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Effects of Digital Sleep Interventions on Sleep Among College Students and Young Adults: Systematic Review and Meta-Analysis

Effects of Digital Sleep Interventions on Sleep Among College Students and Young Adults: Systematic Review and Meta-Analysis

Digital sleep interventions demonstrated a significant medium effect on sleep efficiency (Hedges g=0.62, 95% CI 0.18-1.05; P=.005; I2=60%), with substantial heterogeneity among studies. However, nonsignificant effects were observed for NWAK (P=.27), TST (P=.07), and WASO (P=.18). The detailed results are provided in Figure 4 [42,45,49,50]. Although sleep parameters are crucial outcomes, the certainty of the evidence ranged from “very low” to “low” (Table S1 in Multimedia Appendix 4).

Yi-An Lu, Hui-Chen Lin, Pei-Shan Tsai

J Med Internet Res 2025;27:e69657

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Large Language Models and Artificial Neural Networks for Assessing 1-Year Mortality in Patients With Myocardial Infarction: Analysis From the Medical Information Mart for Intensive Care IV (MIMIC-IV) Database

Large Language Models and Artificial Neural Networks for Assessing 1-Year Mortality in Patients With Myocardial Infarction: Analysis From the Medical Information Mart for Intensive Care IV (MIMIC-IV) Database

Calibration was considered optimal when the calibration curve was close to the diagonal line, reflected by an observed-to-expected ratio near 1 [14], and the Hosmer-Lemeshow test showed a P value greater than .05. The precision-recall curve was also used to compare different models in the highly skewed data set, addressing the optimism of the ROC curve [15].

Boqun Shi, Liangguo Chen, Shuo Pang, Yue Wang, Shen Wang, Fadong Li, Wenxin Zhao, Pengrong Guo, Leli Zhang, Chu Fan, Yi Zou, Xiaofan Wu

J Med Internet Res 2025;27:e67253

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Population-Wide Depression Incidence Forecasting Comparing Autoregressive Integrated Moving Average and Vector Autoregressive Integrated Moving Average to Temporal Fusion Transformers: Longitudinal Observational Study

Population-Wide Depression Incidence Forecasting Comparing Autoregressive Integrated Moving Average and Vector Autoregressive Integrated Moving Average to Temporal Fusion Transformers: Longitudinal Observational Study

Among stable periods, t tests comparing the SMAPE of these 4 models (Figure 3) showed that the average SMAPE at 11.6% for multivariate TFT was significantly lower than the SMAPE for univariate TFT at 13.2% (P=.01), for VARIMA at 16.4% (P=.002), and for ARIMA at 14.8% (P=.003) of the same data. Univariate TFT also outperformed VARIMA (P=.03), while there was no significant difference between VARIMA and ARIMA.

Deliang Yang, Yiyi Tang, Vivien Kin Yi Chan, Qiwen Fang, Sandra Sau Man Chan, Hao Luo, Ian Chi Kei Wong, Huang-Tz Ou, Esther Wai Yin Chan, David Makram Bishai, Yingyao Chen, Martin Knapp, Mark Jit, Dawn Craig, Xue Li

J Med Internet Res 2025;27:e67156

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Diagnosis of Sarcopenia Using Convolutional Neural Network Models Based on Muscle Ultrasound Images: Prospective Multicenter Study

Diagnosis of Sarcopenia Using Convolutional Neural Network Models Based on Muscle Ultrasound Images: Prospective Multicenter Study

Statistical significance was set at 2-sided P We enrolled a total of 357 participants (median age 67.00, IQR, 63.00-72.00 years), including 101 participants with sarcopenia (608 ultrasound images) and 256 participants without sarcopenia (2127 ultrasound images), in the training and internal validation cohort.

Zi-Tong Chen, Xiao-Long Li, Feng-Shan Jin, Yi-Lei Shi, Lei Zhang, Hao-Hao Yin, Yu-Li Zhu, Xin-Yi Tang, Xi-Yuan Lin, Bei-Lei Lu, Qun Wang, Li-Ping Sun, Xiao-Xiang Zhu, Li Qiu, Hui-Xiong Xu, Le-Hang Guo

J Med Internet Res 2025;27:e70545

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Online Health Information–Seeking Behaviors Among the Chongqing Population: Cross-Sectional Questionnaire Study

Online Health Information–Seeking Behaviors Among the Chongqing Population: Cross-Sectional Questionnaire Study

Statistical significance was set to a P value of The demographic characteristics of the study sample are listed in Table 1. In total, 67.1% (9704/14,466) of the participants had OHIS experience. The average age was 46.2 (SD 18.0) years, while approximately half (51.8%, 7495/14,466) of the participants were younger than 45 years. More than half (52.0%, 7520/14,466) of the participants were female. Most participants (95.3%, 13,793/14,466) were of Han Chinese ethnicity.

Honghui Rong, Lu Lu, Miao He, Tian Guo, Xian Li, Qingliu Tao, Yixin Li, Chuanfen Zheng, Ling Zhang, Fengju Li, Dali Yi, Enyu Lei, Ting Luo, Qinghua Yang, Ji-an Chen

JMIR Form Res 2025;9:e56028

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