Background: Many studies have confirmed the existence of an extremely close relationship between smartphone addiction and perceived stress. However, the mediating and moderating mechanisms underlying the association between perceived stress and smartphone addiction in medical college students remain largely unexplored.Methods: A questionnaire was distributed among a total of 769 medical college students in Heilongjiang Province, China. Participants completed measures of perceived stress, smartphone addiction, negative emotions, and psychological capital. Pearson’s correlation analysis was used to test the correlations between variables. The analysis of a moderated mediation model was performed using Hayes’s PROCESS macro.Results: Pearson’s correlation analysis indicated that perceived stress (r = 0.18, p < 0.01) and negative emotions (r = 0.31, p < 0.01) were positively correlated with smartphone addiction, and psychological capital was negatively correlated with smartphone addiction (r = −0.29, p < 0.01). The moderated mediation analysis indicated that negative emotions partially mediated the association between perceived stress and smartphone addiction [mediation effect accounted for 33.3%, SE = 0.10, 95% CI = (0.10, 0.24)], and the first stage of the mediation process was significantly moderated by psychological capital [moderated mediation = −0.01, SE = 0.01, 95% CI = (−0.01, −0.00)].Conclusion: Negative emotions play a mediating role between perceived stress and smartphone addiction, and psychological capital plays an important moderating role in the first stage of the mediation process.

The relationship between selenium (Se) and type 2 diabetes (T2D) remains controversial. In previous animal and cell studies, Se was found to be insulin mimic and antidiabetic, whereas recent epidemiological and interventional trials have shown an unexpected association between high Se intake and increased risk of T2D. The present study aimed to investigate the significance of dietary Se and T2D in North Chinese adults. A large sample of the population was enrolled through cluster sampling in Northern China (N=8824). Information on basic characteristics, anthropometric measures, and dietary Se intake was collected from each subject for analysis. Multivariable logistic regression was used to investigate the association between dietary Se and T2D through adjusted odds ratio (OR) and the corresponding 95% confidence interval (CI). The average nutritional Se intake was 52.43 μg/day, and the prevalence of T2D was 20.4% in the studied population. The OR for developing T2D was 1.66 (95% CI: 1.38, 1.99; P for linear trend <0.005), comparing the highest to the lowest quintile of energy-adjusted Se intake in multivariate logistic regression analysis. The mediation analysis discovered that glucose metabolism (indicated by FBG and HbA1c) mediated this association. In conclusion, our research adds further support to the role of high dietary Se in the incidence of T2D. The results also suggested that this association was mediated by glucose metabolism.

The I-PACE (interaction of person-affect-cognition-execution) model explains that the causes of addiction are the result of individual susceptibility (genetic and personality), psychopathological factors (negative emotions), and cognitive and affective factor interaction. The issue of smartphone addiction and its emerging effects are now becoming an essential social enigma. This study is aimed at exploring how personal, affective, cognitive, and execution factors accelerate the mechanism of smartphone addiction among international students. Randomly selected, six hundred international students have constituted the population for our study. All participants were asked to complete self-administered questionnaires. The questionnaire included demographics (gender, place of stay, educational level, and reason for smartphone usage), Mobile Phone Addiction Index, Loneliness Scale (UCLA), Rosenberg Self-Esteem Scale, Beck Depression Inventory, Perceived Stress Scale, Eysenck Personality Questionnaire, and Simplified Coping Style Questionnaire. Statistical analysis was performed using SPSS. 20.3% (n = 122) of international students are agonized with smartphone addiction, while 79.7% (n = 478) use smartphones at an average level. Students’ place of stay, neuroticism personality, social desirability, self-esteem, loneliness, depression, perceived stress, and passive coping are associated with smartphone addiction. Loneliness and depression show a strong positive significant correlation, among other variables while loneliness, neurotic personality, depression, low self-esteem, stress, and passive coping are risk factors for smartphone addiction. This study reveals that international students are a high-risk group for smartphone addiction. It has a great deal of impact on students’ behavior and psyche. Multiple social, psychological, affective, and cognitive factors affect smartphone addiction. It would be beneficial to direct the students to limit their phone usage and indulge in other healthy physical activities to complete academic goals.

Cardiovascular disease (CVD) is a major complication of type 2 diabetes mellitus (T2DM). In addition to traditional risk factors, psychological determinants play an important role in CVD risk. This study applied Deep Neural Network (DNN) to develop a CVD risk prediction model and explored the bio-psycho-social contributors to the CVD risk among patients with T2DM. From 2017 to 2020, 834 patients with T2DM were recruited from the Department of Endocrinology, Affiliated Hospital of Harbin Medical University, China. In this cross-sectional study, the patients' bio-psycho-social information was collected through clinical examinations and questionnaires. The dataset was randomly split into a 75% train set and a 25% test set. DNN was implemented at the best performance on the train set and applied on the test set. The receiver operating characteristic curve (ROC) analysis was used to evaluate the model performance. Of participants, 272 (32.6%) were diagnosed with CVD. The developed ensemble model for CVD risk achieved an area under curve score of 0.91, accuracy of 87.50%, sensitivity of 88.06%, and specificity of 87.23%. Among patients with T2DM, the top five predictors in the CVD risk model were body mass index, anxiety, depression, total cholesterol, and systolic blood pressure. In summary, machine learning models can provide an automated identification mechanism for patients at CVD risk. Integrated treatment measures should be taken in health management, including clinical care, mental health improvement, and health behavior promotion.

Background: Many studies have confirmed the existence of an extremely close relationship between smartphone addiction and perceived stress. However, the mediating and moderating mechanisms underlying the association between perceived stress and smartphone addiction in medical college students remain largely unexplored.Methods: A questionnaire was distributed among a total of 769 medical college students in Heilongjiang Province, China. Participants completed measures of perceived stress, smartphone addiction, negative emotions and psychological capital. Pearson correlation analysis was used to test correlations between variables. The analysis of moderated mediation model was performed using Hayes’s PROCESS macro. Results: Pearson correlation analysis indicated perceived stress (r = 0.18, p < 0.01) and negative emotions (r = 0.31, p < 0.01) were positively correlated with smartphone addiction, and psychological capital was negatively correlated with smartphone addiction (r = − 0.29, p < 0.01). The moderated mediation analysis indicated that negative emotions partially mediated the association between perceived stress and smartphone addiction (mediation effect accounted for 33.3%, SE = 0.10, 95% CI = [0.10, 0.24]), and the first stage of the mediation process was significantly moderated by psychological capital (moderated mediation = − 0.01, SE = 0.01, 95%CI = [− 0.01, − 0.00]).Conclusions: Negative emotions plays a mediating role between perceived stress and smartphone addiction, and psychological capital plays an important moderating role in the first stage of the mediation process.