Community Engagement and Implementation Science Could Fix Stroke Trials

Stroke clinical trials have saved millions of lives, but the machinery behind them is quietly failing. Trials enroll more slowly than planned, burn through budgets, and sometimes lack the statistical power to detect the very effects they were designed to find. Even when trials succeed, their results often fail to reach the patients who need them. A new perspective published in Annals of Clinical and Translational Neurology argues that the problem is not the science itself but the way trials are implemented, and it proposes a pragmatic framework that treats clinical trials as implementation challenges in their own right, solvable with the same tools that have transformed other areas of medicine.

The authors, led by researchers including Lesli E. Skolarus, point to a familiar litany of failures. Many stroke trials finish later than expected, inflating costs and delaying scientific progress. When enrollment targets are missed, the resulting loss of statistical power can render years of work inconclusive. Trials may also produce results with limited applicability to routine practice, for example when participants do not receive all standard-of-care treatments such as endovascular therapy. And even practice-changing findings can languish: the limited adoption of dual antiplatelet therapy for high-risk transient ischemic attack and minor stroke demonstrates how slowly evidence can translate into care. These challenges, the authors argue, demand approaches that improve trial efficiency, enhance clinical relevance, and accelerate translation into real-world practice.

The central insight of the framework is deceptively simple. A clinical trial is not merely a test of a treatment; it is an intervention that must be adopted by trial sites, integrated into clinical workflows, embraced by patients and caregivers, and coordinated across health systems. Viewed this way, every trial is an implementation problem. Community engagement helps ensure that trials address clinically meaningful questions aligned with the needs and priorities of affected constituents, while implementation science offers structured methods to identify multilevel determinants of success and to select strategies that support trial feasibility, conduct, and eventual translation. Evidence from outside stroke, particularly from COVID-19 vaccine trials and public vaccination rollouts, suggests that pairing community engagement with implementation science can improve trial efficiency, quality, and relevance.

The framework unfolds across four phases, beginning with community partnership. The first task is identifying which partners are needed and determining the optimal level of engagement. Potential constituents span a remarkably wide range: stroke survivors and caregivers, patient advocacy organizations, site principal investigators and clinical teams, healthcare organizations, community-based organizations, employers and government agencies as purchasers, insurers as payers, policymakers, and drug and device manufacturers. The right mix depends on the trial’s objectives and setting. An acute stroke trial might partner with emergency medical services and emergency departments for recruitment, a clinical trial network for conduct, and hospital administrators or payers to address feasibility, reimbursement, and downstream adoption. A recovery trial for chronic stroke survivors, by contrast, might recruit through community organizations, co-develop the intervention with occupational therapists, and engage local government or insurers to sustain the intervention in community settings.

The level of engagement matters as much as the roster of partners. The authors envision most stroke trials benefiting from either consultation or sustained involvement. In the consultation model, constituents provide input at defined stages through focus groups, trial design studios, and, for trials conducted under an exception from informed consent, community consultation and public disclosure. Consultation suits acute stroke trials, where narrow eligibility windows, protocol-driven care, and emergency consent exceptions leave little room for deeper involvement. Prevention and recovery trials, with longer horizons, may instead sustain a community advisory board that influences the trial across its entire lifecycle. Studies co-led by constituents appear more frequently in hybrid effectiveness-implementation research, such as efforts to increase acute stroke treatment rates in underserved communities.

The second phase embeds these perspectives into trial conception and design. Community partners can shape the research question so that it reflects the priorities that matter most to patients, caregivers, and communities, and can inform feasibility, acceptability, and equity considerations from the outset. The research team can then apply implementation science frameworks prospectively, most notably the Consolidated Framework for Implementation Research, or CFIR, which organizes anticipated determinants across intervention characteristics, inner and outer settings, individual characteristics, and implementation processes. Prior efforts to address trial barriers have focused mostly on participant-related issues. The CFIR deliberately broadens that view, prompting systematic evaluation of site-level, organizational, and system-level obstacles alongside participant concerns.

This early assessment surfaces the contextual frictions that so often derail stroke trials: transportation constraints, caregiver burden, workflow pressures in emergency departments, reimbursement worries, and health-related social risks that shape whether survivors can participate and whether sites will adopt a study. Naming these barriers exposes the inevitable trade-offs in trial design, where many decisions lack a single right answer yet directly affect participant experience, feasibility, cost, and future adoption. Trialists may prefer longer, more frequent in-person outcome assessments to capture exploratory endpoints, while participants facing transportation barriers may prioritize shorter, remote assessments. Teams may design higher-intensity interventions to maximize efficacy, while health systems and payers favor simpler, lower-cost approaches that integrate readily into routine care. By surfacing these tensions during conception and design, the framework lets trialists navigate them transparently and refine protocols against real-world constraints.

The third phase carries the approach into trial conduct, supporting efficient rollout and ongoing adaptation. Brief interviews, workflow mapping, surveys, and data review during launch and early enrollment allow teams to identify emerging barriers across CFIR domains. In partnership with engaged constituents, those determinants are then mapped to evidence-based implementation strategies. If enrollment is limited by emergency department workflow pressures, the response might include identifying site champions, redesigning workflows, or restructuring care so that study introduction is embedded in routine clinical practice with a handoff to the research team. If retention suffers from caregiver burden or transportation challenges, remote assessments or flexible scheduling may be warranted. This iterative loop strengthens efficiency while keeping the trial aligned with constituent priorities.

The fourth phase extends engagement into interpretation, dissemination, and translation. Implementation science broadens evaluation beyond efficacy endpoints to include implementation outcomes such as penetration and sustainability, fidelity to trial procedures, feasibility of meeting enrollment goals, and timeliness of completion. Engaged constituents can contextualize results and shape dissemination strategies for audiences as varied as stroke survivors with cognitive, language, or activity limitations, caregivers, clinicians, administrators, and policymakers. Early involvement of payers, healthcare organizations, and policymakers can smooth the path to reimbursement and sustainability if findings change practice. Once efficacy and safety are established, hybrid effectiveness-implementation designs allow clinical outcomes and implementation strategies to be evaluated simultaneously, accelerating adoption, an approach already used in stroke primary prevention and acute treatment and emerging in posthospital stroke services.

The authors are candid about the limitations. Sustaining constituent engagement requires resources that are often scarce, and tokenistic engagement, in which feedback is solicited but never incorporated, remains a real risk. There is also limited evidence comparing the effectiveness of different engagement levels; rigorous evaluation would require randomizing trials to distinct engagement strategies. Still, the framework offers a coherent answer to a stubborn problem: by aligning trial design and conduct with the needs of the people affected by stroke, and by deploying implementation strategies against multilevel barriers, stroke trials could become faster, more relevant, and far more likely to change practice, advancing stroke health for all.

Subject of Research: Integrating community engagement and implementation science into stroke clinical trials

Article Title: Advancing Stroke Clinical Trials Using Community Engagement and Implementation Science Approaches

Article References: Skolarus, L. E., Brown, D. L., & Boden‐Albala, B. (2026). Advancing Stroke Clinical Trials Using Community Engagement and Implementation Science Approaches. Annals of Clinical and Translational Neurology, 13(10), 2148-2153. https://doi.org/10.1002/acn3.70461

Image Credits: AI Generated

DOI: 10.1002/acn3.70461

Keywords: stroke, clinical trials, community engagement, implementation science, CFIR, trial recruitment, patient engagement, hybrid effectiveness-implementation designs, translational research, health equity, stroke prevention, dissemination