Interdisciplinary academic teams perform better when competent in teamwork; however, there is a lack of best practices of how to introduce and facilitate the development of effective learning and functioning within these teams in academic environments.

To close this gap, we tailored, implemented, and evaluated team science training in the year-long Engineering Innovation in Health (EIH) program at the University of Washington (UW), a project-based course in which engineering students across several disciplines partner with health professionals to develop technical solutions to clinical and translational health challenges. EIH faculty from the UW College of Engineering and the Institute of Translational Health Sciences’ (ITHS) Team Science Core codeveloped and delivered team science training sessions and evaluated their impact with biannual surveys. A student cohort was surveyed prior to the implementation of the team science trainings, which served as a baseline.

Survey responses were compared within and between both cohorts (approximately 55 students each Fall Quarter and 30 students each Spring Quarter). Statistically significant improvements in measures of self-efficacy and interpersonal team climate (i.e., psychological safety) were observed within and between teams.

Tailored team science training provided to student-professional teams resulted in measurable improvements in self-efficacy and interpersonal climate both of which are crucial for teamwork and intellectual risk taking. Future research is needed to determine long-term impacts of course participation on individual and team outcomes (e.g., patents, start-ups). Additionally, adaptability of this model to clinical and translational research teams in alternate formats and settings should be tested.

Implementation Science (IS) is a complex and rapidly evolving discipline, posing challenges for educators. We developed, implemented, and evaluated a novel, pragmatic approach to teach IS.

Getting To Implementation (GTI)-Teach was developed as a seven-step educational model to guide students through the process of developing, conducting, and sustaining an IS research project. During the four-week online course, students applied the steps to self-selected implementation problems. Students were invited to complete two online post-course surveys to assess course satisfaction and self-reported changes in IS knowledge and relevance of GTI-Teach Steps to their work. Results were summarized using descriptive statistics; self-reported post-course changes in IS knowledge were compared using paired t-tests.

GTI-Teach was developed to include seven Steps: 1. Define the implementation problem; 2. Conceptualize the problem; 3. Prioritize implementation barriers and facilitators; 4. Select and tailor implementation strategies; 5. Design an implementation study; 6. Evaluate implementation; 7. Sustain implementation. Thirteen students, ranging in experience from medical students to full professors, enrolled in and completed the first GTI-Teach course. Of the seven students (54%) completing an end-of course survey, six (86%) were very satisfied with the course. Ten students (77%) responded to the tailored, 6-month post-course follow-up survey. They retrospectively reported a significant increase in their knowledge across all steps of GTI-Teach (1.3–1.8 points on a 5-point Likert scale) and rated each of the Steps as highly relevant to their work.

GTI-Teach is a seven-step model for teaching IS fundamentals that students reported increased their knowledge and was relevant to their work.

Non-clinical aspects of life, such as social, environmental, behavioral, psychological, and economic factors, what we call the sociome, play significant roles in shaping patient health and health outcomes. This paper introduces the Sociome Data Commons (SDC), a new research platform that enables large-scale data analysis for investigating such factors.

This platform focuses on “hyper-local” data, i.e., at the neighborhood or point level, a geospatial scale of data not adequately considered in existing tools and projects. We enumerate key insights gained regarding data quality standards, data governance, and organizational structure for long-term project sustainability. A pilot use case investigating sociome factors associated with asthma exacerbations in children residing on the South Side of Chicago used machine learning and six SDC datasets.

The pilot use case reveals one dominant spatial cluster for asthma exacerbations and important roles of housing conditions and cost, proximity to Superfund pollution sites, urban flooding, violent crime, lack of insurance, and a poverty index.

The SDC has been purposefully designed to support and encourage extension of the platform into new data sets as well as the continued development, refinement, and adoption of standards for dataset quality, dataset inclusion, metadata annotation, and data access/governance. The asthma pilot has served as the first driver use case and demonstrates promise for future investigation into the sociome and clinical outcomes. Additional projects will be selected, in part for their ability to exercise and grow the capacity of the SDC to meet its ambitious goals.

Arkansans have some of the worst breast cancer mortality to incidence ratios in the United States (5th for Blacks, 4th for Whites, 7th overall). Screening mammography allows for early detection and significant reductions in mortality, yet not all women have access to these life-saving services. Utilization in Arkansas is well below the national average, and the number of FDA-approved screening facilities has decreased by 38% since 2001. Spatial accessibility plays an important role in whether women receive screenings.

We use constrained optimization models within a geographic information system (GIS) to probabilistically allocate women to nearby screening facilities, accounting for facility capacity and patient travel time. We examine accessibility results by rurality derived from rural–urban commuting area (RUCA) codes.

Under most models, screening capacity is insufficient to meet theoretical demand given travel constraints. Approximately 80% of Arkansan women live within 30 minutes of a screening facility, most of which are located in urban and suburban areas. The majority of unallocated demand was in Small towns and Rural areas.

Geographic disparities in screening mammography accessibility exist across Arkansas, but women living in Rural areas have particularly poor spatial access. Mobile mammography clinics can remove patient travel time constraints to help meet rural demand. More broadly, optimization models and GIS can be applied to many studies of healthcare accessibility in rural populations.

Sudden unexpected infant death is the leading cause of infant mortality with black: white infant mortality remaining at 2:1 for the last decade. Smartphone technology provides a convenient and accessible tool for injury prevention anticipatory guidance among at-risk communities.

A convenience sample of pregnant teen mothers who own a smartphone. During a 1-month postnatal home visit, a safe sleep environment survey was administered, infant sleep practices were observed, and mothers trained to take and submit standard infants’ sleep environment photographs. Photographs were independently assessed for inter-rater reliability (IRR) across five sleep safety domains (primary outcome): sleep location, surface, position, presence of soft items, and hazards near the sleep area. Expert and novice coders IRR was measured using Cohen’s kappa coefficient (K). Sleep safety correlation between photographs and observation, and parent report and observation was determined.

Sixteen (57.1%) mothers completed the home visit. Most parents reported infants sleeping supine (78.5) in parents’ bedroom (85.9%). Photographs demonstrated sleep position, soft items without the baby present, and hanging toys had perfect agreement across all three coder pairs. Safe sleep experts’ IRR demonstrated perfect agreement for sleep location, position, and soft items. While 83.8% of parents were observed putting their infants down to sleep on their back, 78.5% of parents reported doing the same and 82.4% of the photographs demonstrated supine infant sleep position.

Using photographs, coders can reliably categorize some key infant sleep safety aspects, and photograph sleep safety is comparable to parent report and direct observation.

This paper reports on the baseline stage of a qualitative evaluation of the application of the Innovative Scorecard (ISC) to the Clinical and Translational Science Award (CTSA) at the University of Texas Medical Branch (UTMB) at Galveston. The ISC is adopted from the established Balanced Scorecard system for strategic planning and performance management. In formulating the evaluation, we focused on the organizational identity literature.

The initial evaluation consisted of a series of semi-structured interviews with 22 participants of the ISC Boot Camp conducted in July 2015.

The logic of grounded theory pointed to the clustering of perceptions of the ISC around respondents’ occupational locations at UTMB. Administrators anticipate the expansion of planning activities to include a wider range of participants under the current CTSA award period (2015–2020) than under our first CTSA approval period (2009–2014). A common viewpoint among the senior scientists was that the scientific value of their work will continue to speak for itself without requiring the language of business. Junior scientists looked forward to the ISC’s emphasis on increasingly horizontal leadership that will give them more access to and more control over their work and resources. Postdocs and senior staff welcomed increased involvement in the total research process at UTMB.

The report concludes with strategies for future follow-up.

Racial disparities in colorectal cancer (CRC) can be addressed through increased adherence to screening guidelines. In real-life encounters, patients may be more willing to follow screening recommendations delivered by a race concordant clinician. The growth of telehealth to deliver care provides an opportunity to explore whether these effects translate to a virtual setting. The primary purpose of this pilot study is to explore the relationships between virtual clinician (VC) characteristics and CRC screening intentions after engagement with a telehealth intervention leveraging technology to deliver tailored CRC prevention messaging.

Using a posttest-only design with three factors (VC race-matching, VC gender, intervention type), participants (N = 2267) were randomised to one of eight intervention treatments. Participants self-reported perceptions and behavioral intentions.

The benefits of matching participants with a racially similar VC trended positive but did not reach statistical significance. Specifically, race-matching positively influenced screening intentions for Black participants but not for Whites (b = 0.29, p = 0.10). Importantly, perceptions of credibility, attractiveness, and message relevance significantly influenced screening intentions and the relationship with race-matching.

To reduce racial CRC screening disparities, investments are needed to identify patient-focused interventions to address structural barriers to screening. This study suggests that telehealth interventions that match Black patients with a Black VC can enhance perceptions of credibility and message relevance, which may then improve screening intentions. Future research is needed to examine how to increase VC credibility and attractiveness, as well as message relevance without race-matching.

COVID-19 has caused tremendous death and suffering since it first emerged in 2019. Soon after its emergence, models were developed to help predict the course of various disease metrics, and these models have been relied upon to help guide public health policy.

Here we present a method called COVIDNearTerm to “forecast” hospitalizations in the short term, two to four weeks from the time of prediction. COVIDNearTerm is based on an autoregressive model and utilizes a parametric bootstrap approach to make predictions. It is easy to use as it requires only previous hospitalization data, and there is an open-source R package that implements the algorithm. We evaluated COVIDNearTerm on San Francisco Bay Area hospitalizations and compared it to models from the California COVID Assessment Tool (CalCAT).

We found that COVIDNearTerm predictions were more accurate than the CalCAT ensemble predictions for all comparisons and any CalCAT component for a majority of comparisons. For instance, at the county level our 14-day hospitalization median absolute percentage errors ranged from 16 to 36%. For those same comparisons, the CalCAT ensemble errors were between 30 and 59%.

COVIDNearTerm is a simple and useful tool for predicting near-term COVID-19 hospitalizations.

Impactful, transdisciplinary scientific discoveries are created by teams of researchers spanning multiple disciplines, but collaboration across disciplines can be challenging. We examined how team dynamics and collaboration are related to successes and barriers faced by teams of researchers from multiple disciplines.

A mixed-methods approach was used to examine 12 research teams granted multidisciplinary pilot awards. Team members were surveyed to assess their team dynamics and individual views about transdisciplinary research. Forty-seven researchers (59.5%) responded, including two to eight members from each funded team. Associations were examined between collaborative dynamics and scholarly product outcomes, including manuscripts, grant proposals, and awarded grants. One member from each team was selected for an in-depth interview to contextualize and extend information about collaborative processes, successes, and barriers to performing transdisciplinary research.

Quality of team interactions was positively associated with achievement of scholarly products (r = 0.64, p = 0.02). Satisfaction with team members (r = 0.38) and team collaboration scores (r = 0.43) also demonstrated positive associations with achievement of scholarly products, but these were not statistically significant. Qualitative results support these findings and add further insight into aspects of the collaborative process that were particularly important to foster success on multidisciplinary teams. Beyond scholarly metrics, additional successes from the multidisciplinary teams were identified through the qualitative portion of the study including career development and acceleration for early career researchers.

Both the quantitative and qualitative study results indicate that effective collaboration is critical to multidisciplinary research team success. Development and/or promotion of team science-based trainings for researchers would promote these collaborative skills.

Given the significant health effects, we assessed geospatial patterns of adverse events (AEs), defined as physical or sexual abuse and accidents or poisonings at home, among children in a mixed rural–urban community.

We conducted a population-based cohort study of children (<18 years) living in Olmsted County, Minnesota, to assess geographic patterns of AEs between April 2004 and March 2009 using International Classification of Diseases, Ninth Revision codes. We identified hotspots by calculating the relative difference between observed and expected case densities accounting for population characteristics ($$Relative\;Difference = {\rm{ }}{{Observed\;Case\;Density - Expected\;Case\;Density} \over {Expected\;Case\;Density}}$$; hotspot ≥ 0.33) using kernel density methods. A Bayesian geospatial logistic regression model was used to test for association of subject characteristics (including residential features) with AEs, adjusting for age, sex, and socioeconomic status (SES).

Of the 30,227 eligible children (<18 years), 974 (3.2%) experienced at least one AE. Of the nine total hotspots identified, five were mobile home communities (MHCs). Among non-Hispanic White children (85% of total children), those living in MHCs had higher AE prevalence compared to those outside MHCs, independent of SES (mean posterior odds ratio: 1.80; 95% credible interval: 1.22–2.54). MHC residency in minority children was not associated with higher prevalence of AEs. Of addresses requiring manual correction, 85.5% belonged to mobile homes.

MHC residence is a significant unrecognized risk factor for AEs among non-Hispanic, White children in a mixed rural–urban community. Given plausible outreach difficulty due to address discrepancies, MHC residents might be a geographically underserved population for clinical care and research.

The Great CTSA Team Science Contest (GTSC) was developed to discover how Clinical and Translational Science Award (CTSA) hubs promote and support team science [1]. The purpose of this study was a secondary qualitative analysis of the GTSC submissions to better understand the diversity of team science initiatives across the CTSA consortium.

Secondary qualitative analysis of the GTSC data addressed the following research questions, which defined the top-level coding: (1) What CTSA component sponsored it? (2) Who was the team doing the work? (3) Who were the intended beneficiaries? (4) What was the intended outcome? (5) What strategies did they use? (6) What translational science (TS) stage was addressed? (7) How do they align with the NCATS team science strategic goals? (8) How do the CTSA’s team science efforts align with the National Academies Research Council (NRC) recommendations for enhancing the effectiveness of team science?

The GTSC received 170 submissions from 45 unique CTSA hubs. Qualitative analysis revealed a great variety of team science strategies for virtually all team science stakeholders. In addition to strategies to promote team science, results show successful examples that focus on outcomes and illustrate ways of measuring success.

The GTSC shows that the CTSA consortium is involved in an extremely diverse array of team science activities, which align well with both the NRC recommendations for enhancing the effectiveness of team science and the NCATS strategic goals for team science. Future research should evaluate the efficacy of team science strategies.

SPARK launched in 2016 to build a US cohort of autistic individuals and their family members. Enrollment includes online consent to share data and optional consent to provide saliva for genomic analysis. SPARK’s recruitment strategies include social media and support of a nation-wide network of clinical sites. This study evaluates SPARK’s recruitment strategies to enroll a core study population.

Individuals who joined between January 31, 2018, and May 29, 2019 were included in the analysis. Data include sociodemographic characteristics, clinical site referral, the website URL used to join, how the participant heard about SPARK, enrollment completion (online registration, study consents, and returning saliva sample), and completion of the baseline questionnaire. Logistic regressions were performed to evaluate the odds of core participant status (completing enrollment and baseline questionnaire) by recruitment strategy.

In total, 31,715 individuals joined during the study period, including 40% through a clinical site. Overall, 88% completed online registration, 46% returned saliva, and 38% were core participants. Those referred by a clinical site were almost twice as likely to be core participants. Those who directly visited the SPARK website or performed a Google search were more likely to be core participants than those who joined through social media.

Being a core participant may be associated with the “personal” connection and support provided by a clinical site and/or site staff, as well as greater motivation to seek research opportunities. Findings from this study underscore the value of adopting a multimodal recruitment approach that combines social media and a physical presence.

A Health Equity Task Force (HETF) of members from seven Centers funded by the National Cancer Institute’s (NCI) Implementation Science in Cancer Control Centers (ISC3) network sought to identify case examples of how Centers were applying a focus on health equity in implementation science to inform future research and capacity-building efforts.

HETF members at each ISC3 collected information on how health equity was conceptualized, operationalized, and addressed in initial research and capacity-building efforts across the seven ISC3 Centers funded in 2019–2020. Each Center completed a questionnaire assessing five health equity domains central to implementation science (e.g., community engagement; implementation science theories, models, and frameworks (TMFs); and engaging underrepresented scholars). Data generated illustrative examples from these five domains.

Centers reported a range of approaches focusing on health equity in implementation research and capacity-building efforts, including (1) engaging diverse community partners/settings in making decisions about research priorities and projects; (2) applying health equity within a single TMF applied across projects or various TMFs used in specific projects; (3) evaluating health equity in operationalizing and measuring health and implementation outcomes; (4) building capacity for health equity-focused implementation science among trainees, early career scholars, and partnering organizations; and (5) leveraging varying levels of institutional resources and efforts to engage, include, and support underrepresented scholars.

Examples of approaches to integrating health equity across the ISC3 network can inform other investigators and centers’ efforts to build capacity and infrastructure to support growth and expansion of health equity-focused implementation science.

Early life exposures affect health and disease across the life course and potentially across multiple generations. The Clinical and Translational Research Institutes (CTSIs) offer an opportunity to utilize and link existing databases to conduct lifespan research.

A survey with Lifespan Domain Taskforce expert input was created and distributed to lead lifespan researchers at each of the 64 CTSIs. The survey requested information regarding institutional databases related to early life exposure, child-maternal health, or lifespan research.

Of 64 CTSI, 88% provided information on a total of 130 databases. Approximately 59% (n=76/130) had an associated biorepository. Longitudinal data were available for 72% (n=93/130) of reported databases. Many of the biorepositories (n=44/76; 68%) have standard operating procedures that can be shared with other researchers.

The majority of CTSI databases and biorepositories focusing on child-maternal health and lifespan research could be leveraged for lifespan research, increased generalizability and enhanced multi-institutional research in the United States.