Association between cognitive insight and anxiety among community-dwelling schizophrenia patients: the chain mediating effects of family cohesion and chronotype.

Objective: To investigate the effect of cognitive insight on anxiety in community-dwelling schizophrenia patients and to construct a chain mediating model to determine the underlying mechanisms of the relationship between cognitive insight and anxiety through family cohesion and chronotype.

Methods: The Beck Cognitive Insight Scale, the Chinese version of the Family Adaptability and Cohesion Scale, the Morningness-Eveningness Scale, and the Generalized Anxiety Disorder Scale were used to assess cognitive insight, family cohesion, chronotype, and anxiety in a sample of 785 individuals with schizophrenia living in the community. Spearman correlation analysis, multiple linear regression and Bootstrap methods were employed to analyze the four variables.

Resting-state functional connectivity of the cerebellum-cerebrum in older women with depressive symptoms.

Background: Although there has been much neurobiological research on major depressive disorder, research on the neurological function of depressive symptoms (DS) or subclinical depression is still scarce, especially in older women with DS.

Objectives: Resting-state functional magnetic resonance imaging (rs-fMRI) was used to compare functional connectivity (FC) between the cerebellum and cerebral in older women with DS and normal controls (NC), to explore unique changes in cerebellar FC in older women with DS.

Methods: In all, 16 older women with DS and 17 NC were recruited.

Meta-analysis of the relationship between bullying and depressive symptoms in children and adolescents.

Childhood and adolescence are critical periods for physical and mental development; thus, they are high-risk periods for the occurrence of mental disorders. The purpose of this study was to systematically evaluate the association between bullying and depressive symptoms in children and adolescents. We searched the PubMed, MEDLINE and other databases to identify studies related to bullying behavior and depressive symptoms in children and adolescents.

A fused biometrics information graph convolutional neural network for effective classification of patellofemoral pain syndrome.

Patellofemoral pain syndrome (PFPS) is a common, yet misunderstood, knee pathology. Early accurate diagnosis can help avoid the deterioration of the disease. However, the existing intelligent auxiliary diagnosis methods of PFPS mainly focused on the biosignal of individuals but neglected the common biometrics of patients.

Comprehensive quality of elderly rehabilitation nursing staff in medical and health care institutions in Liaoning Province, China: a cross-sectional study.

Background: With the global aging problem is becoming increasingly severe, the elderly care has become an important issue that needs attention. Chinese government attaches great importance to the development of medical and health care institutions, and is committed to improving the comprehensive quality of elderly rehabilitation nursing staff in medical and health care institutions.

Methods: From June to September 2019, a cross-sectional study among 193 elderly rehabilitation nursing staff was conducted in Liaoning Province, China.

Determining the Online Measurable Input Variables in Human Joint Moment Intelligent Prediction Based on the Hill Muscle Model.

: Human joint moment is a critical parameter to rehabilitation assessment and human-robot interaction, which can be predicted using an artificial neural network (ANN) model. However, challenge remains as lack of an effective approach to determining the input variables for the ANN model in joint moment prediction, which determines the number of input sensors and the complexity of prediction. : To address this research gap, this study develops a mathematical model based on the Hill muscle model to determining the online input variables of the ANN for the prediction of joint moments.