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Objective: College students showed a high prevalence of stress, anxiety, and depression, with medical and nursing students experiencing particularly elevated levels of mental health challenges.Optimism significantly influences overall well-being by promoting a healthy lifestyle and cognitive responses. However, the association of optimism with sleep quality, stress, and mental health in college students remains unexplored. This study aimed to (1) explore the associations of optimism with sleep quality, stress, and mental health and (2) ascertain whether sleep quality and stress mediate the association between optimism and mental health among college students. Methods: A cross-sectional study was conducted using online surveys with students from health science majors at a public university in the northeast United States from September to December 2022. A total of 222 students participated in the study, providing data on sociodemographics, optimism, sleep quality, stress, anxiety, and depression. Parallel and serial mediation models were utilized to examine the potential mediating roles of sleep quality and stress in the association between optimism and mental health. Results: The study found that optimism influences anxiety and depression through both direct and indirect pathways. In line with predictions, the parallel mediation analysis revealed that the impact of optimism on anxiety (ßtotal = -0.598, 95% confident interval [CI]: -0.778 to -0.392) and depression (ßtotal = -0.724, 95% CI: -0.919 to -0.519) was mediated by stress and sleep quality. Furthermore, the serial mediation models revealed that stress and sleep quality co-mediated the relationship betweenoptimism and anxiety (indirect effect [IE] = -0.074, 95% CI: -0.135 to -0.029) or depression (IE = -0.084, 95% CI: -0.142 to -0.036) in a sequential manner. Conclusion: Optimism was negatively correlated with poor sleep quality, stress, anxiety, and depression. Enhanced optimism was linked to high sleep quality and less stress, anxiety, and depression. These insights emphasize the potential for school-based optimism interventions to improve sleep quality, ameliorate stress-related concerns, and alleviate mental health challenges in college students.
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Purpose: Long COVID, also known as post-acute sequelae of COVID-19, refers to the constellation of long-term symptoms experienced by people suffering persistent symptoms for one or more months after SARS-CoV-2 infection. Blood biomarkers can be altered in long COVID patients; however, biomarkers associated with long COVID symptoms and their roles in disease progression remain undetermined. This study aims to systematically evaluate blood biomarkers that may act as indicators or therapeutic targets for long COVID. Methods: A systematic literature review in PubMed, Embase, and CINAHL was performed on 18 August 2022. The search keywords long COVID-19 symptoms and biomarkers were used to filter out the eligible studies, which were then carefully evaluated. Results: Identified from 28 studies and representing six biological classifications, 113 biomarkers were significantly associated with long COVID: (1) Cytokine/Chemokine (38, 33.6%); (2) Biochemical markers (24, 21.2%); (3) Vascular markers (20, 17.7%); (4) Neurological markers (6, 5.3%); (5) Acute phase protein (5, 4.4%); and (6) Others (20, 17.7%). Compared with healthy control or recovered patients without long COVID symptoms, 79 biomarkers were increased, 29 were decreased, and 5 required further determination in the long COVID patients. Of these, up-regulated Interleukin 6, C-reactive protein, and tumor necrosis factor alpha might serve as the potential diagnostic biomarkers for long COVID. Moreover, long COVID patients with neurological symptoms exhibited higher levels of neurofilament light chain and glial fibrillary acidic protein whereas those with pulmonary symptoms exhibited a higher level of transforming growth factor beta. Conclusion: Long COVID patients present elevated inflammatory biomarkers after initial infection. Our study found significant associations between specific biomarkers and long COVID symptoms. Further investigations are warranted to identify a core set of blood biomarkers that can be used to diagnose and manage long COVID patients in clinical practice.