The Clinical Breast Care Project (CBCP) conducts coordinated clinical care and research across military and civilian medical centers, requiring secure and integrated management of participant records and biospecimens. To support enrollment, biospecimen processing, and translational research in this specialized environment, the Data Tracking System for the Clinical Breast Care Project (DTS-CBCP) was developed.

DTS-CBCP collects participant, clinical, consent, pathology, and biospecimen metadata through a web-based platform. It uses a patient-centric model to connect clinical events with biospecimen data. Development utilized a tiered web-application architecture and an Oracle database environment that meet Department of War (DOW) and Health Insurance Portability and Accountability Act standards. Audit trails, encryption, and role-based access ensure secure multi-site participation. DTS-CBCP also integrates with the Data Warehouse for Translational Research (DW4TR), Freezerworks, and digital pathology tools.

DTS-CBCP has supported participant enrollment (n = 11,452) and biospecimen tracking (n = 104,671 specimens, including 18,974 frozen tissue and 9866 Formalin-Fixed Paraffin-Embedded samples). Additionally, 219,280 blood aliquots and 19,937 slides have been tracked across three military and civilian sites. The system enables consent tracking, clinical annotation, specimen chain-of-custody, remote digital pathology, and automated reporting. DTS-CBCP has supported breast cancer research initiatives such as The Cancer Genome Atlas and the Applied Proteogenomic Organizational Learning and Outcomes projects.

DTS-CBCP addresses coordination of clinical and biospecimen data across military and civilian institutions. In addition to supporting breast cancer research, it creates an informatics framework for expanded translational research networks and future DOW-aligned programs.

Meaningful inclusion of communities in research is both an ethical imperative and a driver of more equitable, relevant, and trustworthy science. Yet communities remain underrepresented as research partners due to historical non-inclusion, structural barriers, and a lack of institutional pathways that build shared language and sustained opportunities for engagement. We developed and evaluated community scientist (CS) training program to prepare community members to engage as partners across the translational research continuum.

Mayo Clinic launched the CS program in 2021 as a one-day training and expanded to a four-week course in 2022 and an eight-week program with a six-week experiential assignment in 2023–2024, with asynchronous options added in 2025. The curriculum integrates didactic instruction with applied learning in research ethics and Institutional Review Board processes, genomics, biobanking, clinical trial diversity, social determinants of health, and researcher-community collaboration. Pre- and post-training surveys assessed participants’ familiarity with key research domains, with additional evaluation of experiential learning.

Forty-eight participants completed pre-training survey and 30 completed the full didactic program. Familiarity with CS role increased from 43.8% to 100%. Familiarity with genomics and biobanking increased from 20.8% to 94.1%, and familiarity with research ethics/IRB processes increased from 45.8% to 94.1%. Participants reported improved understanding (82%), confidence (80%), overall satisfaction (89%), and ability (70%) to partner with research teams.

This CS experiential training model increased readiness for partnership among diverse community members across three regions. The model strengthens institutional infrastructure for community-engaged research and supports community-relevant translation across research settings.

Remote technologies and research methods have the potential to improve accessibility and promote participation in clinical research. Understanding strategies for mitigating barriers and facilitating better access to remote research engagement is crucial for increasing research access for all.

Surveys (n = 105) of and interviews (n = 35) with health researchers at the University of Washington, Seattle Children’s Research Institute, and the Fred Hutch Cancer Center and interviews with research participants (n = 19) involved in studies at these institutions were conducted to determine challenges and facilitators encountered in remote engagement and how they might be addressed and implemented to provide more comprehensive and equitable access to clinical research.

Both researchers and participants identified convenience and potential broader access as benefits of remote research engagement. Challenges identified included device and connectivity resource barriers, limited support for those unfamiliar with digital tools, insufficient multilingual access, and incomplete replication of in-person research experiences. Proposed facilitators highlighted remote device and resource allocation, education/training in remote technology use for participants and research teams, and having readily available research team support for troubleshooting difficulties in remote engagement.

Remote technologies have great potential to enhance access to clinical research for all, particularly when anticipating potential barriers and implementing facilitators to address engagement barriers. Optimal strategies can be informed by stakeholder feedback and better understanding of the specific barriers among cohorts.

Aging in place depends on older adults’ confidence in managing routine home-based tasks. This study examined psychological and environmental correlates of comfort performing routine home maintenance among adults aged 50+ affiliated with a university-based lifelong learning program.

This cross-sectional study used an anonymous online survey distributed through program-based email communication. The primary outcome was comfort performing routine home maintenance, originally measured as No, Somewhat, or Yes. For the primary analysis, responses were dichotomized to compare participants reporting full comfort with those reporting less than full comfort. Binary logistic regression examined associations with perceived home-based support, stress management capacity, age, and gender. An ordinal logistic regression sensitivity analysis used the original three-category outcome.

Of 120 consenting respondents, 101 completed the survey and provided valid outcome responses to the primary outcome. The model was statistically significant, χ2(4) = 18.42, p = 0.001, Nagelkerke R2 = .287. Better stress management was associated with higher odds of full comfort (OR = 3.19, 95% CI [1.43, 7.13], p = 0.005). Greater home-based support (OR = 0.64, 95% CI [0.44, 0.92], p = 0.015) and older age (OR = 0.90, 95% CI [0.83, 0.97], p = 0.009) were associated with lower odds. The ordinal sensitivity analysis produced a similar pattern.

Task-specific confidence in routine home maintenance may reflect psychological resources and perceived support needs. Community-based aging-in-place initiatives may benefit from addressing coping, home maintenance planning, and support navigation before challenges become urgent.

Participant retention is a critical determinant of Phase 1 clinical trial validity. Published data on dropout and retention, specifically in Phase 1 healthy participant settings, remains limited.

We conducted a retrospective observational analysis of all trials performed at a Phase 1 Clinical Studies Unit in Porto, Portugal, between January 2021 and December 2025.

Across 99 trials and 14,331 scheduled screening visits, 4,013 participants were enrolled. The study population was predominantly female, with a mean age of 32.9 years. The average post-randomization retention rate was 92.2%, improving progressively over the study period. The leading causes of post-randomization dropout were adverse events (AEs) (40.6%) and participant-initiated withdrawal (38.4%).

This analysis demonstrates high and improving retention rates over five years, namely due to COVID-19 pandemic resolution, with AEs and participant-initiated withdrawal as the primary drivers of post-randomization dropout. These findings support unit-level retention tracking and highlight priority areas for operational improvement in Phase 1 research.

SARS-CoV-2 virus pandemic, beginning in March 2020, disrupted dietary habits, lifestyles, and mental health, potentially exacerbating weight-related health differences. Existing evidence lacks a comprehensive nationwide longitudinal analysis of pandemic-related weight changes among Hispanic adults, particularly across demographic subgroups and comorbidities.

To examine national longitudinal changes in body weight among U.S. Hispanic adults during SARS-CoV-2 virus pandemic (2019–2023).

We utilized electronic health records(EHRs) from National Clinical Cohort Consortium (N3C) database (January 2019 to December 2023), covering Hispanic adults aged ≥21 years in 2019 with complete data records over these five years. Statistical approaches included paired/independent t-tests, ANOVA, repeated-measures ANOVA, McNemar-Bowker tests, and linear mixed models.

The study included 11,452 Hispanics aged 21–83 years; 65.1% were female; 83.5% were overweight/obese at baseline. Mean weight exhibited a peak-then-decline pattern, increasing from 80.6 kg (pre-pandemic) to 81.1 kg (2021), then decreasing to 80.8 kg (2023). This trajectory persisted across demographic and clinical subgroups. Younger adults (<40 years) and under- or healthy weight individuals continued gain weight, while older adults (>59 years) and those with obese II/III continued to lose weight. Differences in weight gain during 2019–2021 were seen in sex, race, smoking status, dietary environment, and SARS-CoV-2 virus infection. Chronic conditions showed divergent associations, with diabetes, stroke, cancer, kidney disease and dementia experienced weight loss.

Hispanic adults exhibited shifts in weight patterns during SARS-CoV-2 virus pandemic, with significant differences observed across population subgroups. These findings highlight the need for targeted interventions that address the prolonged metabolic impacts of the pandemic in this population.

In Nigeria and Africa, the use of artificial intelligence (AI) large language models such as ChatGPT as a source of health and cancer information is increasing; however, the quality of this information remains largely unknown. This study assessed whether ChatGPT-generated cancer patient education material (PEM) aligns with clinician-authored content in usefulness, understandability, and clarity.

Using a cross-sectional study design, 409 adults were recruited to complete questionnaires assessing the usefulness, understandability, and clarity of cancer PEMs created by AI-ChatGPT (using GPT-4o) and clinicians.

Of 371 participants who completed the questionnaire, most were female (70%), held a bachelor’s degree or higher (90%), were urban residents (80%), and over half (58%) lacked health insurance. The findings showed that ChatGPT-using GPT-4o–produced PEMs were comparable to clinician-developed materials in usefulness, understandability, and clarity, with no overall significant differences. However, clinician statements on “healthy diet” and “limit alcohol” were rated clearer than AI’s equivalents, with statistically significant differences for both (p = 0.025, d = 0.24; p = 0.006, d = 0.30). Only 14% of participants reported using AI for health information, yet 58% expressed trust in it, suggesting potential for rapid adoption.

ChatGPT (GPT-4o) can produce PEMs comparable to clinician-created ones in usefulness, understandability, and clarity. This is the first Africa-based study to compare clinician- and AI-generated cancer PEMs.

Clinicians and health educators may consider using AI, particularly ChatGPT, to support PEM development in Africa; however, outputs require clinician review, cultural adaptation, and alignment with the health system.

Pragmatic trials involve patient recruitment, intervention delivery, and data collection leveraging usual systems and processes of care. Yet pragmatic does not mean easy, such that enacting pragmatic trial protocols requires considerable effort to engage patients and practice members. Home versus Office versus Telehealth for Medication Enhanced Recovery (HOMER) was a national pragmatic trial testing comparative effectiveness of office, home-based, and telehealth induction of medications for opioid use disorder (MOUD). Research implementation practice and patient liaisons (RIPPLs) were employed to support pragmatic trial conduct across 100 participating practices nationwide. The objective of this paper is to report on RIPPL roles and impact.

Fourteen RIPPLs were matched to practices based on geographic proximity, research network membership, and caseload. Study records, field notes, and a qualitative survey were used to describe RIPPL processes and experiences and to assess impact.

RIPPLs had backgrounds in research coordination, project management, primary care delivery support, and adult learning. RIPPL activities supported practice motivation, follow-through, and protocol fidelity, and included several elements of practice facilitation. RIPPLs provided real-time feedback to the research team on opportunities for research protocol adaptations. Impact of the RIPPLs included protocol adaptations to decrease practice burden and improve ease of patient participation, regular eligible criteria fidelity monitoring, data completeness, and quality, and educating clinicians and staff on MOUD delivery.

RIPPLs can effectively support pragmatic trial conduct in primary care. HOMER RIPPLs enabled the research protocol to be iteratively more pragmatic (both feasible and aligned with the primary care context) while maintaining rigor and fidelity of intervention implementation.

Persistent challenges with clinical trial enrollment and retention limit the extent to which novel approaches are translated into clinical and community practice for real-world benefit. Community engagement is one strategy that may improve enrollment and retention. The current study sought to 1) describe the extent to which clinical trials utilized specific levels of community engagement and 2) examine associations between level of community engagement and study process outcomes. We hypothesized that clinical trials with higher levels of community engagement would have more successful participant enrollment and retention.

Using manifest content analysis, we examined associations between community engagement strategies and three study process outcomes: total enrollment, time to full enrollment, and retention, as documented on ClinicalTrials.gov.

Of 619 studies that met inclusion criteria, 349 published findings, of which only eight studies described any community engagement. The eight studies with publications that described community engagement had higher actual enrollments and shorter time to full enrollment than studies without any description of community engagement in their associated publications.

Results demonstrate positive associations between documented community engagement and enrollment in clinical trials. Community engagement has strong promise for increasing the efficiency and real-world impact of clinical research. However, findings revealed the infinitesimal number of clinical trials that utilized community engagement and the rarity of co-leadership.

Linked electronic health records (EHR) and Medicare claims data are excellent sources for amyotrophic lateral sclerosis (ALS) research. However, quality assessment of data in these sources is critical to produce accurate real-world evidence.

In this study we evaluated the consistency and concordance of ALS-linked EHR and Medicare data across the Greater Plain Collaborative (GPC) clinical research network. We used rule-based methods to assess the consistency of demographic, ALS diagnosis, riluzole prescription, and percutaneous endoscopic gastrostomy (PEG) procedure data in both data sources. We used Cohen’s Kappa statistics (k) to assess the concordance between the two data sources and multiple logistic regression models to identify potential driving factors of discordance.

Our findings revealed that demographic data was mostly consistent across most sites, with the highest discrepancies observed in race and ethnicity. For ALS-specific diagnosis, most sites demonstrate moderate (k = 0.41–0.60) to substantial (k = 0.61–0.80) concordance for ALS diagnosis, riluzole prescription, and PEG procedure. Sensitivity analysis showed that the data in both data sources were concordant across many sites (Sensitivity > 70%). However, results also revealed discordant data at some sites. Age distribution, sex, and the type of insurance used in the index encounter were key factors contributing to discordance.

These results provided insight into the level of ALS data concordance between EHR and Medicare, as well as illustrated quality issues requiring assessment before use in clinical research and in providing recommendations based solely on available secondary data.

Although monitors in Japanese academic research organizations shoulder broad responsibilities to ensure the reliability of investigator-initiated trials, systematic educational opportunities remain limited. To address this gap, we developed a competency-based, level-specific training program and have implemented it since 2019. This study describes our educational model, including its continuous improvement process, and evaluates its effectiveness using multi-year participant feedback.

Two types of surveys were administered to participants from 2020 to 2024: a post-workshop survey conducted within one week (n = 322) and a follow-up survey within two years (n = 216). Quantitative analyses assessed satisfaction, application of learning, continued material use, and post-program networking. Qualitative analysis assessed participant responses regarding key program design elements (“practice-oriented,” “supportive environment,” and “peer interaction”).

Across five years, median satisfaction scores remained consistently high (4–5 and 3–5 for the foundational and the early-intermediate levels, respectively, on a 5-point Likert scale). Qualitative analysis revealed that the majority of favorable responses referenced at least one of the key design elements. The follow-up survey showed that the program and materials were beneficial in daily practice, and a notable proportion increased professional connections, especially in-person attendees.

Despite methodological limitations in its evaluation (a single-arm, self-reported design), our program consistently showed high participant satisfaction and practical utility in daily practice. Furthermore, the program helped foster professional networking, supporting ongoing mutual learning beyond participation. This model provides a versatile, internationally adaptable approach for establishing clinical research professional training in resource-constrained settings.