Participatory study maps 27 levers for durable community research

A participatory systems science study identified 27 strategies that could help sustain community-engaged research within U.S. academic institutions, with participants prioritizing stronger relationships, more accessible funding for community partners and less burdensome administrative processes. By mapping interacting feedback loops rather than treating sustainability as an isolated problem, the study connected funding, institutional barriers and authentic partnerships to the academic culture that shapes all three. The research used an adapted form of group model building, a participatory systems science method in which stakeholders work with modelers to develop a shared account of the forces behind a complex problem.

Semi-structured interviews conducted from April 2024 through March 2025 supplied the evidence for an initial causal loop diagram, a visual tool linking variables through hypothesized cause-and-effect relationships. Separate September 2024 workshops were then held with principal investigators and study staff to reduce the possible influence of workplace power differences. Three investigators attended the principal-investigator workshop and seven study staff attended the staff workshop.

Participants reviewed the preliminary model, questioned or added variables, discussed missing mechanisms and proposed ways to improve community-engaged research. A causal loop diagram contains variables, directional connections and closed feedback loops. Positive links indicate that two variables change in the same direction, while negative links indicate changes in opposite directions.

A reinforcing loop tends to amplify growth or decline; a balancing loop tends to stabilize a system. The researchers used Vensim to develop and refine their diagrams after workshops, and then reviewed session notes to incorporate missing variables and connections. This adapted procedure began with interview-derived evidence rather than asking participants to build an entire model from a blank page, a design choice intended to make the final discussion more feasible and actionable.

Recommendations were de-duplicated, assigned to domains and levels of influence, and then examined with survey ratings and a structured plenary ranking exercise. Three reinforcing loops described potentially self-amplifying forms of community engagement. In the first, greater community involvement leads researchers to prioritize community needs, which strengthens authentic partnerships and encourages further involvement.

A second links authentic partnerships to more community-based research and more meaningful community outputs, which can support continued engagement. A third connects research activity to the growth and long-term sustainability of community-based programs: programs that improve community health outcomes may, in the model, reinforce community commitment to research participation. The analysis also contained balancing loops that constrain these reinforcing dynamics.

Misalignment between academic grant cycles and community timelines can reduce research productivity and funding availability, limiting the scope and durability of community-engaged work. Funding formed one of the study’s three focal domains, alongside institutional barriers and authentic partnerships. One reinforcing loop described the traditional academic incentive structure, in which peer-reviewed publications and quantitative findings are rewarded while community forums, brief reports, storytelling for advocacy and other locally relevant outputs may receive less recognition.

The authors interpreted the conventional productivity loop as likely exerting stronger influence in the current research climate than two countervailing loops in which wider acceptance of community-based methods could legitimize qualitative measures, relationship-building and other forms of research output. The model did not establish which loop would ultimately prevail. Instead, it showed how recognition of community-responsive work could redirect academic and funding incentives, while grant acquisition and the recruitment or retention of faculty engaged in community-based work could further reinforce institutional capacity.

The institutional-barrier model connected administrative and cultural pressures to the loss of both researchers and research capacity. A balancing loop linked the emotional toll of community-engaged scholarship to burnout, attrition and reduced productivity, which could weaken institutional momentum for this work. Other reinforcing loops suggested that accumulated institutional knowledge could encourage a shift in academic culture, revised policies and more appropriate support for community-engaged scholarship.

Recognition of such work in promotion and tenure processes appeared capable of increasing institutional support and funding opportunities, which could in turn reinforce its value. The authors situated burnout within these wider institutional dynamics rather than treating it only as an individual well-being issue. Their model suggests that policy alignment may support researcher retention and partnership continuity, but the study did not test whether particular reforms would produce either outcome.

Authentic partnerships formed the third major domain. Active community participation, researcher responsiveness, inclusive representation, mutual respect and trust appeared as mutually reinforcing features of durable collaboration. Research productivity and grant funding were also important because they support researchers and make fair compensation for community partners possible.

Balancing loops showed how schedule and resource conflicts can weaken this system: community priorities may not follow conventional grant cycles, and fixed budgets may not accommodate expenses such as food or participant incentives. The participants described these mismatches as potential sources of strain, reduced productivity and depleted financial resources. The model therefore links the durability of partnerships not only to interpersonal commitment but also to institutional funding, budgeting and administrative arrangements that determine whether community-engaged work can continue.

The January 2025 plenary session selected a leading strategy in each domain. For authentic partnerships, participants ranked embedding relationship-building within study-staff responsibilities and hiring team members from the community first. For funding, the top choice was to streamline and expand grant opportunities for community partners by simplifying applications and reporting and allowing community organizations to serve as primary applicants and recipients.

For institutional barriers, participants prioritized flexible payment processes, including simpler reimbursement and billing procedures. The wider set of 27 strategies included understanding community culture and needs before setting research priorities, creating community advisory boards, applying community-based participatory research principles, supporting bidirectional communication, diversifying grant-review panels, assessing community impact beyond quantitative metrics, extending pilot projects to at least two years and increasing post-award flexibility so project aims can reflect community priorities. Nineteen participants completed the online survey, rating each strategy on five-point scales for perceived feasibility and perceived impact.

Eight partnership- and funding-related strategies occupied the upper-right region of the authors’ feasibility-impact plot, indicating comparatively favorable judgments under those two dimensions. They included relationship-building combined with community hiring, understanding community context, community advisory boards and equitable compensation, bidirectional communication, mentorship, diversified grant-review panels, broader assessment criteria and stronger community-engagement requirements in funding announcements. These were perceptions reported by a small group rather than measured effects from an implementation trial.

Respondent numbers also varied by domain—19 for authentic partnerships, 15 for funding and 13 for institutional barriers—so the ratings should not be interpreted as population estimates or proof that any strategy will work as intended. The multi-stage design gave principal investigators and study staff several opportunities to examine the same system, first through interviews, then in role-specific workshops, a survey and a final plenary. Participants came from varied roles, areas of expertise, geographic locations and levels of community-engaged research experience, helping the researchers identify both shared and role-specific challenges.

The authors argue that beginning with interview evidence made the adapted group-model-building approach more likely to produce actionable interventions than beginning with an empty diagram. The diagrams also exposed consequences that a simple list of barriers could miss: an effort to recognize community work could strengthen research capacity and funding, while inflexible grants could simultaneously constrain productivity and community participation. This is a model-based interpretation developed with participants, not a quantitative demonstration of causal effects in academic institutions.

The findings have important limitations. Workshop and plenary participation was small relative to the 48-person interview sample, limiting the breadth and completeness of feedback. The causal loop diagram represented a cross-sectional view of current systems rather than changes over time, and the three preselected domains may have excluded other influences on sustainability.

Community partners themselves did not participate in the model-building process. Institutional leaders and other stakeholders were also not included, although the authors acknowledge that their perspectives could clarify why reforms often fail to gain traction. Focusing on academic settings was a deliberate scope choice because institutions govern policies that condition community engagement, but it means the model does not represent every part of the wider research ecosystem.

The evidence therefore identifies participant-informed options for coordinated action and further testing; it does not establish that any one intervention will sustain partnerships or improve community health.

Subject of Research: Participatory systems analysis of sustainability strategies for community-engaged research in U.S. academic institutions.

Article Title: Identifying leverage points to sustain community-engaged research infrastructure in academic systems: a participatory systems science approach

Article References: Đoàn, L. N., Thompson, R. L., Chan, S. W., Chebli, P., & Yi, S. S. (2026). Identifying leverage points to sustain community-engaged research infrastructure in academic systems: a participatory systems science approach. Frontiers in Public Health, 14, Article 1970793. https://doi.org/10.3389/fpubh.2026.1970793

Image Credits: AI Generated

DOI: 10.3389/fpubh.2026.1970793

Keywords: community-engaged research, systems science, group model building, causal loop diagrams, research sustainability, community partnerships, research funding, academic institutions, health disparities, participatory methods, Identifying, leverage