Child and Adolescent Psychiatry and Mental Health最新文献

Background: Attention-deficit/hyperactivity disorder (ADHD) is diagnosed in accordance with Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition criteria by using subjective observations and information provided by parents and teachers. However, subjective analysis often leads to overdiagnosis or underdiagnosis. There are two types of motor abnormalities in patients with ADHD. First, hyperactivity with fidgeting and restlessness is the major diagnostic criterium for ADHD. Second, developmental coordination disorder characterized by deficits in the acquisition and execution of coordinated motor skills is not the major criterium for ADHD. In this study, a machine learning-based approach was proposed to evaluate and classify 96 patients into ADHD (48 patients, 26 males and 22 females, with mean age: 7y6m) and non-ADHD (48 patients, 26 males and 22 females, with mean age: 7y8m) objectively and automatically by quantifying their movements and evaluating the restlessness scales.

Methods: This approach is mainly based on movement quantization through analysis of variance in patients' skeletons detected in outpatient videos. The patients' skeleton sequence in the video was detected using OpenPose and then characterized using 11 values of feature descriptors. A classification analysis based on six machine learning classifiers was performed to evaluate and compare the discriminating power of different feature combinations.

Results: The results revealed that compared with the non-ADHD group, the ADHD group had significantly larger means in all cases of single feature descriptors. The single feature descriptor "thigh angle", with the values of 157.89 ± 32.81 and 15.37 ± 6.62 in ADHD and non-ADHD groups (p < 0.0001), achieved the best result (optimal cutoff, 42.39; accuracy, 91.03%; sensitivity, 90.25%; specificity, 91.86%; and AUC, 94.00%).

Conclusions: The proposed approach can be used to evaluate and classify patients into ADHD and non-ADHD objectively and automatically and can assist physicians in diagnosing ADHD.

Background: Mental health issues (depression and suicidal ideation) are increasingly common in children and emerge as escalating public health concerns. The syndemics that underline the importance of risk factor clustering provides a framework for intervention, but there is a lack of research on syndemics involving the adverse interactions of children's mental health problems. This study therefore examined the cumulative and synergistic effects of vulnerable conditions on depression and suicidal ideation among children in China.

Methods: A mental health screening census of students in grades 5-12 was conducted from November 2022 to January 2023 in Nanling County, Anhui Province, China. The prevalence and co-occurrence of vulnerable conditions (unfavorable parental marital status, left-behind experience, bullying victimization, and self-harm behavior), depression, and suicidal ideation and the cumulative and synergistic effects of vulnerable conditions on depression and suicidal ideation were explored.

Results: Nearly a quarter of students (24.8%) reported at least two syndemic conditions. Overall, the prevalence of depression and suicidal ideation were 20.2% and 24.2% respectively. The odds of depression and suicidal ideation were higher for children with one or more vulnerable conditions and were ten times higher for children with three or more vulnerable conditions compared with those without any vulnerable condition. These four vulnerable conditions can increase the odds of depression and suicidal ideation by interacting synergistically with each other.

Conclusion: Our findings signal the importance of addressing mental health syndemics among children in China by simultaneously considering concurrent vulnerable conditions.

Background: To reduce psychopathologies in children, various treatment approaches focus on the parent-child relationship. Disruptions in the parent-child relationship are outlined in the most recently revised versions of the Diagnostic Classification of Mental Health and Developmental Disorders of Infancy and Early Childhood (DC:0-3R/DC:0-5). The measures used to assess the parent-child relationship include the Parent-Infant Relationship Global Assessment Scale (PIRGAS) and the Relationship Problems Checklist (RPCL), which cover, e.g., essential concepts like over- or underinvolvement of the caregiver. However, not much is known about the cross-sectional and predictive value of PIRGAS and RPCL scores at admission to discharge, namely whether changes in these scores are correlated with child and maternal psychopathologies and changes through treatment.

Methods: Based on clinical records of 174 preschool-aged children of the Family Day Hospital, we report related basic descriptive data and changes from admission to discharge for the parent-child relationship, child behaviour, and maternal psychopathology. We used a Pearson correlation or a point-biserial correlation to describe the associations and performed a paired t-test to examine differences before and after measurement.

Results: Our results show overall improvements in our parent-child relationship measures and in child and maternal psychopathology. However, we observed little or no correlation between the parent-child relationship measures and child or maternal psychopathology.

Conclusions: We highlight potential drawbacks and limitations of the two relationship measures used that may explain the results of this study on the associations between the variables assessed. The discussion emphasizes the assessment of DC:0-3R/DC:0-5, which are popular in clinical practice for economic reasons.

Aims: This two-wave, longitudinal study aimed to examine the potential moderating and mediating effects of resilience on the association between perceived school bullying and psychotic-like experiences among Chinese sexual minority adolescents.

Methods: A total of 4192 senior high students were included and 984 (23.5%) of them were identified as a sexual minority (mean age = 16.68 years, SD = 0.71). Participants completed two online surveys during April 21 to May 12, 2021 and December 17 to 26, 2021, respectively, as well as completed self-report measures of sample characteristics, perceived school bullying, resilience, and psychotic-like experiences (including two dimensions: delusional experiences and hallucinatory experiences).

Results: Perceived school bullying and resilience were associated with psychotic-like experiences in sexual minority adolescents. Resilience mediated the relationship between perceived school bullying and subsequent psychotic-like experiences (b = 0.03, 95% CI = 0.01 ~ 0.04)/ delusional experiences (b = 0.03, 95% CI = 0.01 ~ 0.04)/ hallucinatory experiences (b = 0.02, 95% CI = 0.01 ~ 0.03). Additionally, resilience only moderated the associations of perceived school bullying with hallucinatory experiences (b = -0.06, 95% CI = -0.12 ~ -0.01).

Conclusions: These findings indicated that resilience plays a crucial role in mediating or moderating the relationship between perceived school bullying and psychotic-like experiences. Assessing and reducing school bullying, as well as promoting resilience, may have important clinical implications for reducing the risk of psychotic-like experiences in sexual minority adolescents.

Background: Adolescent suicides are more likely to form clusters than those of other age groups. However, the definition of a cluster in the space-time dimension has not been established, neither are the factors contributing to it well known. Therefore, this study aimed to identify space-time clusters in adolescent suicides in Korea and to examine the differences between clustered and non-clustered cases using novel statistical methods.

Methods: From 2016 to 2020, the dates and locations, including specific addresses from which the latitude and longitude of all student suicides (aged 9-18 years) in Korea were obtained through student suicide reports. Sociodemographic characteristics of the adolescents who died by suicide were collected, and the individual characteristics of each student who died by suicide were reported by teachers using the Strengths and Difficulties Questionnaire (SDQ). Density-Based Spatial Clustering of Applications with Noise (DBSCAN) analysis was used to assess the clustering of suicides.

Results: We identified 23 clusters through the data analysis of 652 adolescent suicides using DBSCAN. By comparing the size of each cluster, we identified 63 (9.7%) spatiotemporally clustered suicides among adolescents, and the temporal range of these clusters was 7-59 days. The suicide cluster group had a lower economic status than the non-clustered group. There were no significant differences in other characteristics between the two groups.

Conclusion: This study has defined the space-time cluster of suicides using a novel statistical method. Our findings suggest that when an adolescent suicide occurs, close monitoring and intervention for approximately 2 months are needed to prevent subsequent suicides. Future research using DBSCAN needs to involve a larger sample of adolescents from various countries to further corroborate these findings.