Student dropout in higher education has been of great interest to the academic community, state and social actors over the last three decades, due to the various effects that this event has on the student, the family, higher education institutions, and the state itself. It is recognised that dropout at this level of education is extremely complex due to its multi-causality which is expressed in the existing relationship in its explanatory variables associated with the students, their socioeconomic and academic conditions, as well as the characteristics of the educational institutions. Thus, the aim of this article was to identify the individual, socioeconomic, academic, and institutional explanatory variables involved in student dropout in rural populations, based on a synthesis of the evidence available in the SCOPUS database. In order to achieve it, a mixed systematic review was defined under the PRISMA 2020 method. The analysis was approached in two stages; the first concerned the identification of the documents and the conformation of the sample, where 21 documents were distinguished for effectively dealing with dropout in rural higher education; and the second corresponded to the procedures defined for the development of the bibliometric analysis and synthesis of the information found in the documents. The results showed the distribution of studies by country, years of publication, the categorisation of the documents in SCOPUS, their classification by type and the methodologies used in the development of the studies analysed, as well as the variables that have been addressed in previous research. In this way, it is concluded that the results of the studies are not generalisable, either because of the size of the sample or because of the marked social asymmetries that exist in some countries, which can make the findings lack significance; on the other hand, the interest in research on variables associated with individual and academic determinants to explain rural student dropout is highlighted. In addition, some future research lines which can be addressed as a complement to the current view of the dropout event in rural higher education were identified.

Community Health Worker (CHW) interventions can help improve diabetes self-management and health outcomes. There is limited evidence on how to effectively integrate CHW programs with primary care efforts. Mobile health technology (mHealth) can connect CHWs to members of the healthcare team and enhance care. We tested a model for the integration of a CHW delivered mHealth intervention to improve diabetes self-management. Seventy-two African American patients with diabetes were followed using the mHealth tool. This project partnered an academic institution, a safety-net clinic, and African American churches. The integration of mHealth technology into CHW programs was successfully achieved and readily accepted.

Background Gamification uses elements of game design to enhance learner engagement. We introduced a microbiology “trivia game” for first year medical students (MS1), leveraging principles of gamification (self-efficacy, points, leaderboards, etc.) to enhance participation. We hypothesized this would engage learners and improve course performance. Methods We created a “microbiology trivia game” using Kaizen-Education, a software platform (Kaizen) developed by our Center for Clinical and Translational Science. All MS1 in the Microbiology course at the University of Alabama at Birmingham (Fall 2019) were invited to participate by downloading the smartphone app. We created 56 questions emphasizing high yield concepts and their clinical application. Participation was voluntary during the Microbiology course (3 weeks). We collected app utilization and test performance data in this IRB approved investigation. We completed descriptive analyses of student engagement including a Player Efficiency Rating (PER). The PER is a student-level composite measure of student accuracy, play frequency and question completion. We calculated Spearman rank correlation of mean exam scores and PER. At course completion students received a survey about their experience. Results 181 (96%) of 189 Microbiology students answered ≥ 1 question. Across those 181 students, 161 (89%) completed all questions (table 1). An average of 67 students answered questions each day. Collectively, students answered 96% of all published questions (n=10,136; 56 questions x 181 students). A total of 49% of questions were answered < 24H from publication. Survey response rate was 34% (n=61), and our teaching innovation was positively received (table 2). Final exam performance increased from 80% (2018) to 87% (2019) among students in the gamification enhanced Microbiology course. A correlation between higher PER and better exam scores was found (0.34; p≤0.0001). Conclusion Our gamification infused Microbiology course was well received. Students appreciated the opportunity to apply core foundational microbiology concepts to clinical medicine scenarios early in training. Novel teaching methods may increase student engagement in Medical Microbiology courses, for many the birthplace of their passion for Infectious Diseases. Disclosures All Authors: No reported disclosures

BackgroundMeticulous tracking of study data must begin early in the study recruitment phase and must account for regulatory compliance, minimize missing data, and provide high information integrity and/or reduction of errors. In behavioral intervention trials, participants typically complete several study procedures at different time points. Among HIV-infected patients, behavioral interventions can favorably affect health outcomes. In order to empower newly diagnosed HIV positive individuals to learn skills to enhance retention in HIV care, we developed the behavioral health intervention Integrating ENGagement and Adherence Goals upon Entry (iENGAGE) funded by the National Institute of Allergy and Infectious Diseases (NIAID), where we deployed an in-clinic behavioral health intervention in 4 urban HIV outpatient clinics in the United States. To scale our intervention strategy homogenously across sites, we developed software that would function as a behavioral sciences research platform.ObjectiveThis manuscript aimed to: (1) describe the design and implementation of a Web-based software application to facilitate deployment of a multisite behavioral science intervention; and (2) report on results of a survey to capture end-user perspectives of the impact of this platform on the conduct of a behavioral intervention trial.MethodsIn order to support the implementation of the NIAID-funded trial iENGAGE, we developed software to deploy a 4-site behavioral intervention for new clinic patients with HIV/AIDS. We integrated the study coordinator into the informatics team to participate in the software development process. Here, we report the key software features and the results of the 25-item survey to evaluate user perspectives on research and intervention activities specific to the iENGAGE trial (N=13).ResultsThe key features addressed are study enrollment, participant randomization, real-time data collection, facilitation of longitudinal workflow, reporting, and reusability. We found 100% user agreement (13/13) that participation in the database design and/or testing phase made it easier to understand user roles and responsibilities and recommended participation of research teams in developing databases for future studies. Users acknowledged ease of use, color flags, longitudinal work flow, and data storage in one location as the most useful features of the software platform and issues related to saving participant forms, security restrictions, and worklist layout as least useful features.ConclusionsThe successful development of the iENGAGE behavioral science research platform validated an approach of early and continuous involvement of the study team in design development. In addition, we recommend post-hoc collection of data from users as this led to important insights on how to enhance future software and inform standard clinical practices.Trial RegistrationClinicaltrials.gov NCT01900236; (https://clinicaltrials.gov/ct2/show/NCT01900236 (Archived by WebCite at http://www.webcitation.org/6qAa8ld7v)