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.

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.

Help-Seeking Intentions for Depression from Mental Health Professionals Among Community-Dwelling Persons in Central China.

Understanding the intention of community residents to seek help from mental health professionals (MHPs) is essential in targeting interventions that promote the prevention and treatment of depression. This study aimed to investigate the current status of Chinese community populations' depression help-seeking intentions from MHPs and explore factors influencing the intentions. Data were used from a survey conducted in a city in central China (n = 919 aged 38.68 ± 17.34, 72.1% female). Help-seeking intentions, help-seeking attitude, depression stigma, family function and depressive symptoms were measured. The total mean score on the intent to seek help from MHPs was 11.01 ± 7.78 and most of respondents were unwilling to seek professional help. Multiple linear regression showed that participants who were students, held a positive help-seeking attitude and had low personal stigma were more likely to have the intention to seek help from MHPs. It is necessary to utilize effective interventions to improve community residents' intention to seek professional help. These include promoting the importance of seeking professional assistance, optimizing the quality of mental health services and altering residents' prejudice to seeking professional help.

The relationship between childhood trauma and insomnia among college students with major depressive disorder: Mediation by the role of negative life events and dysfunctional attitudes.

BACKGROUND: Insomnia is a common problem among patients with major depressive disorder (MDD). According to previous studies, the development and severity of Insomnia are influenced by childhood trauma experience. Furthermore, negative life events and dysfunctional attitudes may also mediate the impact. So, this study aimed to examine the association between childhood trauma, negative life events, dysfunctional attitudes and insomnia and investigate how negative life events and dysfunctional attitudes mediate the relationship between childhood trauma and insomnia in MDD. METHOD: This cross-sectional study recruited 621 college students with MDD. The Childhood Trauma Questionnaire (CTQ), Life Event Scale (LES), Dysfunctional Attitude Scale (DAS), Insomnia Severity Index (ISI), and Hamilton Depression Scale-17 (HAMD-17) were used to assess participants' psychosocial factors. Descriptive analysis, Chi-square test, t-test, Pearson correlations, and serial mediation analyses were used in data analysis. In order to eliminate the influence of the severity of depression symptoms, severity of depression symptoms was used as a control variable in this study. RESULTS: There were 166 (26.7%) participants having clinical insomnia (ISI score > 14). After controlling for the effect of severity of depression symptoms, results of serial mediation analyses determined that childhood trauma has a direct (Estimate = 0.109, 95%CI: 0.023,0.190) and indirect (Estimate = 0.090, 95%CI: 0.054,0.137) impact to insomnia. The indirect impact of childhood trauma on insomnia through the pathways of negative life events alone (Estimate = 0.050, 95%CI: 0.024,0.093), dysfunctional attitudes alone (Estimate = 0.027, 95%CI: 0.008,0.050), and negative life events to dysfunctional attitudes (Estimate = 0.013, 95%CI: 0.006,0.024) were significant. CONCLUSIONS: This study demonstrates that screening for childhood trauma should be considered when treating insomnia in college students with MDD. Managing negative life events and dysfunctional attitudes may mitigate the negative impact of childhood trauma on insomnia in college students with MDD.

Suicidal ideation in college students having major depressive disorder: Role of childhood trauma, personality and dysfunctional attitudes.

BACKGROUND: Suicide in college students is a major public health concern. Suicidal ideation (SI) is associated with childhood trauma, personality, dysfunctional attitudes and depressive symptoms, but how they interact to predict SI remains unclear. METHODS: Using cross-sectional design and convenience sampling method, a survey was conducted among 565 college students having major depressive disorder (MDD). The Childhood Trauma Questionnaire, Eysenck Personality Questionnaire, Dysfunctional Attitudes Scale and Hamilton Depression Scale assessed participants' psychosocial factors. Chi-square test, t-test, Pearson correlation, and Structural Equation Model were used in data analysis. RESULTS: Overall, 66.02% of participants with MDD had SI. Those with SI showed significant differences in physical abuse, emotional abuse, physical neglect, emotional neglect, psychoticism, neuroticism, extroversion, dysfunctional attitudes and depressive symptoms compared with those without SI. Childhood trauma, psychoticism, neuroticism, extroversion and dysfunctional attitudes affected SI through chain mediation. In addition, depressive symptoms, psychoticism, neuroticism and extroversion directly affected SI. LIMITATIONS: The convenience sampling method may limit the generalizability of the findings. Results may be biased due to the self-report nature of the data collection procedure, the number of research subjects and differences in suicide risk assessment. The cross-sectional study cannot be used to infer causality. CONCLUSIONS: The factors of childhood trauma, personality and dysfunctional attitudes affect SI through chain mediation. In addition, depressive symptoms and personality independently predict the occurrence of SI.