Experimental evidence is needed to evaluate interventions that curtail burnout for physical therapists. The goal of this research was to assess the impact of mindfulness-based training (MBT) on the well-being of physical therapists. We hypothesized physical therapists would demonstrate greater work engagement, empathy, and job satisfaction, and lower depression, anxiety, stress, and moral distress following MBT.

Thirteen physical therapists (10 female/3 male; 35.38 ± 9.32 years old) completed this two-arm embedded mixed-methods pilot study. The control group (n = 4) was followed while the intervention group (n = 9) completed six MBT sessions over 3 months. Sessions were assigned a representative topic area (meaning in physical therapy, situational- and self-awareness, compassion fatigue/burnout, implicit biases, establishing boundaries and managing conflict, self-care) with relevant reflective writing, small group discussions, and mindfulness strategies. Non-parametric statistics compared quantitative outcomes across and within groups, and a thematic framework matrix was established by way of qualitative description for data analysis.

Physical therapists in the intervention group had improved pre- to post-scores for work engagement, mental health, and moral distress (p ≤ 0.043). Inability to effect change contributed to compassion fatigue/burnout, whereas difficulty prioritizing self/limited personal time impeded self-care. “I realized how easy it is to get caught up in life and in helping out those around you, you completely forget to take time to check in with how you are doing (Physical Therapist 3).”

Implementing an MBT program demonstrates promise and may benefit the well-being of physical therapists while simultaneously enhancing employee retention and improving patient care.

UMHealthResearch is the University of Michigan’s digital health research recruitment platform. It allows health researchers to connect efficiently with potentially eligible volunteers.

In 2013, the UMHealthResearch team strategically adapted a consumer behavior model, the buying funnel, to create the Digital Health Research Participation Funnel. The Digital Health Research Participation Funnel was then used to design a more active way for potential participants to volunteer for research studies through UMHealthResearch.

In the 5 years before the redesign (2007–2012), an average of 1844 new accounts were created every year, whereas in the completed years after the redesign (2013–2016) the annual average improved to 3906, an increase of 111%.

Although a randomized design was not possible in this instance, these preintervention and postintervention data suggest that the focus on user experience is an effective strategy for improving web-based research recruitment platforms.

Dissemination of results to research participants is largely missing from the practices of most researchers. Few resources exist that describe best practices for disseminating information to this important stakeholder group.

Four focus groups were conducted with a diverse group of individuals. All participants were part of a Patient-Centered Outcomes Research Institute-funded survey study. Focus groups aimed to identify participants’ preferences about receiving research results and their reactions to three different dissemination platforms.

Four focus groups with 37 participants were conducted, including: (1) adults with one comorbidity, at least a college education, and high socioeconomic status (SES); (2) adults with one comorbidity, less than a college education, and lower SES; (3) adults with low health literacy and/or numeracy; and (4) Black or African American adults. Participants discussed their preferences for research results delivery and how each of the platforms met those preferences. This included information needs as they relate to content and scope, including a desire to receive both individual and aggregate results, and study summaries. Email, paper, and website were all popular avenues of presentation. Some desired a written summary, and others preferred videos or visual graphics. Importantly, participants emphasized the desire for having a choice in the timing, frequency, and types of results.

Research participants prefer to receive research results, including study impact and key findings, disseminated to them in an engaging format that allows choice of when and how the information is presented. The results encourage new standards whereby research participants are considered a critical stakeholder group.

Despite the critical role that quantitative scientists play in biomedical research, graduate programs in quantitative fields often focus on technical and methodological skills, not on collaborative and leadership skills. In this study, we evaluate the importance of team science skills among collaborative biostatisticians for the purpose of identifying training opportunities to build a skilled workforce of quantitative team scientists.

Our workgroup described 16 essential skills for collaborative biostatisticians. Collaborative biostatisticians were surveyed to assess the relative importance of these skills in their current work. The importance of each skill is summarized overall and compared across career stages, highest degrees earned, and job sectors.

Survey respondents were 343 collaborative biostatisticians spanning career stages (early: 24.2%, mid: 33.8%, late: 42.0%) and job sectors (academia: 69.4%, industry: 22.2%, government: 4.4%, self-employed: 4.1%). All 16 skills were rated as at least somewhat important by > 89.0% of respondents. Significant heterogeneity in importance by career stage and by highest degree earned was identified for several skills. Two skills (“regulatory requirements” and “databases, data sources, and data collection tools”) were more likely to be rated as absolutely essential by those working in industry (36.5%, 65.8%, respectively) than by those in academia (19.6%, 51.3%, respectively). Three additional skills were identified as important by survey respondents, for a total of 19 collaborative skills.

We identified 19 team science skills that are important to the work of collaborative biostatisticians, laying the groundwork for enhancing graduate programs and establishing effective on-the-job training initiatives to meet workforce needs.

Advancing understanding of human health promotion and disease prevention and treatment often requires teamwork. To evaluate academic medical institutions’ support for team science in the context of researchers’ career development, we measured the value placed on team science and specificity of guidance provided for documenting team science contributions in the promotion and tenure (P&T) documents of Colleges/Schools of Medicine (CoMs) in the National Center for Advancing Translational Sciences’ Clinical and Translational Science Award (CTSA) program.

We reviewed complete P&T documents from 57 of 63 CTSA CoMs to identify career paths defined by three dimensions: academic rank (associate versus full professor), tenure eligibility (tenure track versus not), and role (research, clinical, education, and administrative), and we rated team science value and documentation guidance for each path. Multilevel models were estimated to compare team science value and documentation guidance as a function of the three career path dimensions while accounting for the clustered data (N = 357 career paths within 57 CoMs).

Team science value was greater for associate than full professors, non-tenure-eligible versus tenure-eligible positions, and roles prioritizing clinical, education, and administrative responsibilities versus those prioritizing research. Guidance for documenting team science achievements was more explicit for roles that prioritized research.

Although P&T policies at most CTSA institutions express value for team science, inconsistent within-institutional patterns of recognition and reward across career paths may have implications for researchers’ involvement in team science. We discuss the implications of our findings for research and for P&T policies that promote team science.

Routine patient care data are increasingly used for biomedical research, but such “secondary use” data have known limitations, including their quality. When leveraging routine care data for observational research, developing audit protocols that can maximize informational return and minimize costs is paramount.

For more than a decade, the Latin America and East Africa regions of the International epidemiology Databases to Evaluate AIDS (IeDEA) consortium have been auditing the observational data drawn from participating human immunodeficiency virus clinics. Since our earliest audits, where external auditors used paper forms to record audit findings from paper medical records, we have streamlined our protocols to obtain more efficient and informative audits that keep up with advancing technology while reducing travel obligations and associated costs.

We present five key lessons learned from conducting data audits of secondary-use data from resource-limited settings for more than 10 years and share eight recommendations for other consortia looking to implement data quality initiatives.

After completing multiple audit cycles in both the Latin America and East Africa regions of the IeDEA consortium, we have established a rich reference for data quality in our cohorts, as well as large, audited analytical datasets that can be used to answer important clinical questions with confidence. By sharing our audit processes and how they have been adapted over time, we hope that others can develop protocols informed by our lessons learned from more than a decade of experience in these large, diverse cohorts.

Translating complex behavior change interventions into practice can be accompanied by a loss of fidelity and effectiveness. We present the evaluation of two sequential phases of implementation of a complex evidence-based community workshop to reduce falls, using the Replicating Effective Programs Framework. Between the two phases, workshop training and delivery were revised to improve fidelity with key elements.

Stepping On program participants completed a questionnaire at baseline (phase 1: n = 361; phase 2: n = 2219) and 6 months post-workshop (phase 1: n = 232; phase 2: n = 1281). Phase 2 participants had an additional follow-up at 12 months (n = 883). Outcomes were the number of falls in the prior 6 months and the Falls Behavioral Scale (FaB) score.

Workshop participation in phase 1 was associated with a 6% reduction in falls (RR = 0.94, 95% CI 0.74–1.20) and a 0.14 improvement in FaB score (95% CI, 0.11– 0.18) at 6 months. Workshop participation in phase 2 was associated with a 38% reduction in falls (RR = 0.62, 95% CI 0.57–0.68) and a 0.16 improvement in FaB score (95% CI 0.14–0.18) at 6 months, and a 28% reduction in falls (RR = 0.72, 95% CI 0.65–0.80) and a 0.19 score improvement in FaB score (95% CI 0.17–0.21) at 12-month follow-up.

Effectiveness can be maintained with widespread dissemination of a complex behavior change intervention if attention is paid to fidelity of key elements. An essential role for implementation science is to ensure effectiveness as programs transition from research to practice.

During the COVID-19 pandemic, research organizations accelerated adoption of technologies that enable remote participation. Now, there’s a pressing need to evaluate current decentralization practices and develop appropriate research, education, and operations infrastructure. The purpose of this study was to examine current adoption of decentralization technologies in a sample of clinical research studies conducted by academic research organizations (AROs).

The setting was three data coordinating centers in the U.S. These centers initiated coordination of 44 clinical research studies during or after 2020, with national recruitment and enrollment, and entailing coordination between one and one hundred sites. We determined the decentralization technologies used in these studies.

We obtained data for 44/44 (100%) trials coordinated by the three centers. Three technologies have been adopted across nearly all studies (98–100%): eIRB, eSource, and Clinical Trial Management Systems. Commonly used technologies included e-Signature (32/44, 73%), Online Payments Portals (26/44, 59%), ePROs (23/44, 53%), Interactive Response Technology (22/44, 50%), Telemedicine (19/44, 43%), and eConsent (18/44, 41%). Wearables (7/44,16%) and Online Recruitment Portals (5/44,11%) were less common. Rarely utilized technologies included Direct-to-Patient Portals (1/44, 2%) and Home Health Nurse Portals (1/44, 2%).

All studies incorporated some type of decentralization technology, with more extensive adoption than found in previous research. However, adoption may be strongly influenced by institution-specific IT and informatics infrastructure and support. There are inherent needs, responsibilities, and challenges when incorporating decentralization technology into a research study, and AROs must ensure that infrastructure and informatics staff are adequate.