BMC Psychiatry最新文献

{"title":"The global burden of depression in adolescents and young adults, 1990-2021: systematic analysis of the global burden of disease study.","authors":"Zhuo Liu, Mengni Kuai","doi":"10.1186/s12888-025-07201-8","DOIUrl":"10.1186/s12888-025-07201-8","url":null,"abstract":"<p><strong>Background: </strong>Depression is a leading cause of disability among adolescents and young adults, yet comprehensive assessments of its global burden and associated risk factors in this population remain limited. This study aimed to evaluate the global, regional, and national trends in depression burden among individuals under 30 years of age from 1990 to 2021, and to identify key risk factors and disparities.</p><p><strong>Methods: </strong>We analyzed data from the Global Burden of Disease Study 2021, focusing on depression incidence and disability-adjusted life years (DALYs) among individuals aged under 30. Temporal trends were assessed using an age-period-cohort (APC) model. We further examined trends using estimated annual percentage change (EAPC), frontier analysis, and inequality metrics to provide a comprehensive evaluation.</p><p><strong>Results: </strong>From 1990 to 2021, both the incidence of depression and related DALYs in individuals under 30 increased by over 50%. Males experienced a larger proportional increase, although females had an age-standardized incidence rate (ASIR) 23 times higher than males in 2021. The highest burden was observed in the 20-24 age group, while the fastest growth occurred among those aged 15-19. Individuals born after 2000 showed a higher prevalence of depression. High sociodemographic index (SDI) regions-particularly high-income North America and Greenland-had the highest ASIR and age-standardized DALY rate (ASDR). The most prominent risk factors were bullying victimization (61.8%), childhood sexual abuse (12.0%), and intimate partner violence (12.6%). Notable regional disparities were observed, with countries like Switzerland, Norway, Monaco, and Germany showing rapid increases in depression burden.</p><p><strong>Conclusions: </strong>The burden of depression among young people has risen substantially over the past three decades, with disproportionate impacts on females, post-2000 birth cohorts, and those in high-SDI regions. Interventions targeting modifiable risk factors-particularly bullying, childhood abuse, and intimate partner violence-are essential to reduce the burden. Tailored, region-specific strategies are necessary to effectively address disparities and improve mental health outcomes in youth.</p>","PeriodicalId":9029,"journal":{"name":"BMC Psychiatry","volume":"25 1","pages":"767"},"PeriodicalIF":3.4,"publicationDate":"2025-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12326784/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144793317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genetically proxied glucagon-like peptide-1 receptor perturbation and risk of mood disorders: a Mendelian randomization study.","authors":"Yaejin Jeon, Ju Han Kim","doi":"10.1186/s12888-025-07152-0","DOIUrl":"10.1186/s12888-025-07152-0","url":null,"abstract":"<p><strong>Background: </strong>Glucagon-like peptide-1 receptor (GLP1R) agonists have gained attention for their role in diabetes treatment along with their diverse effects, such as appetite suppression, suggesting potential psychiatric benefits. This study aimed to assess the effect of GLP1R perturbation on mood disorders based on protein and biomarker levels using Mendelian randomization (MR) approach.</p><p><strong>Methods: </strong>We conducted two-sample MR using summary statistics for GLP1R plasma levels (n = 3,301) from the INTERVAL study, glycated hemoglobin (HbA1c) levels (n = 128,610) from the Meta-Analyses of Glucose and Insulin-related traits Consortium, and bipolar disorder (BD: 371 cases/360,823 controls) and major depressive disorder (MDD: 776 cases/360,418 controls) incidences from the UK Biobank. Genetic variants associated with the plasma levels of GLP1R and HbA1c were used as proxies for the variation in GLP1R.</p><p><strong>Results: </strong>GLP1R level was significantly associated with a reduced risk of MDD (odds ratio [OR] = 0·9988, 95% confidence interval [CI] = 0·9978-0·9999, P = 0·0291) and of BD (OR = 0·9990, 95% CI = 0·9982-0·9998, P = 0·0182). GLP1R's HbA1c level-lowering effect was significantly associated with a decreased risk of BD (OR = 0·9786, 95% CI = 0·9613-0·9962, P = 0·0175) but not with MDD.</p><p><strong>Conclusions: </strong>GLP1R perturbation may have protective effects on MDD and BD through different mechanisms, although additional clinical trials are required to determine the therapeutic implications.</p><p><strong>Trial registration: </strong>Clinical trial number not applicable.</p>","PeriodicalId":9029,"journal":{"name":"BMC Psychiatry","volume":"25 1","pages":"768"},"PeriodicalIF":3.4,"publicationDate":"2025-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12330103/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144793315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association between the number of children and depression in the population aged 50 years and older: a multi-national cross-sectional analysis.","authors":"Jinming Zhang, Penghui Feng, Xingtong Chen, Jiaming Wu, Falin He","doi":"10.1186/s12888-025-07206-3","DOIUrl":"10.1186/s12888-025-07206-3","url":null,"abstract":"<p><strong>Background: </strong>Few studies have explored the relationship between the number of children and depression in older adults, especially across multiple countries.</p><p><strong>Methods: </strong>In this Multi-National Cross-Sectional Analysis, we included the Health and Retirement Study (HRS, US), the English Longitudinal Study of Ageing (ELSA), the Survey of Health, Ageing and Retirement in Europe (SHARE), the Chinese Longitudinal Healthy Longevity Survey (CLHLS), the Korean Longitudinal Study of Aging (KLoSA), and the Longitudinal Aging Study in India (LASI), encompassing a total of 20 countries. The number of children was based on self-reports from the participants. The Center for Epidemiologic Studies Depression Scale (CESD) and the European Depression Scale (EURO-D) were used to assess depression. Logistic regression was used to evaluate the relationship between the number of children and depression, adjusting for potential confounders. A random-effects meta-regression model was used to examine differences in the relationship between the number of children and depression between Asian and Western countries. To explore potential non-linear relationships, restricted cubic spline (RCS) curves were utilized, and threshold effect analyses were performed to validate. Additionally, subgroup analyses were stratified by age, sex, and marital status.</p><p><strong>Results: </strong>A total of 110,015 participants from six datasets were included. The prevalence of depressive symptoms ranged from 10.7% in the UK to 48.8% in Poland. Childlessness was most common in ELSA (15.8%), followed by SHARE (9.6%) and HRS (8.4%), while lower proportions were observed in CLHLS (1.5%), KLoSA (2.3%), and LASI (3.1%). In Western countries, childlessness was not significantly associated with depression (HRS: OR = 1.00, 95% CI: 0.83-1.23; ELSA: OR = 0.90, 95% CI: 0.69-1.17; SHARE: OR = 1.05, 95% CI: 0.97-1.15). However, in Asian countries, it was linked to a higher risk (CLHLS: OR = 2.00, 95% CI: 1.29-3.12; KLoSA: OR = 1.78, 95% CI: 1.24-2.55; LASI: OR = 1.33, 95% CI: 1.19-1.49). A random-effects meta-analysis confirmed this regional difference (β = 0.35, 95% CI: 0.15-0.55; P < 0.001). A non-linear association was observed between the number of children and depression in LASI and SHARE, with risk initially decreasing and then rising beyond a threshold. Subgroup analysis found a stronger association among ≤ 75 years individuals and men in KLoSA. In HRS, childlessness was associated with a higher risk of depression only among those living alone.</p><p><strong>Conclusions: </strong>The relationship between the number of children and depression varies across countries. Individuals in Asian countries may be more prone to depression than those in Western nations when they do not have children.</p>","PeriodicalId":9029,"journal":{"name":"BMC Psychiatry","volume":"25 1","pages":"765"},"PeriodicalIF":3.4,"publicationDate":"2025-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12326767/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144793313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A correlation study on EEG signals during visual concentration test and clinical evaluation in schizophrenia patients.","authors":"Min-Wei Huang, Qun-Wei Chang, Wen-Lin Chu","doi":"10.1186/s12888-025-07237-w","DOIUrl":"10.1186/s12888-025-07237-w","url":null,"abstract":"<p><strong>Background: </strong>This study addresses the challenge of accurately classifying the severity of schizophrenia in patients through a clever approach. By leveraging electroencephalography (EEG) signals, we aim to establish a method for evaluating patient conditions, thereby contributing to the psychiatric diagnosis and treatment field.</p><p><strong>Methods: </strong>Our research methodology encompasses a comprehensive system framework designed to analyze EEG signals with the Positive and Negative Syndrome Scale (PANSS) for correlation analysis. The process involves: (1) administering the PANSS test to create a database of schizophrenia patients; (2) developing a visual concentration test system that measures EEG signals in real-time; (3) processing these signals to construct an EEG feature database; (4) employing support vector machine and decision tree methods for illness severity classification; (5) conducting statistical analysis to correlate PANSS scores with EEG features, assessing the effectiveness of these correlations in clinical applications.</p><p><strong>Results: </strong>The study successfully demonstrated the potential of a concentration detection system, integrating EEG signal analysis with PANSS scores, to classify schizophrenia severity accurately. Applying SVM and decision tree methods established significant correlations between EEG features and clinical scales, indicating the system's efficacy in supporting psychiatric diagnosis.</p><p><strong>Conclusions: </strong>Our findings suggest that the proposed analytical methods, focusing on EEG signals and employing a novel system framework, can effectively assist in classifying the severity of schizophrenia. This approach offers promising implications for enhancing diagnostic accuracy and tailoring treatment strategies for patients with schizophrenia.</p>","PeriodicalId":9029,"journal":{"name":"BMC Psychiatry","volume":"25 1","pages":"761"},"PeriodicalIF":3.4,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12326833/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144788216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the perceptions and requirements of exergames for adolescents with depression: a qualitative study.","authors":"Yuqi Chen, Xiaolong Huang, Wei Luo, Haiyan Liu, Yaqin Gao, Muyao Wang, Yan Zhang, Jingjing Liu, Changyan Zhong, Aixiang Xiao, Yu Chen","doi":"10.1186/s12888-025-07195-3","DOIUrl":"10.1186/s12888-025-07195-3","url":null,"abstract":"<p><strong>Background: </strong>The prevalence of depression among adolescents has been steadily increasing in recent years. Exergames hold the potential to provide a positive entertainment experience, yet their utilization among adolescents with depression remains limited. This study aims to investigate the perceptions and requirements regarding exergames in adolescents with depression, with the goal of designing tailored exergame intervention programs for clinical applications.</p><p><strong>Methods: </strong>Semi-structured interviews were conducted with adolescents with depression (n = 33) at a tertiary psychiatric hospital from September to November 2024. Data were analyzed using Colaizzi's seven-step method to ensure a rigorous and systematic qualitative analysis. The study adhered to the COREQ checklist when reporting qualitative research.</p><p><strong>Results: </strong>The perceptions and requirements of adolescents with depression regarding exergames were categorized into three themes and seven sub-themes: (1) characteristics of physical activity (lack of exercise motivation and low levels of physical activity); (2) willingness to use exergames (a preference for exergames over traditional exercise, a desire to alleviate depressive symptoms through exergaming and a tendency to engage in exergames collaboratively rather than individually); (3) expectations for exergames (emphasizing the need for safety and tangible benefits from exergames participation).</p><p><strong>Conclusions: </strong>While exergames are widely utilized among adolescents, their application in adolescents with depression remains under-explored. This study indicates that adolescents with depression have a positive attitude towards exergames and perceive them as potential interventions to increase physical activity and alleviate depressive symptoms.</p><p><strong>Trial registration: </strong>Chinese Clinical Trial Registry, ChiCTR2400090678. Registered on 11th October 2024.</p>","PeriodicalId":9029,"journal":{"name":"BMC Psychiatry","volume":"25 1","pages":"762"},"PeriodicalIF":3.4,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12326674/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144788217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Latent profile analysis and influencing factors of post-traumatic stress disorder symptoms in young and middle-aged spinal cord injury patients.","authors":"Songbo Jia, Zhenzhen Wang, Qiaoju Yang, Jiayi Guan, Yange Yang, Lijun Min","doi":"10.1186/s12888-025-07211-6","DOIUrl":"10.1186/s12888-025-07211-6","url":null,"abstract":"<p><strong>Background: </strong>Post-traumatic stress disorder (PTSD) has a profound impact on the physiological, psychological, social functioning, and occupational development of young and middle-aged spinal cord injury (SCI) patients, with a multitude of factors influencing its manifestation. However, the majority of current studies treat all spinal cord injury patients as a homogeneous group, thereby ignoring the intrinsic characteristics of patients and the inter-individual heterogeneity that exists. The aim of this study was to identify distinct subgroups of young and middle-aged SCI patients according to their PTSD symptom severity and to explore the factors affecting different subgroups.</p><p><strong>Methods: </strong>A cross-sectional study was conducted at a tertiary level Chinese hospital in Zhengzhou, China. A total of 240 young and middle-aged spinal cord injury patients completed the Sociodemographic questionnaire, Post-traumatic stress disorder self-assessment scale(PCL-C), Perceived social support scale PSSS Simplified Coping Style Questionnaire and Event Related Rumination Inventory ERRI The objective of this study was to identify potential categories of PTSD symptom severity in young and middle-aged spinal cord injury patients. To this end, latent profile analysis (LPA) was employed to ascertain the underlying categories, while multivariate logistic regression was utilized to explore the factors influencing these categories.</p><p><strong>Results: </strong>Three potential categories were identified: low-level PTSD symptom group(61.3%),medium-level PTSD symptom group(21.7%) and high-level PTSD symptom group(17.0%). The results of the multivariate logistic regression analysis indicated that patients who were self-funded, had comorbidities, demonstrated poor disease awareness, exhibited a low level of self-care, displayed a high level of rumination thinking, and adopted negative coping styles were more likely to be categorized in the high-level PTSD symptom group. Conversely, patients who had good social support and adopted positive coping styles were more likely to be categorized in the low-level PTSD symptom group and medium-level PTSD symptom group.</p><p><strong>Conclusions: </strong>PTSD symptom severity in young and middle-aged spinal cord injury patients is characterized by substantial heterogeneity. A number of factors may influence the potential categories of PTSD symptom severity in young and middle-aged spinal cord injury patients, including the patient's form of medical payment, the occurrence of complications, disease awareness, level of self-care, positive and negative coping strategies, social support, and rumination thinking. The findings of this study may serve as a new reference point for the implementation of different intervention and prevention strategies for patients.</p>","PeriodicalId":9029,"journal":{"name":"BMC Psychiatry","volume":"25 1","pages":"763"},"PeriodicalIF":3.4,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12326593/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144788218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Altered inter-hemispheric and intra-hemispheric functional connectivity dynamics in male cigarette smokers.","authors":"Mengzhe Zhang, Huiyu Huang, Xiaoyu Niu, Jinghan Dang, Jieping Sun, Qiuying Tao, Weijian Wang, Shaoqiang Han, Jingliang Cheng, Yong Zhang","doi":"10.1186/s12888-025-07222-3","DOIUrl":"10.1186/s12888-025-07222-3","url":null,"abstract":"<p><strong>Background: </strong>Previous study has overlooked the heterogeneity between hemispheres and the knowledge of brain temporal dynamics in tobacco use disorder (TUD) individuals was limited. Traditional whole-brain based approaches hampered the exploration of dynamic functional connectivity at the hemisphere level.</p><p><strong>Methods: </strong>We recruited 110 male subjects, including 70 smokers (32 high dependence smokers, 38 low dependence smokers) and 40 non-smokers, then obtained their rs-fMRI data and smoking clinical scales. The functional connections of whole-brain were decomposed into inter-hemispheric and intra-hemispheric connections. Meanwhile, sliding window method was used to evaluate inter- and intra-hemispheric dynamic functional connectivity density (dFCD) variability. Finally, correlation analyses were conducted to explore the relationship between dFCD variability and clinical scales.</p><p><strong>Results: </strong>We found shared dFCD variability in visual cortex of bilateral hemispheres among all smokers. Compared to low dependence smokers, high dependence smokers showed higher inter-hemispheric dFCD variability in left insula, and lower intra-hemispheric dFCD variability in right inferior frontal gyrus (IFG) and right inferior parietal lobule (IPL). Moreover, intra-hemispheric dFCD variability of right IPL in high dependence smokers was associated with physical dependence rather than psychosocial factors.</p><p><strong>Conclusions: </strong>This study revealed shared inter/intra-hemispheric dFCD variability of visual cortex, and different connection patterns of frontoparietal control network and insula at hemisphere level in smokers. These findings supply novel insights into brain functional aberrance in TUD from a dynamic perspective, and suggest hemispheric specialization and aberrant inter-hemispheric communication in TUD.</p>","PeriodicalId":9029,"journal":{"name":"BMC Psychiatry","volume":"25 1","pages":"758"},"PeriodicalIF":3.4,"publicationDate":"2025-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12323142/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144783448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The impact of adverse childhood experiences in the development of post-traumatic stress disorder in adults over 18 years of age: a systematic review.","authors":"Muhammad Umar, Manahil Mustajab, Zaineb Fatima, Riya Mary Richard, Sindh Rani Qureshi, Siraj Ul Muneer, Laiba Shamim, Shahzaib Ahmed, Hashim Talib Hashim, Ashraf Fhed Mohammed Basalilah","doi":"10.1186/s12888-025-07090-x","DOIUrl":"10.1186/s12888-025-07090-x","url":null,"abstract":"<p><strong>Background: </strong>Post-traumatic stress disorder (PTSD) affects mental health in the long term and is often associated with past psychological trauma. This systematic review was conducted with a purpose to investigate the correlation between adverse childhood experiences (ACE), experiences of child maltreatment, and the occurrence of PTSD in adults over 18 years to optimize treatment guidelines accordingly.</p><p><strong>Method: </strong>The review utilized articles searched on PubMed, Google Scholar, Scopus, and Cochrane. Inclusion criteria include original studies (RCTs, cross-sectional, and cohorts) involving adults over 18 years with PTSD with a history of ACE published during the last decade (2014 and 2025). This study was conducted according to preferred reported items in systematic reviews and meta-analysis (PRISMA) guidelines. A quality assessment of the included studies was conducted using Newcastle Ottawa scale for cohort studies and the axis scale for cross-sectional studies.</p><p><strong>Results: </strong>Out of 356 articles, 169 were screened, of which 26 studies were included in this review. These studies discussed various forms of childhood maltreatment, including sexual abuse, physical abuse, traumatic events, and neglect from parents. Most of these studies indicate a direct correlation between childhood maltreatment and Adulthood PTSD.</p><p><strong>Conclusion: </strong>A robust association exists between ACE and childhood maltreatment and the development of PTSD in adulthood. There is a need for more literature to study the effects of maltreatment and comorbid mental health conditions for policymaking to protect child mental health.</p>","PeriodicalId":9029,"journal":{"name":"BMC Psychiatry","volume":"25 1","pages":"759"},"PeriodicalIF":3.4,"publicationDate":"2025-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12323241/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144783450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An open dataset and machine learning algorithms for Niacin Skin-Flushing Response based screening of psychiatric disorders.","authors":"Xuening Lyu, Rimsa Goperma, Dandan Wang, Chunling Wan, Liang Zhao","doi":"10.1186/s12888-025-07196-2","DOIUrl":"10.1186/s12888-025-07196-2","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Niacin Skin-Flushing Response (NSR) has emerged as a promising objective biomarker for the precise diagnosis of mental disorders. However, its diagnostic potential has been constrained by the limitations of traditional statistical approaches. The advent of Artificial Intelligence (AI) offers a transformative opportunity to overcome these challenges. This study presents a novel contribution to the field by establishing an open-access dataset and developing advanced AI-driven tools to enhance the diagnostic accuracy of psychiatric disorders through NSR analysis.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;This study introduces the world's first open dataset specifically developed for AI studies of Niacin Skin-Flushing Response (NSR), a physiological biomarker associated with mental illnesses including depression, bipolar disorder, and schizophrenia. Leveraging this dataset, we developed an advanced Machine Learning (ML) approach designed for the broad diagnosis of mental disorders. Distinct from prior studies which are often limited to First Episode Schizophrenia and depend on specific devices, our approach champions device independence. The core of our methodology involves a novel algorithm featuring an Efficient-Unet based Deep Learning model for the precise segmentation of NSR areas. This segmentation is significantly enhanced by runtime data augmentation and trained on a robust train/validation/test dataset split. Subsequently, a Support Vector Machine (SVM) method is employed for psychiatric disorder classification utilizing feature vectors extracted from the segmentation of NSR areas with a 3-scale quantization. The SVM training incorporates 5-fold cross-validation, Synthetic Minority Over-sampling Technique (SMOTE) for managing class imbalance, and hyperparameter tuning to optimize balanced accuracy.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;The established dataset comprises 600 high-quality NSR images from 120 individuals, encompassing a diverse cohort of healthy controls and patients with various mental illnesses. The developed AI tools offer an objective, swift, and highly accurate approach that is demonstrably independent of the diagnosed condition or the specific device used for image acquisition. Comparative results demonstrate that the ML-based diagnostic approach achieves a sensitivity ranging from 60.0 to 65.0% and a specificity from 75.0 to 88.3% across various types of illnesses, further underscoring its broad applicability and device independence.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;This research conclusively demonstrates the significant potential of advanced AI tools in achieving precise diagnosis of psychiatric disorders, potentially surpassing human capabilities in both speed and accuracy. With the provision of the proposed open dataset and the introduction of novel methodologies, this study marks substantial progress in developing an objective and accurate NSR-based screening process for a wide spectrum of psychiatr","PeriodicalId":9029,"journal":{"name":"BMC Psychiatry","volume":"25 1","pages":"757"},"PeriodicalIF":3.4,"publicationDate":"2025-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12323195/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144783449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A bayesian network model for neurocognitive disorders digital screening in Chinese population: development and validation study.","authors":"Yifan Yu, Shuaijie Zhang, Hongkai Li, Fuzhong Xue","doi":"10.1186/s12888-025-07189-1","DOIUrl":"10.1186/s12888-025-07189-1","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Neurocognitive disorders (NCDs), classified under the ICD-10 codes F00-F09, are a category of mental disorders associated with brain disease, injury, or systemic conditions leading to cerebral dysfunction. NCDs represent a significant disease burden and an increasingly critical global public health challenge. Early screening for neurocognitive disorders is conducive to improving patients' quality of life and reducing healthcare costs. Therefore, there is an urgent need to develop an inexpensive and convenient screening model for neurocognitive disorders that can be applied to large populations to improve the efficiency of neurocognitive disorders screening.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;This study aimed to construct a classification model for screening neurocognitive disorders (NCDs) based on cross-sectional electronic health record data from the Cheeloo Whole Lifecycle eHealth Research-based Database (2015-2017). Eligible participants were adults aged 18 years or older, without prior diagnosis of neurocognitive disorders at baseline, covering multiple cities in Shandong Province, China. Among 1,626,817 individuals initially screened, 4,518 diagnosed NCD cases were included for model building and validation. Participants were assigned to a training set or a validation set based on their geographic locations. A Bayesian network classification model was developed by initially screening variables through univariate logistic regression. Gender and the top 30 variables with the highest coefficient of determination () in explaining the variance in NCD status were retained for model construction. Subsequently, the optimal network structure was identified using the Tabu search algorithm guided by Bayesian Information Criterion, with parameters estimated by maximum likelihood estimation. The model's performance was benchmarked against a multivariable logistic regression model. The model's performance was validated through ROC curves, calibration curves, and decision curves analysis. Sensitivity analyses were performed by introducing random missingness into the dataset to evaluate robustness of Bayesian network model and multivariable logistic regression model.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;The final Bayesian network model included 31 variables in total, of which eight were directly connected to the neurocognitive disorders node in the learned Bayesian network structure. The Bayesian network model had good predictive discrimination, with AUC of 0.849 (95% CI; 0.839-0.859), 0.821 (95% CI; 0.803-0.840) and 0.800 (95% CI; 0.785-0.815) in the training, testing and validation sets, respectively. The calibration curves were well calibrated, and the decision curve analysis demonstrated its clinical applicability. In sensitivity analysis, the AUC of the Bayesian network model was 0.791 (95% CI; 0.777-0.806), with good robustness to missing data.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;The findings of this study indicated that the es","PeriodicalId":9029,"journal":{"name":"BMC Psychiatry","volume":"25 1","pages":"760"},"PeriodicalIF":3.4,"publicationDate":"2025-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12323206/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144783447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}