Journal of Clinical and Translational Science最新文献

{"title":"Institutional transformations for authentic community engaged and participatory research.","authors":"Nina Wallerstein, Milton Mickey Eder, Lori Carter-Edwards, Paige Castro-Reyes, Tanja Gangarova, Linda Sprague Martinez, Lloyd Michener","doi":"10.1017/cts.2026.10715","DOIUrl":"https://doi.org/10.1017/cts.2026.10715","url":null,"abstract":"<p><p>This special issue of the <i>Journal of Clinical Translational Science</i> on Institutional Transformation provides strategies to strengthen community and patient engagement in research in which collaborative knowledge creation is valued and centered in the history, knowledge, and evidence within communities. Recognizing the important role of academic health centers, schools of public health and research institutes in engaged research, the guest editors sought articles that challenged institutions to transform policies, practices, norms and structures towards power-sharing in research and towards commitment to sustainable research partnerships for health equity. While these articles were mostly written before the current context of large-scale terminations of grants and programs, this special issue recognized the well-founded historical distrust of communities in academic centers and the ongoing challenges of regaining trust in science. We first provide an historical context of institutional barriers and facilitators of engaged and participatory research and then review articles, including from the Engage for Equity PLUS national initiative. We end with recommendations for the field, as we recognize we still need to be self-critical about the structures that maintain academic dominance in research rather than valuing multiple ways of knowing and the importance of communities for authentic co-creation and leadership of research.</p>","PeriodicalId":15529,"journal":{"name":"Journal of Clinical and Translational Science","volume":"10 1","pages":"e60"},"PeriodicalIF":2.0,"publicationDate":"2026-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13107354/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147772931","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Precision risk assessment for pediatric hospitalization using address-level data in Cincinnati, Ohio.","authors":"Carson S Hartlage, Qing Duan, Erika Rasnick Manning, Judith W Dexheimer, Andrew F Beck, Cole Brokamp","doi":"10.1017/cts.2026.10733","DOIUrl":"10.1017/cts.2026.10733","url":null,"abstract":"<p><strong>Introduction: </strong>Persistent disparities in child health highlight the need for clinical and public health research approaches to identify and address risks with greater spatial precision. This study linked residence-and neighborhood-specific socio-environmental data to population-wide healthcare data to characterize pediatric hospitalization risk for every residential address in Cincinnati, Ohio.</p><p><strong>Methods: </strong>We linked hospitalization data (07/01/2016-06/30/2022) to parcel-level housing data from the Hamilton County Auditor and Cincinnati Department of Buildings & Inspections and street-range crime data from the Cincinnati Police Department. Addresses were localized to 2010 census tracts to join variables from the US Census American Community Survey and Eviction Lab. Generalized random forest models estimated address-level hospitalization risk and birth-adjusted hospitalization risk, accounting for child residency using vital birth records. Model performance was assessed based on varying diagnostic thresholds; fairness was evaluated by census block-level racial demographics.</p><p><strong>Results: </strong>We matched 81.5% of hospitalizations to residential addresses. Among 77,077 addresses, 7.4% had ≥1 hospitalization. Our model performed well (ROC-AUC: 0.98-0.99; PR-AUC: 0.65-0.72) in characterizing high-risk addresses, with housing violations, violent crime, and market total value among top features. The birth-adjusted model also showed high performance (ROC-AUC: 0.92-0.93; PR-AUC: 0.65-0.78) and moderate agreement with the hospitalization risk model (<i>κ</i> = 0.43).</p><p><strong>Conclusions: </strong>Our results highlight the potential of address-level modeling and multiscale data integration to build on traditional area-level analyses and advance precision population health. Future directions include geographic expansion, stakeholder engagement, and patient-level validation. This work offers a scalable approach to precisely identifying pediatric health risks, supporting targeted clinical and policy interventions.</p>","PeriodicalId":15529,"journal":{"name":"Journal of Clinical and Translational Science","volume":"10 1","pages":"e75"},"PeriodicalIF":2.0,"publicationDate":"2026-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13107074/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147771514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Retrieval-enhanced drafting of ClinicalTrials.gov data elements from clinical protocols.","authors":"Ramya Sri Baluguri, Nicholas Anderson","doi":"10.1017/cts.2026.10735","DOIUrl":"https://doi.org/10.1017/cts.2026.10735","url":null,"abstract":"<p><strong>Background: </strong>Manual submission of clinical trial data to the ClinicalTrials.gov registry is labor-intensive and error-prone, contributing to variability in the completeness and consistency of registry entries. To explore whether recent advances in large language models could support this process, we developed ChatCT, a pilot retrieval-augmented system that drafts ClinicalTrials.gov registry elements.</p><p><strong>Methods: </strong>We evaluated ChatCT-generated registry elements across three dimensions: 1. semantic similarity to the public ClinicalTrials.gov record, 2. formatting compliance with ClinicalTrials.gov requirements, and 3. coverage of key trial biomedical concepts.</p><p><strong>Results: </strong>ChatCT-generated registry elements were highly semantically similar to human-authored ClinicalTrials.gov records (median BERTScore F1 ≈ 0.82). Formatting compliance was high for structured elements, including Study Design (91% of required fields present; mean completeness 0.897) and Arms/Interventions (75%; 0.772), while narrative sections showed greater variability, including Outcome Measures (79%; 0.929) and Study Description (57%; 0.784). Ontology-based concept extraction and matching demonstrated consistently high precision, with scores ranging from 90% to 100%.</p><p><strong>Conclusions: </strong>A retrieval-augmented large language model can generate ClinicalTrials.gov registry drafts that preserve essential protocol details and adhere to most formatting requirements. However, light post-processing (e.g., automated schema validation) remains necessary for full submission readiness. This proof-of-concept evaluation suggests that ChatCT-assisted drafting could support registry reporting by improving consistency between protocol documents and publicly reported trial information.</p>","PeriodicalId":15529,"journal":{"name":"Journal of Clinical and Translational Science","volume":"10 1","pages":"e76"},"PeriodicalIF":2.0,"publicationDate":"2026-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13107080/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147771489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Competency-based compensation adjustment model: A new paradigm for clinical research coordinator merit advancement.","authors":"Kate Marusina, Paige Kular, David Grigoryan, Brian Linhardt","doi":"10.1017/cts.2026.10737","DOIUrl":"https://doi.org/10.1017/cts.2026.10737","url":null,"abstract":"<p><p>Attrition of experienced clinical research coordinators (CRCs) remains one of the most significant challenges to clinical and translational research. While multiple factors contribute to CRC retention, adequate compensation remains one of the most important. This manuscript describes a novel methodology for applying Joint Task Force (JTF) clinical research competencies as a guiding framework for salary adjustments via a pilot program for clinical research staff. This methodology can be adapted to a variety of institutional settings, especially in environments where opportunities for salary advancement are constrained by labor contracts. At UC Davis, CRC salary advancements are defined by contractual agreements with the Union of the Professional and Technical Employees, Research Support Professionals Unit (UPTE RX). While the union contract allows for periodic, across-the-board (all UPTE RX members) salary increases, it does not include clear provisions for merit-or competency-based increases. The CRC Equity Pathway is the first institutional compensation strategy that ties salary advancement to CRC competency, taking a significant step toward eliminating historical salary inequities. The pilot program described in this manuscript demonstrated that the CRC Equity Pathway is a viable mechanism for standardizing job descriptions around the JTF competencies, and for informing corresponding salary adjustments.</p>","PeriodicalId":15529,"journal":{"name":"Journal of Clinical and Translational Science","volume":"10 1","pages":"e80"},"PeriodicalIF":2.0,"publicationDate":"2026-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13126407/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147815716","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Erratum: Evaluating efforts to advance equity and inclusion in academic medicine: Charting a path for transformative change - CORRIGENDUM.","authors":"Ju-Hsin Chen, Emma K T Benn, Erin Brittain, Nihal E Mohamed","doi":"10.1017/cts.2026.10731","DOIUrl":"https://doi.org/10.1017/cts.2026.10731","url":null,"abstract":"<p><p>[This corrects the article DOI: 10.1017/cts.2026.10237.].</p>","PeriodicalId":15529,"journal":{"name":"Journal of Clinical and Translational Science","volume":"10 1","pages":"e53"},"PeriodicalIF":2.0,"publicationDate":"2026-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13107353/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147772878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Leveraging brief annual pauses in implementation: Using a rapid qualitative approach to inform iterative planning and adaptation of a school-based asthma program.","authors":"Julia Reedy, Nicole M Wagner, Amy G Huebschmann, Avery Schaefer, Anowara Begum, Rachel Armstrong, Michaela Brtnikova, Melanie Gleason, Stanley Szefler, Lisa Cicutto, Sarah E Brewer","doi":"10.1017/cts.2026.10730","DOIUrl":"https://doi.org/10.1017/cts.2026.10730","url":null,"abstract":"<p><strong>Background: </strong>Asthma is a prevalent chronic pediatric condition associated with significant health disparities. The Better Asthma Control for Kids (BACK) program aims to reduce asthma disparities and improve asthma control for children in high-need schools in four regions of Colorado.</p><p><strong>Methods: </strong>We conducted in-depth, semi-structured interviews (Dec 2023-June 2024) with key roles involved in BACK including school nurses, asthma navigators, and caregivers of participating students with asthma. Interviews and rapid qualitative analysis were informed by the Practical Robust, Implementation, and Sustainability Model (PRISM). We gathered perspectives, feedback, and recommendations about BACK to inform adaptation of the intervention and implementation strategy packages.</p><p><strong>Results: </strong>Participants (<i>n</i> = 39) included 6 asthma navigators, 17 school nurses, and 16 caregivers. Four overarching themes emerged: 1) perceived benefits of the BACK program, 2) challenges with school nurse engagement, communication, and perceptions of BACK, 3) difficulty with identification, documentation, and enrollment of students with asthma at the beginning of the school year, and 4) mismatches in program scope and alignment with school and family contexts.</p><p><strong>Conclusion: </strong>Identifying key challenges and participant recommendations supported the research team's \"adapt and tailor to context\" strategy in annual rapid evaluation and planning cycles. Obtaining feedback from program adopters, implementers, and recipients led to complementary recommendations to improve program delivery and user experiences. This approach may be transferable to other implementation-effectiveness trials, particularly those in schools or with other natural pauses that facilitate annual iterations in program delivery.</p><p><strong>Trial registration: </strong>Clinicaltrials.gov identifier NCT06003569, registered on August 22, 2023, https://clinicaltrials.gov/study/NCT06003569.</p>","PeriodicalId":15529,"journal":{"name":"Journal of Clinical and Translational Science","volume":"10 1","pages":"e64"},"PeriodicalIF":2.0,"publicationDate":"2026-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13107077/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147772908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of the National Dental PBRN central IRB since its inception in 2014 until 2025.","authors":"Muna Anabtawi, Gregg H Gilbert, Joana Cunha-Cruz, Vanessa Champigny, Adam McClintock","doi":"10.1017/cts.2026.10728","DOIUrl":"10.1017/cts.2026.10728","url":null,"abstract":"<p><strong>Introduction: </strong>The National Dental PBRN Central Institutional Review Board (CIRB) at the University of Alabama-Birmingham (UAB) was established in 2014 to reduce administrative burden while allowing Local Context Review (LCR) by local institutions (LIs). The National Institutes of Health implemented a single IRB policy in 2018; CIRB meets its requirements.</p><p><strong>Methods: </strong>The CIRB reviews study protocols, documents, consent forms, and HIPAA forms. Once CIRB approval is obtained, the study packet is sent to LIs for LCR. LIs may revise specific sections agreed on in reliance agreements but must make determinations regarding the HIPAA Privacy Rule. Once a LI completes a reliance agreement and the LCR, the CIRB becomes responsible for subsequent reviews.</p><p><strong>Results: </strong>The CIRB has reviewed 27 studies, 8 of which were declared exempt; LIs are responsible for exempt studies. Nineteen studies were declared expedited or full review. For all expedited/full review studies combined, the mean (SD) calendar days from initial submission to approval was 55.2 (35.2) days; for studies with available tracking, 35% of this time was due to waiting on study investigator responses. Post-approval submissions for 19 studies, such as revision amendments, continuing reviews, site amendments, prompt reports, and personnel amendments, totaled to 374.</p><p><strong>Conclusions: </strong>The CIRB did not ensure a shorter approval time because LCR approvals must wait for initial CIRB approval, but LIs did benefit by starting with an already-approved packet. However, substantial benefits were realized later because subsequent amendments and annual reviews only required CIRB review, saving LIs from involvement in these reviews.</p>","PeriodicalId":15529,"journal":{"name":"Journal of Clinical and Translational Science","volume":"10 1","pages":"e71"},"PeriodicalIF":2.0,"publicationDate":"2026-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13107356/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147772903","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using the readiness assessment for pragmatic trials (RAPT) model to structure partner engagement and strengthen pragmatic research readiness.","authors":"Rosa R Baier, Peter T Serina, Ann Reddy, Anna Stanislawski, Nate Hunkins, Ellen McCreedy","doi":"10.1017/cts.2026.10726","DOIUrl":"10.1017/cts.2026.10726","url":null,"abstract":"<p><p>Partner engagement is critical for embedded pragmatic research, yet few structured methods guide early collaboration to strengthen feasibility and mutual understanding. In this case study, Brown University researchers and leaders from a US-based medical practice, Bluestone Physician Services, used the readiness assessment for pragmatic trials (RAPT) model to guide structured discussion and qualitative readiness assessment of a partner-identified intervention concept aimed at improving the timing of palliative care services. Collaborative completion of RAPT created a shared process for assessing feasibility, contextual fit, and alignment with Bluestone priorities. The exercise identified domains needing refinement and guided planning to strengthen data, workflows, and measurement, demonstrating that RAPT can serve as a practical framework for early-stage co-design in pragmatic research.</p>","PeriodicalId":15529,"journal":{"name":"Journal of Clinical and Translational Science","volume":"10 1","pages":"e63"},"PeriodicalIF":2.0,"publicationDate":"2026-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13058754/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147644905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Characteristics of interventional clinical trials registered in ClinicalTrials.gov, 2018-2023.","authors":"Rebecca D Sullenger, Robert M Clare, Ali B Abbasi, Karen E Chiswell, Lesley H Curtis, Bradley G Hammill, Martin J Landray, Christopher J Lindsell, Scott M Palmer, Sara Bristol Calvert, Adrian F Hernandez","doi":"10.1017/cts.2026.10701","DOIUrl":"https://doi.org/10.1017/cts.2026.10701","url":null,"abstract":"<p><strong>Introduction: </strong>It remains unclear whether the US clinical trial ecosystem is optimized to evaluate medical interventions efficiently. This study characterizes interventional clinical trials in the USA and examines trial progress over five years.</p><p><strong>Methods: </strong>Using the Aggregate Analysis of ClinicalTrials.gov (AACT) database, we conducted a cross-sectional study of interventional trials initiated in 2023 and a follow-up cohort tracking five-year completion for trials started in 2018 and registered in ClinicalTrials.gov as of 05/01/2024 by sponsor and therapeutic area. Trials with at least one US site were included. Primary outcomes were enrollment, completion status, intervention type, study arm design, and plan to share individual participant data.</p><p><strong>Results: </strong>Over 7,500 trials met inclusion criteria for each cohort. Most trials started in 2018 (68.4%) and 2023 (62.5%) enrolled fewer than 100 participants. Median enrollment in 2023 was higher for NIH (90) than industry-sponsored (76) trials. Within five years, 60.5% of the 2018 trials were completed, with higher completion among industry (60.9%) than NIH-sponsored (54.3%) trials. In 2023, industry predominantly funded cancer studies and trials testing drug interventions, whereas the NIH prioritized mental health studies and behavioral interventions. More than one-quarter of trials used a single-group design, 72.0% did not plan to share participant-level data, and 72.6% of drug trials were early phase.</p><p><strong>Conclusion: </strong>Many clinical trials are small, lack a control group, and are incomplete within five years, with differences by sponsor. Given the urgent need to improve health through rigorous evidence generation, there are likely opportunities to improve the US clinical trial ecosystem.</p>","PeriodicalId":15529,"journal":{"name":"Journal of Clinical and Translational Science","volume":"10 1","pages":"e66"},"PeriodicalIF":2.0,"publicationDate":"2026-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13107079/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147772867","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development and psychometric analyses of a mentee competency self-assessment (MCSA) tool.","authors":"So Hee Hyun, Jonathan M Orsini, Kimberly Spencer, Stephanie C House, Christine Pfund","doi":"10.1017/cts.2026.10727","DOIUrl":"https://doi.org/10.1017/cts.2026.10727","url":null,"abstract":"<p><strong>Introduction: </strong>This paper presents the development and psychometric analyses of the Mentee Competency Self-Assessment (MCSA), a tool designed to evaluate mentee skills in research mentoring relationships and assess the <i>Mentoring Up</i> curriculum. By assessing mentee competencies across diverse settings, the study aims to enhance understanding of mentoring dynamics and highlight the importance of considering both mentor and mentee perspectives in assessing mentorship effectiveness.</p><p><strong>Methods: </strong>The 26-item MCSA instrument was developed based on the validated Mentoring Competency Assessment (MCA) to evaluate the <i>Mentoring Up</i> curriculum. Data was obtained from 401 mentees who attended <i>Mentoring Up</i> workshops between 2015 and 2022. Principal component analysis (PCA) was performed with varimax rotation to examine the internal structure of the MCSA. A team of mentoring experts independently reviewed and reached consensus on component alignment. Confirmatory factor analysis (CFA) and internal consistency were performed to assess construct validity and reliability.</p><p><strong>Results: </strong>Factor and reliability analyses support an eight-component structure of a 22-item MCSA. All parameter estimates were significant, and the components demonstrated acceptable to high internal consistency (Cronbach's alpha = 0.58-0.90).</p><p><strong>Conclusions: </strong>The final 22-item scale (MCSA-22) aligns with eight competencies and is now suited for measuring mentee mentorship skills. Given the modest sample size and other study limitations, replication of this proposed modification of the MCSA is an important next step. Additional recommendations for future scale development are offered.</p>","PeriodicalId":15529,"journal":{"name":"Journal of Clinical and Translational Science","volume":"10 1","pages":"e70"},"PeriodicalIF":2.0,"publicationDate":"2026-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13107358/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147772921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}