Burnout increased among university students during the COVID-19 pandemic: a systematic review and meta-analysis.

Generally, university students are at risk of burnout. This likely was exacerbated during the COVID-19 pandemic. We aimed to investigate burnout prevalence among university students during the COVID-19 pandemic and examine its distribution across countries, sexes, fields of study, and time-period. PubMed, EMBASE, PsycINFO, World Health Organization's Global COVID-19 database, Scopus, Epistemonikos, ERIC and Google Scholar were searched (protocol: https://doi.org/10.17605/OSF.IO/BYRXW ). Studies were independently screened and extracted. Random-effects meta-analysis was performed. Study quality was appraised, and certainty of evidence was assessed using the Grading of Recommendations Assessment, Development, and Evaluation approach. We identified 44 primary studies comprising 26,500 students. Global prevalence rates were 56.3% for high emotional exhaustion (EE), 55.3% for high cynicism (CY) and 41.8% for low personal accomplishment (PA). Prevalence of EE, CY, and PA domains varied significantly across fields of study, countries and WHO and World Bank regions, but not sex. All studies demonstrated good internal validity, although substantial heterogeneity existed between studies. The certainty of evidence was rated as moderate. Considering its potentially severe consequences, burnout is a significant public health concern. The development and implementation of evidence-based localized interventions at organizational and individual levels are necessary to mitigate burnout.

Sleep disorders and associated factors among medical students in the Middle East and North Africa: a systematic review and meta-analysis.

Sleep disturbances like poor and insufficient sleep are common among medical students in the Middle East and North Africa (MENA) countries; however, the extent of medically defined sleep disorders (SDs) remains unclear. This meta-analysis determines SD prevalence and identifies associated factors among medical students in the MENA. PubMed, Web of Science, Google Scholar, and reference lists of included studies were searched (latest search: June 2022). Meta-analyses included 22 studies and were performed using random-effect models. Included studies used self-reported screening tools for assessing SDs and then estimated the proportion of participants at high risk of developing a SD. Central disorders of hypersomnolence were the most prevalent SD [prevalencepooled range: 30.9% (Jordan) to 62.5% (Saudi Arabia)], followed by insomnia disorders [prevalencepooled range: 30.4% (Jordan) to 59.1% (Morocco)], circadian rhythm sleep-wake disorders [prevalencepooled range: 13.5% (Jordan) to 22.4% (Saudi Arabia)], sleep-related breathing disorders [prevalencepooled range: 12.2% (Jordan) to 22.5% (Pakistan)], sleep-related movement disorders [prevalencepooled range: 5.9% (Egypt) to 30.6% (Saudi Arabia)], and parasomnias [prevalencepooled range: 5.6% (Jordan) to 17.4% (Saudi Arabia)]. Female sex, studying in the latter academic years, having anxiety, excessive internet use, and poor academic performance were significantly associated with SDs. SDs are prevalent among MENA medical students. Implementing student-centered interventions targeting high risk groups in medical schools should be considered to improve students' health and wellbeing.

Setting research priorities for global pandemic preparedness: An international consensus and comparison with ChatGPT's output.

Background: In this priority-setting exercise, we sought to identify leading research priorities needed for strengthening future pandemic preparedness and response across countries. Methods: The International Society of Global Health (ISoGH) used the Child Health and Nutrition Research Initiative (CHNRI) method to identify research priorities for future pandemic preparedness. Eighty experts in global health, translational and clinical research identified 163 research ideas, of which 42 experts then scored based on five pre-defined criteria. We calculated intermediate criterion-specific scores and overall research priority scores from the mean of individual scores for each research idea. We used a bootstrap (n = 1000) to compute the 95% confidence intervals. Results: Key priorities included strengthening health systems, rapid vaccine and treatment production, improving international cooperation, and enhancing surveillance efficiency. Other priorities included learning from the coronavirus disease 2019 (COVID-19) pandemic, managing supply chains, identifying planning gaps, and promoting equitable interventions. We compared this CHNRI-based outcome with the 14 research priorities generated and ranked by ChatGPT, encountering both striking similarities and clear differences. Conclusions: Priority setting processes based on human crowdsourcing - such as the CHNRI method - and the output provided by ChatGPT are both valuable, as they complement and strengthen each other. The priorities identified by ChatGPT were more grounded in theory, while those identified by CHNRI were guided by recent practical experiences. Addressing these priorities, along with improvements in health planning, equitable community-based interventions, and the capacity of primary health care, is vital for better pandemic preparedness and response in many settings.