Suicidal behavior, depression and loneliness among college students: the role of school belonging.

Suicide among college students, as a subgroup of young people, has received increasing attention in recent years. Exploring the determination of protective and risk factors related to suicide is imperative to understanding the reason for committing suicide and how to take action. We examined loneliness and school belonging as predictors of suicide risk (viz., suicidal behavior and depression) in college students in China by a cross-sectional study. In total, 393 college students participated in the study. The results of hierarchical regression analyses that controlled for age and sex indicated that school belonging buffers the negative effects of loneliness on suicidal behavior and depression. Evidence of a significant loneliness × school belonging interaction as a predictor of both suicidal behavior and depression was found. The present findings show that school belonging represents a positive psychological resource that should be considered in understanding suicide risk among college students in China. More attention should be given to improving the school belonging of college students.

Factors Influencing Self-Management of Schizophrenia: A Cross-Sectional Study.

The purpose of the current study was to (a) understand the influencing factors of self-management in schizophrenia, (b) explore the relationship between social support and self-management, and (c) explore the intermediary role of coping modes between social support and self-management. From May to December 2020, a total of 320 community-dwelling persons with schizophrenia were recruited and completed self-report questionnaires. Spearman's correlation analysis was used to determine the relationship between the three variables and the bootstrap method was used to test the intermediary hypothesis. Results showed that 21.9% of persons with schizophrenia had low social support, 78.1% had medium social support, and convalescent persons with schizophrenia had high social support. Self-management was positively correlated with social support (r = 0.372, p < 0.05), confrontation coping mode (r = 0.576, p < 0.05), and avoidance coping mode (r = 0.204, p < 0.05), and negatively correlated with resignation coping mode (r = -0.057, p < 0.05). Confrontation and avoidance coping modes have a mediating effect between social support and self-management. Mental health nurses should understand the influence of social support and coping modes on self-management, and help persons with schizophrenia find social resources, build confidence, and confront the disorder positively. [Journal of Psychosocial Nursing and Mental Health Services, 61(2), 19-26.].

[Negative symptoms predict the improvement of social functioning of patients with schizophrenia].

OBJECTIVE: To identify predictive factors associated with the improvement of social functioning of schizophrenia patients in a community. METHODS: 101 schizophrenia patients undergoing community rehabilitation were assessed with the Positive and Negative Syndrome Scale (PANSS), Personal and Social Performance Scale (PSP), Self-Esteem Scale (SES), Family Function Questionnaire (APGAR), and the World Health Organization Disability Assessment Scale II (WHODAS-II) twice 6 months apart. Pearson correlation and hierarchical multiple linear regression analyses were performed to identify the influencing and predictive factors associated with the improvement of social functioning. RESULTS: The increase of PSP score was correlated with age (r = 0.220), reduced PANSS negative score (r = 0.468), reduced PANSS general score (r = 0.392), reduced PANSS total score (r = 0.472), and reduced WHODAS-II Score (r = 0.247). The predictive factors of the change of PSP score followed the following order: change of PANSS negative score [the change of coefficient of determination (deltaR2 ) = 0.197], age of onset (deltaR2 = 0.048), change of WHODAS-II score and psychiatric rehabilitation (deltaR2 = 0.031). CONCLUSION: Improvement of negative symptoms predicts the short-term improvement of social functioning of schizophrenia patients.

Applications of Artificial Intelligence in Psychiatric Nursing: A Scope Review.

Rapid advances in artificial intelligence (AI) have reshaped healthcare, including psychiatric nursing, to address the limitations of traditional approaches and meet escalating mental health challenges. A scoping review analyzed 48 articles examining the application of AI in psychiatric nursing across different technologies and topics, noting trends in publications and countries involved. The articles covered different aspects of mental health using AI technologies such as machine learning and robotics, and primarily explored AI applications in mental health, specifically dementia, autism and schizophrenia. These studies highlighted the role of AI in personalized care plans, symptom monitoring and risk assessment. AI is promising, but faces challenges such as data bias and ethical concerns. Future research needs to focus on long-term studies, diverse populations, patient interaction and personalized treatments for practical integration into psychiatric nursing.

Baseline symptom-related white matter tracts predict individualized treatment response to 12-week antipsychotic monotherapies in first-episode schizophrenia.

There is significant heterogeneity in individual responses to antipsychotic drugs, but there is no reliable predictor of antipsychotics response in first-episode psychosis. This study aimed to investigate whether psychotic symptom-related alterations in fractional anisotropy (FA) and mean diffusivity (MD) of white matter (WM) at the early stage of the disorder may aid in the individualized prediction of drug response. Sixty-eight first-episode patients underwent baseline structural MRI scans and were subsequently randomized to receive a single atypical antipsychotic throughout the first 12 weeks. Clinical symptoms were evaluated using the eight "core symptoms" selected from the Positive and Negative Syndrome Scale (PANSS-8). Follow-up assessments were conducted at the 4th, 8th, and 12th weeks by trained psychiatrists. LASSO regression model and cross-validation were conducted to examine the performance of baseline symptom-related alterations FA and MD of WM in the prediction of individualized treatment outcome. Fifty patients completed both clinical follow-up assessments by the 8th and 12th weeks. 30 patients were classified as responders, and 20 patients were classified as nonresponders. At baseline, the altered diffusion properties of fiber tracts in the anterior thalamic radiation, corticospinal tract, callosum forceps minor, longitudinal fasciculi (ILF), inferior frontal-occipital fasciculi (IFOF) and superior longitudinal fasciculus (SLF) were related to the severity of symptoms. These abnormal fiber tracts, especially the ILF, IFOF, and SLF, significantly predicted the response to antipsychotic treatment at the individual level (AUC = 0.828, P < 0.001). These findings demonstrate that early microstructural WM changes contribute to the pathophysiology of psychosis and may serve as meaningful individualized predictors of response to antipsychotics.

Effectiveness of video-based psychiatric rehabilitation for patients with early-phase schizophrenia spectrum: A randomized controlled trial.

AIM: This study aimed to establish a comprehensive set of recovery-oriented rehabilitation programs for individuals with schizophrenia, comparing the efficacy of video-based rehabilitation to traditional face-to-face interventions. The primary objective was to assess whether video-based rehabilitation could serve as a viable alternative for individuals with schizophrenia residing in remote areas. METHODS: A randomized controlled study was used to recruit 80 patients with schizophrenia in a stable post-hospitalization stage following discharge. Participants were categorized into three groups: 24 in the control group, 21 in the face-to-face group, and 35 in the remote group. Assessment parameters included psychiatric symptoms, social skills, family function and self-stigma. RESULTS: A total of 68 participants completed the program. The findings indicated significant differences (p < .05) between the control group and intervention group, particularly in the Positive and Negative Syndrome Scale (PANSS) and the Personal and Social Performance Scale (PSP). CONCLUSIONS: The rehabilitation program, tailored for patients in the early phase of the schizophrenia spectrum, demonstrates both effectiveness and feasibility in enhancing clinical symptoms and social functions. Notably, interventions conducted via video proved to be equally effective as those administered face-to-face.

Brain Structure Measurements Predict Individualized Treatment Outcome of 12-Week Antipsychotic Monotherapies in First-episode Schizophrenia.

BACKGROUND AND HYPOTHESIS: Early prediction of treatment response to antipsychotics in schizophrenia remains a challenge in clinical practice. This study aimed to investigate if brain morphometries including gray matter volume and cortical thickness could serve as potential predictive biomarkers in first-episode schizophrenia. STUDY DESIGN: Sixty-eight drug-naïve first-episode patients underwent baseline structural MRI scans and were subsequently randomized to receive a single antipsychotic throughout the first 12 weeks. Assessments for symptoms and social functioning were conducted by eight "core symptoms" selected from the Positive and Negative Syndrome Scale (PANSS-8) and the Personal and Social performance scale (PSP) multiple times during follow-ups. Treatment outcome was evaluated as subject-specific slope coefficients for PANSS-8 and PSP scores using linear mixed model. LASSO regression model were conducted to examine the performance of baseline gray matter volume and cortical thickness in prediction of individualized treatment outcome. STUDY RESULTS: The study showed that individual brain morphometries at baseline, especially the orbitofrontal, temporal and parietal cortex, pallidum and amygdala, significantly predicted 12-week treatment outcome of PANSS-8 (r[predicted vs observed] = 0.49, P = .001) and PSP (r[predicted vs observed] = 0.40, P = .003) in first-episode schizophrenia. Moreover, the gray matter volume performed better than cortical thickness in the prediction the symptom changes (P = .034), while cortical thickness outperformed gray matter volume in the prediction of outcome of social functioning (P = .029). CONCLUSIONS: These findings provide initial evidence that brain morphometry have potential to be used as prognostic predictors for antipsychotic response in patients, encouraging the future investigation of the translational value of these measures in precision psychiatry.

Disease information disclosure among patients with mental illness and their family members in China.

Objective: The disclosure of mental illness is a first and crucial step in alleviating stigma and promoting mental recovery. However, at present, there is a lack of research on this subject in the Chinese context. Therefore, we conducted this survey among patients with mental illness and their family members and analyzed the influencing factors. Methods: Questionnaires were distributed to qualified patients with mental illness and their family members, who were enrolled from the inpatient departments of two major mental health centers in China. Hierarchical linear regression analysis was used to evaluate the factors affecting the disclosure of disease information by patients with mental illness and their family members. Results: A total of 153 patients and 159 family members were included. The percentages of patients and family members who intended to disclose disease information were 34.6 and 18.2%, respectively. Regarding the benefits of being out (BBO), marital status and the number of hospitalizations explained 13.1% of the variance, and stigma explained 4.3% of the variance. Regarding the reasons for staying in (RSI), marital status and family history of mental illness explained 14.4% of the variance, and stigma explained 14.8% of the variance. In the model predicting the influencing factors of family member disclosure, stigma was a predictor of both BBO and RSI, explaining 8.1 and 8.7% of the variance, respectively. Conclusion: Both patients and their families were more reluctant than willing to disclose. Marital status, number of hospitalizations and family history of mental illness were all influencing factors of patients' intentions to disclose disease information. Stigma is closely related to disclosure intention and plays an important role in the disclosure intentions of patients and their families. This suggests that the disclosure of disease information is complex, and many factors need to be considered. Disclosure guidelines should be tailored to individuals.

Cross-sectional survey of the relationship of symptomatology, disability and family burden among patients with schizophrenia in Sichuan, China.

BACKGROUND: Schizophrenia is a chronic condition that leads to high rates of disability and high levels of family burden but the interactive relationship between these variables remains unclear, particularly in low- and middle-income countries where the vast majority of patients live with their families. AIM: Assess the symptom severity, level of disability, and family burden among clinically stable outpatients with schizophrenia in Sichuan, China. METHODS: A total of 101 clinically stable outpatients with schizophrenia who had a median duration of illness of five years were assessed using the World Health Organization Disability Assessment Scale 2.0 (WHODAS II), the Positive and Negative Syndrome Scale (PANSS) and the Family Adaptation, Partnership, Growth, Affection and Resolve Index scale (APGAR); and their caregivers were surveyed using the Family Burden Interview Schedule (FBIS). RESULTS: Among the 101 patients, 92 lived with their immediate family members, 74 had clinically significant disability, and 73 were unemployed. The level of disability was associated with the severity of symptoms (r=0.50, p<0.001), duration of illnesses (r=0.22, p=0.028), age of onset (r=-0.22, p=0.024) and patients' level of satisfaction with family support (r=-0.30, p=0.020). Disability was also associated with the overall level of family burden (r=0.40, p<0.001), and with several subtypes of family burden: financial burden (r=0.21, p=0.040), the degree of disruption in family routines (r=0.33, p=0.001), the effect on family leisure activities (r=0.31, p=0.001) and the quality of family interactions (r=0.43, p< 0.001). Four variables remained significantly associated with the level of disability in the stepwise multivariate linear regression: duration of illness, severity of symptoms, patient satisfaction with family support, and the overall burden of the illness on the family. CONCLUSIONS: Even after adjusting for the severity of patients' symptoms, patient disability is independently associated with family burden. This highlights the importance of targeting both symptoms and disability in treatment strategies for this severe, often lifelong, condition. In countries like China where most individuals with schizophrenia live with their families, family burden is an important component of the impact of the illness on the community that should be included in measures of the relative social and economic importance of the condition.

The impact of educational status on the clinical features of major depressive disorder among Chinese women.

BACKGROUND: Years of education are inversely related to the prevalence of major depressive disorder (MDD), but the relationship between the clinical features of MDD and educational status is poorly understood. We investigated this in 1970 Chinese women with recurrent MDD identified in a clinical setting. METHODS: Clinical and demographic features were obtained from 1970 Han Chinese women with DSM-IV major depression between 30 and 60 years of age across China. Analysis of linear, logistic and multiple logistic regression models were used to determine the association between educational level and clinical features of MDD. RESULTS: Subjects with more years of education are more likely to have MDD, with an odds ratio of 1.14 for those with more than ten years. Low educational status is not associated with an increase in the number of episodes, nor with increased rates of co-morbidity with anxiety disorders. Education impacts differentially on the symptoms of depression: lower educational attainment is associated with more biological symptoms and increased suicidal ideation and plans to commit suicide. LIMITATIONS: Findings may not generalize to males or to other patient populations. Since the threshold for treatment seeking differs as a function of education there may an ascertainment bias in the sample. CONCLUSIONS: The relationship between symptoms of MDD and educational status in Chinese women is unexpectedly complex. Our findings are inconsistent with the simple hypothesis from European and US reports that low levels of educational attainment increase the risk and severity of MDD.