Effective recruitment techniques are essential for researchers to recruit and retain potential participants in studies, particularly as recruitment numbers into clinical trials have decreased. While recruitment techniques have been investigated, there is a gap in understanding the perspectives of clinical trials recruiters. This paper examines recruiters’ usage and perceived effectiveness of various recruitment techniques, as well as their perspectives on related ethical issues.

We conducted a cross-sectional survey of 381 clinical trials recruiters. Closed-ended items examined whether recruiters had used 31 pre-defined recruitment techniques and their perceptions of the effectiveness of each technique. For techniques perceived to be highly effective or ineffective, open-ended items examined recruiter reasoning. The multiple methods analysis integrated the closed-ended and open-ended data.

Recruitment techniques such as reassured potential participants about confidentiality (96.3%) and reassured about data sharing (95.8%) had high usage, while techniques like having the PI approach and enroll had a high average perceived effectiveness (M = 4.23, SD = 0.91). Recruiters often rated techniques as more highly effective when they had prior experience using them. They also identified concerns about professionalism, ethics, and transparency in standard practice recruitment techniques.

Our findings indicate that there is significant variation in the usage of clinical trial recruitment techniques and how different recruiters view the effectiveness of each technique. The unique perspectives of those who recruit into clinical trials can help inform future decisions regarding which recruitment techniques to utilize, along with how and when to use particular recruitment techniques in an ethical manner.

Over the last two decades, there have been significant investments designed to advance clinical and translational research (CTR) with an emphasis on supporting early career investigators and building a cadre of skilled researchers. Despite the investments, there are no comprehensive measurement tools to track individual-level progress along the research continuum as supports are put in place.

The Researcher Investment Tool (RIT) is a novel tool that was created to provide a consistent approach for measuring individual-level changes in the research career trajectory of investigators receiving support from CTR programs.

The RIT is a 90-item questionnaire, with eight domains and four sub-domains, designed to measure a researcher’s experiences and perceptions. Several rounds of testing were conducted to assess the tool’s face and content validity as well as the internal consistency and test-retest reliability.

Psychometric testing revealed strong content validity and good internal consistency with Cronbach’s alpha coefficients ranging from 0.85 to 0.97 across all domains. Test-retest reliability results also revealed stability in the domain measures over time with Pearson’s correlation coefficients ranging from 0.70 to 0.98 for all but one domain (.53).

This novel RIT may be useful to evaluators when measuring the impact of investments designed to support early career clinical and translational researchers.

Academic Medical Centers (AMCs) with Clinical and Translational Science Awards (CTSAs) offer a range of resources to support clinical and translational research and science. However, research professionals often face challenges in navigating these resources effectively.

Our study sought to examine research navigation services across CTSA hubs to identify successful strategies, common challenges, and best practices for supporting research teams.

We conducted interviews with representatives from ten CTSA hubs and performed a landscape analysis to explore the types of research navigation services available, the methods of advertising and orienting faculty and staff, and the challenges faced in launching and maintaining these services.

Our analysis identified three primary types of research navigation services offered at CTSA hubs: online resource libraries, personalized research navigation with dedicated staff, and interdisciplinary research “studios” for protocol development. Despite these offerings, challenges such as low awareness, difficulties coordinating across siloed university systems, and limited metrics for evaluating navigation services persist.

Effective research navigation requires a combination of web-based applications and in-person support, backed by institutional commitment to foster engagement and streamline access. Key strategies for successful navigation services include proactive advertising, integration with orientation programs, and cross-departmental collaboration. Our findings offer actionable recommendations for enhancing research navigation at AMCs, ultimately aiming to increase research productivity and collaboration.

Understanding how different symptoms co-occur and are correlated may provide insights into the pathophysiology of disease. The lack of group-to-individual generalizability of co-occurrence of symptoms was recently demonstrated by comparing intra-individual and inter-individual correlations in several psychological studies. Here, we investigate this phenomenon for lower urinary tract symptoms (LUTS).

We analyzed data collected in the Symptoms of Lower Urinary Tract Dysfunction Research Network Recall Study. Participants responded to questions about their urinary symptoms for 25 consecutive days. These questions queried urologic symptoms including storage (urinary urgency, frequency, nocturia, and urinary incontinence), voiding (slow/weak stream), and post-micturition (incomplete emptying and post-micturition dribble) symptoms. We calculated Pearson correlation coefficients and cosine similarity measures and compared distributions of intra-individual and inter-individual (cohort) metrics.

Among 234 participants, distributions of intra-individual measures were 10-fold wider than those of inter-individual correlations. There are pairs of questions with distributions of correlations and cosine similarities containing individuals with extreme positive (>0.8) and extreme negative values (<–0.8). There are groups of participants with strong positive and negative correlations of urinary frequency and nocturia, urinary incontinence and weak flow, as well as strong negative and positive correlations of urinary frequency and dribbling. Information on these extreme groups is averaged out and lost in the inter-individual correlations.

Lack of group-to-individual generalizability previously shown for psychological symptoms is confirmed for LUTS. Wealth of information on the co-occurrence and co-evolution of LUTS in the intra-individual correlations and cosine similarities corroborates heterogeneity of LUTS and can be useful for deep phenotyping and for identifying personalized treatments of LUTS.

Although decentralized research is being used more frequently, few data are available regarding barriers for potential subjects related to engaging in decentralized research with remote biospecimen collection, especially within pregnancy and birth cohorts that include individuals of diverse racial and ethnic backgrounds.

Focus groups and individual interviews with pregnant and postpartum women were conducted in English and Spanish. Thematic analysis was used to identify motivators and barriers to participation in decentralized research involving biospecimens.

Sixty women (35% Hispanic/Latino, 23% Black, 18% Asian, 15% non-Hispanic White) participated in 10 focus groups (English = 8, Spanish = 2) and 11 individual interviews (English = 7, Spanish = 4). Three themes emerged about factors that could promote participation in decentralized biospecimen collection: 1) convenience, 2) autonomy, and 3) benefit (to self, community or society). Four themes emerged about potential barriers: 1) lack of interaction with trained professionals, 2) inability to coordinate with existing clinical care, 3) discomfort and invasiveness, and 4) concerns about data transparency and security. Overall, participants felt more comfortable providing biospecimens for themselves compared to their child and with biospecimens perceived as less painful or invasive to obtain.

Our findings suggest that transparency about the purposes and use of collecting biospecimen and clear instructions (such as written and instructional videos) could improve biospecimen collection in decentralized pregnancy and birth cohorts. Additionally, opportunities for virtual interaction with study staff and options related to collection of certain biospecimens such as blood (mobile collection unit with trained staff versus a self-collection device) may also improve participant engagement.

Asthma exacerbations are frequent causes of pediatric hospital admissions. We sought to develop a time series algorithm to forecast next-day daily asthma hospitalizations.

Daily hospitalizations for asthma were collected at Cincinnati Children’s from January 1, 2016, to December 31, 2023. We evaluated Autoregressive Integrated Moving Average (ARIMA), Exponential Smoothing (ETS), Prophet, and Ensemble models to forecast next-day asthma hospitalizations validated on 2023 data, considering varying historical training data lengths. Forecasts were calibrated to identify days exceeding a 5% high-risk threshold of historical totals and considered multiple validation years and years before and during the COVID-19 pandemic.

A total of 5,593 hospital admissions were recorded for asthma. Over 2,922 days, 166 days met the 5% high-risk threshold equating to 6 or more admissions. The Ensemble (Median Absolute Percentage Error (MAPE): 46.7%; Positive Predictive Value (PPV): 0.278; Negative Predictive Value (NPV): 0.942; Area Under the ROC Curve (AUC): 0.740; Sensitivity: 0.800; Specificity: 0.656) model achieved higher accuracy of high-risk days than ARIMA (MAPE: 46.5%; PPV: 0.278; NPV: 0.942; AUC: 0.709; Sensitivity: 0.760; Specificity: 0.571), ETS (MAPE: 47.2%; PPV: 0.222; NPV: 0.939; AUC: 0.711; Sensitivity: 0.800; Specificity: 0.668), and Prophet (MAPE: 48.9%; PPV: 0.444; NPV: 0.951; AUC: 0.732; Sensitivity: 0.680; Specificity: 0.741) models.

Our Ensemble model of mean predictions from ARIMA, ETS, and Prophet models was the most accurate in forecasting future asthma hospitalizations. Integrating forecasting techniques with clinical operations could enable proactive prevention through enhanced population care management.

The Office of Human Research Protections and the National Academy of Sciences, Engineering, and Medicine (NASEM) recommend the return of individual research results (IRRs) to study participants as a strategy to build public trust in science. However, the feasibility of sharing IRRs is unclear. Within a National Institutes of Health (NIH) funded parent study about Long COVID, we embedded the My ILLInet RECOVER Return of Results study to explore clinician-level considerations (e.g., validity, actionability, recommendations for follow-up) about returning a clinically used biomarker for heart failure (N-terminal pro-B-type natriuretic peptide, (NT-proBNP) collected as part of the NIH RECOVER study protocol.

Clinicians participated in a three-phase modified Delphi process that sought their input to guide appropriate follow up recommendations the research team should provide to research participants with an abnormal NT-proBNP.

Clinicians agreed that NT-proBNP results could be returned to study participants. However, consensus was not reached on specific NT-proBNP thresholds that warrant immediate medical attention versus general follow-up.

Lack of clinical context presents a challenge in returning IRRs. Clinicians expressed concerns about the potential harm caused by misinformation or misinterpretation of these findings. While the NASEM report offers guidance on communicating IRRs, careful consideration is essential to ensure that clinical uncertainty is conveyed clearly, minimizing the risk of misinterpretation.

The feasibility of returning IRRs to study participants depends, in part, on sufficient clinical context for the information to be actionable.

Rural communities make up 19% of the US population, yet are underrepresented in clinical trials. Community engagement methods can facilitate collaboration and trust with local healthcare personnel to enhance enrollment. The purpose of this manuscript is to describe community engagement methods and their impact on enrollment in a pragmatic clinical trial.

We describe a variety of methods used in the Fibromyalgia TENS in Physical Therapy Study (FM-TIPS) to enhance enrollment in rural communities and low-enrolling clinics. Community engagement methods were implemented partway through the trial for selected groups: Targeted Rural (TR) (n = 10), Targeted Low Enrolling (TLE) (n = 6), and compared to Untargeted Groups (UT) (n = 13). The impact of these methods on inquiries, screening, and enrollment were evaluated by comparing actual enrollment to projected enrollment.

We trained and employed community engagement coordinators to implement strategies in TR and TLE physical therapy clinics. These included, posting flyers, community events, physician outreach, social media ads, and direct mailing. These methods increased study inquiries, screening and enrollment in the study. Specifically, when compared to projected values there were increases in enrollment for both the TR and the TLE groups, but not the UT group. Of those that passed screening 99% of rural and 32% of urban residents enrolled in the study.

A multi-pronged and individualized community engagement approach can increase enrollment of rural residents in clinical trials. Building strong relationships and partnering with community clinics and local communities is essential to success.

Hospital-acquired pressure injuries (HAPIs) are a preventable source of patient harm, contributing to morbidity, mortality, and billions in healthcare costs. Risk assessment tools rely on subjective evaluation and may not accurately capture real-time mobility. Existing technologies have not been widely adopted and have failed to significantly reduce HAPI rates. Our study explores the feasibility of a novel, wireless mattress-attachable motion sensor designed for continuous mobility monitoring in hospitalized patients.

Sensor accuracy was first validated against video analysis in three healthy volunteers. A single-arm prospective cohort study was then conducted in hospitalized patients. A motion sensor was attached to each patient’s bed to continuously record movement. Sensor-derived mobility data were compared with nursing-assessed mobility scores and other patient characteristics. Simulated immobility alerts were generated based on periods of inactivity.

The sensor’s movement detection strongly correlated with video-based analysis in three healthy volunteers (r = 0.89, 95% CI [0.51, 0.99]). Forty-seven patients were enrolled with an average of 9.7 movements/hour and average recording duration of 22.9 hours. No significant differences in age, comorbidities, or nursing mobility scores were observed between high- and low-movement groups. Simulated immobility alerts identified 15 patients who would have triggered a notification, predominantly those with lower movement and BMI.

The sensor system provides objective mobility data and overcomes limitations of current assessment tools. These findings support its potential role in pressure injury prevention and highlight key areas for future clinical integration.

Complex, knowledge-intensive projects present challenges in terms of defining the work and determining roles. Time pressure makes these challenges more acute. External leadership can provide necessary direction and shape, giving the work a clear focus guiding the team’s efforts. With hackathons and rapid product prototyping more feasible than they ever have been, collaborations that fast-track innovation by drawing together teams of unfamiliar experts are more common than ever.

Drawing on the process perspective on creative action, we seek to understand the generation of new ideas and solutions when teams are working within an extremely brief time frame of one week. The influence of mentors on these interactions has received limited attention. We fill this gap through a study of fifteen case teams who participated in a week-long boot camp where they generated proposals for public health studies, guided by mentors who were experts in the field. The teams’ proposals were evaluated by independent panels, and the evaluations provided metrics for team success.

Our results suggest that even in short-term teams, the timing of mentor interventions is critical to team success.

To overcome the dearth of high-quality, evidence-based, role-specific training for community health workers and promotoras (CHW/Ps) working with research teams, we developed and evaluated a peer-led research best practices training for CHW/Ps. This article qualitatively explores the training experiences from the perspectives of CHW/Ps.

CHW/Ps were recruited from communities and partners affiliated with study sites in Michigan, Florida, and California to participate in peer facilitated trainings in English and Spanish. A purposeful sample of CHW/Ps completed interviews from July to December 2023 about their perceptions of the training. Three coders analyzed the interviews using a combination of the rigorous and accelerated data reduction (RADaR) technique and thematic text analysis.

Seventeen CHW/Ps participated in interviews (N = 10 in English; N = 7 in Spanish). The mean age was 43.7 ± 14.5 years, most were female (59%), and 47% identified as Hispanic, Latino, or Spanish. We identified three primary themes, each with resulting subthemes: (1) CHW/Ps’ Perceptions of the Training, (2) Factors Influencing Receipt of the Training, and (3) CHW/Ps’ Recommendations for Future Trainings. Despite offering some opportunities for improvement in various areas, CHW/P learners found the training further clarified their role as CHW/Ps, enhanced their knowledge and skills, and provided a beneficial foundation for CHW/Ps working in community-engaged research.

A peer-led research best practices training for CHW/Ps is an effective strategy for enhancing CHW/Ps’ knowledge and skills. Training CHW/Ps in research best practices is a strategy for enhancing the capacity and capability of this community-engaged research workforce