Engagement of understudied populations as community change: The South Texas ADRC model

Abstract

Many populations experiencing the highest burdens of Alzheimer's disease and related dementias remain understudied, in part because traditional recruitment and retention models are insufficient to support sustained engagement. The Outreach, Recruitment, and Engagement Core (OREC) of the South Texas Alzheimer's Disease Research Center reconceptualized participant recruitment as a long‐term system change in a Hispanic‐majority, urban–rural region. OREC institutionalizes shared power through community advisory governance, aligns research protocols with local lived realities (through patient navigators, community health workers/promotores, and decentralized access points), and employs a data‐driven feedback loop for continuous improvement. In 1 year, 46 outreach events touched 10,134 individuals (71% Hispanic) and generated 172 new registry enrollments. Qualitative engagement (focus groups/key‐informant interviews) progressed to high‐sensitivity topics (e.g., brain donation), signaling maturation of trust. This shift from outreach to reciprocity infrastructure reflects a systems‐level change, one that lowers barriers, builds trust, and enables research participation to become routine rather than exceptional.

Highlights

• Recruitment of participants for Alzheimer's disease and related dementias (ADRD) research is a long‐term system change.

• The recruitment paradigm shifts from one‐off transactions to building relationships.

• Resources spent on engagement infrastructure are investments that reduce waste and improve data quality.

• Relational governance and reciprocity infrastructure lower barriers and build trust.

• Navigation, community health workers/promotores, and decentralized access points align protocols to life of participants.

1. RECRUITMENT AS SYSTEM CHANGE

Effective recruitment strategies are essential for research on Alzheimer's disease (AD) and AD‐related dementias (ADRD). AD and ADRD constitute a U.S. public health crisis, ¹ and the burden of dementia falls disproportionally on several racial and ethnic groups, including Hispanic/Latino communities. ² , ³ , ⁴ In South Texas, where the majority of the population is Hispanic, dementia risk is amplified by persistent poverty, ⁵ neighborhood disadvantage, limited access to specialty care across urban–rural settings, and a high cardiometabolic burden. ⁴ , ⁶ , ⁷ , ⁸ , ⁹ In parts of the Texas border region, AD prevalence among adults ≥65 years may reach ≈13%–18%. ¹⁰ The South Texas Alzheimer's Disease Research Center (STAC) was established to pair mature scientific platforms with settled and sustainable community trust, cultural competence, and broad access across this high‐need region.

Despite the clear epidemiologic imperative to generate evidence applicable across the U.S., the populations most affected by AD/ADRD remain grossly underrepresented in the evidence base used to shape biomarkers, diagnostics, and therapeutics. AD/ADRD neuroimaging cohorts and drug trials in the United States report limited racial/ethnic heterogeneity, a disparity driven by restrictive eligibility criteria, study burden, and access barriers that tend to make it difficult for individuals with constrained resources or comorbidities to participate in research. ¹¹ , ¹² , ¹³ , ¹⁴ Recruitment and retention challenges are longstanding in AD trials and cohorts. ¹⁵ Reviews emphasize that past initiatives have been fragmented and insufficient, calling for stronger methodological standards and consistent measurement of engagement outcomes. ¹⁶

The gaps in recruitment cannot be closed by simply doing “better recruitment” framed as one‐time outreach campaigns. Underrepresentation is produced by interacting determinants at multiple levels: community capacity and lived constraints; clinical and health‐system referral pathways; and research‐enterprise design choices (e.g., language accessibility, consent workflows, data systems, and return‐of‐results). Treating recruitment as a system change is, therefore, a scientific necessity. Successful recruitment and retention entail building durable, bidirectional infrastructure that lowers barriers, increases trust, and makes research participation a routine, easy option. Implementation science offers a lens for assessing recruitment using performance metrics beyond raw enrollment counts (e.g., evaluating acceptability, adoption, feasibility, fidelity, penetration, and sustainability of engagement efforts). ¹⁷

2. FROM TRANSACTIONAL RECRUITMENT TO RECIPROCITY INFRASTRUCTURE

The persistence of underrepresentation in research, despite decades of “outreach” efforts supported by the National Institutes of Health (NIH) and other funding bodies, suggests that the standard recruitment model is structurally flawed when applied to understudied populations. We refer to this standard approach as the “Transactional Model.” ¹⁸ , ¹⁹ In this paradigm, recruitment is operationalized as a discrete exchange: a researcher obtains data (e.g., biospecimens, cognitive tests) from a participant in exchange for compensation (monetary, return of results, or some other incentive). The interaction is bounded by the study visit; the relationship typically ends when data collection is complete. 

FIGURE 1.

Transactional model versus reciprocity infrastructure—conceptual contrast.

The Transactional Model assumes that “barriers to participation” are primarily informational (communities simply do not know about the study or understand the importance of research) or logistical (individual's lack transportation). Consequently, conventional “recruitment strategies” focus on better marketing through, for example, brochures and radio spots, and providing transactional support such as taxi vouchers and monetary incentives. These tactics may yield enrollment in the short term, but they fail to generate durable retention or community trust that will support long‐term studies or future participation in new studies. In the context of AD/ADRD research, which increasingly demands longitudinal follow‐up, ¹⁵ invasive procedures such as lumbar punctures and positron emission tomography (PET) scans, and post‐mortem brain donation, the Transactional Model is fundamentally mis‐specified. It produces “brittle” cohorts that suffer from non‐random attrition, as those with the highest social and economic vulnerabilities (who are often those with the highest risk of disease) drop out when the small incentives are not sufficient to overcome the structural friction of their lives. Remuneration practices alone rarely resolve these selection and attrition biases, ²⁰ especially without parallel investments to reduce burden and increase feedback to participants.

In contrast, we propose a model of reciprocity infrastructure that establishes community‐engaged capabilities that make inclusive participation possible across studies and over time. Instead of one‐off transactions, reciprocity infrastructure treats engagement as an ongoing relationship. We use this term to describe a system encompassing (1) culturally and linguistically congruent workforce (e.g., community health workers [CHWs], also known as promotores), (2) navigation supports (e.g., guidance, find services and resources) to mitigate logistical barriers like transportation and scheduling, (3) decentralized access points bringing research opportunities into community settings, and (4) routine feedback loops providing transparent communication of results and health information back to participants. These capabilities shift the unit of analysis from a study visit to the system's long‐term capacity to engage the community (see Figure 1).

The STAC was established in 2021 as a partnership between the University of Texas Health Science Center at San Antonio (UT Health San Antonio) and the University of Texas Rio Grande Valley (UTRGV). The STAC provided an opportunity to fundamentally re‐engineer the relationship between the research enterprise and the Hispanic‐majority community of South Texas. The STAC Outreach, Recruitment, and Engagement Core (OREC) was designed not simply to “recruit subjects” but to enact system change in how research engages with the community.

This perspective paper argues that AD/ADRD research requires a paradigm shift from short‐term transactional recruitment to reciprocity infrastructure. This shift is not ad hoc; it is grounded in a rigorous “theory stack” that integrates three complementary frameworks:

1. Institute of Medicine (IOM) Framework for Collaborative Public Health Action: Provides the macro‐level roadmap for community change, moving engagement from episodic events to standing coalition ²¹ , ²² (see Table 1).

2. Consolidated Framework for Implementation Research (CFIR): This framework provides meso‐level diagnostic tools to identify and address multi‐level barriers to implementation ²³ (see Table 2).

3. Applied Behavior Analysis (ABA): Provides micro‐level behavior‐change principles to ensure engagement strategies are effective, reproducible, and reinforcing for participants. ²⁴

TABLE 1.

IOM/Fawcett collaborative public health action pathway mapped to STAC OREC operations.

Phase/core processes	Implementation intent	STAC OREC operationalization (observable signals)
Assessment & collaborative planning • Analyze information • Establish shared vision/mission • Develop strategic action plans • Build/strengthen partnerships	Define the equity problem using local context; align partners around shared aims; specify measurable work.	Standing CABs; recurring pláticas and co‐produced community forums; co‐design of outreach scripts, materials, and venues; cross‐institution steering routines and partner memorandum of understanding.
Implementation & action • Develop leadership • Mobilize resources • Implement community/system changes • Provide supports that reduce access barriers	Translate plans into standing capabilities; redistribute power and resources; make participation feasible and trustworthy.	Investment in CHWs/promotores and participant navigation; bilingual consent and navigation; clinic‐to‐community pathways (including home/community entry points when appropriate); workforce development (CHW continuing education; mentoring REC Scholars).
Evaluation & sustainability • Document progress and use feedback • Make outcomes matter • Communicate results • Institutionalize effective practices	Measure more than enrollment; use feedback loops to improve; embed practices so they persist beyond single studies.	Funnel metrics and contact‐history tracking; CheckBox–REDCap–EHR linkages (Epic/MyChart) for continuous quality improvement; routine feedback to partners; institutionalization via a planned Family Member Registry and workforce pipelines.

Abbreviations: CABs, community advisory boards; CHWs, community health workers; EHR, electronic health record; OREC, outreach, recruitment and engagement core; REC, research education component; REDCap, research electronic data capture; STAC, south texas Alzheimer's disease research center.

TABLE 2.

CFIR domains: Determinants mapped to reciprocity infrastructure in STAC OREC.

CFIR domain	Priority constructs	STAC OREC practices (examples)	Why this supports reciprocity (vs transactions)
Intervention characteristics	Adaptability; complexity	Bilingual/culturally congruent materials and formats; tailoring engagement without losing protocol integrity; bundling early steps (screening/consent) through community entry points when feasible.	Reduces burden and mismatch between protocol design and lived constraints, lowering differential exclusion.
Outer setting	Patient needs & resources; External policy/incentives	Navigation for transportation, scheduling, and reimbursements; CHWs/promotores to address language and trust; alignment with equity expectations for ADRCs and trials.	Shifts the center of gravity from paying for time to removing structural barriers and standardizing equitable access.
Inner setting	Structural characteristics; Readiness; Networks/communication	Cross‐institution governance and co‐ownership of standard procedures; bilingual workforce solutions; routine cross‐core integration so engagement is embedded in scientific workflows.	Prevents reversion to transactional shortcuts by routinizing inclusive practices as “the way work is done”.
Characteristics of individuals	Knowledge/beliefs; Self‐efficacy	Training and tools for culturally congruent communication and addressing concerns about procedures; continuing education for CHWs and primary care partners.	Builds scalable competence for trust‐building rather than relying on a few individuals.
Process	Planning; Reflecting & evaluating	CAB‐ and qualitative‐informed planning; funnel tracking; rapid‐cycle review and refinement using implementation outcomes.	Creates a learning system where engagement strategies are testable and improvable, not ad hoc tactics.

Abbreviations: ADRCs, Alzheimer's disease research centers; CAB, community advisory board; CHWs, community health workers; OREC, outreach, recruitment and engagement core; STAC, south texas Alzheimer's disease research center.

By triangulating these frameworks, the STAC OREC has built a model that converts community engagement from a “cost” into a “scientific asset,” yielding high‐fidelity data, robust retention, and meaningful community capacity, which in turn supports the collection of high‐fidelity data (See Figure 2 for a summary of each framework's role). The following sections detail the theoretical underpinnings, operational mechanics, and observed outcomes of this model, offering a blueprint that may be generalizable across the national Alzheimer's Disease Research Centers (ADRCs) network.

FIGURE 2.

Why a stack framework (IOM + CFIR + ABA) is used. ABA, applied behavior analysis; CABs, community advisory boards; CFIR, consolidated framework for implementation research; IOM, institute of medicine; STAC, south texas Alzheimer's disease research center.

3. THE STAC OREC MODEL: INFRASTRUCTURE AND OPERATIONS

A central thesis of the STAC OREC model is that no single framework is sufficient to address the complex ecosystem of underrepresentation. Public health frameworks often lack granular behavioral mechanisms; behavioral frameworks may ignore organizational context; and implementation science frameworks can overlook the power dynamics in community relations. Therefore, STAC employs a theory stack, using specific frameworks to address specific dimensions of the recruitment challenge, as summarized.

In practice, the STAC OREC converts these frameworks into an operational model that bridges academic and community systems. OREC functions as the connective tissue between two institutions (a mature research hub in San Antonio and a newer university in the Rio Grande Valley) and the community at large. Four core operational domains illustrate how the model works:

Relational governance. OREC operationalizes shared power through standing community advisory boards (CABs) and distributed leadership. The CAB functions as a recurring governance structure with sustained membership, regular monthly meetings, and defined roles in reviewing protocols, aiding in outreach strategies, and assessing communication materials. It plays a key role in ensuring cultural alignment with the community and shared decision‐making. CAB members, community stakeholders, and individuals with lived experiences co‐guide priorities, acceptable procedures, communication approaches, and definitions of meaningful outcomes, following best practices for coalitions and the principles of community‐engaged research. ²¹ , ²² , ²⁵ , ²⁶ In South Texas, this relational governance is crucial: STAC spans an asymmetric partnership (a long‐established academic health center and a newer university), and OREC's shared decision‐making structures help stabilize the alliance with transparency and co‐ownership of engagement processes.

Governance is also treated as a workforce strategy: OREC invests in capacity‐building that can outlast a single grant cycle, including mentoring pathways for early career investigators such as those who are Scholars in the Research Education Component (REC) of the STAC and continuing education for CHWs and primary care partners. In other words, local leadership and human capital are viewed as implementation determinants to strengthen recruitment and community engagement, rather than downstream byproducts.

Articulation work: bridging protocols to lived realities. OREC performs the often‐invisible labor of synchronizing research protocols with participants’ daily realities. This includes providing participant navigation services to reduce logistical barriers (scheduling appointments, arranging transportation, streamlining reimbursements) and deploying CHWs/promotores as culturally and linguistically concordant liaisons who can address concerns and facilitate understanding. ²⁷ , ²⁸ In South Texas, OREC has developed “community‐first intake” pathways, which include informal pláticas (community chats) and co‐produced community events alongside clinic‐integrated approaches, such as electronic health record (EHR)–supported messaging and referral workflows. This dual approach ensures that the pathways into research participation are not limited to specialty clinics; community members can explore opportunities to participate in research studies through familiar, trusted venues.

OREC also links engagement to reciprocal value. For example, OREC initiatives integrate dementia support and education into research activities with clinician‐promotores teams extending care into participants’ homes and turning research visits into opportunities for service. Services provided during home visits include consent/re‐consent, blood pressure checks, medication reviews, resolution of barriers to care, and navigation to community or medical resources. Services are provided in either English or Spanish, according to the participant's preference. If a longitudinal cohort participant does not respond to calls, a home visit is scheduled. More recently, we incorporated home visits into our processes to assess the home environment and provide advice on opportunities for physical activity, nutrition, cognitive stimulation, and family support. Partnerships with local organizations make the research enterprise tangibly beneficial for families and thereby strengthen trust and retention. ¹ , ²⁷ Co‐design with stakeholders is a continuous process that helps shape procedures and messaging, and these inputs are documented through multi‐stakeholder methods and advisory council processes. ²⁹ , ³⁰

Routine reciprocity: closing the loop. A critical failing of the Transactional Model is data and sample extraction without long‐term engagement. The STAC model counters this with routine reciprocity, operationalized through several tiered practices. First, participants receive significant feedback on their health metrics collected during study visits. Routine metrics, such as blood pressure and other vital signs, are returned immediately to provide real‐time awareness. For conventional routine laboratory tests, results are returned according to participant preference, either during individualized educational sessions or at the point of care, provided the tests are performed in a CLIA‐certified environment. Specialized biomarkers follow a more stringent protocol: they are not returned unless analytically confirmed and CLIA‐certified and are communicated only to treating clinicians upon the participant's explicit request. Impairment status informs what results (if any) are actionable, particularly given current disease modifying therapies.

Beyond generating clinical data, OREC conducts extensive educational workshops (pláticas) on brain health, caregiving, and navigating the healthcare system for research participants, so that their involvement in research becomes a gateway to broader health literacy. Finally, large‐scale community events such as the annual Memory & Heart Connections forum are co‐hosted with community partners, including local school districts and churches, ensuring that the agenda reflects community priorities rather than just academic interests.

Data infrastructure for continuous improvement. OREC employs a robust data system to monitor the quality of the engagement process itself. Event data are collected on electronic forms (using tablets) and on paper forms, with consent for registry contact. Repeat attendees are tracked using registry contact logs. The two main opportunities to collect information are during event registration and during attendance at the event. Using a documentation system ³¹ and Research Electronic Data Capture (REDCap)–based tracking (and in San Antonio, integration with clinical systems [Epic/MyChart]), OREC tracks the recruitment funnel (reach → interest → contacts → registry enrollment → study enrollment → visit completion → retention). This process facilitates the identification of drop‐off points (for instance, if many participants fail to schedule a follow‐up, or if certain zip codes have higher no‐show rates) so that the team can investigate causes and intervene promptly. ³² Key implementation outcomes are also tracked (e.g. time from referral to enrollment, participant satisfaction feedback), and these data are regularly reviewed with both the team and community for rapid‐cycle improvements. In this way, OREC treats engagement itself as a measurable, improvable process and applies the same quality improvement principles used for clinical workflows. ¹⁷

Looking forward, OREC is positioned to codify reciprocity with explicit targets (e.g., retention benchmarks; uptake of higher‐burden procedures among eligible participants) and to test discrete engagement elements using pragmatic designs (e.g., stepped‐wedge or adaptive trials), while tracking cost and fidelity alongside inclusion outcomes.

4. ADDRESSING THE CONDITIONS OF SOUTH TEXAS

It is important to note that STAC operates in a Hispanic/Latino‐majority region where socioeconomic disadvantage and high cardiometabolic risk factors shape the dementia burden. ⁴ , ⁶ , ⁷ , ⁹ Here, inclusion in research requires more than participant “interest”. Rather, the research system must actively work to reduce the costs of participating in research; these costs include the time required to participate in the study, to travel to the clinic, and to navigate the study‐associated bureaucracy; and the stress and confusion associated with language barriers. The research system must actively build sufficient trust to sustain the multi‐year participation required for most AD/ADRD basic science and translational research. ¹⁵ , ¹⁶ For the STAC, an operational reality in this setting is the institutional asymmetry: a well‐resourced clinical hub in San Antonio versus a newer, resource‐limited medical campus associated with a university in the Rio Grande Valley. OREC addresses this by designing a dual‐pathway recruitment strategy. At the clinical hub, recruitment and retention efforts are embedded into high‐volume clinical workflows where specialty care is readily available. In the resource‐limited setting where specialty care is scarce, community‐anchored pathways to research are created so that the opportunity to participate in studies does not depend solely on proximity to an academic clinic. ³³

Sociocultural characteristics and of the community also inform design choices. Strong family networks and tight‐knit communities can greatly support longitudinal participation if engagement is culturally congruent and family‐centered. Conversely, historical trauma and institutional mistrust can suppress enrollment and limit uptake of higher‐burden procedures such as lumbar punctures. Thus, OREC emphasizes relationship‐based governance involving stable CABs, recurring dialogue with the community, and co‐production of priorities with the community partners. This aligns with community‐based participatory research principles and echoes evidence that recruiting underrepresented groups requires greater methodological rigor and sustained engagement efforts. ¹⁶ , ²⁵ , ²⁶

In operational terms, these context considerations have been translated into infrastructure rather than one‐off tactics (see Table 3). For example, to mitigate geographic and economic barriers, OREC uses decentralized entry points (e.g., churches, community centers) and navigation support that coordinates transport and scheduling solutions. To accommodate linguistic and cultural needs, OREC employs bilingual, culturally concordant staff (e.g., CHWs/promotores) to facilitate research protocols despite social barriers. Such strategies are supported by broader evidence that CHW interventions can improve care engagement among vulnerable populations while also being cost‐effective. ²⁷ , ³⁴ To extend reach in low‐specialty settings, OREC additionally invests in capacity‐building and clinician partnership models that disseminate dementia‐relevant knowledge and strengthen referral pathways across primary care and community systems. ³⁵

TABLE 3.

South Texas determinants and the STAC OREC design response (integrated).

Context determinant	What it produces for AD/ADRD research	OREC design response (observable signals)
Geographic dispersion; limited transportation (colonias/rural)	High transaction costs → selection bias, no‐shows, attrition.	Decentralized entry points; satellite access; trusted venues.
Poverty; competing work/care demands	High‐effort participation → differential exclusion and attrition.	Navigation for scheduling, transport options, reimbursements and in‐home visits.
Hispanic/Latino majority; strong family networks	Retention asset when engagement is family‐centered and in‐language.	Bilingual/bicultural teams; in‐language governance and materials.
Historical trauma; institutional mistrust	Lower enrollment; reduced uptake of higher‐burden procedures; less follow‐up.	CHWs/promotores for continuity; transparency; feedback/return‐of‐results.
Clinical capacity asymmetry (UT Health San Antonio vs UTRGV)	Clinic‐only pipelines concentrate recruitment and widen inequity.	Dual pathway: clinical integration plus coalition/community pathways.
Bilingual workforce constraints	Limits readiness and scale; inconsistent delivery.	Flexible hiring pathways; workforce development (CHW continuing education; mentoring).

4.1. Impact of the reciprocity infrastructure

The transition from transactional recruitment to a reciprocity infrastructure in South Texas has yielded measurable gains in both the quantity and quality of community engagement. Below, we present a snapshot from the third year of STAC, when many of the OREC strategies described were in full implementation (see Table 4).

• Recruitment from populations underrepresented in AD/ADRD research: During Year 3 of the STAC cycle, 172 individuals were recruited to the STAC registry. We will not know their cognitive status until their assessment if they choose to be part of the longitudinal study. Of these new enrollees, 94% were Hispanic. This high level of minority participation vastly exceeds national averages for AD/ADRD research centers and reflects the composition of the local community at highest risk of AD/ADRD.

• Outreach and enrollment metrics: In Year 3, the OREC executed 46 community outreach events, reaching a total of 10,134 individuals in the region. Of particular importance: (1) Demographic precision: 71% of all outreach event attendees identified themselves as Hispanic, reflecting the demography of the region. The composition of the audience validates the targeted and culturally tailored nature of the OREC outreach efforts. (2) Conversion to registry: From this broad outreach, OREC enrolled 172 new individuals into our research registry. The registry includes community members who have consented to being contacted regarding their possible participation in research studies. (3) Enrolled from registry: From among those enrolled in the third year, 82 have joined the longitudinal cohort. As of April 2026 (our fifth year), the registry includes 1064 individuals, 232 (22%) of whom enrolled as participants, 108 (10%) of whom are no longer interested or ineligible, and 724 (68%) individuals who remain registered as potential participants.

• Total enrollment in the longitudinal STAC cohort: As of March 2026, the longitudinal STAC cohort includes 845 participants who have completed at least one visit. Approximately 25% of these participants were recruited through community‐based pathways. There is notable regional variation in recruitment approaches, with 75% of cohort members entering through community engagement in the Rio Grande Valley, while recruitment in San Antonio remains predominantly clinic‐based. By systematically tracking the flow from event exposure to registry enrollment and cohort accrual, OREC identifies critical drop‐off points and adapts engagement strategies to sustain inclusive participation among historically underserved populations.

• Cohort representation: By March 2026, as a cumulative result, the STAC's cohort was 60% Hispanic. This fundamentally shifts the representation of the data available for analysis and improves the generalizability of findings. Of the 845 participants in the longitudinal cohort, 409 (48%) are cognitively unimpaired, 207 (25%) have mild cognitive impairment (MCI), 11 (1%) are cognitively impaired (not MCI), and 218 (26%) have dementia. Cognitive status is relevant to both actionability and disclosure procedures.

TABLE 4.

Example indicators that recruitment is functioning as system change (STAC OREC, Year 3).

Domain	Indicator	Observed signal	Why it matters
Reach	Community exposure to brain health/research	46 events reaching 10,134 individuals; 71% Hispanic.	Locates access points where the burden resides, not only where research is easiest.
Conversion	Registry sign‐ups from touchpoints	172 new registry enrollments; 94% Hispanic.	Signals reduced friction and increased perceived value.
Representation	Underrepresented‐group participation	79.2% underrepresented‐group representation in non‐clinical cohorts.	Primary equity outcome that improves external validity and fairness of inference.
Trust/acceptability	Ability to engage in high‐sensitivity topics	Focus groups (n = 17) and key‐informant interviews (n = 18) progressed to topics such as brain donation.	Trust is an enabling condition for higher‐burden procedures and long‐term retention.
Sustainability	Institutionalization of capabilities	Planned family member registry; workforce pathways for CHWs/primary care partners.	Reduces restart costs and supports durable inclusion across studies.

4.1.1. Qualitative shifts: The metrics of trust

Beyond the numbers, OREC tracks indicators of growing trust and research readiness in the community, particularly in navigating high‐sensitivity topics that were once considered taboo. To explore these shifts, the core conducted 17 focus groups and 18 key‐informant interviews as formal qualitative studies, using separate structured guides, informed consent, and audio recording to support rigorous thematic analysis. These formal engagements, which are intended for future publication, have assessed complex domains:

• High‐sensitivity topics: Over the first 3 years of STAC's implementation, focus groups and key‐informant interviews have assessed sensitive domains like genetic risk disclosure and end‐of‐life care preferences. The ability to openly explore such issues suggests that the community's “relational bank account” ³⁶ now has sufficient capital to support difficult conversations.

• Brain donation: Historically, brain autopsy has been viewed with deep suspicion in Hispanic/Latino communities. ³⁷ Through consistent education and culturally sensitive dialogue (ongoing pláticas), OREC has seen an increased willingness to discuss and even consent to brain donation from a third of its participants.

The fact that more participants are willing to discuss biomarker or brain donation procedures signals a shift in behavior from lower‐intensity engagement to higher‐commitment research behaviors. The engagement in higher‐commitment research behaviors is also evident in follow‐up completion rates (missed visit rates were 34%, 34%, and 41% for follow‐up Visits 1–3, respectively, for South Texas ADRC according to the 2026 March National Alzheimer's Coordinating Center [NACC] report), and the willingness of participants to be recontacted for annual assessments and/or future studies.

4.2. Implementation outcomes

Using the lens of implementation science (CFIR constructs), we see evidence of improved process outcomes in Year 3. (Table 4 provides additional quantitative indicators reflecting these outcomes and why they matter for equity.):

• Acceptability: High repeat attendance at community events (e.g., many participants return for the annual Fiesta de Salud health fair, and the Memory and Heart Connections Forum) suggests that the community finds value in OREC's activities and messaging, an indicator of acceptability.

• Feasibility: The OREC can initiate research pathways independent of specialty‐clinic referral, and often enrolls individuals who do not have existing primary care provider (PCP). When unmet needs are identified, navigators actively connect individuals to primary care or community resources. Furthermore, although OREC assists in navigating these complex systems, the primary obstacles to healthcare access in the region are poverty, the high number of uninsured residents (30%), and the absence of public hospitals in many South Texas counties. Introducing mobile research screenings and home visits are feasible ways to rural participants who would otherwise be “invisible” to traditional clinic‐based research. This demonstrates an effective adaptation to our outer‐setting context (geographic dispersion).

• Sustainability: Perhaps most encouraging, OREC's training of local students and CHWs has created a pipeline of bilingual, community‐savvy personnel. This workforce development means the capabilities for engagement are likely to persist beyond the initial grant, embedding reciprocity as a permanent feature of our regional research infrastructure.

• Institutionalization of gains: The STAC intends to expand its registry to include family members of participants (leveraging family networks for longitudinal follow‐up), to strengthen CHW and primary‐care partnerships (e.g., offering continuing education units in brain health for providers), and to continue embedding bilingual navigation, decentralized entry points, and bidirectional communication as routine practices across all studies. In this way, inclusive engagement becomes standard operating procedure rather than a special initiative.

5. REDEFINING “INFRASTRUCTURE” IN BIOMEDICAL RESEARCH

The STAC's experience challenges the conventional definition of “research infrastructure.” Traditionally, infrastructure in our field refers to physical and technical resources such as magnetic resonance imaging (MRI) scanners, biobanks, and analytical software. We argue that reciprocity is also infrastructure. Just as a freezer preserves biological samples, reciprocity infrastructure preserves the social integrity of the research enterprise. Without it, the “samples” (participants) degrade—they drop out, they provide incomplete data, or they never enroll at all.

5.1. The economics of reciprocity

A frequent critique of models like OREC's is that this kind of “high‐touch” engagement involving navigators, CHWs/promotores, and extensive community interactions is too expensive or resource intensive. This view is myopic. Consider the hidden costs of the status quo:

• The cost of churn: The Transactional Model is plagued by high attrition. ¹⁵ Recruitinga participant, collecting baseline data, and then losing that participant to follow‐up is an enormous waste of resources. Each lost participant means lost data and requires recruiting a replacement, resulting in a costly cycle of churn. ³ , ³⁸

• The value of retention: The Reciprocity Model, by front‐loading investment in relationships, achieves higher retention. A retained participant who contributes data over many years is exponentially more valuable (in scientific terms) than a one‐time participant. ³⁹ Thus, if one calculates the cost per analyzable data‐point, the reciprocity approach may actually lower the cost over the life of a study or grant, because data yield and quality are so much higher per participant.

Retention is a challenge in longitudinal AD studies, for both clinical trials and basic research. Recent literature reports attrition ranging from 10%–54%, depending on study burden and length. ⁴⁰ According to the March 2026 NACC Uniform Data Set (UDS) monthly report, the South Texas ADRC had 87% active/minimal contact participants, and 9% discontinued‐not‐deceased dropouts: missed visit rates were 34%, 34%, and 41% at follow‐up Visit 1–3, respectively. ⁴¹ These metrics compare favorably to peer centers with high Hispanic representation that have been established for longer periods of time (e.g., 1Florida ADRC, Columbia ADRC). We also reference Kaplan–Meier survival analysis for time‐to‐dropout estimates, as illustrated in Figure S1. These curves offer a complementary metric to missed‐visit snapshots by modeling the probability of retention over time, excluding death as a censoring event. In the UDS monthly report for March 2026, South Texas ADRC exhibited a steeper retention curve compared to most centers with high Hispanic representation, maintaining ≈90% follow‐up at Year 1 and over 70% at Year 3. These longitudinal probabilities help contextualize cohort durability by accounting for staggered enrollment and variable follow‐up times. Cohort maturity must be considered in interpretation, as earlier‐established sites have longer exposure to loss over time.

• Supporting Altruism: Reciprocity in this framework complements rather than displaces altruism. Many participants are motivated by helping future families and advancing science; reciprocity matters because altruistic participation is more sustainable when communities also receive information, access, and respect. ⁴² In short, resources spent on engagement infrastructure are not “extra” costs, they are prudent investments that reduce waste and improve data quality. Funders and administrators should recognize that community relationship‐building has a strong return on investment in terms of scientific output.

6. SCALING THE MODEL

The “theory stack” employed by STAC—IOM for strategy, CFIR for context, ABA for mechanics—is portable. Although the content of our model is tailored to South Texas (e.g., fiesta‐style events, Spanish‐speaking CHWs), the process of building reciprocity infrastructure can be replicated by other ADRCs or research centers. Programs serving diverse and understudied communities could all apply these principles with appropriate cultural adaptation.

Recommendation. Future NIH, Alzheimer's Association, and other funding organizations should explicitly recognize engagement infrastructure as a core component of research. This means funding these activities not as administrative overhead or outreach “extras,” but as essential scientific methodology. Just as every study budgets for lab equipment or imaging time, studies of AD/ADRD should budget for community navigators, participant feedback systems, and the like to facilitate implementation of the reciprocity model. Such a shift in mindset, where engagement infrastructure is considered an essential component of any study, would go a long way toward addressing underrepresentation nationally.

Implementation lessons. A few pragmatic lessons have emerged from our experience: First, we have learned that dual channels work best. Having both clinic‐integrated recruitment pathways (e.g., EHR prompts, warm hand‐offs in memory clinics) and community‐anchored pathways (e.g., promotores‐led intakes in community centers, church‐based education sessions) facilitates reaching different segments of the population and together reduces selection bias. Second, we have learned that shared governance must be genuine. Simply having a CAB on paper is not enough; the Board must have real influence. Standing CABs and co‐produced events became decision‐making infrastructure for us, since they influenced how protocols were adapted, how messages are crafted, and how results are disseminated. Third, we learned that articulation work is an intervention. We found that tracking the mechanics of engagement (number of contact attempts, turnaround time for follow‐ups, points of friction in enrollment) allowed us to systematically improve convenience and retention without compromising protocol fidelity. In other words, engagement can be managed with the same rigor as other study interventions.

7. LIMITATIONS

We acknowledge several limitations or challenges of our model. First, it is labor‐intensive. It requires a workforce with specialized “soft skills” like cultural humility, bilingual communication, and community trust‐building, which are often undervalued in academic hiring and promotion systems. We have had to creatively advocate for these skill sets to be recognized as critical. Second, the “return of results” pipeline introduces ethical and practical complexity, given the need to ensure that participants understand the difference between research findings and clinical diagnoses, to ensure that investigators are responsible in their return of health information to participants. Third, when community preferences favor lower‐burden participation over more intensive procedures, OREC provides paths for participation that are shaped by CAB input, iterative consent processes, and a staged approach that allows entry through lower‐burden activities first and offers imaging or other higher‐burden procedures as optional components later. As a result, lumbar punctures and PET imaging numbers are lagging.

Certain constraints to our research in South Texas persist. Despite our successes, we still have a limited supply of bilingual professionals to conduct research and engagement activities. The large catchment area requires significant travel by study staff that can be taxing and requires additional time for recruitment activities. Finally, the variability in clinical capacity across sites presents challenges to generating comparable data and clinical care across sites. Moreover, there is a structural mismatch between the multi‐year trust required for some AD/ADRD studies, especially those involving end‐of‐life procedures or autopsy, and the typical research funding cycles of 3 to 5 years. Investigators need to anticipate these constraints and budget specifically for ongoing workforce development, intensive navigation support, and cross‐site data integration as non‐negotiables, rather than optional, add‐ons.

8. FUTURE DIRECTIONS

Moving forward, we plan to codify reciprocity infrastructure as a testable package that other centers could adopt. This includes developing a minimal set of process measures (a “reciprocity fidelity index”) and pragmatic trial designs to evaluate discrete components of the model. For example, we may test a stepped‐wedge introduction of an enhanced navigation protocol, or an adaptive strategy where participants with higher friction (e.g., long travel distance) receive more intense support. We are also extending our model to additional underserved communities within our region. At STAC, a Family Member Registry is being launched to involve family caregivers and younger generations, and we are formalizing CHW and primary care pipelines to maintain engagement across generations. These steps aim to ensure that our gains in inclusive research are sustained and even broadened over time, creating a self‐replenishing cycle of community partnership.

OREC uses the Community Check Box Evaluation System (formerly ODSS) ³¹ to track outreach and engagement. We welcome collaboration with other ADRCs and are willing to share logic models, data entry structures, and templates upon request.

9. A NEW STANDARD FOR EQUITY

The South Texas ADRC's OREC model demonstrates that the underrepresentation of certain population groups in AD/ADRD research is not an intractable problem of “hard‐to‐reach” communities. Rather, it is a problem of “hard‐to‐access” research systems. By systematically dismantling barriers using the IOM, CFIR, and ABA frameworks, and by replacing transactional extraction with reciprocity infrastructure, STAC has transformed the demographics of its research cohorts. What was once a liability (our region's demographics and resource constraints) has become a major advantage for discovery. This approach helps fulfill the mandate that the advances of tomorrow, the biomarkers, preventions, and cures, will apply to everyone, fulfilling the ultimate promise of the National Alzheimer's Project Act. ⁴³ It points toward a new standard for equity in research, one in which infrastructure includes community relationships and inclusivity is built into the science from the ground up.

CONFLICT OF INTEREST STATEMENT

The authors declare no conflicts of interest. Author disclosures are available in the Supporting Information.

Supporting information

Supporting Information

Supporting Information