Comparison of corrected QT (QTc) interval of electrocardiogram calculated from various formulas.

QT interval in an electrocardiogram (ECG) is interpreted after correction (QTc) by various formulas. This study aimed to compare the QTcs calculated by nine formulas. Sinus rhythm ECG reports of 1140 anonymous subjects showed uncorrected QT interval of 388.49 ± 42.74 ms. The QTc calculated by Bazett (443.96 ± 57.58 ms), Fridericia (424.37 ± 50.1 ms), Dmitrienko (433.59 ± 53.37 ms), Framingham (422.59 ± 45.55 ms), Schlamowitz (433.89 ± 48.05 ms), Hodges (421.6 ± 46.4 ms), Ashman (434.33 ± 54.05 ms), Rautaharju (427.75 ± 47.4 ms), and Sarma (429.22 ± 48.67 ms) showed a significant difference F (8, 10251) = 22.78 p < 0.0001. Hence, ECG should contain the formula for proper reporting and ease of interpretation by clinicians.

A Brief Review on Good Clinical Practice and its Training Methods.

The field of clinical research continues to advance, and for ethical conduct of research, researchers need to have a strong foundation in good clinical practice (GCP). GCP guidelines are internationally recognized standards that govern the conduct of clinical trials, ensuring the protection of human subjects and the generation of reliable data. However, novice researchers or postgraduate medical students who would delve into research activities may face difficulty getting avenues for GCP training. Hence, in this brief review article, we discuss the significance of GCP in the field of clinical research with a glimpse of its history, development, and key principles. We provide a list of online courses, benefits, and disadvantages of those courses, and a list of organizations that conduct GCP workshops or continued medical education programs in India.

Social Media and Urticaria - A Data Audit of Facebook®, LinkedIn®, and Twitter® Posts.

Introduction: Urticaria is a common debilitating dermatological disorder impairing a patient's quality of life. Such patients are increasingly using socialmedia to manage their health and interact with peers, particularly during the ongoing COVID-19 pandemic. Objectives: To explore and analyse the quality of urticaria related social-media information available to patients. Materials and Methods: An in-depth data audit of the three most commonly used social networks viz. Facebook®, LinkedIn®, and Twitter® were done on a single day, as posts may change or lose relevance over time. The word "urticaria" was searched on three social media, and the first 100 posts in each were further analysed. The post-creator was either categorised as "individual" or "group", and non-English posts were excluded. All types of posts have been analysed, including text, images, video, and website links. We also collected the comments/replies, share/re-tweet, and likes on the posts. Results: Among the total 300 social-media posts, the highest number of "individual" posts was on LinkedIn® followed by Twitter® and Facebook® (χ2 = 82.86, P < 0.0001). Regarding thematic content, most Facebook® posts discussed disease symptoms, followed by the promotion of journal or blog posts, and discussion about causative and triggering agents. LinkedIn® was primarily used for the promotion of journal articles or blog posts, followed by educational webinars and urticaria treatment stories. Twitter® users mostly interacted with peers about their urticaria symptoms and perceived etiologic and triggering factors. Regarding the type of post, images were maximally shared on Facebook®, while video/video links and web links were highest on LinkedIn® (χ2 = 21.59, P < 0.0001). Conclusion: The overall quality of urticaria related information on these 3 social media platforms is satisfactory for patients. Dermatologists may consider utilising social media to further educate such patients and improve the overall treatment outcome. The use of such networking channels will continue to grow, as communication remains crucial for urticaria management.

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.

Accuracy of a Non-Invasive Home Glucose Monitor for Measurement of Blood Glucose.

Introduction: Patients with diabetes mellitus monitor their blood glucose at home with monitors that require a drop of blood or use a continuous glucose monitoring device that implants a small needle in the body. However, both cause discomfort to the patients which may inhibit them for regular blood glucose checks. Photoplethysmogram (PPG) sensing technology is an approach for non-invasive blood glucose measurement and PPG sensors can be used to predict hypoglycaemic episodes. InChcek is a PPG-based non-invasive glucose monitor. However, its accuracy has not been checked yet. Hence, this study aimed to evaluate the accuracy of InCheck, a non-invasive glucose monitor for the estimation of blood glucose. Methods: In a tertiary care hospital, patients who came for blood glucose estimation were tested for blood glucose non-invasively on the InCheck device and then by the laboratory method (glucose oxidase-peroxidase). These two readings were compared. We used International Organization for Standardization (ISO) 15197:2013 (95% of values should be within ± 15 mg/dL of reference reading if reference glucose <100 mg/dL or within ± 15% of reference reading if reference glucose ≥100 mg/dL and 99% of the values should be within zones A and B in consensus error grid), and Surveillance Error Grid for analyzing the accuracy. Results: A total of 1223 samples were analyzed. There was a significant difference between the reference method glucose level (135 [Q1-Q3: 97 - 179] mg/dL) and monitor-measured glucose level (188.33 [Q1-Q3: 167.33-209.33] mg/dL) (P < 0.0001). A total of 18.5% of readings were following ISO 15197:2013 criteria and 67.25% of coordinates were within zone A and zone B of the consensus error grid. In the surveillance error grid analysis, about 29.4% of values were in the no-risk zone, 51.8% in slight risk, 18.6% in moderate risk, and 0.2% were in the severe risk zone. Conclusion: The accuracy of the InCheck device for the estimation of blood glucose by PPG signal is not following the recommended guidelines. Hence, further research is necessary for programming or redesigning the hardware and software for a better result from this optical sensor-based non-invasive home glucose monitor.

ChatGPT in Answering Queries Related to Lifestyle-Related Diseases and Disorders.

Background Lifestyle-related diseases and disorders have become a significant global health burden. However, the majority of the population ignores or do not consult doctors for such disease or disorders. Artificial intelligence (AI)-based large language model (LLM) like ChatGPT (GPT3.5) is capable of generating customized queries of a user. Hence, it can act as a virtual telehealth agent. Its capability to answer lifestyle-related diseases or disorders has not been explored. Objective This study aimed to evaluate the effectiveness of ChatGPT, an LLM, in providing answers to queries related to lifestyle-related diseases or disorders. Methods A set of 20 lifestyle-related disease or disorder cases covering a wide range of topics such as obesity, diabetes, cardiovascular health, and mental health were prepared with four questions. The case and questions were presented to ChatGPT and asked for the answers to those questions. Two physicians rated the content on a three-point Likert-like scale ranging from accurate (2), partially accurate (1), and inaccurate (0). Further, the content was rated as adequate (2), inadequate (1), and misguiding (0) for testing the applicability of the guides for patients. The readability of the text was analyzed by the Flesch-Kincaid Ease Score (FKES).  Results Among 20 cases, the average score of accuracy was 1.83±0.37 and guidance was 1.9±0.21. Both the scores were higher than the hypothetical median of 1.5 (p=0.004 and p<0.0001, respectively). ChatGPT answered the questions with a natural tone in 11 cases and nine with a positive tone. The text was understandable for college graduates with a mean FKES of 27.8±5.74. Conclusion The analysis of content accuracy revealed that ChatGPT provided reasonably accurate information in the majority of the cases, successfully addressing queries related to lifestyle-related diseases or disorders. Hence, initial guidance can be obtained by patients when they get little time to consult a doctor or wait for an appointment to consult a doctor for suggestions about their condition.

ChatGPT in academic writing: Maximizing its benefits and minimizing the risks.

This review article explores the use of ChatGPT in academic writing and provides insights on how to utilize it judiciously. With the increasing popularity of AI-powered language models, ChatGPT has emerged as a potential tool for assisting writers in the research and writing process. We have provided a list of potential uses of ChatGPT by a novice researcher for getting help during research proposal preparation and manuscript writing. However, there are concerns regarding its reliability and potential risks associated with its use. The review highlights the importance of maintaining human judgment in the writing process and using ChatGPT as a complementary tool rather than a replacement for human effort. The article concludes with recommendations for researchers and writers to ensure responsible and effective use of ChatGPT in academic writing.

Assessing the Utilization of Large Language Models in Medical Education: Insights From Undergraduate Medical Students.

Background Artificial intelligence (AI) has the potential to be integrated into medical education. Among AI-based technology, large language models (LLMs) such as ChatGPT, Google Bard, Microsoft Bing, and Perplexity have emerged as powerful tools with capabilities in natural language processing. With this background, this study investigates the knowledge, attitude, and practice of undergraduate medical students regarding the utilization of LLMs in medical education in a medical college in Jharkhand, India. Methods A cross-sectional online survey was sent to 370 undergraduate medical students on Google Forms. The questionnaire comprised the following three domains: knowledge, attitude, and practice, each containing six questions. Cronbach's alphas for knowledge, attitude, and practice domains were 0.703, 0.707, and 0.809, respectively. Intraclass correlation coefficients for knowledge, attitude, and practice domains were 0.82, 0.87, and 0.78, respectively. The average scores in the three domains were compared using ANOVA. Results A total of 172 students participated in the study (response rate: 46.49%). The majority of the students (45.93%) rarely used the LLMs for their teaching-learning purposes (chi-square (3) = 41.44, p < 0.0001). The overall score of knowledge (3.21±0.55), attitude (3.47±0.54), and practice (3.26±0.61) were statistically significantly different (ANOVA F (2, 513) = 10.2, p < 0.0001), with the highest score in attitude and lowest in knowledge. Conclusion While there is a generally positive attitude toward the incorporation of LLMs in medical education, concerns about overreliance and potential inaccuracies are evident. LLMs offer the potential to enhance learning resources and provide accessible education, but their integration requires further planning. Further studies are required to explore the long-term impact of LLMs in diverse educational contexts.

Perceived leadership quality and empathy among Indian undergraduate medical students.

BACKGROUND: Efficient leaders from the medical fraternity may understand healthcare in depth. Empathy is important for patient care, job satisfaction, and the psychological well-being of doctors. Empathic leadership is concerned with an interest in the people around them. This study aimed to observe the perceived leadership quality and empathy among Indian medical undergraduate students, find any correlation between them, and assess age, sex, and semester of study as predictor variables for leadership and empathy. MATERIALS AND METHODS: An online cross-sectional survey was conducted on Google Forms with undergraduate medical students in India with a convenient snowball sample. The Abbreviated Self Leadership Quality (ASQL) was used to find the leadership quality and the eight-item Empathy Quotient (EQ-8) to find the empathy. Spearman's correlation coefficient was calculated between ASQL and EQ-8 score. Age, sex, and semester were used as predictor variables in regression analysis with leadership and empathy as dependent variables. RESULT: A total of 439 (50.8% male, 49.2% female) Indian undergraduate students participated in the study. Males showed higher leadership qualities. There was no gender difference in empathy. Leadership was positively correlated (rs =0.13, P = .006) with empathy in the overall sample. The age (P = .001), sex (P < .0001), and semester of study (P < .0001) successfully predicts leadership (F = 57.167, P < .0001). Although age, sex, and semester combined successfully predict empathy (F = 5.31, P = .001), individually, only a semester of study (P = .009) significantly contributes to the prediction. CONCLUSION: Male and female medical students show a similar level of empathy but male shows higher leadership quality. Leadership and empathy are positively correlated; hence, students with higher leadership quality would show higher empathy and vice versa. The age, sex, and semester of study are determinants of leadership whereas semester of study is the determinant of empathy.

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.

A pilot study on the capability of artificial intelligence in preparation of patients' educational materials for Indian public health issues.

Background: Patient education is an essential component of improving public health as it empowers individuals with the knowledge and skills necessary for making informed decisions about their health and well-being. Primary care physicians play a crucial role in patients' education as they are the first contact between the patients and the healthcare system. However, they may not get adequate time to prepare educational material for their patients. An artificial intelligence-based writer like ChatGPT can help write the material for physicians. Aim: This study aimed to ascertain the capability of ChatGPT for generating patients' educational materials for common public health issues in India. Materials and Methods: This observational study was conducted on the internet using the free research version of ChatGPT, a conversational artificial intelligence that can generate human-like text output. We conversed with the program with the question - "prepare a patients' education material for X in India." In the X, we used the following words or phrases - "air pollution," "malnutrition," "maternal and child health," "mental health," "noncommunicable diseases," "road traffic accidents," "tuberculosis," and "water-borne diseases." The textual response in the conversation was collected and stored for further analysis. The text was analyzed for readability, grammatical errors, and text similarity. Result: We generated a total of eight educational documents with a median of 26 (Q1-Q3: 21.5-34) sentences with a median of 349 (Q1-Q3: 329-450.5) words. The median Flesch Reading Ease Score was 48.2 (Q1-Q3: 39-50.65). It indicates that the text can be understood by a college student. The text was grammatically correct with very few (seven errors in 3415 words) errors. The text was very clear in the majority (8 out of 9) of documents with a median score of 85 (Q1-Q3: 82.5-85) in 100. The overall text similarity index was 18% (Q1-Q3: 7.5-26). Conclusion: The research version of the ChatGPT (January 30, 2023 version) is capable of generating patients' educational materials for common public health issues in India with a difficulty level ideal for college students with high grammatical accuracy. However, the text similarity should be checked before using it. Primary care physicians can take the help of ChatGPT for generating text for materials used for patients' education.

Current distribution of medical colleges in India and its potential predictors: A public domain data audit.

Background: A teaching hospital or medical college may help provide better health care delivery to the people of the vicinity. Hence, building new medical colleges and upgrading existing hospitals to teaching hospitals are being implemented in India. Objective: This study aimed to observe the current distribution of medical colleges in Indian states and find correlation with area, population, and net state domestic product (NSDP). Methods: We collected data from public domain websites provided by government agencies. The State-wise number of government and private medical colleges and their annual intake were obtained from the National Medical Commission website. The state-wise number of medical colleges, geographical area, and population were calculated as the percentage of total Indian colleges, area, and population, respectively. Spearman's correlation was calculated to find any correlation of colleges and annual intake versus parameters such as area, population, and NSDP. Results: India has a total of 612 [321 (52.45%) government-run and 291 (47.55%) private] medical colleges. Tamil Nadu (70), Uttar Pradesh (67), Karnataka (63), Maharashtra (62), and Telangana (34) are the top five states with 296 (48.37%) medical colleges. States and union territories such as Karnataka, Kerala, Maharashtra, Puducherry, Tamil Nadu, and Telangana have higher medical colleges, and states such as Assam, Bihar, Odisha, Madhya Pradesh, Rajasthan, and Uttar Pradesh have lower medical colleges when compared with their population percentages. There was significant positive correlation of number of medical colleges with area (rs = 0.769, P < 0.0001), population (rs = 0.91, P < 0.0001), and NSDP (rs = 0.91, P < 0.0001). Conclusion: The current distribution of medical colleges in India is clustered over some states. Although geographical area and population are major predictors of medical colleges in Indian states, a more population-based balanced distribution of medical colleges would help distribute quality health care to the majority of the population.

A cross-sectional audit of informed consent of online survey: Characteristics and adherence to prevalent guidelines.

Background: Research on human participants requires formal approval from a competent ethics committee. During the recruitment of the research participants, obtaining informed consent is a prerequisite. The online survey method is used by many researchers as it can collect the data from a diverse population in a short time. Aim: This study aimed to observe the characteristics and adherence to prevalent guidelines (set by the Indian Council of Medical Research [ICMR]) of informed consent coupled with online surveys. Methods: We collected the informed consent text from online survey links obtained from a network of colleagues who got a request to participate in a survey. Data were collected from July 2020 to June 2022. The text was anonymized for further analysis. The word count, sentences, and Flesch reading ease score were calculated. The adherence to ICMR guidelines where checked by two authors individually and a consensus was reached to prepare the final result. Results: A total of 44 online surveys in English were audited and among them, 10 did not have informed consent. The informed consent in 34 surveys had a median of 6 sentences and 84 words. The median reading ease score was 45.7 (college level). The majority of the consent states the purpose of the research (91.18%), the voluntary nature of the participation (85.29%), and mentioned that it is research (64.71%). However, the rest of the components are ignored by the majority of the survey consent form. Conclusion: Informed consent form with online surveys lacks adherence to the components suggested by ICMR. Hence, the forms should be made carefully by the researchers so that the vigor of informed consent is maintained in the online surveys.

Student perceptions of Twitter poll-based formative assessment in a rural medical college in India.

Formative assessment is vital for student learning and engagement. Social media platforms like Twitter have gained popularity in medical education, but little research has explored student perceptions of formative assessment through Twitter. This study aimed to observe participation rates in Twitter poll-based formative assessment and survey students' perceptions of it in a rural medical college in India. Fifteen formative assessment sessions were conducted using a Twitter poll after physiology lectures, with five multiple-choice questions per session. The number of participants in each poll was recorded. A questionnaire collected student perceptions after the sessions. Across 15 Twitter poll sessions, we received an average of 12.65 ± 5.53 (median 12) responses. Most students (63%) did not participate, with only 4% participating in over 10 sessions. A total of 107 students participated in the survey, resulting in an 85.6% response rate. Students found social media-based formative assessment interesting and effective for increasing attention in class. However, they preferred alternative platforms like Telegram and Instagram for formative assessment. In conclusion, most students in a rural medical college in India do not participate in Twitter poll-based formative assessment. Nevertheless, students found it interesting and effective, highlighting the importance of considering students' platform preferences for implementing social media-based formative assessment.NEW & NOTEWORTHY The study presents the participation of medical students in Twitter poll-based formative assessment in a rural medical college in India. Despite low participation rates, students found social media-based formative assessment highly effective in increasing their attention during class. The study also reveals student preferences for alternative platforms like Telegram and Instagram. These insights contribute significantly to understanding the impact and relevance of social media-based formative assessment in diverse educational contexts.