With breakthroughs in Natural Language Processing and Artificial Intelligence (AI), the usage of Large Language Models (LLMs) in academic research has increased tremendously. Models such as Generative Pre-trained Transformer (GPT) are used by researchers in literature review, abstract screening, and manuscript drafting. However, these models also present the attendant challenge of providing ethically questionable scientific information. Our study provides a snapshot of global researchers’ perception of current trends and future impacts of LLMs in research. Using a cross-sectional design, we surveyed 226 medical and paramedical researchers from 59 countries across 65 specialties, trained in the Global Clinical Scholars’ Research Training certificate program of Harvard Medical School between 2020 and 2024. Majority (57.5%) of these participants practiced in an academic setting with a median of 7 (2,18) PubMed Indexed published articles. 198 respondents (87.6%) were aware of LLMs and those who were aware had higher number of publications (p < 0.001). 18.7% of the respondents who were aware (n = 37) had previously used LLMs in publications especially for grammatical errors and formatting (64.9%); however, most (40.5%) did not acknowledge its use in their papers. 50.8% of aware respondents (n = 95) predicted an overall positive future impact of LLMs while 32.6% were unsure of its scope. 52% of aware respondents (n = 102) believed that LLMs would have a major impact in areas such as grammatical errors and formatting (66.3%), revision and editing (57.2%), writing (57.2%) and literature review (54.2%). 58.1% of aware respondents were opined that journals should allow for use of AI in research and 78.3% believed that regulations should be put in place to avoid its abuse. Seeing the perception of researchers towards LLMs and the significant association between awareness of LLMs and number of published works, we emphasize the importance of developing comprehensive guidelines and ethical framework to govern the use of AI in academic research and address the current challenges.

Aims: Understanding of the perceived stress and coping strategies adopted by people is important for contemplating the consequences of a pandemic on mental health of people globally. In this study, we intended to assess the perceived stress status under quarantine/isolation globally during the COVID-19 pandemic.Methods: This is a multicentre, multinational cross-sectional study that recruited isolated/quarantined individuals suspected or confirmed to have COVID-19 to assess the psychological impact of the quarantine/isolation experience by answering a survey distributed online.Results: The study was conducted across 63 participating countries, gaining 1,871 valid responses. There was a higher proportion of female participants in the Moderate to High Perceived Stress Scores (MH-PSS) group compared to the Low Perceived Stress Score group (66.0 vs. 52.0%) and a higher proportion of individuals whose marital status was single had MH-PSS (57.1%). Also, individual's religion (Christian, Hindu, and Muslim), no formal education level, being exposed to a confirmed or suspected COVID-19 patient, being forced to be quarantined/isolated, uncomfortable feeling during quarantine period may significantly increase the risk of MH-PSS (p < 0.05).Conclusions: Many factors can predict stress in COVID-19 pandemic including female sex, being single, religion, no formal education, involuntary quarantine, location and reason of quarantine/isolation, and place of exposure.

As a result of the high contagiousness and transmissibility of SARS-CoV-2, studying the location of the case clusters that will follow, will help understand the risk factors related to the disease transmission. In this study, we aim to identify the transmission cluster category and settings that can guide decision-makers which areas to be opened again. A thorough review of the literature and the media articles were performed. After data verification, we included cluster data from eight countries as of 16th May 2020. Clusters were further categorized into 10 categories and analysis was performed. The data was organized and presented in an easily accessible online sheet. Among the eight included countries, we have found 3905 clusters and a total number of 1,907,944 patients. Indoor settings (mass accommodation and residential facilities) comprised the highest number of both number of clusters (3315/3905) and infected patients (1,837,019/1,907,944), while the outdoor ones comprised 590 clusters and 70,925 patients. Mass accommodation was associated with the highest number of cases in 5 of the 7 countries with data available. Social events and residential settings were responsible for the highest number of cases in the two remaining countries. In the USA, workplace facilities have reported 165 clusters of infection including 122 food production facilities. Lockdown could truly be a huge burden on a country’s economy. However, with the proper knowledge concerning the transmissibility and the behaviour of the disease, better decisions could be made to guide the appropriate removal of lockdown across the different fields and regions.

As India continues to recover from the COVID-19 pandemic after more than 44 million cumulative cases, an upsurge in cases of measles has been reported in multiple states across the country, particu...