Multimodal artificial intelligence and online learning in youth mental health: a scoping review [0.03%]
多模态人工智能与青年心理健康在线学习：系统综述研究
Michael S Ramirez Campos,Kamal Barati,Reza Samavi et al.
Michael S Ramirez Campos et al.
Youth mental health-related problems and disorders have garnered increased attention due to global prevalence estimates that have, in some cases, increased following the COVID-19 pandemic. Various methodologies have been proposed to leverag...
Predictors of depression outcomes among university students following brief smartphone-based interventions [0.03%]
面向大学生的简短手机干预后抑郁预后的预测因素
Xuanchen Liu,WuYi Zheng,Leonard Hoon et al.
Xuanchen Liu et al.
Smartphone-delivered interventions offer a scalable solution for university students experiencing depression, yet outcomes remain inconsistent. This study examined predictors of depression remission and response in the AI-enhanced Vibe Up a...
Testing bidirectional associations of major depressive disorder with medical conditions: two-sample Mendelian randomization study [0.03%]
双向孟德尔随机化研究抑郁症与医疗状况的关联性
Yu Fang,Srijan Sen,Gita A Pathak et al.
Yu Fang et al.
Depression is associated with increased risk for a variety of medical conditions. However, the extent to which these associations reflect a causal impact of depression on medical conditions, or vice-versa, remains unresolved. We tested bidi...
Syndemics of complex risk factors in adolescents: findings from the youth risk behavior survey, 2021 [0.03%]
2021年青少年行为风险调查中复杂危险因素的 syndemic 现象研究
Ashley V Hill,Morgan J Grant,Jamilia Blake et al.
Ashley V Hill et al.
Syndemic theory posits that multiple, interconnected health behaviors-such as substance use, anxiety, depression, sexual risk behaviors, and societal or social stressors-interact synergistically within specific populations, particularly in ...
A systematic review on mindfulness-based immersive interventions in depressive disorders [0.03%]
正念沉浸式干预在抑郁障碍中的系统综述
Peng Tan,Yuqi Wu,Xinrong Chen et al.
Peng Tan et al.
Depressive disorders are characterized by persistent negative affect, rumination, and impaired emotion regulation, contributing substantially to global disease burden. As recurrent rumination and negative attentional biases are central cogn...
Exploratory characterization of gut microbiota and cognitive profiles in adolescents with subthreshold depression: a shotgun metagenomics sequencing study [0.03%]
青少年亚临床抑郁患者肠道微生物组及认知特征的探究性研究：宏基因组鸟枪法测序分析
Runhua Wang,Rong Ma,Yuanyuan Cai et al.
Runhua Wang et al.
Subthreshold depression (SD) in adolescents is a prevalent condition associated with significant functional impairment and an increased risk of developing major depressive disorder. Currently, the lack of reliable objective markers complica...
Dynamic bidirectional relationships between perceived stress and emotion regulation in emergency medical service clinicians [0.03%]
急诊医学临床医师感知压力与情绪调节的动态双向关系
Enzo G Plaitano,Madelyn R Frumkin,Nicholas C Jacobson et al.
Enzo G Plaitano et al.
Emergency medical services (EMS) clinicians are first responders who experience recurrent occupational stressors. Cross-sectional research suggests that higher self-regulation of emotions may be related to lower stress, especially in indivi...
A multi-omics analysis of gut bacteriome, virome, and serum metabolome in bipolar depression [0.03%]
联合分析肠道菌群、病毒和血清代谢组在双相情感障碍中的作用
Lingzhuo Kong,Yifan Zhuang,Boqing Zhu et al.
Lingzhuo Kong et al.
The involvement of microbiota-gut-brain axis in bipolar disorder (BD) has been uncovered, yet the specific tripartite interplay between the gut bacteriome, virome, and serum metabolome remains to be elucidated. We conducted a cross-sectiona...
Mark Deady,Daniel A J Collins,Aimee Gayed et al.
Mark Deady et al.
Aged care staff are exposed to workplace risk factors that have the potential to considerably impact mental health. This study aimed to explore mental ill health, burnout, and associated occupational factors in a nationwide sample of reside...
Navigating the complexity of AI adoption in psychotherapy by identifying key facilitators and barriers [0.03%]
识别关键促进因素和障碍以应对心理治疗中AI采纳的复杂性
Julia Cecil,Insa Schaffernak,Danae Evangelou et al.
Julia Cecil et al.
Artificial intelligence (AI) technologies in mental healthcare offer promising opportunities to reduce therapists' burden and enhance healthcare delivery, yet adoption remains challenging. This study identified key facilitators and barriers...