As clinical trials adopt remote methodologies, there is need to optimize efficiency of remote enrollment. Within a remote clinical trial, we aim to (1) assess if sociodemographic factors differ among those consenting via mail vs. technology-based procedures (e-consent), (2) determine if, among those consenting via mail, a small unconditional monetary reward ($5) increases likelihood of subsequent enrollment, (3) economically evaluate additional cost per additional participant enrolled with $5 reward.

In the parent nationwide randomized clinical trial of adult smokers (N = 638), participants could enroll via mail or e-consent. Logistic regression models assessed relationships between sociodemographics and enrollment via mail (vs e-consent). Mailed consent packets were randomized (1:4) to include $5 unconditional reward or not, and logistic regression modeling examined impact of reward on subsequent enrollment, allowing for a randomized study within a study. Incremental cost-effectiveness ratio analysis estimated additional cost per additional participant enrolled with $5 incentive.

Older age, less education, lower income, and female sex predicted enrolling via mail vs e-consent (p < .05’s). In adjusted model, older age (AOR = 1.02, p = .016) and less education (AOR = 2.23, p < .001) remained predictive of mail enrollment. The $5 incentive (vs none) increased enrollment rate by 9% (AOR = 1.64, p = .007), with estimated cost of additional $59 per additional participant enrolled.

As e-consent methods become more common, they have potential to reach many individuals but with perhaps diminished inclusion across all sociodemographic groups. Provision of an unconditional monetary incentive is possibly a cost-effective mechanism to increase recruitment efficiency for studies employing mail-based consenting procedures.

Real-world data, such as administrative claims and electronic health records, are increasingly used for safety monitoring and to help guide regulatory decision-making. In these settings, it is important to document analytic decisions transparently and objectively to assess and ensure that analyses meet their intended goals.

The Causal Roadmap is an established framework that can guide and document analytic decisions through each step of the analytic pipeline, which will help investigators generate high-quality real-world evidence.

In this paper, we illustrate the utility of the Causal Roadmap using two case studies previously led by workgroups sponsored by the Sentinel Initiative – a program for actively monitoring the safety of regulated medical products. Each case example focuses on different aspects of the analytic pipeline for drug safety monitoring. The first case study shows how the Causal Roadmap encourages transparency, reproducibility, and objective decision-making for causal analyses. The second case study highlights how this framework can guide analytic decisions beyond inference on causal parameters, improving outcome ascertainment in clinical phenotyping.

These examples provide a structured framework for implementing the Causal Roadmap in safety surveillance and guide transparent, reproducible, and objective analysis.

Purposeful training and ongoing career support are necessary to meet the evolving and expanding roles of clinical research professionals (CRP). To address the training and employment needs of clinical research coordinators (CRCs), one of the largest sectors of the CRP workforce, we designed, developed, and implemented an online career navigation system, eMPACTTM (eMpowering Purposeful Advancement of Careers and Training).

A design-based research method was employed as an overarching approach that frames iterative design, development, and implementation of educational interventions. The five major phases of this project – conceptualization, task analysis for measurement development, algorithms development, algorithms validation, and system evaluation – presented specific goals and relevant methods.

The results reported how the eMPACTTM system was conceptualized, developed, and validated. The system allowed CRCs to navigate tailored training and job opportunities by completing their task competencies and career goals. The data sets could, in turn, support employees’ and training coordinators’ informed decisions about organizational training needs and recruitment. The early dissemination results showed steady growth in registered CRCs and diversity in users’ ethnicity and job levels.

The eMPACTTM service showed the possibility of supporting CRCs’ individual career advancement and organizational workforce enhancement and diversity. Long-term research is needed to evaluate its impact on CRC workforce development, explore key factors influencing workforce sustainability, and expand eMPACTTM service to other CRP sectors.

Greater than 40% of women are obese, a key risk factor for cardiometabolic, neurocognitive disease, mood disorders, and certain cancers. Obesity and unfavorable body composition can compromise physical and psychological health and well-being. Preliminary evidence demonstrates Meditative Movement (i.e., Tai Chi Easy) improves health outcomes and body composition among midlife/older women. This single-group pilot study explored relationships between well-being predictors related to body composition and associated behavioral risk factors in midlife/older women pre-to-post Tai Chi Easy intervention.

Eligible women 45–75 years old, participated in once-weekly 30-minute Tai Chi Easy classes over 8-weeks. Pre/post-intervention data included self-report surveys and on-site body composition. Multivariate linear regression models were fitted with putative predictor variables having correlations p-values of 0.20 or less with sleep quality and eating behaviors.

Participants (N = 36) (M age = 53.7) were White (80.4%) and attended ≥ 4 years of college (70.6%). Analyses resulted in one independent variable per model as a predictor of the dependent variables of sleep quality and emotional eating. Results indicated: (1) stress explained 13.4% sleep quality variance (F (2, 20) = 2.71, p = 0.09) and (2) self-compassion explained 42.1% emotional eating variance (F (2, 31) = 12.54, p < .01).

Findings suggest stress and self-compassion partially explain variance in the dependent variables of sleep quality and emotional eating, both associated behavioral risk factors of body composition. Additional research may guide interventions to test efficacy and examine mediators to improve well-being predictors, body composition, and associated behavioral risk factors among midlife/older women.

The Fibrosis-4 (FIB-4) index, a simple index that includes age, liver enzymes, and platelet count has been studied as a tool to identify patients at a risk of requiring mechanical ventilation due to its high negative predictive value. It is unknown if FIB-4 remains useful to predict the severity of respiratory disease requiring mechanical ventilation amongst new Coronavirus disease 2019 (COVID-19) variants and whether a relationship also exists between FIB-4 and 30-day mortality. The main objective was to determine if FIB-4 can predict mechanical ventilation requirements and 30-day mortality from COVID-19 across variants including Alpha, Delta, and Omicron.

This was a population-based, retrospective cohort analysis of 232,364 hospitalized patients in the National COVID-19 Cohort Collaborative between the age of 18–90 who tested positive for COVID-19 between April 27, 2020 and June 25, 2022. The primary outcome was association between FIB-4 and need for mechanical ventilation. Secondary measures included the association of FIB-4 with 30-day mortality.

A FIB-4 > 2.67 had 1.8 times higher odds of requiring mechanical ventilation across all variants of COVID-19 (OR 1.81; 95% CI: [1.76, 1.86]). The area under the ROC curve showed high diagnostic accuracy with values ranging between 0.79 (Omicron wave) and 0.97 (delta wave). Increased FIB-4 was associated with 30-day mortality across the variates.

The FIB-4 was consistently associated with both increased utilization of mechanical ventilation and 30-day mortality among COVID-19 patients across all waves in both adjusted and unadjusted models. This provides a simple tool for risk-stratification for front-line health care professionals.

The United States Congress passed the 21st Century Cures Act mandating the development of Food and Drug Administration guidance on regulatory use of real-world evidence. The Forum on the Integration of Observational and Randomized Data conducted a meeting with various stakeholder groups to build consensus around best practices for the use of real-world data (RWD) to support regulatory science. Our companion paper describes in detail the context and discussion of the meeting, which includes a recommendation to use a causal roadmap for study designs using RWD. This article discusses one step of the roadmap: the specification of a sensitivity analysis for testing robustness to violations of causal model assumptions.

We present an example of a sensitivity analysis from a RWD study on the effectiveness of Nifurtimox in treating Chagas disease, and an overview of various methods, emphasizing practical considerations on their use for regulatory purposes.

Sensitivity analyses must be accompanied by careful design of other aspects of the causal roadmap. Their prespecification is crucial to avoid wrong conclusions due to researcher degrees of freedom. Sensitivity analysis methods require auxiliary information to produce meaningful conclusions; it is important that they have at least two properties: the validity of the conclusions does not rely on unverifiable assumptions, and the auxiliary information required by the method is learnable from the corpus of current scientific knowledge.

Prespecified and assumption-lean sensitivity analyses are a crucial tool that can strengthen the validity and trustworthiness of effectiveness conclusions for regulatory science.

Previous studies have examined the impact of Clinical and Translational Science Awards programs on other outcomes, but not on grant seeking. The authors examined the effects on grant seeking of the Michigan Institute for Clinical & Health Research (MICHR), a Clinical and Translational Science Awards institute at the University of Michigan.

We assessed over 63,000 grant proposals submitted at the University of Michigan in the years 2002–2012 using data from the university and MICHR’s Tracking Metrics and Reporting System. We used a retrospective, observational study of the dynamics of grant-seeking success and award funding. Heckman selection models were run to assess MICHR’s relationship with a proposal’s success (selection), and subsequently the award’s size (outcome). Models were run for all proposals and for clinical and translational research (CTR) proposals alone. Other covariates included proposal classification, type of grant award, academic unit, and year.

MICHR had a positive and statistically significant relationship with success for both proposal types. For all grants, MICHR was associated with a 29.6% increase in award size. For CTR grants, MICHR had a statistically nonsignificant relationship with award size.

MICHR’s infrastructure, created to enable and enhance CTR, has also created positive spillovers for a broader spectrum of research and grant seeking.

Text message-delivered interventions for chronic disease self-management have potential to reduce health disparities, yet limited research has explored implementing these interventions into clinical care. We partnered with safety net clinics to evaluate a texting intervention for type 2 diabetes called REACH (Rapid Encouragement/Education And Communications for Health) in a randomized controlled trial. Following evaluation, we explored potential implementation determinants and recommended implementation strategies.

We interviewed clinic staff (n = 14) and a subset of intervention participants (n = 36) to ask about REACH’s implementation potential. Using the Consolidated Framework for Implementation Research (CFIR) as an organizing framework, we coded transcripts and used thematic analysis to derive implementation barriers and facilitators. We integrated the CFIR-ERIC (Expert Recommendations for Implementing Change) Matching Tool, interview feedback, and the literature to recommend implementation strategies.

Implementation facilitators included low complexity, strong evidence and quality, available clinic resources, the need for a program to support diabetes self-management, and strong fit between REACH and both the clinics’ existing workflows and patients’ needs and resources. The barriers included REACH only being available in English, a lack of interoperability with electronic health record systems, patients’ concerns about diabetes stigma, limited funding, and high staff turnover. Categories of recommended implementation strategies included training and education, offering flexibility and adaptation, evaluating key processes, and securing funding.

Text message-delivered interventions have strong potential for integration in low-resource settings as a supplement to care. Pursuing implementation can ensure patients benefit from these innovations and help close the research to practice gap.

Studies that measure environmental exposures in biological samples frequently provide participants their results. In contrast, studies using personal air monitors do not typically provide participants their monitoring results. The objective of this study was to engage adolescents who completed personal air sampling and their caregivers to develop understandable and actionable report-back documents containing the results of their personal air sampling.

Adolescents and their caregivers who previously completed personal air sampling participated in focus groups to guide the development of report-back materials. We conducted thematic analyses of focus group data to guide the design of the report-back document and convened experts in community engagement, reporting study results, and human subjects research to provide feedback. Final revisions to the report-back document were made based on follow-up focus group feedback.

Focus groups identified critical components of an air-monitoring report-back document to include an overview of the pollutant being measured, a comparison of individual personal sampling data to the overall study population, a guide to interpreting results, visualization of individual data, and additional information on pollution sources, health risks, and exposure reduction strategies. Participants also indicated their desire to receive study results in an electronic and interactive format. The final report-back document was electronic and included background information, participants’ results presented using interactive maps and figures, and additional material regarding pollution sources.

Studies using personal air monitoring technology should provide research participants their results in an understandable and meaningful way to empower participants with increased knowledge to guide exposure reduction strategies.

Physician-scientists have long been in high demand owing to their role as key drivers of biomedical innovation, but their dwindling prevalence in research and medical communities threatens ongoing progress. As the principal avenue for physician-scientist development, combined MD–PhD training programs and NIH-funded Medical Scientist Training Programs (MSTPs) must address all aspects of career development, including grant writing skills.

The NIH F-series grants – the F30 grant in particular – model the NIH format of federal funding, and are thus ideal opportunities to acquire biomedical research grant preparation experience. Therefore, in this report, we describe a curricular model through which predoctoral MSTP students obtain exposure to – and training for – F-series grant conceptualization, writing, and evaluation.

Since the development of these longitudinal courses, we observed trending improvements in student funding success rates, particularly among original submissions, and perceived benefits among participating students.

The Clinical and Translational Science Award Program (CTSA) Trial Innovation Network (TIN) was launched in 2016 to increase the efficiency and effectiveness of multisite trials by supporting the development of national infrastructure. With the advent of the COVID-19 pandemic, it was therefore well-positioned to support clinical trial collaboration. The TIN was leveraged to support two initiatives: (1) to create and evaluate a mechanism for coordinating Data and Safety Monitoring Board (DSMB) activities among multiple ongoing trials of the same therapeutic agents, and (2) to share data across clinical trials so that smaller, likely underpowered studies, could be combined to produce meaningful and actionable data through pooled analyses. The success of these initiatives was understood to be dependent upon the willingness of investigators, study teams, and US National Institutes of Health research networks to collaborate and share information.

To inform these two initiatives, we conducted semistructured interviews with members of CTSA hubs and clinical research stakeholders that probed barriers and facilitators to collaboration. Thematic analysis identified topics relevant across institutions, individuals, and DSMBs.

The DSMB coordination initiative was viewed as less controversial, while the data pooling initiative was seen as complex because of its potential impact on publication, authorship, and the rewards of discovery. Barriers related to resources, centralization, and technical work were significant, but interviewees suggested these could be handled by the provision of central funding and supportive frameworks. The more intractable findings were related to issues around credit and ownership of data.

Based on our interviews, we conclude with nine recommended actions that can be implemented to support collaboration.

This study examined the effectiveness of a formal postdoctoral education program designed to teach skills in clinical and translational science, using scholar publication rates as a measure of research productivity.

Participants included 70 clinical fellows who were admitted to a master’s or certificate training program in clinical and translational science from 1999 to 2015 and 70 matched control peers. The primary outcomes were the number of publications 5 years post-fellowship matriculation and time to publishing 15 peer-reviewed manuscripts post-matriculation.

Clinical and translational science program graduates published significantly more peer-reviewed manuscripts at 5 years post-matriculation (median 8 vs 5, p=0.041) and had a faster time to publication of 15 peer-reviewed manuscripts (matched hazard ratio = 2.91, p=0.002). Additionally, program graduates’ publications yielded a significantly higher average H-index (11 vs. 7, p=0.013).

These findings support the effectiveness of formal training programs in clinical and translational science by increasing academic productivity.