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Nonpharmacological Multimodal Interventions for Cognitive Functions in Older Adults With Mild Cognitive Impairment: Scoping Review

Nonpharmacological Multimodal Interventions for Cognitive Functions in Older Adults With Mild Cognitive Impairment: Scoping Review

.001; VFT-Categoryam: mean difference 2.81, P=.23) PT only ATT (SCWT) GC (ACEan and MMSEao) ME (ACE and AVLT) PS (DRT-IIap) VF (ACE) ATT (SCWT: η2=0.0001, P=.97) GC (ACE: Cohen d=0.71, P=.002; MMSE: η2=0.189, P=.001) ME (ACE: Cohen d=0.64, P=.007; AVLT: η2=0.173, P=.001) PS (DRT-II: η2=0.033, P=.11) VF (Cohen d=0.73, P=.001) HEaq ATT (TMT-A and TMT-B) GC (ADAS-Cog and KMMSEar) PS (DSST) Group×time interaction ATT—TMT-A: P GC (ADAS-Cog: P=.11); KMMSE (P=.72) PS (P=.02) CT only EF (EFPT-Kas and FABat) EF (EFPT-K:

Raffy Chi-Fung Chan, Joson Hao-Shen Zhou, Yuan Cao, Kenneth Lo, Peter Hiu-Fung Ng, David Ho-Keung Shum, Arnold Yu-Lok Wong

JMIR Aging 2025;8:e70291

Clinical Laboratory Parameter–Driven Machine Learning for Participant Selection in Bioequivalence Studies Among Patients With Gastric Cancer: Framework Development and Validation Study

Clinical Laboratory Parameter–Driven Machine Learning for Participant Selection in Bioequivalence Studies Among Patients With Gastric Cancer: Framework Development and Validation Study

To compensate for the aperiodicity of the data, the distribution of data points was increased by computing a simple combination method as follows: C(n,k)=P(n, k)k!=n!(n−k)!k! (1) where P indicates the permutation function, n is the number of data points, and k is the number of selected sequential data points (4 in this study).

Byungeun Shon, Sook Jin Seong, Eun Jung Choi, Mi-Ri Gwon, Hae Won Lee, Jaechan Park, Ho-Young Chung, Sungmoon Jeong, Young-Ran Yoon

JMIR AI 2025;4:e64845

Readdressing the Ongoing Challenge of Missing Data in Youth Ecological Momentary Assessment Studies: Meta-Analysis Update

Readdressing the Ongoing Challenge of Missing Data in Youth Ecological Momentary Assessment Studies: Meta-Analysis Update

Similarly, standardized residuals larger than the 100×(1−0.05/(2×k))th percentile of a standard normal distribution indicated outliers [63]. Expecting widespread missingness across reported variables, we conducted separate meta-regressions with single predictors.

Konstantin Drexl, Vanisha Ralisa, Joëlle Rosselet-Amoussou, Cheng K Wen, Sébastien Urben, Kerstin Jessica Plessen, Jennifer Glaus

J Med Internet Res 2025;27:e65710