Study of item text in the Chinese Symptom Checklist-90

Mental health status among children and adolescents in one-child and multichild families: a meta-analysis of comparative studies

PURPOSE OF REVIEW

Controversy remains about the difference in mental health status among children and adolescents between one-child and multichild families in China. Thus, we conducted a meta-analysis of studies comparing mental health status between both groups and explored their potential moderating factors.

RECENT FINDINGS

Totally, 113 eligible studies encompassing 237 899 participants (one-child families: 83 125; multichild families: 154 774) were included. The pooled SMD of SCL-90 total score was -0.115 [95% confidence interval (95% CI): -0.152; -0.078; I2  = 86.9%]. Specifically, children and adolescents from one-child families exhibited lower scores in terms of somatization (SMD = -0.056; 95% CI: -0.087; -0.026), obsessive-compulsive symptoms (SMD = -0.116; 95% CI: -0.154; -0.079), interpersonal sensitivity (SMD = -0.140; 95% CI: -0.171; -0.109), depression (SMD = -0.123; 95% CI: -0.159; -0.088); anxiety (SMD = -0.121; 95% CI: -0.151; -0.092); phobic anxiety (SMD = -0.124; 95% CI: -0.166; -0.081); paranoid ideation (SMD = -0.040; 95% CI: -0.070; -0.009); and psychoticism (SMD = -0.119; 95% CI: -0.148; -0.089). Study publication year was significantly associated with differences in mental health status between both groups ( P  = 0.015).

SUMMARY

Children and adolescents from one-child families had better mental health status compared to those from multichild families in China. Future studies should investigate the underlying factors contributing to such mental health differences, and the potential interventions that could address these mental health problems.

Gender differences in the prevalence and impact factors of adolescent dissociative symptoms during the coronavirus disease 2019 pandemic

The purpose of this study was to explore the differences between the prevalence and impact factors of adolescent dissociative symptoms (ADSs) by using sex-stratification during the coronavirus disease 2019 (COVID-19) pandemic. A school-based, two-center cross-sectional study was conducted in Hangzhou City, China, between January 1, 2021 and April 30, 2022. The sample included 1,916 adolescents aged 13-18 years that were randomly selected using a multiphase, stratified, cluster sampling technique. A two-stage assessment procedure was used to find out the ADSs. We used a multivariate logistic regression analysis to assess the impact factors of ADSs during the COVID-19 pandemic. The adolescent dissociative scores (t = 4.88, P < 0.001) and positive ADSs rate (Chi-square = 15.76, P < 0.001) in males were higher than in females. Gender-stratified, stepwise multiple logistic regression analysis revealed that the conflict relationship of teacher-student [adjusted odds ratio (AOR) 1.06, 95% confidence interval (CI) 1.01-1.10], family expressiveness (AOR 0.87, 95% CI 0.78-0.98), family conflict (AOR 1.15, 95% CI 1.05-1.27), family organization (AOR 0.88, 95% CI 0.78-0.99), and family cohesion (AOR 0.87, 95% CI 0.77-0.99) were linked to ADSs only in males, while individual psychological states of somatic complaint (AOR 1.04, 95% CI 1.00-1.08) and paranoid ideation (AOR 1.09, 95% CI 1.01-1.19) were associated with female ADSs only. The ADSs seemed to be prevalent in Hangzhou City, studied during the COVID-19 pandemic. Gender differences in the prevalence and impact factors of dissociative symptoms seem to be significant among adolescents. Thus, gender-specific intervention programs against ADSs should be considered as reducing this risk.

Development and validation of a prediction model for depression in adolescents with polycystic ovary syndrome: A study protocol

Introduction

The high prevalence and severity of depression in adolescents with polycystic ovary syndrome (PCOS) is a critical health threat that must be taken seriously. The identification of high-risk groups for depression in adolescents with PCOS is essential to preventing its development and improving its prognosis. At present, the routine screening of depression in adolescents with PCOS is mainly performed using scales, and there is no early identification method for high-risk groups of PCOS depression in adolescents. It is necessary to use a warning model to identify high-risk groups for depression with PCOS in adolescents.

Methods and analysis

Model development and validation will be conducted using a retrospective study. The study will involve normal adolescent girls as the control group and adolescent PCOS patients as the experimental group. We will collect not only general factors such as individual susceptibility factors, biological factors, and psychosocial environmental factors of depression in adolescence, but will also examine the pathological factors, illness perception factors, diagnosis and treatment factors, and symptom-related factors of PCOS, as well as the outcome of depression. LASSO will be used to fit a multivariate warning model of depression risk. Data collected between January 2022 and August 2022 will be used to develop and validate the model internally, and data collected between September 2022 and December 2022 will be used for external validation. We will use the C-statistic to measure the model's discrimination, the calibration plot to measure the model's risk prediction ability for depression, and the nomogram to visualize the model.

Discussion

The ability to calculate the absolute risk of depression outcomes in adolescents with PCOS would enable early and accurate predictions of depression risk among adolescents with PCOS, and provide the basis for the formulation of depression prevention and control strategies, which have important theoretical and practical implications.

Trial registration number

[ChiCTR2100050123]; Pre-results.

Effect of a group-based acceptance and commitment therapy program on the mental health of clinical nurses during the COVID-19 sporadic outbreak period

Aim

To develop and implement of a group‐based acceptance and commitment therapy programme in helping clinical nurses with mental health problems during the sporadic COVID‐19 outbreak period.

Background

In the face of the continuing COVID‐19 pandemic, clinical nurses have a high risk of mental health issues.

Methods

A quasi‐experimental design was used. Two hundred twenty‐six nurses were recruited from four general hospitals to receive 10 sessions of acceptance and commitment therapy programme. The Symptom Checklist‐90, Perceived Stress Scale and Connor–Davidson Resilience Scale were used to assess nurses' mental health symptom, perceived stress and psychological resilience at pre‐intervention and 4‐week post‐intervention.

Results

The mean attendance sessions was 5.78. The Symptom Checklist‐90 score was significantly lower at post‐intervention than pre‐intervention (P < 0.01), and there were no significant changes of perceived stress and psychological resilience. There were significant correlations among the changed rates of mental health, perceived stress and psychological resilience (P < 0.01).

Conclusion

The acceptance and commitment therapy programme was effective in relieving mental health symptoms for clinical nurses and could protect clinical nurses' perceived stress and psychological resilience. However, a randomized controlled trial is needed to confirm the findings.

Implication for Nursing Management

To facilitate clinical nurses' psychological health in crisis situation, nursing management team should provide and allocated appropriate resources to support the healthcare providers.

Relationships Between Depressive Symptoms, Interpersonal Sensitivity and Social Support of Employees Before and During the COVID-19 Epidemic: A Cross-lag Study

This study examined the correlation between depressive symptoms, interpersonal sensitivity, and social support before and during the COVID-19 pandemic and verified causal relationships among them. The study used Social Support Scale and Symptom Self-Rating Scale to investigate relevant variables. A total of 1,414 employees from company were recruited for this longitudinal study, which a follow up study was conducted on the same group of participants 1 year later. Paired sample t-test results showed that significant differences were only found in social support, not in depressive symptoms or interpersonal sensitivity. The results of correlation analysis showed that social support, depressive symptoms, and interpersonal sensitivity were significantly correlated between wave 1 and wave 2. The cross-lag autoregressive pathway showed that employees’ social support level, depressive symptoms, and interpersonal sensitivity all showed moderate stability. Crossing paths showed that wave 1 social support could significantly predict wave 2 depressive symptoms (β = −0.21, p < 0.001) and wave 2 interpersonal sensitivity (β = −0.21, p < 0.001). Wave 1 depressive symptoms (β = −0.10, p < 0.01) could significantly predict wave 2 social support, while wave 1 interpersonal sensitivity (β = 0.07, p = 0.10) could not predict wave 2 social support. Social support can be considered as a protective factor against mental health problems.

The potency of psychiatric questionnaires to distinguish major mental disorders in Chinese outpatients

BACKGROUND

Considering the huge population in China, the available mental health resources are inadequate. Thus, our study aimed to evaluate whether mental questionnaires, serving as auxiliary diagnostic tools, have efficient diagnostic ability in outpatient psychiatric services.

METHODS

We conducted a retrospective study of Chinese psychiatric outpatients. Altogether 1,182, 5,069, and 4,958 records of Symptom Checklist-90 (SCL-90), Hamilton Anxiety Rating Scale (HAM-A), and Hamilton Depression Rating Scale (HAM-D), respectively, were collected from March 2021 to July 2022. The Mann-Whitney U test was applied to subscale scores and total scores of SCL-90, HAM-A, and HAM-D between the two sexes (male and female groups), different age groups, and four diagnostic groups (anxiety disorder, depressive disorder, bipolar disorder, and schizophrenia). Kendall's tau coefficient analysis and machine learning were also conducted in the diagnostic groups.

RESULTS

We found significant differences in most subscale scores for both age and gender groups. Using the Mann-Whitney U test and Kendall's tau coefficient analysis, we found that there were no statistically significant differences in diseases in total scale scores and nearly all subscale scores. The results of machine learning (ML) showed that for HAM-A, anxiety had a small degree of differentiation with an AUC of 0.56, while other diseases had an AUC close to 0.50. As for HAM-D, bipolar disorder was slightly distinguishable with an AUC of 0.60, while the AUC of other diseases was lower than 0.50. In SCL-90, all diseases had a similar AUC; among them, bipolar disorder had the lowest score, schizophrenia had the highest score, while anxiety and depression both had an AUC of approximately 0.56.

CONCLUSION

This study is the first to conduct wide and comprehensive analyses on the use of these three scales in Chinese outpatient clinics with both traditional statistical approaches and novel machine learning methods. Our results indicated that the univariate subscale scores did not have statistical significance among our four diagnostic groups, which highlights the limit of their practical use by doctors in identifying different mental diseases in Chinese outpatient psychiatric services.