Risk Prediction Model for Non-Suicidal Self-Injury in Chinese Adolescents with Major Depressive Disorder Based on Machine Learning.

Background: Non-suicidal self-injury (NSSI) is a significant social issue, especially among adolescents with major depressive disorder (MDD). This study aimed to construct a risk prediction model using machine learning (ML) algorithms, such as XGBoost and random forest, to identify interventions for healthcare professionals working with adolescents with MDD. Methods: This study investigated 488 adolescents with MDD. Adolescents was randomly divided into 75% training set and 25% test set to testify the predictive value of risk prediction model. The prediction model was constructed using XGBoost and random forest algorithms. We evaluated the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, accuracy, recall, F Score of the two models for comparing the performance of the two models. Results: There were 161 (33.00%) participants having NSSI. Compared without NSSI, there were statistically significant differences in gender (P=0.035), age (P=0.036), depressive symptoms (P=0.042), sleep quality (P=0.030), dysfunctional attitudes (P=0.048), childhood trauma (P=0.046), interpersonal problems (P=0.047), psychoticism (P) (P=0.049), neuroticism (N) (P=0.044), punishing and Severe (F2) (P=0.045) and Overly-intervening and Protecting (M2) (P=0.047) with NSSI. The AUC values for random forest and XGBoost were 0.780 and 0.807, respectively. The top five most important risk predictors identified by both machine learning methods were dysfunctional attitude, childhood trauma, depressive symptoms, F2 and M2. Conclusion: The study demonstrates the suitability of prediction models for predicting NSSI behavior in Chinese adolescents with MDD based on ML. This model improves the assessment of NSSI in adolescents with MDD by health care professionals working. This provides a foundation for focused prevention and interventions by health care professionals working with these adolescents.

A Social Media-Based Mindfulness Psycho-Behavioral Intervention (MCARE) for Patients With Acute Coronary Syndrome: Randomized Controlled Trial.

BACKGROUND: Psychological distress is common among patients with acute coronary syndrome (ACS) and has considerable adverse impacts on disease progression and health outcomes. Mindfulness-based intervention is a promising complementary approach to address patients' psychological needs and promote holistic well-being. OBJECTIVE: This study aims to examine the effects of a social media-based mindfulness psycho-behavioral intervention (MCARE) on psychological distress, psychological stress, health-related quality of life (HRQoL), and cardiovascular risk factors among patients with ACS. METHODS: This study was a 2-arm, parallel-group randomized controlled trial. We recruited 178 patients (mean age 58.7, SD 8.9 years; 122/178, 68.5% male) with ACS at 2 tertiary hospitals in Jinan, China. Participants were randomly assigned to the MCARE group (n=89) or control group (n=89). The 6-week intervention consisted of 1 face-to-face session (phase I) and 5 weekly WeChat (Tencent Holdings Ltd)-delivered sessions (phase II) on mindfulness training and health education and lifestyle modification. The primary outcomes were depression and anxiety. Secondary outcomes included psychological stress, HRQoL, and cardiovascular risk factors (ie, smoking status, physical activity, dietary behavior, BMI, blood pressure, blood lipids, and blood glucose). Outcomes were measured at baseline (T0), immediately after the intervention (T1), and 12 weeks after the commencement of the intervention (T2). RESULTS: The MCARE group showed significantly greater reductions in depression (T1: ß=-2.016, 95% CI -2.584 to -1.449, Cohen d=-1.28, P<.001; T2: ß=-2.089, 95% CI -2.777 to -1.402, Cohen d=-1.12, P<.001) and anxiety (T1: ß=-1.024, 95% CI -1.551 to -0.497, Cohen d=-0.83, P<.001; T2: ß=-0.932, 95% CI -1.519 to -0.346, Cohen d=-0.70, P=.002). Significantly greater improvements were also observed in psychological stress (ß=-1.186, 95% CI -1.678 to -0.694, Cohen d=-1.41, P<.001), physical HRQoL (ß=0.088, 95% CI 0.008-0.167, Cohen d=0.72, P=.03), emotional HRQoL (ß=0.294, 95% CI 0.169-0.419, Cohen d=0.81, P<.001), and general HRQoL (ß=0.147, 95% CI 0.070-0.224, Cohen d=1.07) at T1, as well as dietary behavior (ß=0.069, 95% CI 0.003-0.136, Cohen d=0.75, P=.04), physical activity level (ß=177.542, 95% CI -39.073 to 316.011, Cohen d=0.51, P=.01), and systolic blood pressure (ß=-3.326, 95% CI -5.928 to -0.725, Cohen d=-1.32, P=.01) at T2. The overall completion rate of the intervention (completing ≥5 sessions) was 76% (68/89). Positive responses to the questions of the acceptability questionnaire ranged from 93% (76/82) to 100% (82/82). CONCLUSIONS: The MCARE program generated favorable effects on psychological distress, psychological stress, HRQoL, and several aspects of cardiovascular risk factors in patients with ACS. This study provides clues for guiding clinical practice in the recognition and management of psychological distress and integrating the intervention into routine rehabilitation practice. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR2000033526; https://www.chictr.org.cn/showprojEN.html?proj=54693.

Prediction of non-suicidal self-injury in adolescents at the family level using regression methods and machine learning.

BACKGROUND: Adolescent non-suicidal self-injury (NSSI) is a major public health issue. Family factors are significantly associated with NSSI in adolescents, while studies on forecasting NSSI at the family level are still limited. In addition to regression methods, machine learning (ML) techniques have been recommended to improve the accuracy of family-level risk prediction for NSSI. METHODS: Using a dataset of 7967 students and their primary caregivers from a cross-sectional study, logistic regression model and random forest model were used to test the forecasting accuracy of NSSI predictions at the family level. Cross-validation was used to assess model prediction performance, including the area under the receiver operator curve (AUC), precision, Brier score, accuracy, sensitivity, specificity, positive predictive value and negative predictive value. RESULTS: The top three important family-related predictors within the random forest algorithm included family function (importance:42.66), family conflict (importance:42.18), and parental depression (importance:27.21). The most significant family-related risk predictors and protective predictors identified by the logistic regression model were family history of mental illness (OR:2.25) and help-seeking behaviors of mental distress from parents (OR:0.65), respectively. The AUCs of the two models, logistic regression and random forest, were 0.852 and 0.835, respectively. LIMITATIONS: The key limitation is that this cross-sectional survey only enabled the authors to examine predictors that were considered to be proximal rather than distal. CONCLUSIONS: These findings highlight the significance of family-related factors in forecasting NSSI in adolescents. Combining both conventional statistical methods and ML methods to improve risk assessment of NSSI at the family level deserves attention.

Relationships between disease severity, psychological stress, and health-related quality of life among patients with acute coronary syndrome: Mediation of illness perception.

AIMS: Patients with acute coronary syndrome (ACS) often experience reduced health-related quality of life (HRQOL), which may be attributable to the disease severity and psychological stress. While illness perception is speculated to be a potential pathway underlying these relationships, evidence supporting this mechanism remains limited. This study aimed to investigate the relationships between disease severity, psychological stress, and HRQOL and whether these relationships are mediated by illness perception in patients with ACS. METHODS AND RESULTS: Data were collected from June to July 2019 and June to September 2020 in the cardiology departments of four public hospitals in China. Eligible patients completed measures of disease severity, psychological stress, illness perception, HRQOL, and sociodemographic and clinical characteristics. Data were analyzed employing hierarchical multiple regression and structural equation modeling. This study included 405 participants (mean age 60.63 years, 67.4% male). After controlling for sociodemographic and clinical covariates, higher levels of disease severity (ß=0.115, P=0.024) and psychological stress (ß=-0.209, P＜0.001) were associated with poorer HRQOL; however, the relationships became non-significant after adding illness perception into the regression model. Structural equation modeling analysis suggested that illness perception played a mediating role between disease severity, psychological stress, and HRQOL, accounting for 45.95% and 65.79% of the total effects, respectively. CONCLUSION: This study found that illness perception mediated the relationships between disease severity, psychological stress, and HRQOL among patients with ACS. Improving patients' HRQOL should consider its important influencing factors with a focus on promoting positive illness perception.

Integrated virtual simulation and face-to-face simulation for clinical judgment training among undergraduate nursing students: a mixed-methods study.

BACKGROUND: Virtual simulation and face-to-face simulation are effective for clinical judgment training. Rare studies have tried to improve clinical judgment ability by applying virtual simulation and face-to-face simulation together. This study aimed to evaluate the effect of an integrated non-immersive virtual simulation and high-fidelity face-to-face simulation program on enhancing nursing students' clinical judgment ability and understanding of nursing students' experiences of the combined simulation. METHODS: A sequential exploratory mixed-methods study was conducted in a nursing simulation center of a university in Central China. Third-year nursing students (n = 122) taking clinical training in ICUs were subsequentially assigned to the integrated non-immersive virtual simulation and high-fidelity face-to-face simulation program arm (n = 61) or the face-to-face simulation-only arm (n = 61) according to the order in which they entered in ICU training. Clinical judgment ability was measured by the Lasater Clinical Judgment Rubric (LCJR). Focus group interviews were conducted to gather qualitative data. RESULTS: Students in both arms demonstrated significant improvement in clinical judgment ability scores after simulation, and students in the integrated arm reported more improvement than students in the face-to-face simulation-only arm. The qualitative quotes provided a context for the quantitative improvement measured by the LJCR in the integrated arm. Most of the quantitative findings were confirmed by qualitative findings, including the domains and items in the LJCR. The findings verified and favored the effect of the combination of non-immersive virtual simulation and high-fidelity face-to-face simulation integrated program on enhancing nursing students' clinical judgment ability. CONCLUSIONS: The integrated virtual simulation and face-to-face simulation program was feasible and enhanced nursing students' self-reported clinical judgment ability. This integrated non-immersive virtual simulation and high-fidelity face-to-face simulation program may benefit nursing students and newly graduated nurses in the ICU more than face-to-face simulation only.

Treatment of allergic rhinitis with asthma by different ways of inhaling corticosteroids / 中华耳鼻咽喉头颈外科杂志

<p><b>OBJECTIVE</b>To observe the therapeutical effect on allergic rhinitis with asthma by different ways of inhaling corticosteroids.</p><p><b>METHODS</b>Ninety patients suffering from allergic rhinitis with asthma were classified into three groups in random and treated with budesonide (BUD) by nasal spray, inhaling and nasal spray-inhaling combined administration for 12 weeks, respectively. The concentration of serum total IgE, eosinophil cationic protein (ECP) and IL-5, pulmonary functions were examined before and after treatment.</p><p><b>RESULTS</b>The improvement of symptom scores of rhinitis and asthma in three groups were significant (P < 0.05). The concentration of serum total IgE, ECP and IL-5 in three groups decreased greatly after treatment (P < 0.05). There were significant improvement in FEV1, FEV1/FVC and FEF25%-75% in inhaling group before and after treatment (P < 0.05): FEV1 from (2.04 +/- 0.45) L to (2.47 +/- 0.54) L, FEV1/FVC from (72.73 +/- 5.59)% to (75.42 +/- 5.94)% and FEF25%-75% from 1.69 +/- 0.52 to 2.06 +/- 0.77. There was also significant improvement in nasal spray-inhaling combined groups before and after treatment (P < 0.05): FEV1 from (2.32 +/- 0.56) L to (2.76 +/- 0.58) L, FEV1/FVC from (73.80 +/- 4.17)% to (76.04 +/- 4.49)% and FEF25%-75% from 2.09 +/- 0.45 to 2.34 +/- 0.64. The significant difference of FEV1 among the three treatment groups was observed (P = 0.041).</p><p><b>CONCLUSIONS</b>The symptoms of rhinitis and asthma in three groups by three ways of inhaling BUD were greatly improved, no significant difference in symptom scores and serum parameters was found.</p>