Relationship of emotional intelligence and capability of answering higher-order knowledge questions in physiology among first-year medical students.

Emotional intelligence (EI) has a positive correlation with the academic performance of medical students. However, why there is a positive correlation needs further exploration. We hypothesized that the capability of answering higher-order knowledge questions (HOQs) is higher in students with higher EI. Hence, we assessed the correlation between EI and the capability of medical students to answer HOQs in physiology. First-year undergraduate medical students (n = 124) from an Indian medical college were recruited as a convenient sample. EI was assessed by the Schutte Self-Report Emotional Intelligence Test (SSEIT), a 33-item self-administered validated questionnaire. A specially designed objective examination with 15 lower-order and 15 higher-order multiple-choice questions was conducted. The correlation between the examination score and the EI score was tested by Pearson's correlation coefficient. Data from 92 students (33 females and 59 males) with a mean age of 20.14 ± 1.87 yr were analyzed. Overall, students got a percentage of 53.37 ± 14.07 in the examination, with 24.46 ± 9.1 in HOQs and 28.91 ± 6.58 in lower-order knowledge questions (LOQs). They had a mean score of 109.58 ± 46.2 in SSEIT. The correlation coefficient of SSEIT score with total marks was r = 0.29 (P = 0.0037), with HOQs was r = 0.41 (P < 0.0001), and with LOQs was r = 0.14 (P = 0.19). Hence, there is a positive correlation between EI and the capability of medical students to answer HOQs in physiology. This study may be the foundation for further exploration of the capability of answering HOQs in other subjects.NEW & NOTEWORTHY This study assessed the correlation between emotional intelligence (EI) and the capability of medical students to answer higher-order knowledge questions (HOQs) in the specific context of physiology. The finding reveals one of the multifaceted dimensions of the relationship between EI and academic performance. This novel perspective opens the door to further investigations to explore the relationship in other subjects and other dimensions to understand why students with higher EI have higher academic performance.

Small Dense Low-Density Lipoprotein Level in Newly Diagnosed Type 2 Diabetes Mellitus Patients With Normal Low-Density Lipoprotein.

Background and objective There are three subtypes of low-density lipoprotein (LDL): large buoyant (lb), intermediate, and small dense (sd). Among these LDL subtypes, small dense low-density lipoprotein (sdLDL) has been proven to be an independent risk factor for atherosclerosis. Type 2 diabetes mellitus (T2DM) encompasses several metabolic abnormalities and patients suffering from T2DM without good glycemic control are prone to develop atherosclerosis. Hence, in T2DM, it is recommended to evaluate blood lipids for early detection of hyperlipidemia to identify the risk. A larger percentage of sdLDL in T2DM patients with an optimal or near-optimal LDL level might be a hidden risk factor for atherosclerosis. Hence, we aimed to find the level of sdLDL cholesterol (sdLDL-C) among newly diagnosed T2DM patients with optimal or near-optimal blood lipids and to compare it with age and sex-matched controls. Materials and methods In this study, we enrolled newly diagnosed T2DM patients from the diabetic clinic of a tertiary care hospital. The patients were then tested for blood lipids, namely, total cholesterol, triglyceride, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol (LDL-C), including sdLDL-C. Then, age and sex-matched controls with similar baseline lipid levels to the T2DM group (without sdLDL-C) were recruited. After recruitment, both groups were measured for blood lipids including sdLDL-C in a single day. The level of sdLDL-C between the groups was tested statistically by the Mann-Whitney U test. Results A total of 50 T2DM patients with a median age of 36 years (Q1-Q3: 33.75-41) were included as the study group and 50 age and sex-matched controls with a median age of 34 years (32-37.25; p = 0.09) were recruited. The median fasting glucose was 165 (Q1-Q3: 145-199.25) mg/dL and 90.5 (Q1-Q3: 87.75-95.25) mg/dL (p < 0.0001) in the study and control groups, respectively. The LDL-C was 109.9 (Q1-Q3: 99.4-119.4) mg/dL and 108.5 (Q1-Q3: 87.55-124.1) mg/dL (p = 0.94) in the study and control groups, respectively. The sdLDL-C was 40.11 (Q1-Q3: 36.28-43.58) mg/dL and 24.64 (Q1-Q3: 22-32.49) mg/dL (p < 0.0001) in the study and control groups, respectively. Conclusion Newly diagnosed T2DM patients with blood lipids within an optimum or near-optimum level may have a higher percentage of sdLDL-C when compared with healthy controls. Hence, they may have a higher risk of atherosclerosis and cardiovascular diseases. Clinicians may miss the potential risks if they do not advise the sdLDL-C component of LDL-C while advising for the test for blood lipid.

Evaluation of the Effectiveness of a Structured Educational Program on Improving the Knowledge of COVID-19 Among the Vaccine-Reluctant Population in a Block of Jharkhand, India.

Background Low vaccination uptake is a major public health concern and is more prevalent in rural areas. Educational interventions have been proposed as an effective strategy to increase vaccine acceptance. The objective of this study was to assess the impact of an educational program on acquiring knowledge for promoting vaccination uptake among a sample of participants. Methodology This study was conducted in a rural area in the state of Jharkhand, India. The study period was from July 2022 to September 2022. The area was surveyed for COVID-19 vaccination and a total of 510 people did not take any dose or took only the first dose and then skipped the second dose. An educational program was designed in the local language. The knowledge of the sample was assessed before and after a week of intervention with a surveyor-administered questionnaire. The vaccination status before and after the intervention was also recorded. We used the chi-square test, Fisher's exact test, and binomial test for comparing the categorical variables. Results A total of 178 participants' data were analyzed. The majority of the participants were in the age group of 18-25 years. The pre-intervention score regarding the knowledge of COVID-19 and vaccination was 18.93 ± 5.10 which significantly increased after the intervention to 25.06 ± 4.35 (p <0.0001). The number of individuals receiving vaccination significantly increased. Before the program, 95 participants did not take the vaccine and 83 received the first dose and did not take the second dose. After the program, 17 participants did not take the vaccine, 161 completed the first dose, and 112 completed the second dose (p <0.0001). Conclusions The educational program was successful in improving knowledge and awareness about vaccination, leading to an increase in the number of individuals receiving vaccination. These findings suggest the importance of educational interventions in the local language in promoting vaccination uptake and can be used to design effective public health campaigns to increase vaccine acceptance.

Evaluation of Blended Learning Method Versus Traditional Learning Method of Clinical Examination Skills in Physiology Among Undergraduate Medical Students in an Indian Medical College.

Introduction Clinical skills are crucial for medical professionals and are a vital part of a physician's identity. Medical students start learning these skills during their pre-clinical years of study. However, little research has been done on how novice medical students learn to improve these skills. Along with traditional teaching-learning methods, an approach to incorporating e-learning into medical education is through blended learning, which combines traditional classroom instruction with online learning activities. Objective This study aimed to compare the effectiveness of blended learning and traditional learning methods in teaching clinical examination skills to first-year undergraduate medical students by evaluating the objective structured clinical examination (OSCE) test scores. Methodology This was a two-arm prospective cross-over randomized study involving first-year MBBS students. The experimental group (group A) received blended learning, while the control group (group B) received traditional learning for the cardiovascular system examination (phase 1). The groups were then switched for the respiratory system examination (phase 2). An unpaired student t-test was used to compare the mean OSCE scores between the experimental and control groups in each phase, with statistical significance defined as a p-value < 0.05. Results The study involved 25 students in each group during phase 1 and 22 students in each group during phase 2. The experimental group had a mean age of 18.4 (±0.96) years in phase 1 and 18.35 (±1) years in phase 2, while the control group had a mean age of 18.06 (±1.04) years in phase 1 and 18.55 (±0.74) years in phase 2. In phase 1, the experimental group had a higher mean OSCE score (43 {±2.92}) than the control group (26.4 {±2}) (p <0.001). After switching in phase 2, the experimental group (previously the control group) had a higher mean OSCE score (47.82 {±1.68}) than the control group (33.59 {±1.59}) (p <0.001). Conclusion Blended learning is more effective than traditional learning in teaching clinical examination skills to medical undergraduate students. This study suggests that blended learning has the potential to replace the traditional method of learning clinical skills.

Free software applications for authors for writing a research paper.

Basic computer skills are essential for authors writing research papers as it has the potential to make the task easier for a researcher. This article provides a glimpse about the essential software programs for a novice author writing a research paper. These software applications help streamline the writing process, improve the quality of work, and ensure that papers are formatted correctly. It covers word processing software, grammar correction software, bibliography management software, paraphrasing tool, writing tools, and statistical software. All of the tools described are free to use. Hence, it would help researchers from resource-limited settings or busy physicians who get lesser time for research writing. We presume this review paper would help provide valuable insights and guidance for novice authors looking to write a high-quality research paper.

The Capability of ChatGPT in Predicting and Explaining Common Drug-Drug Interactions.

Background Drug-drug interactions (DDIs) can have serious consequences for patient health and well-being. Patients who are taking multiple medications may be at an increased risk of experiencing adverse events or drug toxicity if they are not aware of potential interactions between their medications. Many times, patients self-prescribe medications without knowing DDI. Objective The objective is to investigate the effectiveness of ChatGPT, a large language model, in predicting and explaining common DDIs. Methods A total of 40 DDIs lists were prepared from previously published literature. This list was used to converse with ChatGPT with a two-stage question. The first question was asked as "can I take X and Y together?" with two drug names. After storing the output, the next question was asked. The second question was asked as "why should I not take X and Y together?" The output was stored for further analysis. The responses were checked by two pharmacologists and the consensus output was categorized as "correct" and "incorrect." The "correct" ones were further classified as "conclusive" and "inconclusive." The text was checked for reading ease scores and grades of education required to understand the text. Data were tested by descriptive and inferential statistics. Results Among the 40 DDI pairs, one answer was incorrect in the first question. Among correct answers, 19 were conclusive and 20 were inconclusive. For the second question, one answer was wrong. Among correct answers, 17 were conclusive and 22 were inconclusive. The mean Flesch reading ease score was 27.64±10.85 in answers to the first question and 29.35±10.16 in answers to the second question, p = 0.47. The mean Flesh-Kincaid grade level was 15.06±2.79 in answers to the first question and 14.85±1.97 in answers to the second question, p = 0.69. When we compared the reading levels with hypothetical 6th grade, the grades were significantly higher than expected (t = 20.57, p < 0.0001 for first answers and t = 28.43, p < 0.0001 for second answers). Conclusion ChatGPT is a partially effective tool for predicting and explaining DDIs. Patients, who may not have immediate access to the healthcare facility for getting information about DDIs, may take help from ChatGPT. However, on several occasions, it may provide incomplete guidance. Further improvement is required for potential usage by patients for getting ideas about DDI.

The Effect of a One-Day Workshop on the Quality of Framing Multiple Choice Questions in Physiology in a Medical College in India.

Background Multiple choice questions (MCQs) are commonly used in medical exams for more objectivity in assessment. However, the quality of the questions should be optimum for a proper assessment of the students. A faculty development program (FDP) may improve the quality of MCQs. The effect of a one-day workshop on framing MCQ as a part of a FDP has not been explored in our institution. Aim This study aimed to evaluate the quality of MCQ in the subject of physiology before and after a one-day workshop on framing MCQ as a part of a FDP. Methods This was a retrospective study conducted in the Department of Physiology, All India Institute of Medical Sciences, Deoghar, Jharkhand, India. A one-day workshop on framing MCQ as a part of a FDP was conducted in March 2022. We took 100 MCQs and responses from the students from examinations conducted before the workshop and 100 MCQs and responses from the students after the workshop. In pre-workshop and post-workshop, the same five faculties framed the questions. Post-validation item analysis including difficulty index (DIFI), discrimination index (DI), distractor effectiveness (DE), and Kuder-Richardson Formula 20 (KR-20) for internal consistency was calculated. Results Pre-workshop and post-workshop quality of the MCQ remain equal in terms of DIFI (chi-square {3} = 2.42, P = 0.29), DI (chi-square {3} = 2.44, P = 0.49), and DE (chi-square {3} = 4.97, P = 0.17). The KR-20 in pre-workshop and post-workshop was 0.65 and 0.87, respectively. Both had acceptable internal consistency. Conclusion The one-day workshop on framing MCQs as a part of a FDP did not have a significant impact on the quality of the MCQs as measured by the three indices of item quality but did improve the internal consistency of the MCQs. Further educational programs and research are required to find out what measures can improve the quality of MCQs.

Effect of COVID-19 on Stress and Biomarkers: An Exploratory Cross-Sectional Study.

Background Anxiety and stress in COVID-19 lead to continual pro-inflammatory cytokine activity resulting in excessive inflammation. Levels of different bio indices of COVID-19 may predict clinical outcomes and the severity of COVID-19 disease and may correlate with anxiety and stress levels. Objectives To measure the level of anxiety in COVID-19 patients using the coronavirus anxiety scale (CAS) as an assessment of psychological stress. To measure the levels of blood biomarkers and biochemical and hematological markers of inflammation in COVID-19. To record and measure the indices of short-term HRV in COVID-19 patients to assess their physiological and psychological stress levels. To determine the relationship between anxiety scores, levels of laboratory indices (blood biomarkers), and HRV parameters across mild, moderate and severe cases of COVID-19. Material and method A total of 300 COVID-19 patients aged between 18 and 55 years were included. A questionnaire-based CAS was used to assess anxiety levels. Short-term HRV was recorded to measure stress. Blood biomarkers: Biochemical and hemato-cytological markers of inflammation were measured. Statistical analyses were performed using the SPSS software version 20.0. Results Anxiety and stress increased with the severity of COVID-19. A positive correlation was detected between anxiety and serum ferritin, IL-6, MCV, and MCH levels, and a negative correlation between the corona anxiety score and RBC count. The increase in the severity of COVID-19 showed elevated levels of WBC count, neutrophil%, platelet count, neutrophil/lymphocyte ratio, serum ferritin, D-dimer, C-reactive protein, procalcitonin, interleukin-6, and lactate dehydrogenase, and decreased lymphocyte and monocyte percentages. The increase in the severity of COVID-19 decreased lymphocyte, monocyte, and eosinophil counts. Conclusion The Corona Anxiety Scale and heart rate variability can be used as complementary tools to index COVID-19-related anxiety and stress. An association exists between immune dysregulation and heart rate variability, which can be used to predict the inflammatory response and prognosis of COVID-19.

Large Language Models in Hematology Case Solving: A Comparative Study of ChatGPT-3.5, Google Bard, and Microsoft Bing.

Background Large language models (LLMs), such as ChatGPT-3.5, Google Bard, and Microsoft Bing, have shown promising capabilities in various natural language processing (NLP) tasks. However, their performance and accuracy in solving domain-specific questions, particularly in the field of hematology, have not been extensively investigated. Objective This study aimed to explore the capability of LLMs, namely, ChatGPT-3.5, Google Bard, and Microsoft Bing (Precise), in solving hematology-related cases and comparing their performance. Methods This was a cross-sectional study conducted in the Department of Physiology and Pathology, All India Institute of Medical Sciences, Deoghar, Jharkhand, India. We curated a set of 50 cases on hematology covering a range of topics and complexities. The dataset included queries related to blood disorders, hematologic malignancies, laboratory test parameters, calculations, and treatment options. Each case and related question was prepared with a set of correct answers to compare with. We utilized ChatGPT-3.5, Google Bard Experiment, and Microsoft Bing (Precise) for question-answering tasks. The answers were checked by two physiologists and one pathologist. They rated the answers on a rating scale from one to five. The average score of the three models was compared by Friedman's test with Dunn's post-hoc test. The performance of the LLMs was compared with a median of 2.5 by a one-sample median test as the curriculum from which the questions were curated has a 50% pass grade. Results The scores among the three LLMs were significantly different (p-value < 0.0001) with the highest score by ChatGPT (3.15±1.19), followed by Bard (2.23±1.17) and Bing (1.98±1.01). The score of ChatGPT was significantly higher than 50% (p-value = 0.0004), Bard's score was close to 50% (p-value = 0.38), and Bing's score was significantly lower than the pass score (p-value = 0.0015). Conclusion The LLMs reveal significant differences in solving case vignettes in hematology. ChatGPT exhibited the highest score, followed by Google Bard and Microsoft Bing. The observed performance trends suggest that ChatGPT holds promising potential in the medical domain. However, none of the models was capable of answering all questions accurately. Further research and optimization of language models can offer valuable contributions to healthcare and medical education applications.

Comparing the Efficacy of Individual Approaches and Team-Based Approaches in Solving Clinical Case Vignettes.

Background Clinical case vignettes are a widely adopted pedagogical approach in medical education. The cases may be presented to students with a closed response option for objectivity. While solving clinical cases has demonstrated its effectiveness in enhancing medical students' clinical reasoning, there is an ongoing debate regarding the most effective approach: individual problem-solving or team-based problem-solving. Objective To observe and compare the score obtained from individual clinical problem-solving approaches versus team-based clinical problem-solving approaches. Methods After obtaining consent, a total of 100 students were randomly selected for the study. The participants were divided into two groups: an individual approach group (IAG) (n=25) and a team-based approach group (TAG) comprising 25 groups of three students each. Both groups were presented with a set of 10 clinical problems, each requiring a closed-answer response of "yes", "no", or "don't know". The participants' responses were recorded and analyzed to evaluate their problem-solving efficacy. Results A total of 25 responses were obtained from 25 students from the IAG group and 25 responses from 25 groups from the TAG group. There was no difference between the score in IAG (7.44±1.12) and TAG (7.52 1.66) p-value=0.58. There was no difference between individual scores in 10 questions between IAG and TAG groups. Conclusion The study found no significant score differences between individual and team-based clinical case-solving groups. Hence, for the objective type of case-solving pattern used in this study, a team-based approach may not be necessary. Further research is needed to explore factors for such findings in future studies.