BMC Psychiatry最新文献

{"title":"The association between positive school climate and school identification and probable depression among Chinese adolescents: serial mediation mechanisms via resilience, mindfulness, and loneliness.","authors":"Yanqiu Yu, Deborah Baofeng Wang, Mengni Du, Anise M S Wu, Juliet Honglei Chen, Stefanie H Y Yen, Guohua Zhang, Dong-Wu Xu, Joseph T F Lau","doi":"10.1186/s12888-025-07308-y","DOIUrl":"https://doi.org/10.1186/s12888-025-07308-y","url":null,"abstract":"<p><strong>Background: </strong>Adolescent depression is a significant public health issue. Both environmental factors (e.g., school climate and school identification) and personal factors (e.g., resilience, mindfulness, and loneliness) are associated with depression.</p><p><strong>Methods: </strong>An anonymous cross-sectional study (n = 7,554) was conducted among secondary school students in Taizhou, China from February to March 2022. Probable depression was defined as the 9-item Patient Health Questionnaire (PHQ-9) score ≥ 10.</p><p><strong>Results: </strong>The prevalence of probable depression was 18.81%. It was negatively associated with school climate, school identification, resilience, and mindfulness, and positively associated with loneliness. The negative association between school climate and probable depression was significantly/fully mediated by three single-mediator indirect paths (involving resilience, self-compassion, and loneliness, respectively) and two two-mediator indirect paths (first via resilience then via loneliness, and first via self-compassion then via loneliness, respectively). The mediation effect sizes for the five paths were 17.05%, 6.82%, 39.20%, 7.39%, And 3.52%, respectively. Similar significant mediation paths were identified regarding the association between school identification and probable depression, although these exhibited relatively small mediation effect sizes of < 10%.</p><p><strong>Conclusions: </strong>This study observed high prevalence of probable depression among Chinese secondary school students. School climate and school identification at the environmental level were directly and indirectly (via personal factors of resilience, mindfulness, and loneliness) associated with adolescent depression. Future studies are needed to confirm the above findings and pilot interventions to modify these factors.</p>","PeriodicalId":9029,"journal":{"name":"BMC Psychiatry","volume":"25 1","pages":"905"},"PeriodicalIF":3.4,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145204940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A review of the scope of non-suicidal self-injury behavior in adolescents with depressive disorders: an analysis of related influencing factors.","authors":"Yijing Ling, Yujia Gu, O Mensah Solomon, Lihong Li, Xufeng Chen, Ying Wang, Yehong Wei","doi":"10.1186/s12888-025-07361-7","DOIUrl":"https://doi.org/10.1186/s12888-025-07361-7","url":null,"abstract":"<p><strong>Background: </strong>Non-suicidal self-injury (NSSI) behavior is one of the major causes of death and disability in adolescents with depressive disorders, and this behavior has a high detection rate among adolescents globally, which seriously affects their physical and mental health and quality of life. Given the high prevalence and severity of NSSI behavior, this study provides a reference for the future construction of a risk-grading-based preventive intervention framework for NSSI in adolescents with depressive disorders by systematically sorting out the factors affecting non-suicidal self-injury.</p><p><strong>Methods: </strong>This study adopted Arksey and O'Malley's methodology and the scoping review framework. The search took place from the creation of the database until November 12, 2024, in professional guideline websites like NICE and GIN and databases like China Knowledge, Wanfang, CINAHL, PubMed, and Web of Science. The topics searched for were adolescent depressive disorder, NSSI and behavioral influencing factors in relevant Chinese and English literature. We identified the research questions, completed the literature screening and quality assessment, extracted the data, summarized it, and analyzed it.</p><p><strong>Results: </strong>The study included a total of 15 papers, comprising 1 guideline, 3 systematic evaluations, 1 Literature review, and 10 cross-sectional studies. Study topics focused on four categories: individual characteristics and psychological factors (e.g., gender, age, sexual orientation), illness and treatment factors (duration of illness, degree of depression), behaviors and lifestyles (Internet addiction, stressful events), and family and social environment (family functioning, social support).</p><p><strong>Conclusion: </strong>Factors affecting NSSI behaviors in adolescent patients with depression are intricate and complex, covering multiple dimensions such as personal traits, family environment. The findings of this review emphasize that when conducting NSSI risk assessment for depressed adolescents in clinical practice, in addition to the depressive symptoms themselves, it is also necessary to systematically evaluate those individual psychological traits, behavioral patterns, and environmental factors. We should integrate relevant risk factors to create personalized prevention plans. We aim to decrease the frequency of NSSI behaviors in teenage patients suffering from depressive disorders and halt the progression of additional suicidal actions. Future research can focus on verifying the role of these risk factors in the predictive model and the effectiveness of intervention measures.</p>","PeriodicalId":9029,"journal":{"name":"BMC Psychiatry","volume":"25 1","pages":"913"},"PeriodicalIF":3.4,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145205442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CD4 + T lymphocyte and cytokine profiles in depressive disorders.","authors":"Wanting Zhang, Chao Wang, Tiantian Fu, Shengxiao Zhang, Feng Tian","doi":"10.1186/s12888-025-07344-8","DOIUrl":"https://doi.org/10.1186/s12888-025-07344-8","url":null,"abstract":"<p><strong>Background: </strong>Immune system dysfunction has been associated with depressive disorders; however, the specific alterations in CD4 + T lymphocytes and cytokines among individuals with varying severities of depression remain unclear. This study aimed to investigate the immunological changes in patients with mild, moderate, and severe depression, to identify potential biomarkers for clinical diagnosis and disease severity assessment, and to uncover the immunological mechanisms involved in depression.</p><p><strong>Methods: </strong>Twenty-eight mild depression patients, thirty-one moderate depression patients, twenty-two severe depression patients and eighty-three healthy subjects were included in the mild, moderate, severe and control group. The relative proportions and absolute quantities of Th1, Th2, Th17 and Treg cells in peripheral blood were determined by flow cytometry. In addition, the levels of cytokines in serum were detected by cytometric bead array (CBA), including IL-2, IL-4, IL-6, IL-10, IL-17, IFN-γ and TNF-α.</p><p><strong>Results: </strong>The levels of Th1%, Th17, Th1/Th2, and Th17/Treg ratios were significantly higher in the mild depression group compared to the control group (p < 0.05), with a concurrent decrease in Treg% (p < 0.05). In the moderate depression group, elevated levels of Th1%, Th17%, Th1, Th17, Th1/Th2, and Th17/Treg were observed (p < 0.05), alongside reduced Treg% and Treg counts (p < 0.05). The severe depression group exhibited further increases in Th1%, Th17%, Th1, Th17, Th1/Th2, and Th17/Treg (p < 0.05). IL-4 levels progressively decreased, while IL-6 levels increased across the mild, moderate, and severe depression groups (p < 0.05). A negative correlation was found between depression severity and IL-4 (r = -0.544, p < 0.001), and a positive correlation with IL-6 (r = 0.553, p < 0.001). IL-4 and IL-6 were identified as independent factors influencing depression severity (p < 0.01).</p><p><strong>Conclusions: </strong>The study's findings suggest that abnormalities in CD4 + T lymphocytes and cytokines are characteristic of depression across its severity spectrum, with an increase in Th1 and Th17 cells and a decrease in Treg cells. IL-4 and IL-6 may serve as indicators of depression severity and are significant biomarkers for assessing disease progression. These insights enhance our understanding of the immunological basis of depression and provide novel strategies for its management and treatment.</p>","PeriodicalId":9029,"journal":{"name":"BMC Psychiatry","volume":"25 1","pages":"911"},"PeriodicalIF":3.4,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145205485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating motivational interview quality using large language models and hidden Markov models.","authors":"Kyungho Lim, Young-Chul Jung, Byung-Hoon Kim","doi":"10.1186/s12888-025-07391-1","DOIUrl":"https://doi.org/10.1186/s12888-025-07391-1","url":null,"abstract":"<p><strong>Background: </strong>Motivational Interviewing (MI) is a counseling approach that promotes behavior change by eliciting \"change talk\" and minimizing \"sustain talk.\" Traditional methods for assessing MI quality, such as manual coding, are labor-intensive, subjective, and difficult to scale. This study introduces an automated framework integrating large language models (LLMs) and Hidden Markov Models (HMMs) for evaluation of MI session quality.</p><p><strong>Aims: </strong>This study evaluates the effectiveness of an LLM-HMM framework in predicting MI session quality and examines motivational state transitions in high- and low-quality sessions.</p><p><strong>Method: </strong>A dataset of 40 MI sessions was analyzed. Client utterances were classified and numerically scored by an LLM based on their intention toward or away from change. With HMMs, we used these scores to examine the motivational state transitions across each session. Differences between high- and low-quality sessions were quantified by comparing transition matrices using Frobenius norms. Statistical significance was assessed via a permutation test. Predictive performance was evaluated using logistic regression with leave-one-out cross-validation (LOOCV), where transition matrix elements served as independent variables and interview quality as the dependent variable.</p><p><strong>Results: </strong>High-quality MI sessions exhibited fluid transitions between motivational states, whereas low-quality sessions showed persistence in resistance-oriented states. A statistically significant difference in transition matrices was observed between session groups (p < 0.001). The framework achieved a mean LOOCV accuracy of 0.80, demonstrating strong predictive performance in identifying MI session quality.</p><p><strong>Conclusions: </strong>This study presents a scalable, objective alternative to manual MI evaluation. Future applications may include real-time therapist support, training, and prognosis prediction, pending further validation on field-collected data.</p>","PeriodicalId":9029,"journal":{"name":"BMC Psychiatry","volume":"25 1","pages":"908"},"PeriodicalIF":3.4,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145205457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Network analysis of interrelationships among physical activity, sleep disturbances, depression, and anxiety in college students.","authors":"Jinwei Yang, Wei Li, Xi Jin, Fei YinHeilongjiang Province, Zhengjun Wang, Jianqin Cao","doi":"10.1186/s12888-025-07376-0","DOIUrl":"https://doi.org/10.1186/s12888-025-07376-0","url":null,"abstract":"<p><strong>Background: </strong>Physical activity, sleep disturbances, anxiety, and depression are interrelated, but prior research focused on overall scores, neglecting symptom interactions and triggering effects. This study employed network analysis to explore these connections from a symptom-network perspective.</p><p><strong>Methods: </strong>Physical Activity Scale-3, Pittsburgh Sleep Quality Index Scale, Self-Reating Depression Scale, and Self-Reating Anxiety Scale were conducted on 4683 college students from September to October 2024 by convenience sampling method. Spearman correlation is used to explore the relationship between these variables. Network analysis revealed structural connections between physical activity and sleep disturbances, identifying core and bridge symptoms. Flow network further explored the impacts of physical activity and sleep disturbances on depression and anxiety.</p><p><strong>Results: </strong>Physical activity was negatively correlated with sleep disturbances, depression, and anxiety (p < 0.05), while sleep disturbances was positively correlated with depression and anxiety (p < 0.01). In the symptom network of physical activity and sleep disturbances, \"sleep quality\" (EI = 0.009) and \"daytime dysfunction\"(EI = 0.827) were the core symptoms, while \"daytime dysfunction\" (BEI = 0.035) and \"intensity of physical activity\" (BEI = 0.015) were the bridge symptoms. In the flow networks, \"physical activity frequency\" (r=-0.14) and \"daytime dysfunction\"(r = 0.13) were particularly correlated with depression. \"Sleep disruptions\"(r = 0.18) and \"physical activity frequency\" (r=-0.14) showed a strong correlation with anxiety.</p><p><strong>Conclusion: </strong>The study identified the core and bridge symptoms of the physical activity and sleep disturbances symptom network, as well as key symptoms linked to anxiety and depression. Targeting these symptoms could disrupt their interactions, prevent negative outcomes, and enhance college student well-being.</p>","PeriodicalId":9029,"journal":{"name":"BMC Psychiatry","volume":"25 1","pages":"904"},"PeriodicalIF":3.4,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145205433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical implications of autistic features in the psychosis spectrum: a cross-sectional study using path analysis.","authors":"Ezgi Sıla Ahi Üstün, Serkan Yazıcı, Rifat Serav İlhan, Meram Can Saka","doi":"10.1186/s12888-025-07377-z","DOIUrl":"https://doi.org/10.1186/s12888-025-07377-z","url":null,"abstract":"<p><strong>Background: </strong>Despite the fact that there have been many studies on the connection between autism and psychosis, there are still many things that are unknown about the significance of this connection. Recent studies have highlighted the significant overlap between autistic traits and psychotic disorders, yet the clinical implications of these associations are not well understood. This study aims to address this knowledge gap by investigating the links between autistic features and various clinical, functional and behavioural outcomes in individuals with psychosis spectrum.</p><p><strong>Methods: </strong>The study included 125 patients who had at least one psychotic episode and who had used antipsychotic medication for most of the treatment period. The clinician conducted face-to-face interviews to evaluate all other clinical characteristics, while self-report scales were employed to evaluate autistic features and quality of life. Complex associations were understood using path analysis.</p><p><strong>Results: </strong>Our study showed that there was a negative association between autistic features and functioning, quality of life and subjective treatment benefit; and a positive association with severity of disorder, severity of anxiety and depression, severity of positive and negative symptoms, suicidal ideation and behaviour, psychiatric comorbidity and number of psychotic episodes. Depression intensity mediated autistic features' effect on suicidal thoughts. Those who were non-smokers and bullied by peers reported more autistic traits.</p><p><strong>Conclusions: </strong>Taken together, our results highlight the importance of autistic features in the psychosis spectrum. It is clear that there is a significant gap in clinical knowledge regarding the relationship between autism and psychosis and that further improvements in diagnostic tools and treatment options are needed. As our study is cross-sectional in design, speculation about causality is limited and further prospective research is needed.</p>","PeriodicalId":9029,"journal":{"name":"BMC Psychiatry","volume":"25 1","pages":"902"},"PeriodicalIF":3.4,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145205435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Single- and multiple-dose pharmacokinetics, safety, and tolerability of Aripiprazole once-monthly, long-acting intramuscular injection for Chinese adults with schizophrenia.","authors":"Fang Dong, Feifei Wang, Xiaofei Yuan, Yimin Zhai, Motomichi Uki, Tao Jiang, Anning Li","doi":"10.1186/s12888-025-07407-w","DOIUrl":"https://doi.org/10.1186/s12888-025-07407-w","url":null,"abstract":"<p><strong>Background: </strong>Aripiprazole once-monthly (AOM), a long-acting injectable antipsychotic, is increasingly used in managing schizophrenia. However, to date, there has been no disclosure of pharmacokinetic data for AOM long-acting injection in the Chinese population. The present study aimed to evaluate the pharmacokinetics of AOM of Chinese patients with schizophrenia.</p><p><strong>Methods: </strong>The single-administration part of the study was single-center and multiple-dose, in which 300/400-mg AOM was administered to 24 patients with schizophrenia. In the multiple-administration part of the study, 400-mg of AOM was administered once every 4 weeks for 20 consecutive weeks to 12 subjects. Pharmacokinetic parameters (e.g., e.g., Cmax, tmax, AUC0-∞, t1/2, and CL/F) were derived via non-compartmental analysis using actual sampling times, with bootstrap-derived confidence intervals for non-normal data. Safety evaluation included monitoring of adverse events (AEs), physical examinations, vital signs, and clinical laboratory tests.</p><p><strong>Results: </strong>Following single administration of AOM (300-mg or 400-mg), maximum plasma concentration (C_max) values of aripiprazole were 85.05 ± 42.11 and 175.25 ± 67.84 ng/mL, respectively; median times to achieve C_max (t_max) were 816.17 and 588.84 h, respectively; and elimination half-life (t_1/2) values were 647.18 ± 234.59 and 547.17 ± 258.48 h, respectively. Following multiple administration of AOM, the C_max of aripiprazole was 270.18 ± 113.37 ng/mL, the median t_max was118.83, and the t_1/2 was 1138.78 ± 998.77 h. In vivo exposure to aripiprazole increased with the AOM dose. No severe AEs were observed in single- or multiple-administration studies.</p><p><strong>Conclusions: </strong>The pharmacokinetics of AOM support its clinical use as a 4-week injectable regimen, with favorable tolerability and safety profiles observed in Chinese patients with schizophrenia.</p><p><strong>Trial registration: </strong>ClinicalTrials.gov Identifier: Single-administration NCT03287505 first submitted on 15 May 2017, Multiple-administration NCT03285503 first submitted on 11 Sep 2017.</p>","PeriodicalId":9029,"journal":{"name":"BMC Psychiatry","volume":"25 1","pages":"912"},"PeriodicalIF":3.4,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145204929","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association between sleep duration, depression and cognitive decline trajectories: findings from a prospective cohort study in China.","authors":"Chenyu Li, Xiaomin Wu, Yu Li, Meilin Zhang, Luhan Zhang, Chaohui Zhou, Fei Ma","doi":"10.1186/s12888-025-07387-x","DOIUrl":"https://doi.org/10.1186/s12888-025-07387-x","url":null,"abstract":"<p><strong>Objective: </strong>This study investigated the relationship between sleep duration and cognitive decline trajectories among Chinese adults with age ≥ 45. Additionally, it examined whether baseline depression symptoms mediated the association between sleep duration and cognitive decline trajectories.</p><p><strong>Methods: </strong>Data came from the China Health and Retirement Longitudinal Study (CHARLS), a nationally survey of Chinese adults. Total sleep duration was grouped into shorter (≤ 6 h), normal (6-9 h), and longer (> 9 h). Nighttime sleep duration was categorized as shorter (≤ 6 h), normal (6-8 h), and longer (> 8 h). Daytime nap duration was classified into no nap, shorter (≤ 0.5 h), normal (0.5-1.5 h), and longer (> 1.5 h). Cognitive decline trajectories were identified using a group-based trajectory model (GBTM). Depression symptoms, measured by baseline depression scores, were included as a potential mediating variable. Multinomial logistic regression models were applied to analyze the association between sleep duration and cognitive trajectories.</p><p><strong>Results: </strong>A total of 4,094 respondents were included. Participants were classified into three trajectory groups: high-level stable (n = 1,278, 31.2%), moderate-level slow-decline (n = 2,089, 51.0%), and low-level rapid-decline (n = 727, 17.8%). Compared to the stable group, shorter total sleep duration was associated with both rapid-decline (RRR:1.510; 95%CI:1.079,2.114) and slow-decline (RRR:1.466; 95%CI:1.145,1.877) cognitive trajectories. Similarly, shorter nighttime sleep duration was associated with both rapid-decline (RRR:1.572; 95%CI: 1.089,2.271) and slow-decline (RRR:1.480; 95%CI:1.129,1.939) cognitive trajectories compared to the stable group. Baseline depression symptoms did not mediate these relationships (P > 0.05).</p><p><strong>Conclusions: </strong>Shorter total sleep duration (≤ 6 h) and shorter nighttime sleep duration (≤ 6 h) were significantly associated with cognitive decline trajectories. However, baseline depression symptoms did not mediate these relationships.</p>","PeriodicalId":9029,"journal":{"name":"BMC Psychiatry","volume":"25 1","pages":"907"},"PeriodicalIF":3.4,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145205464","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Classify the fNIRS signals of first-episode drug-naive MDD patients with or without suicidal ideation using machine learning.","authors":"Lan Mou, Yuqi Shen, Qian Tan, Boyuan Wu, Jiayun Zhu, Zefeng Wang, Zhongxia Shen, Xinhua Shen","doi":"10.1186/s12888-025-07394-y","DOIUrl":"https://doi.org/10.1186/s12888-025-07394-y","url":null,"abstract":"<p><strong>Background: </strong>Major Depressive Disorder (MDD) has a high suicide risk, and current diagnosis of suicidal ideation (SI) mainly relies on subjective tools.Neuroimaging techniques, including functional near-infrared spectroscopy (fNIRS), offer potential for identifying objective biomarkers. fNIRS, with its advantages of non-invasiveness, portability, and tolerance of mild movement, provides a feasible approach for clinical research. However, previous fNIRS studies on MDD and suicidal ideation have inconsistent results due to patient and methodological differences.Traditional machine learning in fNIRS data analysis has limitations, while deep - learning methods like one-dimensional convolutional neural network (CNN) are under-explored. This study aims to use fNIRS to explore prefrontal function in first-episode drug-naive MDD patients with suicidal ideation and evaluate fNIRS as a diagnostic tool via deep learning.</p><p><strong>Methods: </strong>A total of 91 first-episode drug-naive MDD patients were included and categorized into two groups based on their scores on the suicidal item of the 17-item Hamilton Depression Rating Scale (HAMD-17): 40 patients with suicidal ideation (SIs) and 51 patients without suicidal ideation (NSIs). Concurrently, 39 healthy controls (HCs) were recruited. We utilized fNIRS to measure the hemodynamic responses in the prefrontal cortex of each group during the verbal fluency task (VFT). A Kruskal-Wallis test was conducted to analyze the changes in oxyhemoglobin concentration among the three groups, and receiver operating characteristic (ROC) curves were generated for each region of interest.</p><p><strong>Results: </strong>Compared to HCs, NSIs exhibited significantly reduced activation in the left dorsolateral prefrontal cortex (lDLPFC), frontopolar prefrontal cortex (FPC), orbitofrontal cortex (OFC), and ventrolateral prefrontal cortex (VLPFC), while SIs showed significantly decreased activation in the entire prefrontal cortex. The activation values of SIs in DLPFC, FPC, and OFC were significantly lower than those of NSIs. The highest accuracy for the three-class classification was observed in the lFPC, reaching 69.80%. The SIs group had the largest area under the ROC curve (AUC = 0.88) in the rFPC, while the NSIs group had the largest area under the ROC curve (AUC = 0.88) in the rDLPFC. The HCs group exhibited the largest area under the ROC curve (AUC = 0.92) in the rDLPFC and rVLPFC.</p><p><strong>Conclusion: </strong>DLPFC, FPC, and OFC may serve as biomarker brain regions for identifying suicidal ideation in first-episode drug-naive MDD patients. The fNIRS-VFT task can be utilized clinically as an auxiliary diagnostic tool for mental disorders.</p>","PeriodicalId":9029,"journal":{"name":"BMC Psychiatry","volume":"25 1","pages":"909"},"PeriodicalIF":3.4,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145205480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Obsessive-compulsive symptoms in adolescents with major depressive disorder: prevalence, clinical correlates, and association with childhood trauma.","authors":"Zhichun Liu, Xianlin Sun, Yachen Feng, Changhao Chen, Zhiwei Liu, Jiawei Wang, Xiangwang Wen, Lei Xia, Huanzhong Liu","doi":"10.1186/s12888-025-07380-4","DOIUrl":"https://doi.org/10.1186/s12888-025-07380-4","url":null,"abstract":"","PeriodicalId":9029,"journal":{"name":"BMC Psychiatry","volume":"25 1","pages":"906"},"PeriodicalIF":3.4,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145204997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}