The Role of Argumentation in Hypothetico-Deductive Reasoning During Problem-Based Learning in Medical Education: A Conceptual Framework

One of the important goals of problem-based learning (PBL) in medical education is to enhance medical students’ clinical reasoning—hypothetico-deductive reasoning (HDR) in particular—through small group discussions. However, few studies have focused on explicit strategies for promoting students’ HDR during group discussions in PBL. This paper proposes a novel conceptual framework that integrates Toulmin’s argumentation model (1958) into Barrows’s HDR process (1994). This framework explains the structure of argumentation (a claim, data, and a warrant) contextualized in each phase of HDR during PBL. This paper suggests four instructional strategies—understanding argument structures, questioning, elaborating on structural knowledge, and assessing argumentation—for promoting medical students’ argumentation in relation to HDR processes. Further implications of the proposed framework for other disciplines, such as science, legal, and engineering education, are also discussed

Challenges Experienced by Korean Medical Students and Tutors During Problem-Based Learning: A Cultural Perspective

How people learn is influenced by the cultural contexts in which their learning occurs. This qualitative case study explored challenges Korean medical students and tutors experienced during their PBL sessions from a cultural perspective using Hofstede’s cultural dimensions. Twelve preclinical medical students and nine tutors from a large Korean medical school participated in interviews. The interview data were analyzed using the constant comparative method and classified according to Hofstede’s cultural dimensions. Twenty-two themes emerged within the following overarching categories: large power distance (6 themes), high uncertainty avoidance (6), individualism (3), collectivism (4), and masculinity/short-term orientation (3). This article discusses culturally responsive solutions with regard to each cultural dimension, which would help overcome these challenges and enhance the experiences of students and tutors with PBL

Extracting regulatory modules from gene expression data by sequential pattern mining

Abstract Background Identifying a regulatory module (RM), a bi-set of co-regulated genes and co-regulating conditions (or samples), has been an important challenge in functional genomics and bioinformatics. Given a microarray gene-expression matrix, biclustering has been the most common method for extracting RMs. Among biclustering methods, order-preserving biclustering by a sequential pattern mining technique has native advantage over the conventional biclustering approaches since it preserves the order of genes (or conditions) according to the magnitude of the expression value. However, previous sequential pattern mining-based biclustering has several weak points in that they can easily be computationally intractable in the real-size of microarray data and sensitive to inherent noise in the expression value. Results In this paper, we propose a novel sequential pattern mining algorithm that is scalable in the size of microarray data and robust with respect to noise. When applied to the microarray data of yeast, the proposed algorithm successfully found long order-preserving patterns, which are biologically significant but cannot be found in randomly shuffled data. The resulting patterns are well enriched to known annotations and are consistent with known biological knowledge. Furthermore, RMs as well as inter-module relations were inferred from the biologically significant patterns. Conclusions Our approach for identifying RMs could be valuable for systematically revealing the mechanism of gene regulation at a genome-wide level.</p

Maternal, infant, and perinatal mortality statistics and trends in Korea between 2018 and 2020

Purpose This study aimed to identify maternal, infant, and perinatal mortality using the national population data of South Korea between 2018 and 2020, and to analyze mortality rates according to characteristics such as age, date of death, and cause of death in each group. This study updates the most recent study using 2009 to 2017 data. Methods Analyses of maternal, infant, and perinatal mortality were done with data identified through the supplementary investigation system for cases of death from the Census of Population Dynamics data provided by Statistics Korea from 2018 to 2020. Results Between 2018 and 2020, a total of 99 maternal deaths, 2,427 infant deaths, and 2,408 perinatal deaths were identified from 901,835 live births. The maternal mortality ratio was 11.3 deaths per 100,000 live births in 2018; it decreased to 9.9 in 2019 but increased again to 11.8 in 2020. The maternal mortality ratio increased steeply in women over the age of 40 years. An increasing trend in the maternal mortality ratio was found for complications related to the puerperium and hypertensive disorders. Both infant and perinatal mortality continued to decrease, from 2.8 deaths per 1,000 live births in 2018 to 2.5 in 2020 and from 2.8 in 2018 to 2.5 in 2020, respectively. Conclusion Overall, the maternal, infant, and perinatal mortality statistics showed improvements. However, more attention should be paid to women over 40 years of age and specific causes of maternal deaths, which should be taken into account in Korea’s maternal and child health policies

The translational network for metabolic disease – from protein interaction to disease co-occurrence

Background The recent advances in human disease network have provided insights into establishing the relationships between the genotypes and phenotypes of diseases. In spite of the great progress, it yet remains as only a map of topologies between diseases, but not being able to be a pragmatic diagnostic/prognostic tool in medicine. It can further evolve from a map to a translational tool if it equips with a function of scoring that measures the likelihoods of the association between diseases. Then, a physician, when practicing on a patient, can suggest several diseases that are highly likely to co-occur with a primary disease according to the scores. In this study, we propose a method of implementing n-of-1 utility (n potential diseases of one patient) to human disease network—the translational disease network. Results We first construct a disease network by introducing the notion of walk in graph theory to protein-protein interaction network, and then provide a scoring algorithm quantifying the likelihoods of disease co-occurrence given a primary disease. Metabolic diseases, that are highly prevalent but have found only a few associations in previous studies, are chosen as entries of the network. Conclusions The proposed method substantially increased connectivity between metabolic diseases and provided scores of co-occurring diseases. The increase in connectivity turned the disease network info-richer. The result lifted the AUC of random guessing up to 0.72 and appeared to be concordant with the existing literatures on disease comorbidity

Internet-Delivered Cognitive Behavioral Therapy in Patients With Irritable Bowel Syndrome: Systematic Review and Meta-Analysis

BackgroundIrritable bowel syndrome is a common functional gastrointestinal disorder that negatively affects all aspects of life. With the widespread use of the internet, internet-delivered cognitive behavioral therapy has been developed and applied to control symptoms and improve the quality of life of those with irritable bowel syndrome. However, few studies have systematically reviewed the effectiveness of internet-delivered cognitive behavioral therapy on irritable bowel syndrome. ObjectiveThis study aimed to systematically review studies that examined the use of internet-delivered cognitive behavioral therapy in patients with irritable bowel syndrome and to evaluate the effects of internet-delivered cognitive behavioral therapy on the improvement of symptom severity, quality of life, psychological status, and cost-effectiveness. MethodsThis meta-analysis involved the search of 6 databases for relevant publications. From the 1224 publications identified through database searches, 9 randomized controlled trials were finally included in the analysis. ResultsThe internet-delivered cognitive behavioral therapies including exposure-based cognitive behavioral therapy, cognitive behavioral therapy for self-management, and cognitive behavioral therapy for stress management were provided in 5 to 13 sessions for 5 to 10 weeks. Internet-delivered cognitive behavioral therapy had medium-to-large effects on symptom severity (standardized mean difference [SMD] –0.633; 95% CI –0.861 to –0.4304), quality of life (SMD 0.582; 95% CI 0.396-0.769), and cost-effectiveness (–0.372; 95% CI –0.704 to –0.039) at postintervention. The effects on symptom severity remained over time even after the intervention, short-term follow-up (SMD –0.391; 95% CI –0.560 to –0.221), and long-term follow-up (SMD –0.357; 95% CI –0.541 to –0.172). There was no significant difference in psychological status, including anxiety and depression, in those with irritable bowel syndrome compared to the controls during the postintervention period. ConclusionsThis review demonstrates that internet-delivered cognitive behavioral therapy could be a cost-effective intervention for improving symptoms and the quality of life in patients with irritable bowel syndrome. However, studies are still insufficient regarding the use of internet-delivered cognitive behavioral therapy in these patients; therefore, more high-quality studies are required in the future

In Vitro and In Vivo Inhibitory Effects of Gaseous Chlorine Dioxide Against Diaporthe batatas Isolated from Stored Sweetpotato

Chlorine dioxide (ClO2) can be used as an alternative disinfectant for controlling fungal contamination during postharvest storage. In this study, we tested the in vitro and in vivo inhibitory effects of gaseous ClO2 against Diaporthe batatas SP-d1, the causal agent of sweetpotato dry rot. In in vitro tests, spore suspensions of SP-d1 spread on acidified potato dextrose agar were treated with various ClO2 concentrations (1-20 ppm) for 0-60 min. Fungal growth was significantly inhibited at 1 ppm of ClO2 treatment for 30 min, and completely inhibited at 20 ppm. In in vivo tests, spore suspensions were drop-inoculated onto sweetpotato slices, followed by ClO2 treatment with different concentrations and durations. Lesion diameters were not significantly different between the tested ClO2 concentrations; however, lesion diameters significantly decreased upon increasing the exposure time. Similarly, fungal populations decreased at the tested ClO2 concentrations over time. However, the sliced tissue itself hardened after 60-min ClO2 treatments, especially at 20 ppm of ClO2. When sweetpotato roots were dip-inoculated in spore suspensions for 10 min prior to treatment with 20 and 40 ppm of ClO2 for 0-60 min, fungal populations decreased with increasing ClO2 concentrations. Taken together, these results showed that gaseous ClO2 could significantly inhibit D. batatas growth and dry rot development in sweetpotato. Overall, gaseous ClO2 could be used to control this fungal disease during the postharvest storage of sweetpotato