The avoidance of asthma triggers, like tobacco smoke, facilitates asthma management. Reliance upon caregiver report of their child’s environmental tobacco smoke (ETS) exposure may result in information bias and impaired asthma management. This analysis aimed to characterize the chronicity of ETS exposure, assess the validity of caregiver report of ETS exposure, and investigate the relationship between ETS exposure and asthma attack.

A secondary data analysis was performed on data from a longitudinal study of 162 children aged 7–12 years with asthma living in federally subsidized housing in three US cities (Boston, Cincinnati, and New Orleans). Data were collected at three time points over 1 year.

Over 90% of children were exposed to ETS (≥0.25 ng/ml of urine cotinine (UC)). Exposure was consistent over 1 year. Questionnaire data had a sensitivity of 28–34% using UC ≥0.25 ng/ml as the gold standard. High ETS exposure (UC ≥ 30 ng/ml) was significantly associated with asthma attack (aOR 2.97, 0.93–9.52, p = 0.07). Lower levels (UC 0.25–30 ng/ml) were not statistically significant (aOR 1.76, 0.71– 4.38, p = 0.22). No association was found using caregiver-reported ETS exposure.

Relying on questionnaire data to assess children’s exposure to tobacco smoke may lead to substantial information bias. For children with asthma, incorrect characterization may substantially impact asthma morbidity.

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 classical randomized clinical trials (RCTs) are the gold standard for proof of drug efficacy, randomized discontinuation trials (RDTs), sometimes called “enriched” trials, are used increasingly, especially in psychiatric maintenance studies.

A narrative review of two decades of experience with RDTs.

RDTs in psychiatric maintenance trials tend to use a dependent variable as a predictor: treatment response. Treatment responders are assessed for treatment response. This tautology in the logic of RDTs renders them invalid, since the predictor and the outcome are the same variable. Although RDTs can be designed to avoid this tautologous state of affairs, like using independent predictors of outcomes, such is not the case with psychiatric maintenance studies

Further, purported benefits of RDTs regarding feasibility were found to be questionable. Specifically, RDTs do not enhance statistical power in many settings, and, because of high dropout rates, produce results of questionable validity. Any claimed benefits come with notably reduced generalizability.

RDTs appear to be scientifically invalid as used in psychiatric maintenance designs. Their purported feasibility benefits are not seen in actual trials for psychotropic drugs. There is warrant for changes in federal policy regarding marketing indications for maintenance efficacy using the RDT design.

Large, transdisciplinary research consortia have increasingly been called upon to address complex and challenging health problems. The National Institutes of Health’s (NIH) Environmental influences on Child Health Outcomes (ECHO) Program developed multisite collaboration strategies to promote impactful collaborative observational research on child health. Team science and implementation science offer theoretical and methodological structure to answer questions about the strategies that facilitate successful consortia. We sought to characterize the elements and conditions that influence the implementation of a complex, interdisciplinary longitudinal research program, ECHO.

Informed by the Practical, Robust, Implementation and Sustainability Model, our ethnographic research included semi-structured interviews with internal stakeholders and program evaluation metrics. We conducted template and matrix analysis and triangulated the qualitative and quantitative data to understand the implementation of ECHO.

Between February and May 2022, we conducted 24 virtual interviews with representatives from ECHO components. The main cross-cutting topics that emerged from thematic analysis were collaboration and team science; communication and decision-making; data processes and harmonization; and diversity, equity, and inclusion. Both the qualitative and secondary quantitative evaluation data provided insights into the reach, adoption, implementation, and effectiveness of the program.

A large, multidisciplinary research consortium such as ECHO has produced conceptual, instrumental, capacity building, and connectivity impact for internal and external stakeholders. Facilitators included infrastructure that supported collaboration and learning, alignment of data processes, and harmonization. Opportunities for enhanced impact include multidisciplinary, multimethod communication strategies, and alignment of research priorities.

Recruiting and retaining racial/ethnic minorities in research remains a significant challenge, often due to mistrust in clinical research and cultural misconceptions related to specific conditions. Despite the anonymity provided by technology-based intervention studies, difficulties in participant recruitment and retention in these studies remain. This paper addresses practical issues in recruiting and retaining Asian American breast cancer survivors with pain and depressive symptoms in a technology-based intervention study.

To identify practical issues in participant recruitment and retention, a content analysis was conducted on all recorded materials, including research diaries of individual research team members, weekly team meeting minutes, and research team members’ posts on Microsoft Teams.

Analysis identified six practical issues: (a) strict inclusion/exclusion criteria; (b) multiple stigmas associated with cancer, depressive symptoms, and pain; (c) lack of interest in research participation; (d) closed Asian American communities/groups; (e) frequent technological issues; and (f) potential unauthentic cases.

Addressing these recruitment and retention issues can inform the design of future culturally tailored, technology-based intervention studies for racial and ethnic minority populations.

Food and Drug Administration’s (FDA) Draft Guidance for Industry on pharmaceutical REMS (Risk Evaluation and Mitigation Strategies) assessment and survey methodology highlights physician knowledge–attitudes–behaviors (KAB) surveys as regulatory science tools. This mixed-methods evaluation advances regulatory science and the assessment of FDA REMS programs when using physician surveys. We: (1) reviewed published physician survey response rates; and (2) assessed response bias in a simulation study of secondary survey data using different accrual cut-off strategies.

A systematic literature review was conducted of US physician surveys (2000–2014) on pharmaceutical use (n = 75). Kruskal–Wallis tests were used to examine the relationships between response rates and survey design characteristics. The simulation was conducted using secondary data from a population-based physician KAB survey on diabetes risk management with antipsychotic use in Missouri Medicaid (n = 973 accrued over 30 weeks). Survey item responses were compared using Pearson’s chi-square tests for two faster completion simulations: Fixed Sample (n = 300) and Fixed Time (8 weeks).

Survey response rates ranged from 7% to 100% (median = 48%, IQR = 34%–68%). Surveys of targeted populations and surveys using member lists were associated with higher response rates (p = 0.02). In the simulation, 9 of 20 (45%) KAB items, including diabetes screening advocacy, differed significantly using the smaller Fixed Sample strategy (achieved in 12 days) versus full accrual. Fewer response differences were found using the Fixed Time strategy (2 of 20 [10%] items).

Published data on physician surveys report low response rates with most associated with the sample source selected. FDA REMS assessments should include formal evaluation of survey accrual and response bias.

Randomized clinical trials (RCT) are the foundation for medical advances, but participant recruitment remains a persistent barrier to their success. This retrospective data analysis aims to (1) identify clinical trial features associated with successful participant recruitment measured by accrual percentage and (2) compare the characteristics of the RCTs by assessing the most and least successful recruitment, which are indicated by varying thresholds of accrual percentage such as ≥ 90% vs ≤ 10%, ≥ 80% vs ≤ 20%, and ≥ 70% vs ≤ 30%.

Data from the internal research registry at Columbia University Irving Medical Center and Aggregated Analysis of ClinicalTrials.gov were collected for 393 randomized interventional treatment studies closed to further enrollment. We compared two regularized linear regression and six tree-based machine learning models for accrual percentage (i.e., reported accrual to date divided by the target accrual) prediction. The outperforming model and Tree SHapley Additive exPlanations were used for feature importance analysis for participant recruitment. The identified features were compared between the two subgroups.

CatBoost regressor outperformed the others. Key features positively associated with recruitment success, as measured by accrual percentage, include government funding and compensation. Meanwhile, cancer research and non-conventional recruitment methods (e.g., websites) are negatively associated with recruitment success. Statistically significant subgroup differences (corrected p-value < .05) were found in 15 of the top 30 most important features.

This multi-source retrospective study highlighted key features influencing RCT participant recruitment, offering actionable steps for improvement, including flexible recruitment infrastructure and appropriate participant compensation.

The US Food and Drug Administration (FDA) is responsible for assessing safety (risks) and effectiveness (benefits) of new drug products using the data provided in a Sponsor’s new drug product marketing application before they can be marketed. The FDA forms cross-disciplinary review teams to conduct these assessments. Recently, the FDA began implementing more interdisciplinary approaches to its assessments, reducing redundancy in review processes and documentation by increasing team integration around review issues.

Through a phenomenological descriptive comparative case study, the impact of FDA’s new interdisciplinary approach on review team integration was compared with its traditional multidisciplinary review approach.

We identified collaborative integration occurring in one FDA review team using the new interdisciplinary review and another team using the traditional review and then modeled and analyzed the collaborative, cross-disciplinary integration in each case using an input-process-output (IPO) model drawn from the Science-of-Team-Science (SciTS).

This study provides a systematic method for understanding and visualizing integration in each type of review previously and presently used at FDA and illustrates how the new interdisciplinary approach can ensure more integration than more traditional approaches previously used. In addition, our study suggests that an IPO model of integration can characterize how effectively FDA review teams are integrating around issues and assist in the evaluation of differences in integration between FDA’s new interdisciplinary review and the existing multidisciplinary approach. The approach used here is a new application of SciTS scholarship in a unique sector, and it also serves as an example for measuring review team effectiveness.

Pragmatic trials aim to speed translation to practice by integrating study procedures in routine care settings. This study evaluated implementation outcomes related to clinician and patient recruitment and participation in a trial of community paramedicine (CP) and presents successes and challenges of maintaining pragmatic study features.

Adults in the pre-hospital setting, emergency department (ED), or hospital being considered for referral to the ED/hospital or continued hospitalization for intermediate-level care were randomized 1:1 to CP care or usual care. Referral and enrollment data were tracked administratively, and patient characteristics were abstracted from the electronic health record (EHR). Enrolled patients completed baseline surveys, and a subset of intervention patients were interviewed. All CPs and a sample of clinicians and administrators were invited to complete a survey and interview.

Between January 2022 and February 2023, 240 enrolled patients (42% rural) completed surveys, and 22 completed an interview; 63 staff completed surveys and 20 completed an interview. Ninety-three clinicians in 27 departments made at least one referral. Factors related to referrals included program awareness and understanding the CP practice scope. Most patients were enrolled in the hospital, but characteristics were similar to the primary care population and included older and medically complex patients. Challenges to achieving representativeness included limited EHR infrastructure, constraints related to patient consenting, and clinician concerns about patient randomization disrupting preferred care.

Future pragmatic trials in busy clinical settings may benefit from regulatory policies and EHR capabilities that allow for real-world study conduct and representative participation. Trial registration: NCT05232799.

Electronic Health Record (EHR) data are critical for advancing translational research and AI technologies. The ENACT network offers access to structured EHR data across 57 CTSA hubs. However, substantial information is contained in clinical narratives, requiring natural language processing (NLP) for research. The ENACT NLP Working Group was formed to make NLP-derived clinical information accessible and queryable across the network.

We established the ENACT NLP Working Group with 13 sites selected based on criteria including clinical notes access, IT infrastructure, NLP expertise, and institutional support. We divided sites into five focus groups targeting clinical tasks within disease contexts. Each focus group consisted of two development sites and two validation sites. We extended the ENACT ontology to standardize NLP-derived data and conducted multisite evaluations using the Open Health Natural Language Processing (OHNLP) Toolkit.

The working group achieved 100% site retention and deployed NLP infrastructure across all sites. We developed and validated NLP algorithms for rare disease phenotyping, social determinants of health, opioid use disorder, sleep phenotyping, and delirium phenotyping. Performance varied across sites (F1 scores 0.53–0.96), highlighting data heterogeneity impacts. We extended the ENACT common data model and ontology to incorporate NLP-derived data while maintaining Shared Health Research Informatics NEtwork (SHRINE) compatibility.

This demonstrates feasibility of deploying NLP infrastructure across large, federated networks. The focus group approach proved more practical than general-purpose approaches. Key lessons include the challenge of data heterogeneity and importance of collaborative governance. This work also provides a foundation that other networks can build on to implement NLP capabilities for translational research.

Rural cancer survivors have worse outcomes than their urban counterparts. To improve outcomes, it is essential that rural survivors participate in research, yet they are underrepresented in cancer research. The aim of this study was to assess urban-rural differences in participation in a cancer survivorship survey and differences in mode of participation (mail, online, or phone) by rurality and age.

We developed a survivorship needs assessment survey and invited cancer survivors to participate by mail, online, or phone. We compared participation between rural and urban invitees and examined differences in mode of participation by rurality and age.

A quarter (25.47%) of invited rural patients and 27.84% of invited urban patients participated in the survivorship study. The probability of participation by urban survivors was approximately 1.09 times higher than for rural survivors (χ2(1) = 4.31, p = 0.038). Rural survivors were more likely to participate by mail (average difference [Rural-Urban] = 9.64%, p < 0.001), while urban survivors were more likely to participate online (average difference [Urban-Rural] = 8.77%, p < 0.001). As participant age increased, the likelihood of survey participation by mail increased (1.16% per year of age, p < 0.001) while the probability of participating online decreased by 1.20% per year of age (p < 0.001).

To ensure equitable access to research for rural and older cancer survivors, researchers should design studies with a range of participation modes. Non-digital methods, such as mailed paper surveys, appear to promote participation among rural and older survivors.

Older adults have a high disease burden but are often underrepresented in research studies due to recruitment and retention obstacles, among others. Geriatric research specialists have identified solutions to these challenges and designed frameworks to help other researchers. Our team utilized three frameworks to create an interactive webinar series aimed to educate research team members on Age-Friendly practices.

We recruited 40 non-aging-trained research team members to participate in a six-session, real-time webinar series from October to November 2022. Sessions were comprised of 20–30 minute didactics and 30–40 minute group discussions. Participants completed pre- and post-program surveys, commitment to change forms, and post-webinar session surveys. Responses were examined for strengths and areas for improvement. Wilcoxon signed-rank tests assessed differences in confidence scores.

Self-reported confidence scores improved after the webinar series. Most participants provided positive feedback and high likeliness to use what they learned and recommend the webinar to others. The strengths were practical tips, applicable tools, and real-world examples. The major area for improvement was information on industry-sponsored trials. The commitment to change responses varied from pledging to use more inclusive language to adapting materials to improve the consent process.

This interactive Age-Friendly Research webinar series was feasible and well received by participants. We created an Age-Friendly Research community fostering commitment to change clinical and translational research to be more inclusive of older adults. Future work will include more information on industry-sponsored trials and expand to other research centers.