Clinical research professionals (CRPs) are essential members of clinical translational science teams. Team science (TS) training exists for clinical research investigators and trainees; however, such training has been lacking for CRP staff. We sought to better understand the TS training and learning preferences for CRPs using a survey and focus group mixed methods study to inform future training.

The survey was distributed to CRP institutional networks and to the members of the Association of Clinical Translational Science CRP Taskforce Special Interest Group. Post-survey, focus groups were also conducted with volunteers from the survey to further elucidate CRP TS training preferences, including facilitators and barriers to training.

A total of 193 CRPs completed the survey over 7 weeks. Most respondents were clinical research coordinators or clinical research nurses. CRPs responded that TS competencies were important and frequently used in their roles; however, TS training was lacking. Respondents preferred a variety of training modalities such as interactive case studies, webinars, and micro-learning. Qualitative focus group results validated the survey results and provided additional insights into facilitators and barriers to CRP professional development, particularly time constraints for training.

This is the first learning needs assessment focusing on CRP TS learning needs and training preferences. Together with recently published CRP TS competencies, this study sets the stage for focused training development to enhance CRP roles and interdisciplinary TS.

Families’ experiences navigating access to comprehensive pediatric care for children with diagnosed or suspected rare disease (RD) in the Texas Rio Grande Valley (RGV) remain unexamined. We explored factors influencing access to specialty medical care, social services, and community support for families of children with RD in the RGV.

We conducted 25 semi-structured qualitative interviews (n = 17 English, n = 8 Spanish) with parents of children up to age 18 with undiagnosed RD enrolled in Project GIVE, which provided genetic evaluation and testing to families in the RGV. We generated themes through an iterative inductive coding process using reflexive thematic analysis.

Four themes captured parents’ experiences accessing services for their child’s medical care and educational accommodations and family support: (1) service shortages resulted in long waits, care disruptions, and long-distance travel; (2) cumbersome administrative and insurance processes led to delays in receiving services; (3) staff-led care coordination mitigated challenges navigating and communicating across fragmented services; and (4) caregiving imposed emotional strain on families amid unmet psychosocial support needs. The process of accessing medical care was a recursive cycle triggered by family-, clinician-, and insurer-initiated disruptions which required parents to reestablish referrals and scheduling, further compounding barriers.

Limited medical and social services in the RGV augmented already considerable financial, logistical, and emotional burdens on families caring for children with RD. Use of digital health platforms to streamline appointment scheduling and medical record access may promote pediatric RD care coordination and continuity and help minimize the recursive cycle of access barriers.

Integrating advanced artificial intelligence (AI) into clinical decision-support often requires the sharing of sensitive patient data with external services, raising privacy concerns. Homomorphic encryption (HE) allows computing directly on encrypted data, without revealing the underlying patient information.

To develop a large language model (LLM)-assisted diagnosis framework while preserving patient privacy in the clinical text analysis, by leveraging HE and using rare disease (RD) diagnosis as a representative application. To demonstrate HE does not hinder the system performance.

Texts from patient histories and a RD knowledge base were embedded by LLMs into vectors, then encrypted using HE to obscure private information while retaining the semantic nuances. Diagnostic recommendations were generated by computing and ranking the similarities between the patient history and RD vectors in the encrypted space. The system was evaluated using 50 synthetic case reports (5 RDs, each with 10 reports).

Applying HE did protect private information from reverse-embedding attacks. HE imposed little disruption to the diagnostic accuracy, with normalized discounted cumulative gains (nDCG) of 0.6108 ± 0.3412 (encrypted) versus 0.6083 ± 0.3415 (unencrypted). The accuracy and computational performance were tunable and consistent, as demonstrated across five different LLMs.

Our privacy-preserving framework opens tremendous opportunities toward hosting and serving powerful AI solutions across institution boundaries, which would remove the need for local deidentification and incentivize users to access secure external decision-support services.

Integrating HE with LLM retrieval can promote the dissemination of nonredundant, high-capacity AI services by preserving both privacy and accuracy.

Efficient, precise operationalization of the clinical trial planning phase is critical to timely trial initiation and overall success. Early missteps – imprecise protocols, unclear manuals, delayed training, or incomplete regulatory preparation – create cascading inefficiencies across submissions, data systems, contracting, and site onboarding. Although literature recommends streamlining procedures, mapping the process, and using checklists, there is limited guidance on how to operationalize the planning phase into an executable, time-bound plan.

Drawing on operational experience from more than 30 multicenter trials and stakeholder interviews, we developed a study planning “blueprint” that maps milestones, roles, tasks, dependencies, and deliverables across a pre-award run up period and planning year (∼15 months). The blueprint prescribes a multi-team structure (Data Analysis and Statistical Reporting; Data Systems Integration; Data Management; Operations and Clinical Affairs; Protocol and sIRB; Financial Operations) to enable parallel work streams, with quarterly milestones aligned to funder performance-based expectations.

The blueprint details quarter-by-quarter deliverables – from pre-award risk assessment to site activation and first enrollment. It emphasizes the centrality of a dedicated project manager, predecessor-successor milestones and tasks, dependency-aware project tools, and routine leadership monitoring to identify and mitigate delays. The model is scalable: smaller teams can consolidate roles and extend timelines while preserving parallelism where feasible.

Formalizing the planning phase with a visual, team-assigned blueprint of parallel work streams may increase operational precision, reduce avoidable delays, and accelerate transition from award to participant enrollment. Future work should quantify milestone- and task-level time and cost metrics to optimize blueprints for diverse trial types.

SCN2A and SCN8A-related disorders are severe neurodevelopmental conditions characterized by infantile seizures, epilepsy, autism spectrum disorder, intellectual disability, and developmental epileptic encephalopathy, with limited therapeutic options. The FamiliesSCN2A Foundation and International SCN8A Alliance launched a multi-stakeholder roadmapping initiative to accelerate therapeutic development for these rare genetic disorders.

A workshop was convened at the 2025 FamiliesSCN2A Foundation Annual Conference bringing together scientists, clinicians, industry partners, and caregivers. Participants conducted collaborative roadmapping to identify therapeutic strategies, prioritize unmet needs, and define implementation pathways. Caregiver input directly informed discussions on treatment burden, symptom management targets, and trial design preferences.

Four key recommendations emerged: (1) validation of non-seizure outcome measures and biomarker correlation studies; (2) long-read sequencing initiatives to enable allele-specific therapeutic targeting; (3) development of decentralized, caregiver-informed clinical trial designs; and (4) early engagement with the FDA on regulatory pathways for novel chemistries and mixed-function variants. Allele-specific antisense oligonucleotides, gene editing platforms, and targeted small molecules were identified as the most promising therapeutic approaches. Cross-stakeholder consensus highlighted critical gaps in variant stratification, human-relevant preclinical models, and validated outcome measures as primary barriers to progress.

The roadmap demonstrates accelerating momentum in SCN2A and SCN8A therapeutic development while identifying concrete next steps. Advancing variant-specific therapeutics requires integrated solutions across improved stratification, preclinical modeling, and outcome validation. This multi-stakeholder approach positions caregiver priorities alongside scientific and clinical expertise to guide translational progress.

Rural health research continues to expand, yet Appalachian-specific contexts differ from other rural contexts. This scoping review examined health priorities in Appalachian and broader rural health research, comparing patterns in methodological frameworks and exploring how community engagement (CE) and team science (TS) are applied in the context of Appalachian health research.

The Population–Concept–Context framework was used to define inclusion criteria for peer-reviewed studies identified through PubMed and Google Scholar searches. Studies selected were grouped by regional focus (Appalachian, Rural, and Rural Appalachian), with thematic synthesis and descriptive analysis applied across domains.

Appalachian studies emphasized cultural context, structural barriers, and participatory methods, integrating cultural considerations directly into research design and implementation. Rural studies framed health disparities in terms of access gaps, infrastructure failure, and resource barriers. Rural Appalachian studies integrated equity, resilience, and intersectional concerns. CE was applied across all groups; formal TS methods were applied inconsistently.

Appalachian and rural studies differ in framing and methodology. Appalachian research emphasizes structural inequities and CE, while broader Rural studies focus on access-related barriers. These differences highlight the importance of place-based approaches to understanding health disparities, emphasizing the need for context-specific research.

We previously developed and tested a peer-led research best practices training for community health workers and promotoras (CHW/Ps) to enhance the capacity of a workforce that is increasingly important for community-engaged research. This paper explores results of training implementation at 4 additional sites – 3 academic institutions and 1 community-based organization.

Forty-two CHW/Ps were trained over 6 trainings and 10 site staff participated. We used a mixed methods design consisting of surveys and interviews to assess site staff’s perceptions of the training and its implementation. Survey data were examined using basic statistics and thematic content analysis. Two coders analyzed the interviews inductively then deductively by mapping codes onto the Consolidated Framework for Implementation Research (CFIR). Survey and interview results were integrated using a joint display to identify meta-inferences.

Surveys of staff quantitatively demonstrated high acceptance, appropriateness, and feasibility of the peer-led research best practices training for CHW/Ps. Several qualitative themes emerged that aligned with CFIR domains, highlighting perceptions of the training and factors related to its implementation. Meta-inferences revealed staff’s perspectives about implementing the training were influenced by characteristics of the training and implementation sites, learner engagement and compensation strategies, and implementation processes.

The peer-led research best practices training for CHW/Ps is acceptable, appropriate, and feasible for implementation by academic and community-based organizations, particularly due to the flexibility of how it was designed. While successful implementation at all sites requires engaged Champion peer facilitators, other needs to support implementation vary based on site characteristics and environment.

An academic medical center’s trustworthiness is a necessary precondition of patient and community trust. Current operationalizations of trustworthiness fail to capture the construct’s complexity at the institutional level. We propose a novel multidimensional scale to assess perceived trustworthiness of academic medical centers.

We propose and psychometrically evaluate a 20-item Multidimensional Institutional Trustworthiness Scale (MITS). Invitations to complete an online survey in REDCap were sent to 175 leaders, investigators, staff and community partners affiliated with an academic medical center. Item-total correlations were calculated and construct validity assessed using confirmatory factor analysis.

Items in the hypothesized four factors demonstrated high factor loadings (>0.7) and explained substantial item variance (>50%), providing strong empirical support for the proposed scale and affirming its conceptual structure and measurement integrity. Tests of scale reliability showed high Cronbach’s alphas (>0.9) for all four factors, suggesting that all subscales produce consistent and dependable scores.

This study provides support for the construct validity and scale reliability of a novel institutional trustworthiness scale, based on perspectives from community and academic affiliates of an academic medical center. We discuss the importance of measuring institutional trustworthiness using multiple dimensions to inform future interventions aiming to improve institutional trustworthiness.

Primary care practice-based research is well positioned to address clinically relevant research questions that can inform real-world practice. However, many practices lack the infrastructure or readiness to participate in research. This study developed and evaluated the Practice Assessment for Research Readiness (PAR2), a survey tool designed to assess research readiness in healthcare systems and community-based primary care practices, including family medicine, pediatrics, and internal medicine.

The PAR2 survey was developed through partner engagement, adapting prior organizational survey questions, and pilot testing. Six Subscales included: Perceived Value of Research, Capacity for Change, Change Commitment, Change Efficacy, Task Knowledge, and Resource Availability. Cronbach’s alphas and composite reliabilities were calculated to assess internal consistency reliability of each subscale. Confirmatory factor analysis was used to assess structural validity.

A total of 249 participants from 50 primary care practices completed the PAR2 survey. The internal consistency reliability of each subscale was high (alpha and CR >0.7) except for the Capacity for Change subscale (CR = 0.77 but alpha = 0.69), which improved (alpha and CR = 0.82) after removing one question due to its low item-total correlation. The scales also showed good structural validity after minor modifications.

The PAR2 survey provides a practice-level research specific measure that can be used to align practices with studies suited to their readiness, potentially improving recruitment, reducing attrition and guiding capacity-building interventions.

The Rapid Acceleration of Diagnostics-Underserved Populations (RADx-UP) initiative sought to catalyze timely scientific understanding of approaches to address COVID-19 disparities through community engaged research. It also sought to foster sustainable community-academic partnerships as key infrastructure for responding to emerging public health crises.

We integrated bibliometric, Altmetric, and network analyses to examine the volume and scope of research produced by the RADx-UP initiative, its translational impacts, and how community partners were integrated into research networks. We identified Scopus- and PubMed-indexed scientific manuscripts supported by RADx-UP funding through June 2024. We extracted metrics from Scopus, PlumX, and iCite, and via structured coding. Network analysis explored community partners’ positioning in co-author networks across three time points.

The initiative produced 334 publications during the study period. Studies most frequently focused on Hispanic/Latino (25.1%), children and adolescents (19.2%), and Black/African American (18.9%) populations. The average relative citation ratio (RCR) was 2.07. Altmetrics indicated public engagement through mentions in earned media (761), social media (1,971), and citations in policy documents (90). Community partners were represented in 18% of network components in 2022 and 41% by 2024. While community partners’ total direct connections to other investigators did not consistently increase, their connections to influential investigators, as measured by power centrality, did (−0.96, −0.75, −0.37 in 2022, 2023, and 2024, respectively).

These findings point to the greater-than-average impact of RADx-UP publications and initial community translation. They also highlight contributions to the research ecosystem that could scaffold long-term research quality and productivity, and broader impact.

Black and Hispanic communities in the United States have been disproportionately affected by COVID-19 but remain underrepresented in health research. We examined whether a culturally tailored digital storytelling intervention increased interest in, and enrollment into, a COVID-19 antibody research study.

We conducted a randomized trial from September 2021 to December 2022 among Black and Hispanic adults in Central Massachusetts. Participants, recruited through respondent-driven and convenience sampling, were randomized to receive a storytelling intervention (narrative videos plus educational content) or a comparison intervention of educational content only (Learn More), using Qualtrics and RedCap surveys. Primary outcome was the rate of participant interest in COVID-19 antibody study enrollment. Secondary outcomes included enrollment in the antibody study and providing a blood sample. Participants were followed from consent through completion of the post-intervention survey, with duration varying based on survey completion timing. Analyses followed an intention-to-treat approach.

Of 390 randomized participants, 343 completed the study (Storytelling: n = 173; Learn More: n = 170). 68% of the Storytelling and 75% in the Learn More group were interested in joining the antibody study (proportion difference = 0.07, 95% CI: −0.02, 0.16). Enrollment rates into the antibody study and blood sample provision were similar. Storytelling group participants who identified with their favorite story were significantly more likely to enroll (OR = 1.29, 95% CI: 1.03–1.60).

The storytelling intervention did not increase overall research participation, but story relevance was associated with greater enrollment, suggesting that stories with personal connection may improve engagement in research among underrepresented communities.

As generative artificial intelligence (GenAI) becomes increasingly embedded in healthcare, it is essential to characterize how AI-enabled approaches can advance community engagement within academic–community partnerships. The purpose of this scoping review was to map and synthesize literature describing GenAI-enabled approaches that support community engagement within health-related academic–community partnerships involving populations disproportionately affected by health inequities.

We reviewed English-language records published between 2015 and 2025 describing academic–community partnerships involving populations disproportionately affected by health inequities. Structured searches were conducted, supplemented by gray literature and hand-searching. We included records describing the use or proposed use of GenAI to support community engagement. Included records were mapped to the US Centers for Disease Control and Prevention (CDC) Principles of Community Engagement.

Seven of 765 records screened met eligibility criteria. Four of the records included completed investigations. Three records highlighted planned approaches to use GenAI in community-engaged research to address health inequities. Among included records, Principle 2 (understanding community context) and Principle 7 (mobilizing community assets) appeared in more records than any other principles. None addressed Principle 1 (clarify goals), Principle 4 (accept community self-determination), Principle 8 (release control), or Principle 9 (foster collaboration).

Within the limited literature identified, GenAI may support community engagement by enhancing understanding of community context and mobilizing community assets. Future research should evaluate broader applications across the CDC Principles of Community Engagement.

Clinicians face rising burnout while being expected to lead transformation in education and care delivery. Although innovation and well-being are often treated as competing priorities, evidence suggests they are interdependent. A one-year Innovation Fellowship grounded in integrative nurse coaching was developed to strengthen innovation competencies while supporting participant well-being. This study examined Fellowship outcomes, including well-being, innovation competency, and perceived connections among innovation, professional identity, and wellness.

A convergent mixed-methods design was used. Quantitative measures included the Integrative Health and Wellness Assessment (IHWA) and a 19-item Benner-based Innovation Competency Scale. Qualitative data included evaluation responses, retreat reflections, and end-of-year surveys. A three-member analytic team conducted content analysis and reflexive thematic development.

Over five years, 63 fellows participated. Fifty IHWA surveys were available, including 14 paired pre–post surveys. Paired IHWA scores improved significantly from 3.84 ± 0.32 to 4.16 ± 0.32 (p = .003; d ≈ 1.08). Innovation competency surveys were completed by 36 fellows at baseline and nine at follow-up, with six paired responses. Overall scores increased descriptively from 3.0 to 3.5, while paired scores increased from 2.79 to 3.73. These findings were considered exploratory because of small paired samples and follow-up attrition. Qualitative themes included innovation identity and legacy formation, boundary-setting to protect creative energy, applied innovation skill-building, community, mentorship, and psychological safety.

Integrating innovation and well-being within professional development may strengthen morale, retention, and readiness to lead change. This Fellowship offers a reproducible, evidence-informed model linking well-being, innovation competency, and institutional impact.

Due to its rapid expansion, translational research has become a strategic priority in biomedical studies, while simultaneously introducing complex ethical and integrity-related challenges that extend beyond traditional bioethical frameworks. These challenges, particularly salient in emerging research contexts, such as Colombia, underscore the need to strengthen research ethics and scientific integrity to ensure responsible and socially accountable scientific practice. This study aims to analyze the conditions and potential needs related to research ethics and scientific integrity in the implementation of translational research in Colombia.

This qualitative study used focus groups with research teams recruited via a nationwide call and applied thematic analysis to interpret participants’ experiences.

The analysis resulted in three main themes: regulatory frameworks for research ethics and scientific integrity, ethics-related needs and practices, and scientific integrity needs and practices. These themes gave rise to ten analytic codes, highlighting key issues, such as risk management, informed consent, and incidental findings in the context of translational research.

The normative analysis identified key gaps that constrain the ethical implementation of translational research, including difficulties in understanding ethics beyond a strictly legal domain, a lack of clarity regarding scientists’ ethical responsibilities, and the reduction of ethical reflection to a discrete evaluative stage within research projects. These findings support the need for recommendations and targeted action, particularly ethics education focused on deliberation and the meaningful use of ethical concepts.

Recruiting older adults into clinical research studies presents unique challenges that can result in failure to meet recruitment targets and contribute to underrepresentation. This article identifies facilitators and barriers to using electronic medical record (EMR)-based alerts to identify eligible older adults for a time-sensitive protocol.

We analyzed a case example in which EMR-based alerts were used to identify older adults with early-stage lower extremity wounds. We examined operational, regulatory, and workflow factors that influence EMR-based alert recruitment and applied the Consolidated Framework for Implementation Research (CFIR) to understand facilitators and barriers associated with this approach.

During the wound study recruitment period, EMR-based alerts automatically triggered 198 times for 123 unique patients across five clinical settings. Of these patients, seven (6%) were referred through EMR-based alerts, whereas traditional recruitment methods including flyers, and provider reminders, yielded no referrals. Referral yield varied by clinical setting, with the highest performance in the Geriatrics clinic (4/39 patients, 10%). Barriers included workflow disruption, alert fatigue, poorly timed notifications, inaccurate patient identification, limited familiarity with the study, and institutional policies requiring provider-mediated referrals.

Despite significant institutional investment in EMR infrastructure, limitations related to data quality, workflow alignment, provider engagement, and institutional recruitment policies continue to impede effective use of EMR-based alerts for research recruitment of older adults. Improving alert design, reducing provider burden, and addressing regulatory barriers, may enhance the identification and recruitment of eligible older adults using this method, particularly for time-sensitive studies and recruitment in outpatient care settings.