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Sponsored AI Networking Cookbook: Practical recipes for AI-assisted network automation and development AI Networking Cookbook: Practical recipes for AI-assisted network automation and development

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Yuxuan Wu

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Review Open access Aug 2026

Associations of outdoor time, sedentary behaviour, and sleep with psychological distress in primary and secondary school students: a cross-sectional study

Previous studies have shown that outdoor activity, sedentary behavior, and sleep duration are associated with psychological distress in children and adolescents. Using an isotemporal substitution model, this study examined the simulated effects of reallocating time among these behaviors with the risk of high psychological distress and whether sex differences exist. From March 2023 to May 2023, 6132 students aged 9–19 years (mean age = 14.0 years, 48.9% males) in Anhui Province were selected. Basic information, outdoor activity, sedentary behavior, and sleep, were collected through a questionnaire survey. The Kessler Psychological Distress Scale was used to measure the psychological distress of the study subjects. The isotemporal substitution model was used to analyze the associations of outdoor activity, sedentary behavior, and sleep duration with high psychological distress, and stratified analysis was performed by gender. The results of this survey indicate that among 6,132 primary and secondary school students, the detection rate of high psychological distress was 38.57%. Compared with students without psychological distress, those with high psychological distress reported significantly less daily outdoor activity (1.24 and 1.45 h/day, respectively) and shorter sleep duration (8.5 and 9.1 h/day, respectively). They also spent significantly more time in sedentary behavior (8.02 and 7.01 h/day, respectively). Replacing 1 h per day of sedentary behavior with the same duration of outdoor activity and sleep is associated with an 18.8% ( P  < 0.001) and 26.8% ( P  < 0.001) reduction in the risk of high psychological distress, respectively. Replacing 1 h per day of outdoor activity or sleep with the same duration of sedentary behavior is associated with a 23.2% ( P  < 0.001) and 36.6% ( P  < 0.001) increase respectively in the risk of high psychological distress. After gender stratification, replacing one hour of daily sedentary behavior with equal-duration outdoor activity or sleep was associated with reduced risk of high psychological distress: 11.5% ( P  = 0.011) and 28.0% ( P  < 0.001) in girls, and 25.8% ( P  < 0.001) and 25.6% ( P  < 0.001) in boys. Replacing one hour per day of outdoor activity or sleep with sedentary behavior was associated with a 13.0% ( P  = 0.010) and 38.8% ( P  < 0.001) increase in girls and a 34.7% ( P  < 0.001) and 34.3% ( P  < 0.001) increase in boys in the risk of high psychological distress, respectively. Therefore, outdoor activity and sleep duration were negatively associated with psychological distress, while sedentary behavior was positively associated with psychological distress among children and adolescents. Reallocating time from sedentary behavior to outdoor activity or sleep was associated with a lower risk of high psychological distress among children and adolescents, with associations differing by sex.

Huayuan Zhang, Xiaoran Yu, Zhiqiang Zong et al. · 0 citations
Review Open access Jul 2026

Artificial intelligence in cardiology: implications for healthcare outcomes

Artificial Intelligence (AI) has the potential to revolutionize medicine, particularly in the field of cardiology. There are significant diagnostics and treatments variabilities in the field of cardiovascular medicine that affects racial and ethnic racially and ethnically diverse populations as well as female patients across all age groups. The efforts put forth towards the development of AI and precision medicine within the cardiovascular practice do not fully account for existing variations in cardiovascular care delivery. AI models and precision medicine tools that were created with uncomprehensive data primarily drawn from White populations risk embedding historical differences into clinical decision-support systems. This paper outlines the integrative approach taken to review the current variabilities that persist within younger adults (<65 years) and older adults (≥ 65 years) who have cardiovascular disease. Additionally, genetic factors, limited access to care, health literacy, lack of insurance coverage and adherence are examined, as these are frequently cited as major contributors to health care adverse outcomes but remain under-researched and unresolved even with the expansion of Medicaid. For instance, Black patients experience higher prevalence of heart failure (HF) and hypertension, especially transthyretin amyloid cardiomyopathy HF, with Black women being disproportionately affected due to higher structural, environmental and clinical factors. Also, racially and ethnically diverse children with CVDs have higher odds of mortality than their White counterparts. The integration of AI in cardiovascular medicine must first be preceded by an active effort to restructure systems and reduce variable outcomes. Future research must prioritize diverse genomic datasets and equitable comprehensive representation in clinical trials. These initiatives are better served if they are driven by institutions that historically serve racially and ethnically diverse populations and communities to better enhance inclusion and fairness in electronic medical record keeping. Accordingly, cardiovascular medical practices and technology can progress forward with AI and precision medicine models that are both equitable and accurate.

Mikayla N. Harris, Parth A. Desai, Eric Yalley et al. · 0 citations

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