Comparing the Performance of ChatGPT-4 and Medical Students on MCQs at Varied Levels of Bloom's Taxonomy.

Introduction: This research investigated the capabilities of ChatGPT-4 compared to medical students in answering MCQs using the revised Bloom's Taxonomy as a benchmark. Methods: A cross-sectional study was conducted at The University of the West Indies, Barbados. ChatGPT-4 and medical students were assessed on MCQs from various medical courses using computer-based testing. Results: The study included 304 MCQs. Students demonstrated good knowledge, with 78% correctly answering at least 90% of the questions. However, ChatGPT-4 achieved a higher overall score (73.7%) compared to students (66.7%). Course type significantly affected ChatGPT-4's performance, but revised Bloom's Taxonomy levels did not. A detailed association check between program levels and Bloom's taxonomy levels for correct answers by ChatGPT-4 showed a highly significant correlation (p<0.001), reflecting a concentration of "remember-level" questions in preclinical and "evaluate-level" questions in clinical courses. Discussion: The study highlights ChatGPT-4's proficiency in standardized tests but indicates limitations in clinical reasoning and practical skills. This performance discrepancy suggests that the effectiveness of artificial intelligence (AI) varies based on course content. Conclusion: While ChatGPT-4 shows promise as an educational tool, its role should be supplementary, with strategic integration into medical education to leverage its strengths and address limitations. Further research is needed to explore AI's impact on medical education and student performance across educational levels and courses.

Evaluation of Short-Term Side Effects Following the First Dose of COVID-19 Vaccines Among Physicians and Dentists: A Cross-Sectional Study from India.

Background: Efficacy and safety are fundamental for the development of successful COVID-19 vaccines. Vaccine-associated side effects influence vaccine hesitancy. This study investigated the prevalence, severity, and onset of side effects following the first dose of COVID-19 vaccines among physicians and dentists working in various healthcare settings across India. Methods: A cross-sectional survey collected self-report data from April to June 2021 on side effects following the first dose of the vaccine. An online validated questionnaire using the Google Docs® platform was circulated via email and social media platforms. Results: More than 40% of participants experienced at least one side effect after the first dose of vaccination; the most common were mild and resolved within three days after vaccination. More than 91% of respondents received the Covishield (AstraZeneca) vaccine; the most prevalent adverse effects were soreness of the injected arm (78.9%), tiredness (71.1%), and fever (54.9%). Logistic regression showed that women were almost 60% less likely to report side effects. Conclusion: Findings supported the safety of the first dose of the COVID-19 vaccine based on relatively few self-limiting side effects, mainly soreness of the injected arm and tiredness. Further research is needed to determine the long-term safety of COVID-19 vaccines, especially after booster doses.

Stochastic mortality forecasts for Bangladesh.

Mortality forecasts are essential part for policymaking in any aging society. In recent years, methods to model and forecast mortality have improved considerably. Among them, Lee-Carter method is one of the most influential method. In this paper, Lee-Carter method is applied to forecast mortality and life expectancy of Bangladesh. A functional data analysis approach is used to decompose the smoothed log-mortality rates in Lee-Carter framework for higher goodness-of-fit of the models and for longer forecast horizons. Bangladesh has been experiencing a mortality transition and has gained life expectancy in last few decades. The fitted model here showed higher pace of mortality decline for women in Bangladesh than that of men. The forecasts showed continuation of mortality improvement in long run and by 2060 life expectancy at birth is expected to reach over 80 years for both sexes in Bangladesh. The study also predicts the effect of reduction in infant mortality on the life expectancy in Bangladesh.

Urban-rural differences in disability-free life expectancy in Bangladesh using the 2010 HIES data.

BACKGROUND: Research on health expectancy has been carried out in Bangladesh but none of it has examined the differences in Disability-Free Life Expectancy (DFLE) between urban and rural setting in context of rapid urbanization of Bangladesh in past decades. OBJECTIVES: The present study aims to estimate DFLE for people of all ages living in urban and rural areas in Bangladesh, and to examine the differences in DFLE between these two areas. METHODS: Data from the Sample Vital Registration System 2010 and the Bangladesh Household Income and Expenditure Survey (HIES) 2010 were used in this study. The Sullivan method was applied to estimate DFLE in Bangladesh. RESULTS: Higher rates of mortality and disability were observed in rural areas compared to urban areas with few exceptions. Statistically significant differences in DFLE were revealed from birth to age 15 years for both sexes between urban and rural areas. Urban males had a longer life expectancy (LE), longer DFLE and shorter LE with disability both in number and proportion when compared to rural males. Rural females at age 20+ years had a longer LE than urban females but urban females had a longer DFLE and a shorter LE with disability in both number and proportion at all ages than did rural females. CONCLUSION: This study demonstrates that there were clear inequalities in LE, DFLE and LE with disability between rural and urban areas of Bangladesh along with age-specific differences as well. These findings may serve as useful and benchmark for intervention and policy implications for reducing the gap in health outcomes.

Explaining fertility transition of a developing country: an analysis of quantum and tempo effect.

BACKGROUND: The Total Fertility Rate (TFR) is defined as the average number of births a woman would have if she were to live throughout the reproductive span and bear children at each age at the rates observed in a particular year or period. The current demographic explanation for decline in TFR is primarily attributed to an increase in postponement in pregnancy. Being cross-sectional, fertility measures can be confounded by changes in the timing of births across women's lifetimes (tempo) and by changes in the numbers of children that they have by the time they end their childbearing (quantum). After a sharp fall in the last two decades, TFR of Bangladesh is now 2.3; whereas the TFR was greater than 3 in the last decade. However, mean age at childbearing showed decreasing trend in the last decade. METHODS: This is a secondary analysis of data from the three consecutive Bangladesh Demographic Health Surveys; BDHS-2004, 2007 and 2011. The method of Bongaarts and Feeney has been applied to estimate the tempo of fertility. Life Table analyses were applied on birth intervals to explain the tempo effect. RESULTS: There was a sustained decline of the fertility quantum (the number of births per woman) as estimated by the conventional TFR; due to tempo effects during the last three BDHS surveys. Mean age at childbearing also showed decreasing trend in the last decade. CONCLUSIONS: The current study shows the presence of a significant tempo effect with variability of timing in having first or higher order births. If this trend continues, Bangladesh will be able to achieve below replacement level of fertility soon.