Big Data for Biomedical Education with a Focus on the COVID-19 Era: An Integrative Review of the Literature

Medical education refers to education and training delivered to medical students in order to become a practitioner. In recent decades, medicine has been radically transformed by scientific and computational/digital advances—including the introduction of new information and communication technologies, the discovery of DNA, and the birth of genomics and post-genomics super-specialties (transcriptomics, proteomics, interactomics, and metabolomics/metabonomics, among others)—which contribute to the generation of an unprecedented amount of data, so-called ‘big data’. While these are well-studied in fields such as medical research and methodology, translational medicine, and clinical practice, they remain overlooked and understudied in the field of medical education. For this purpose, we carried out an integrative review of the literature. Twenty-nine studies were retrieved and synthesized in the present review. Included studies were published between 2012 and 2021. Eleven studies were performed in North America: specifically, nine were conducted in the USA and two studies in Canada. Six studies were carried out in Europe: two in France, two in Germany, one in Italy, and one in several European countries. One additional study was conducted in China. Eight papers were commentaries/theoretical or perspective articles, while five were designed as a case study. Five investigations exploited large databases and datasets, while five additional studies were surveys. Two papers employed visual data analytical/data mining techniques. Finally, other two papers were technical papers, describing the development of software, computational tools and/or learning environments/platforms, while two additional studies were literature reviews (one of which being systematic and bibliometric).The following nine sub-topics could be identified: (I) knowledge and awareness of big data among medical students; (II) difficulties and challenges in integrating and implementing big data teaching into the medical syllabus; (III) exploiting big data to review, improve and enhance medical school curriculum; (IV) exploiting big data to monitor the effectiveness of web-based learning environments among medical students; (V) exploiting big data to capture the determinants and signatures of successful academic performance and counteract/prevent drop-out; (VI) exploiting big data to promote equity, inclusion, and diversity; (VII) exploiting big data to enhance integrity and ethics, avoiding plagiarism and duplication rate; (VIII) empowering medical students, improving and enhancing medical practice; and, (IX) exploiting big data in continuous medical education and learning. These sub-themes were subsequently grouped in the following four major themes/topics: namely, (I) big data and medical curricula; (II) big data and medical academic performance; (III) big data and societal/bioethical issues in biomedical education; and (IV) big data and medical career. Despite the increasing importance of big data in biomedicine, current medical curricula and syllabuses appear inadequate to prepare future medical professionals and practitioners that can leverage on big data in their daily clinical practice. Challenges in integrating, incorporating, and implementing big data teaching into medical school need to be overcome to facilitate the training of the next generation of medical professionals. Finally, in the present integrative review, state-of-art and future potential uses of big data in the field of biomedical discussion are envisaged, with a focus on the still ongoing “Coronavirus Disease 2019” (COVID-19) pandemic, which has been acting as a catalyst for innovation and digitalization.

THE UZBEK MODEL OF BIOETHICS: HISTORY AND MODERNITY

Modern biomedical ethics is based on a rich tradition of systematic moral thought, both philosophical and religious. In the XXI century, the interaction and synthesis of natural and humanitarian disciplines are of paramount importance in the system of biomedical education. One of the ways to solve this problem for future specialists is to study the foundations of biomedical ethics, the formation of a bioethical culture of future doctors. Among the ancient scientists of Central Asia who became famous in the field of medicine and pharmacy, a prominent place is occupied by Abuali Ibn Sino (Avicenna), whose life and work can serve as an example of national and historical identity, patriotic education of the youth of Uzbekistan. The emergence of such a phenomenon as the "Muslim Renaissance" and in this context the life and work of Avicenna, his role in the history of the development of medicine in Uzbekistan, are devoted to many, which, like others, were included in the materials of this study. A kind of bridge from ancient medicine to the medicine of the Renaissance and further to modern medicine was the legacy of doctors in Central Asia and Arab physicians. At present, the social, legal and economic aspects of ethical problems of key issues of bioethics in the field of health, medicine and biomedical technologies in the context of the Islamic faith continue to be studied.

CHALLENGES OF INTERPRETATION OF GENETIC TEST RESULTS ON THE EXAMPLE OF STUDY OF ENDURANCE

The purpose of the research is to study the possibility of predicting the development of aerobic endurance of athletes through a comparative analysis of the outcomes of genetic and computerized testing. Methods and organization of the research. In our research, we used scientific and methodological literature, as well as the outcomes of competitive activity and genetic analysis of a particular athlete. The total number of survey respondents was 158 people including athletes (n = 85) and coaches (n = 73). Results and discussion. Some authors find the relationship between the ability to develop and manifest endurance and the presence of the appropriate alleles of genes: ACE I, ACNT X, ACNT3 (RX, XX), ADRA2A, AMPDI C, PGC1A Gly, NFATC4, UCP2. Most studies reveal the relationship between the ACE gene and endurance supported by the I allele. Genetic foresight of the possibility of developing aerobic endurance of athletes can become the framework for the application of an individual approach in sport training, and contribute to the development of techniques aimed at the refinement of physical qualities. The modern approach to the coaching and competitive activities of athletes should include both genetic and functional studies of the human body. Conclusion. Sport forecast cannot be based solely on genetic testing results. The presence of polymorphisms in one or more genes associated with sport activity is the platform for good performance in a particular sport, but the actual manifestation of genetic predisposition depends on many factors. These factors include nutrition, daily routine and competent organization of the training process, which requires a high level of theoretical and practical competency of coaches in the field of biomedical education.

Clinical Sciences—Leading the Way in Competency-Based Biomedical Education

For decades, educators in the clinical sciences have been at the forefront of innovations in educational practices related to science and medicine. Ultimately, such innovations are often translated and implemented as best practices across the breadth of biomedical disciplines. Far from novel, competency-based approaches to higher education have been around since the 1960s. These have their origins in student outcomes-based models that focus on the assessment of demonstrated competencies through students’ applications of theory, learned in the classroom, to perform a task and/or resolve a defined issue or problem. Despite its long history of contributing to human medical education and, more recently, veterinary medical education, competency-based instruction is still rare in undergraduate biomedical education. Herein, we discuss the value of clinical education in leading the way toward competency-based, undergraduate biomedical programs.

Nursing Students’ Perceptions of Biomedical Education with Augmented Reality

Innovative techniques provide a teaching strategy to improve education in biomedical sciences for nursing students [1]. With augmented reality (AR) technology, elements in the physical environment can be enriched or supplemented by computer-generated sensory inputs such as text, images, 3-dimensional (3D) graphics, and audio. AR has been paradigmatically applied worldwide to education of different disciplines, making some contributions to teaching and learning [2]. However, AR products on the market mainly focus on primary or secondary education where the pleasurable aspects of AR are promoted [3]. Although acceptance of using AR in healthcare education was reported [4], the actual impacts of AR applications in the training of healthcare professionals have not been well-studied [5]. In view of the potential advantages of integrating AR into nursing education, such as a better visualization of body structures [6], a survey was conducted to specifically assess the effectiveness of AR in improving the quality of biomedical education as perceived by nursing students.

How Much Is Needed? Comparison of the Effectiveness of Different Pain Education Dosages in Patients with Fibromyalgia

ObjectiveTo assess the effect of different dosages of pain neuroscience education (PNE) programs on central nociceptive processing in patients with fibromyalgia. Second, to compare the effects of different dosages of PNE programs on numerical pain rating scale (NPRS), disability, and psychological variables.DesignSingle-blind randomized controlled trial.SettingThree fibromyalgia centers in Spain (Valencia, Alcorcón, Alcalá de Henares).SubjectsSeventy-seven patients with fibromyalgia.MethodsParticipants were randomized to four groups of PNE: 1) high-dose PNE (N = 20), 2) low–concentrated dose PNE (N = 20), 3) diluted low-dose PNE (N = 20), and (4) control treatment (N = 17), conducted in two 30–50-minute sessions in groups of four to six participants. Conditioned pain modulation (CPM), temporal summation (TS), and pressure pain thresholds (PPTs) were assessed at baseline and at three-month follow-up. Secondary outcome measures were the Fibromyalgia Impact Questionnaire, Pain Catastrophizing Scale, and Pain Anxiety Symptoms Scale.ResultsThere were significant between-group differences for NPRS in favor of the groups receiving high-dose PNE, with a large effect size at three-month follow-up (P < 0.01, η2p = 0.170), but there were no significant differences between groups for the remaining variables (P > 0.05). All groups improved for central nociceptive processing, psychological variables, disability, and pain intensity (NPRS).ConclusionsIn patients with fibromyalgia, higher dosages of PNE produced a larger improvement in pain severity at three-month follow-up than other dosages of PNE and biomedical education. However, PNE was not superior to biomedical education in the central nociceptive processing, disability, or psychological variables in patients with fibromyalgia.