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Review Open access Aug 2026

Worldwide Trends and Research Hotspots in Long COVID and Mental Health: A Scientometric and Bibliometric Analysis

Long COVID is frequently associated with neuropsychiatric symptoms, including depression, anxiety, and fatigue, which can substantially impair daily functioning and place a considerable burden on healthcare systems worldwide. Although research in this area is expanding rapidly, no comprehensive bibliometric synthesis has characterized the field’s conceptual shifts, critical knowledge gaps, and emerging research directions. This study aimed to map the intellectual evolution and current landscape of research on Long COVID and mental health to inform future clinical and scholarly efforts. We conducted a bibliometric analysis of publications indexed in the Web of Science Core Collection from January 1, 2019, to July 20, 2025. The search strategy combined terms related to Long COVID and mental health. Following title and abstract screening, 1,464 eligible articles were analyzed using CiteSpace for burst detection and timeline visualization, VOSviewer for network mapping of countries, institutions, authors, and keywords, and Excel for trend analysis. Inclusion criteria required original research or reviews published in English. Annual publication output increased rapidly, with growth beginning to level off after 2023. The United States and England accounted for the largest shares of publications. However, citation impact was not directly proportional to publication volume, highlighting the importance of highly influential institutional research hubs. The core journals spanned clinical medicine and public health, reflecting the interdisciplinary nature of the field. Thematic analyses showed that research fronts have expanded beyond depression and anxiety to include neurocognitive impairment, neuroinflammatory mechanisms, and the psychosocial consequences of prolonged disability. This is the systematic bibliometric analysis to map the intellectual structure and thematic evolution of research on Long COVID and mental health. The field has progressed from broad descriptions of psychological distress to syndrome-specific, mechanistic, and interventional investigations, providing a framework for future research priorities. Depression, anxiety, and fatigue remained central research themes, reflecting their persistent clinical burden and continued importance as research priorities.

Xianghui Li, Jiangquan Yu, Yun Zhao · 0 citations
#artificial intelligence Preprint Aug 2026

ScienceArena: Benchmarking LLMs on Latest Scientific Olympiad Competitions

Benchmark saturation and data contamination increasingly obscure genuine scientific reasoning in frontier LLMs. We introduce \textsc{ScienceArena}, an olympiad-style benchmark from thirteen public science competitions in physics, chemistry, and biology, including IPhO and IChO 2025--2026, IBO 2023, USAPhO 2026, and USNCO 2025. Its open-ended, multi-step problems use process-credit rubrics, making faithful scoring difficult. We build ScienceArena through an expert-audited digitization pipeline that converts official exams, figures, solutions, and rubrics into structured items verified by olympiad medalists. To scale evaluation beyond costly human grading, we calibrate LLM-as-judge against medalist ground truth on archived answers from five models across IPhO and IChO; two strong judges stay within one point of expert total scores. Medalist notes show that failures often stem from visual grounding, structure fidelity, and global problem control rather than missing terminology. Evaluating fourteen recent LLMs with interleaved solving, we find that top models obtain medal-equivalent rubric scores on several public international exams, while chemistry and long-horizon consistency remain key bottlenecks. We provide an interactive \href{https://science-arena.onrender.com/}{demo}.

Guangxiang Zhao, Qi-Long Shi, Xusen Xiao et al. · 0 citations

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