processes and support structures. Identifying critical moments, such as screening visits or time-sensitive data capture, allows teams to embed the right support at the right time, reducing the risk of costly disruptions. Where resources allow, service design also informs broader improvements by mapping both the patient-facing and site-facing experience and identifying high-impact opportunities for change.For example, creating a service that helps engage patients interested in a trial and answers their questions promptly when they contact the site, even when staff are busy, rather than keeping them waiting for hours or days.

Importantly, this does not require a large-scale transformation from the outset. Sponsors can start by piloting these approaches on a single trial, either one that is already struggling or one selected to test feasibility. This lowers risk, builds internal confidence, and creates tangible evidence of value.

Translating those insights into a strategic differentiator for your clinical trial

Clinical trial sites are facing increased pressure, with many studies competing for the attention of site staff and limited resources to manage them. When selecting which trials to participate in, sites prioritize not only the scientific value but also the practical aspects of conducting the study. Sites tend to select trials that offer better overall experience for them and their patients, including feasible protocols, lower overall burden, and reliable digital tools. If a site has previously experienced difficulties with the sponsor's digital systems or vendors, it may hesitate to engage in similar studies in the future.

The same goes for patient experience. Investigators often evaluate whether a trial may create undue burden for patients with excessive visits or unnecessary procedures. Even if a treatment shows promise, they might opt out if they think the patient's experience will be poor. Trials that leverage patient-centered design, get feedback from actual patients on the protocols early in the protocol design phase and adjust it based on that feedback, tend to stand out.

In summary

Many clinical trials face challenges because the experience of running or participating in them is often unnecessarily difficult. When trials stall, the typical response is to apply more pressure on the site staff without addressing underlying causes.

This article proposes a more effective approach: proactively measuring patient and site experiences through research and identifying sources of friction. By leveraging behavioral science and service design, we can develop solutions that address unmet patient needs and are grounded in evidence about what works. This method enables sponsors to uncover actionable insights and achieve improvements that traditional approaches often overlook. Additionally, it represents a low-risk intervention that can be piloted in a single study and scaled up once proven beneficial.

As competition for patient participation grows, understanding and improving patient and site experiences becomes crucial. Sponsors who take proactive steps to improve both will ensure their trials are not only run on time but also stand out to patients and sites in a crowded trial landscape.

Olga Elizarova, DDS, MPH, MBA, senior consultant behavioral science, S3 Connected Health