Temporal development of high-performance translational teams.

Successful translation involves the coupled application of knowledge-generating research with product development to advance a device, drug, diagnostic, or evidence-based intervention for clinical adoption to improve human health. Critical to the success of the CTSA consortium, translation can be more effectively accomplished by training approaches that focus on improving team-emergent knowledge skills and attitudes (KSAs) linked to performance. We earlier identified 15 specific evidence-informed, team-emergent competencies that facilitate translational team (TT) performance. Here, we examine the SciTS literature describing developmental, temporal dynamics, and adaptive learning stages of interdisciplinary teams and integrate these with real-world observations on TT maturation pathways. We propose that TTs undergo ordered developmental phases, each representing a learning cycle that we call Formation, Knowledge Generation, and Translation. We identify major activities of each phase linked to development goals. Transition to subsequent phases is associated with a team learning cycle, resulting in adaptations that enabling progression towards clinical translation. We present known antecedents of stage-dependent competencies and rubrics for their assessment. Application of this model will ease assessment, facilitate goal identification and align relevant training interventions to improve performance of TTs in the CTSA context.

Deployment of Real-time Natural Language Processing and Deep Learning Clinical Decision Support in the Electronic Health Record: Pipeline Implementation for an Opioid Misuse Screener in Hospitalized Adults.

BACKGROUND: The clinical narrative in electronic health records (EHRs) carries valuable information for predictive analytics; however, its free-text form is difficult to mine and analyze for clinical decision support (CDS). Large-scale clinical natural language processing (NLP) pipelines have focused on data warehouse applications for retrospective research efforts. There remains a paucity of evidence for implementing NLP pipelines at the bedside for health care delivery. OBJECTIVE: We aimed to detail a hospital-wide, operational pipeline to implement a real-time NLP-driven CDS tool and describe a protocol for an implementation framework with a user-centered design of the CDS tool. METHODS: The pipeline integrated a previously trained open-source convolutional neural network model for screening opioid misuse that leveraged EHR notes mapped to standardized medical vocabularies in the Unified Medical Language System. A sample of 100 adult encounters were reviewed by a physician informaticist for silent testing of the deep learning algorithm before deployment. An end user interview survey was developed to examine the user acceptability of a best practice alert (BPA) to provide the screening results with recommendations. The planned implementation also included a human-centered design with user feedback on the BPA, an implementation framework with cost-effectiveness, and a noninferiority patient outcome analysis plan. RESULTS: The pipeline was a reproducible workflow with a shared pseudocode for a cloud service to ingest, process, and store clinical notes as Health Level 7 messages from a major EHR vendor in an elastic cloud computing environment. Feature engineering of the notes used an open-source NLP engine, and the features were fed into the deep learning algorithm, with the results returned as a BPA in the EHR. On-site silent testing of the deep learning algorithm demonstrated a sensitivity of 93% (95% CI 66%-99%) and specificity of 92% (95% CI 84%-96%), similar to published validation studies. Before deployment, approvals were received across hospital committees for inpatient operations. Five interviews were conducted; they informed the development of an educational flyer and further modified the BPA to exclude certain patients and allow the refusal of recommendations. The longest delay in pipeline development was because of cybersecurity approvals, especially because of the exchange of protected health information between the Microsoft (Microsoft Corp) and Epic (Epic Systems Corp) cloud vendors. In silent testing, the resultant pipeline provided a BPA to the bedside within minutes of a provider entering a note in the EHR. CONCLUSIONS: The components of the real-time NLP pipeline were detailed with open-source tools and pseudocode for other health systems to benchmark. The deployment of medical artificial intelligence systems in routine clinical care presents an important yet unfulfilled opportunity, and our protocol aimed to close the gap in the implementation of artificial intelligence-driven CDS. TRIAL REGISTRATION: ClinicalTrials.gov NCT05745480; https://www.clinicaltrials.gov/ct2/show/NCT05745480.

Family-centered prevention to enhance proactive parenting and parental self-efficacy during early elementary school.

The purpose of this study was to examine the effect of a family-centered intervention delivered during early elementary school, the Family Check-Up (FCU), in supporting parents' use of proactive parenting skills and the role that parental self-efficacy (PSE) has in promoting proactive parenting. We predicted both direct and mediated effects of the FCU on changes in proactive parenting. Participants were the primary caregivers of 321 kindergarten children and were randomly assigned to either the FCU or to a school-as-usual control group (n = 164 assigned to intervention). Results indicated that the FCU initiated during kindergarten enhanced proactive parenting skills directly and was mediated by PSE. These results highlight the FCU as an efficacious intervention in early elementary school in promoting proactive parenting skills and PSE and underscore the role of PSE as a primary pathway toward improved proactive parenting. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Applying the lessons of implementation science to maximize feasibility and usability in team science intervention development.

The Science of Team Science (SciTS) has generated a substantial body of work detailing characteristics of effective teams. However, that knowledge has not been widely translated into accessible, active, actionable, evidence-based interventions to help translational teams enhance their team functioning and outcomes. Over the past decade, the field of Implementation Science has rapidly developed methods and approaches to increase the translation of biomedical research findings into clinical care, providing a roadmap for mitigating the challenges of developing interventions while maximizing feasibility and utility. Here, we propose an approach to intervention development using constructs from two Implementation Science frameworks, Consolidated Framework for Implementation Research, and Reach, Effectiveness, Adoption, Implementation, and Maintenance, to extend the Wisconsin Interventions for Team Science framework described in Rolland et al. 2021. These Implementation Science constructs can help SciTS researchers design, build, test, and disseminate interventions that meet the needs of both adopters, the institutional leadership that decides whether to adopt an intervention, and implementers, those actually using the intervention. Systematically considering the impact of design decisions on feasibility and usability may lead to the design of interventions that can quickly move from prototype to pilot test to pragmatic trials to assess their impact.

Encouraging the scale-up of proven interventions: Infrastructure development for the "Evidence-to-Implementation" award.

BACKGROUND/OBJECTIVE: Although most research universities offer investigators help in obtaining patents for inventions, investigators generally have few resources for scaling up non-patentable innovations, such as health behavior change interventions. In 2017, the dissemination and implementation (D & I) team at the University of Wisconsin's Clinical and Translational Science Award (CTSA) created the Evidence-to-Implementation (E2I) award to encourage the scale-up of proven, non-patentable health interventions. The award was intended to give investigators financial support and business expertise to prepare evidence-based interventions for scale-up. METHODS: The D & I team adapted a set of criteria named Critical Factors Assessment, which has proven effective in predicting the success of entrepreneurial ventures outside the health care environment, to use as review criteria for the program. In March 2018 and February 2020, multidisciplinary panels assessed proposals using a review process loosely based on the one used by the NIH for grant proposals, replacing the traditional NIH scoring criteria with the eight predictive factors included in Critical Factors Assessment. RESULTS: two applications in 2018 and three applications in 2020 earned awards. Funding has ended for the first two awardees, and both innovations have advanced successfully. CONCLUSION: Late-stage translation, though often overlooked by the academic community, is essential to maximizing the overall impact of the science generated by CTSAs. The Evidence-to-implementation award provides a working model for supporting late-stage translation within a CTSA environment.

Connecting Online and Offline Social Skills to Adolescents' Peer Victimization and Psychological Adjustment.

Peer victimization is a common experience among high school students and is associated with many negative adjustment outcomes, making it necessary to investigate the individual and contextual factors that may ameliorate the consequences of peer victimization. The current study explores whether social competence offline and online mediates the relationship between peer victimization and psychological adjustment for adolescents. High school students (n = 303, Mage = 15.83, 65.2% female) reported about their peer victimization experiences, social skills, perceptions of peers' acceptance offline and social media acceptance, and self-worth. By considering both online and offline contexts, the underlying assumption that there are important differences between the two contexts and that these differences have a unique impact on teens who experience peer victimization was tested. The results indicate that teens who experience peer-victimization have deficits in both their offline and online social competence. Path analysis revealed that offline social skills mediate the relationship between peer victimization and self-worth. Also, there was a modest correlation between the indicators of offline social skills and online social skills indicating that they are not identical and have different associations with self-worth. Since teens are interacting with social media as another context of their everyday life, the implications for interventions aimed at targets of peer-victimization are meaningful.

Bullying Victimization Type and Feeling Unsafe in Middle School.

Given their significance to school violence, this study quantifies the association between bullying victimization and perceptions of safety separately for victimization where the type is not specified versus victimization that is physical in nature. Generalized liner mixed modeling was employed with 5,138 sixth- to eighth-grade students in 24 schools who self-reported on their bullying victimization and perceptions of school safety on an anonymous survey in fall 2015. Results indicate a multiplicative interaction exists with regard to the odds of feeling unsafe at school among those who were bullied at all (odds ratio [ OR] = 3.1) compared to those who were bullied physically ( OR = 9.12). For school nurses who work with students with a variety of concerns and health issues, this research indicates that the use of bullying victimization as an outcome, proxy and/or predictor, requires inquiry into the type of bullying experienced to aid in the care and support received.