Depression and Anxiety最新文献

{"title":"Associations of Education Attainment With Postpartum Depression and the Mediating Exploration: A Mendelian Randomization Study","authors":"Xuanping Wang,&nbsp;Fang-Yue Zhou,&nbsp;Yanhui Hao,&nbsp;Jiaying Wu,&nbsp;Kaizhen Su,&nbsp;Si-Yue Chen,&nbsp;Wen Yu,&nbsp;Chen Zhang,&nbsp;Yan-Ting Wu,&nbsp;He-Feng Huang","doi":"10.1155/da/8835118","DOIUrl":"https://doi.org/10.1155/da/8835118","url":null,"abstract":"<div>\u0000 <p><b>Background:</b> Many studies have explored the relationship between education and postpartum depression (PPD), with inconsistent results. Our study is to identify which education-related factors (education attainment, qualifications, cognitive performance) played the predominant role in PPD using Mendelian randomization (MR) analysis. Then, we explored the factors that may mediate the effect of education on PPD.</p>\u0000 <p><b>Method:</b> We performed two-sample multivariable Mendelian randomization (MVMR) to assess the independent impact of education-related factors on PPD. Based on the literature review, three mediating factors that may play a role in the path of education attainment and PPD were involved in mediation analysis, including childbearing age, neuroticism score, and average total household income before tax. Then, we used two-step MR and MVMR to estimate the indirect effect of these mediators.</p>\u0000 <p><b>Results:</b> We identified genetically predicted 1-SD (3.71 years) higher education attainment (OR: 0.632; [95% confidential interval (CI): 0.464–0.860]); qualifications (OR: 0.418; [95% CI: 0.245–0.714]); or cognitive performance (OR: 0.770; [95% CI: 0.652–0.909]) was associated with lower risk of PPD, and the causal effects of education attainment (OR: 0.407; [95% CI: 0.214–0.773]) on PPD were independent of qualifications and cognition. Childbearing age (<i>β</i>: −0.497; [95% CI: −0.788−0.238]; <i>p</i>  &lt; 0.001) and neuroticism score (<i>β</i>: −0.07; [95% CI: −0.120−0.030]; <i>p</i>  &lt; 0.001) were identified as mediators of the association between education attainment and PPD.</p>\u0000 <p><b>Conclusions:</b> These results suggested the predominant impact of education attainment on PPD independent of qualifications and cognition. Education level mainly affects PPD by changing the childbearing age.</p>\u0000 <p><b>Trial Registration:</b> Chinese Clinical Trial Registry identifier: ChiCTR2000033433</p>\u0000 </div>","PeriodicalId":55179,"journal":{"name":"Depression and Anxiety","volume":"2025 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/da/8835118","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143447018","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":"Neurophysiological Signatures of Major Depressive Disorder and Frontocentral Gamma Auditory Response Deficits","authors":"Xiaoya Liu,&nbsp;Shuang Liu,&nbsp;Fangyue Su,&nbsp;Wenquan Zhang,&nbsp;Yufeng Ke,&nbsp;Dong Ming","doi":"10.1155/da/7390951","DOIUrl":"https://doi.org/10.1155/da/7390951","url":null,"abstract":"<div>\u0000 <p><b>Background:</b> Aberrant gamma oscillations in major depressive disorder (MDD) have attracted extensive attention, but evidence delineating such neural signatures is lacking. The auditory steady-state response (ASSR) elicited by periodic auditory stimuli is a robust probe of gamma oscillations. Here, we sought to characterize early transient auditory evoked responses (AEPs) and sustained gamma ASSRs in MDD, thereby identifying reliable neurophysiological signatures and providing preliminary interpretations of gamma auditory response deficits in MDD.</p>\u0000 <p><b>Methods:</b> Electroencephalographic data were obtained from 40 first-episode drug-naïve patients with MDD and 41 demographically matched healthy controls (HCs) during a 40-Hz ASSR paradigm, encompassing two periodic stimuli—chirp and click stimuli. Source analysis of transient AEPs was performed to identify generators involved in early information processing dysfunction. In addition, spectrotemporal and spatial characteristics of 40-Hz ASSRs were analyzed using event-related spectral perturbation, inter-trial phase coherence, and functional connectivity index.</p>\u0000 <p><b>Results:</b> Compared to HCs, patients showed a reduced P200 amplitude that was source-localized to the middle temporal gyrus, possibly reflecting an underlying impairment in the processes of early allocation or auditory information perception within the auditory pathways. Meanwhile, attenuated 40-Hz power and phase coherence, in conjunction with suppressed right frontotemporal and frontocentral connectivity, were observed in MDD, highlighting the multidimensional entrained gamma inhibition. Correlation analyses revealed that the decreased right frontocentral connectivity was strongly related to increased anxiety severity. Importantly, these abnormalities correlated with the patient’s symptoms were only found with the chirp stimulus, suggesting that the chirp stimulus has tremendous potential to reveal specific neurophysiological signatures of MDD.</p>\u0000 <p><b>Conclusions:</b> Our data reveal impaired gamma auditory responses in first-episode drug-naïve patients with MDD and suggest that right frontocentral connectivity elicited by the chirp stimulus may represent a promising signature for predicting clinical symptoms.</p>\u0000 </div>","PeriodicalId":55179,"journal":{"name":"Depression and Anxiety","volume":"2025 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/da/7390951","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143439141","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":"Distributed White Matter Abnormalities in Major Depressive Disorder: A Diffusion Tensor Imaging Combined Support Vector Machine Study","authors":"Sen Li,&nbsp;Yinghong Xu,&nbsp;Jian Cui,&nbsp;Kun Li,&nbsp;Shanling Ji,&nbsp;Hailong Shen,&nbsp;Yu Wan,&nbsp;Chunyu Dong,&nbsp;Hao Zheng,&nbsp;Wanru Qiu,&nbsp;Liangliang Ping,&nbsp;Hao Yu,&nbsp;Cong Zhou","doi":"10.1155/da/3246717","DOIUrl":"https://doi.org/10.1155/da/3246717","url":null,"abstract":"<div>\u0000 <p><b>Objectives:</b> Existing research by machine learning analysis based on neuroimaging in major depressive disorder (MDD) is limited. This study intends to investigate the integrity of white matter in patients with MDD using diffusion tensor imaging (DTI) combining machine learning approaches and to develop a model to differentiate MDD patients from healthy controls (HCs).</p>\u0000 <p><b>Materials and Methods:</b> Clinical and neuroimaging data were collected from 60 MDD patients and 52 HCs. The tract-based spatial statistics (TBSS) and automated fiber quantification (AFQ) techniques were employed to analyze DTI data. Differences in diffusion metrics were then used in a support vector machine (SVM) model to determine the most significant features for distinguishing MDD patients from HC.</p>\u0000 <p><b>Results:</b> No significant differences were observed in the TBSS between two groups. The AFQ analysis revealed that MDD patients exhibited reduced axial diffusivity (AD) and fractional anisotropy (FA) in specific segments of nerve fibers. The combined FA + AD model demonstrated better predictive performance with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.833 and a predictive accuracy of up to 85.00%, surpassing models utilizing single FA or AD metrics.</p>\u0000 <p><b>Conclusion:</b> DTI combined with machine learning distinguished MDD patients through specific white matter alterations, underscoring the role of microstructural connectivity in depression pathology.</p>\u0000 </div>","PeriodicalId":55179,"journal":{"name":"Depression and Anxiety","volume":"2025 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/da/3246717","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143404721","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":"Determining PTSD, Anxiety, and Depression Levels in Individuals Migrating From Ukraine to Türkiye due to the War","authors":"Songül Duran","doi":"10.1155/da/3869391","DOIUrl":"https://doi.org/10.1155/da/3869391","url":null,"abstract":"<div>\u0000 <p>The aim of this study is to determine the levels of post-traumatic stress disorder (PTSD), anxiety, and depression in individuals who migrated to Türkiye from Ukraine due to the ongoing conflict in their home country. In the study, 194 individuals were reached by using the Socio-Demographic Information Form, the Generalized Anxiety Disorder-7 (GAD-7), the Patient Health Questionnaire-9 (PHQ-9), and the Impact of Event Scale-Revised (IES-R). It was determined that 38.1% of the participants were in the risk group for GAD, 21.6% were at risk for severe depression, and 7.2% were at risk for very severe depression. Being young and having a low level of education increases the risk of depression and PTSD. Overall, the participants were found to be at risk for PTSD.</p>\u0000 </div>","PeriodicalId":55179,"journal":{"name":"Depression and Anxiety","volume":"2025 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/da/3869391","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143389097","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":"Drift-Diffusion Modeling of Attentional Shifting During Frustration: Associations With State Frustration and Trait Irritability","authors":"Nellia Bellaert,&nbsp;Peter J. Castagna,&nbsp;Christen M. Deveney,&nbsp;Michael J. Crowley,&nbsp;Wan-Ling Tseng","doi":"10.1155/da/1618163","DOIUrl":"https://doi.org/10.1155/da/1618163","url":null,"abstract":"<div>\u0000 <p>Irritability, a prevalent and impairing symptom in many mood and anxiety disorders, is characterized by aberrant responses to frustrative nonreward. Past research investigating irritability have used a cued-attention task with rigged feedback, the affective Posner task (AP), to induce frustrative nonreward. Previous studies have not been successful in linking differences in self-reported irritability to traditional AP metrics (i.e., reaction time and accuracy). Computational modeling, via the estimation of parameters reflecting latent cognitive processes, may provide insight into the cognitive mechanisms of irritability and reveal potential targets for mechanism-based interventions. This study applied the drift-diffusion model (DDM) to the AP to determine if DDM parameters are associated with individual differences in irritability. Young adults (<i>N</i> = 152, <i>M</i>_age = 20.93 ± 1.98) completed the AP and self-reported state frustration and trait irritability. Multiple linear regressions were used to evaluate whether DDM parameters better predict state frustration and trait irritability over traditional AP metrics. Higher state frustration was predicted by lower decision threshold during the frustration block and larger decrease in this parameter between nonfrustration and frustration blocks, over traditional AP metrics. These findings demonstrate the potential of applying the DDM to study frustrative nonreward in healthy adult populations. The utility of DDM awaits validation in populations with clinical levels of irritability.</p>\u0000 </div>","PeriodicalId":55179,"journal":{"name":"Depression and Anxiety","volume":"2025 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/da/1618163","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143380599","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":"Intra- and Extracellular White Matter Micromorphology Predict the Antidepressant Effects of Transcranial Magnetic Stimulation in Patients With Major Depressive Disorder","authors":"Sirui Wang,&nbsp;Xiaochen Zhang,&nbsp;Gai Kong,&nbsp;Yuhao Lin,&nbsp;Tianyuan Zhu,&nbsp;Zhenying Qian,&nbsp;Lihua Xu,&nbsp;Huiru Cui,&nbsp;Jijun Wang,&nbsp;Hui Li,&nbsp;Yingying Tang","doi":"10.1155/da/1749444","DOIUrl":"https://doi.org/10.1155/da/1749444","url":null,"abstract":"<div>\u0000 <p><b>Background:</b> Transcranial magnetic stimulation (TMS) is a widely used treatment for major depressive disorders (MDD). However, its physiological effects remain unclear, and its efficacy varies among patients. Functional connectivity (FC) within MDD-related networks has shown potential for predicting TMS efficacy. White matter (WM) micromorphology contributes to these connections and may provide new insights into the prediction of TMS effects and its antidepressant mechanism in MDD, which has not been thoroughly investigated. Therefore, this study aimed to identify potential predictors of TMS efficacy using whole-brain WM microstructural characteristics.</p>\u0000 <p><b>Methods:</b> This retrospective study included 41 patients with MDD who completed 20-session TMS treatments. We examined intra- and extracellular WM using neurite orientation dispersion and density imaging (NODDI). We examined the correlations between pre-TMS whole-brain WM measures and the reduction in Montgomery–Åsberg Depression Rating Scale (MADRS) scores after TMS, as well as the longitudinal changes in regional WM measures correlated with MADRS reduction.</p>\u0000 <p><b>Results:</b> The pre-TMS intracellular neurite density index (NDI) within the bilateral internal capsule (IC), right posterior corona radiata (PCR), right superior corona radiata (SCR), corpus callosum (CC), and bilateral posterior thalamic radiation (PTR) were positively associated with the reduction in MADRS scores. The pre-TMS extracellular free-water fraction (FWF) within the bilateral IC, splenium of the CC, and right SCR was significantly related to the reduction in MADRS scores. The FWF within the left posterior limb of the IC, left PCR, and left SCR decreased after TMS treatment.</p>\u0000 <p><b>Limitations:</b> The study’s findings cannot rule out the potential effects of concurrent pharmaceutical therapies, as a control group not receiving TMS treatment was not included.</p>\u0000 <p><b>Conclusions:</b> Regional NDI and FWF values at baseline could predict TMS efficacy in patients with MDD. Reducing the extracellular FWF in the left hemisphere may be a potential therapeutic mechanism of TMS in MDD.</p>\u0000 </div>","PeriodicalId":55179,"journal":{"name":"Depression and Anxiety","volume":"2025 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/da/1749444","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143110878","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":"Identification of Subthreshold Depression Based on fNIRS–VFT Functional Connectivity: A Machine Learning Approach","authors":"Lin Li,&nbsp;Jingxuan Liu,&nbsp;Yifan Zheng,&nbsp;Chengchao Shi,&nbsp;Wenting Bai","doi":"10.1155/da/7645625","DOIUrl":"https://doi.org/10.1155/da/7645625","url":null,"abstract":"<div>\u0000 <p><b>Background:</b> Subthreshold depression (SD) is regarded as a prodromal stage and a substantial risk factor for major depressive disorder (MDD). The timely identification of SD is of critical clinical significance. This study aimed to develop a machine learning (ML) classification model for the identification of individuals with SD using functional near-infrared spectroscopic imaging (fNIRS) and the verbal fluency task (VFT).</p>\u0000 <p><b>Methods:</b> This study recruited a total of 70 participants with SD and matched 73 healthy controls (HCs) to differentiate between the two groups based on functional connectivity (FC) features during fNIRS–VFT, using an interpretable random forest (RF) classification model.</p>\u0000 <p><b>Results:</b> The RF model demonstrated an area under the curve (AUC) of 0.77, an accuracy (ACC) of 75.86%, a sensitivity of 75.00%, a specificity of 76.00% and an F1 score of 0.75 for identifying participants with SD. The highest-ranked FC features, in terms of importance, were identified between Channel (CH) 26 (the right frontal eye fields (FEFs)) and CH 30 (the right FEF), CH 3 (the left premotor and supplementary motor cortex (PMC-and-SMA)) and CH 42 (the right PMC-and-SMA), as well as CH 26 (the right FEF) and CH 32 (the right primary somatosensory cortex (PSC)).</p>\u0000 <p><b>Conclusion:</b> The RF model has the capacity to effectively classify individuals with SD efficacy based on the abnormal FC features of fNIRS–VFT, particularly in the right FEF, bilateral PSC and right PMC-and-SMA. The findings of this study have provided a foundation for large-scale screening of SD populations, offering promising opportunities for the early diagnosis and prevention of MDD.</p>\u0000 </div>","PeriodicalId":55179,"journal":{"name":"Depression and Anxiety","volume":"2025 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/da/7645625","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143121305","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":"Global Scientific Trends on Anxiety Disorders in the Early Twenty-First Century: A Data-Driven Bibliometric Analysis","authors":"Zhongqing Wang,&nbsp;Fang Wang,&nbsp;Zhiying Cui,&nbsp;Fanyu Meng,&nbsp;Haoxin Guo,&nbsp;Bailing Tian,&nbsp;Nannan Li","doi":"10.1155/da/5541514","DOIUrl":"https://doi.org/10.1155/da/5541514","url":null,"abstract":"<div>\u0000 <p><b>Objective:</b> Interest in the study of anxiety disorders is growing rapidly. However, there is still a lack of comprehensive bibliometrics research in measuring and analyzing global scientific publications. The aim of this article is to review the current research status and trends of anxiety disorders worldwide through bibliometrics and to provide reliable support for future in-depth research.</p>\u0000 <p><b>Methods:</b> In this bibliometric study, we utilized VOSviewer to evaluate the Web of Science Core Collection (WoSCC) publications and to build visualizing maps to analyze the research progress on this topic between January 1, 2000, and August 7, 2024.</p>\u0000 <p><b>Results:</b> Up to August 7, 2024, the study included a total of 67,386 English original articles and review articles published in 4054 journals by 206,496 authors from 164 countries/regions. The United States was a leader in articles, researchers, and institutions in the field of anxiety disorders. Using cluster analysis, the keywords were divided into five major clusters: (1) etiology and pathogenesis, (2) clinical classification and interventions, (3) comorbidity, (4) anxiety caused by the COVID-19 pandemic and specific groups, and (5) anxiety disorders in children and adolescents.</p>\u0000 <p><b>Conclusion:</b> Molecular and neural circuit mechanisms, adolescent psychological problems, objective indicators of diagnosis and classification, and technology-assisted therapy are still the focus of future research. The findings provide a comprehensive overview of anxiety disorder research, which may help physicians, researchers, and local authorities and community health staff to more fully understand trends and influence in the field and highlight under-researched areas, which could be the basis for future research.</p>\u0000 </div>","PeriodicalId":55179,"journal":{"name":"Depression and Anxiety","volume":"2025 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/da/5541514","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143120320","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":"Artificial Intelligence–Based Psychotherapeutic Intervention on Psychological Outcomes: A Meta-Analysis and Meta-Regression","authors":"Ying Lau,&nbsp;Wei How Darryl Ang,&nbsp;Wen Wei Ang,&nbsp;Patrick Cheong-Iao Pang,&nbsp;Sai Ho Wong,&nbsp;Kin Sun Chan","doi":"10.1155/da/8930012","DOIUrl":"https://doi.org/10.1155/da/8930012","url":null,"abstract":"<div>\u0000 <p><b>Background:</b> Artificial intelligence (AI)–based psychotherapeutic interventions may bring a new and viable approach to expanding psychiatric care. However, evidence of their effectiveness remains scarce. We evaluated the efficacy of AI-based psychotherapeutic interventions on depressive, anxiety, and stress symptoms at postintervention and follow-up assessments.</p>\u0000 <p><b>Methods:</b> A three-step comprehensive search via nine electronic databases (PubMed, Embase, CINAHL, Cochrane Library, Scopus, IEEE Xplore, Web of Science, PsycINFO, and ProQuest Dissertations and Theses) was performed.</p>\u0000 <p><b>Results:</b> Thirty randomized controlled trials (RCTs) in 31 publications involving 6100 participants from nine countries were included. The majority (79.1%) of trials with intention-to-treat analysis but less than half (48.6%) of trials with perprotocol analysis were graded as low risk. Meta-analyses showed that interventions significantly reduced depressive symptoms at the postintervention assessment (<i>t</i> = −4.40, <i>p</i> = 0.001) with medium effect size (<i>g</i> = −0.54, 95% CI: −0.79 to −0.29) and at 6–12 months of assessment (<i>t</i> = −3.14, <i>p</i> &lt; 0.016) with small effect size (<i>g</i> = −0.23, 95% CI: −0.40 to −0.06) in comparison with comparators. Our subgroup analyses revealed that the depressed participants had a significantly larger effect size in reducing depressive symptoms than participants with stress and other conditions. At postintervention and follow-up assessments, we discovered that AI-based psychotherapeutic interventions did not significantly alter anxiety, stress, and the total scores of depressive, anxiety, and stress symptoms in comparison to comparators. The random-effects univariate meta-regression did not identify any significant covariates for depressive and anxiety symptoms at postintervention. The certainty of evidence ranged between moderate and very low.</p>\u0000 <p><b>Conclusions:</b> AI-based psychotherapeutic interventions can be used in addition to usual treatments for reducing depressive symptoms. Well-designed RCTs with long-term follow-up data are warranted.</p>\u0000 <p><b>Trial Registration:</b> CRD42022330228</p>\u0000 </div>","PeriodicalId":55179,"journal":{"name":"Depression and Anxiety","volume":"2025 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/da/8930012","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143119667","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":"How Does Virtual Reality Exposure Treatment Change the Brain Function of Acrophobia Patients? A Randomized Controlled Trial","authors":"Meilin Guo,&nbsp;Yongjun Chen,&nbsp;Ya Xie,&nbsp;Yumin Zhang,&nbsp;Aoran Xu,&nbsp;Guojia Zhang,&nbsp;Jingya Kong,&nbsp;Yuan Zhong,&nbsp;Chun Wang","doi":"10.1155/da/7823251","DOIUrl":"https://doi.org/10.1155/da/7823251","url":null,"abstract":"<div>\u0000 <p><b>Background:</b> Virtual reality exposure therapy (VRET), an innovative form of exposure therapy (ET), has been demonstrated to be effective in treating acrophobia. However, its neural mechanisms of action and how it differs from traditional imaginal exposure therapy (IET) remain unclear. This study utilized resting-state functional magnetic resonance imaging (fMRI) to investigate the effects of VRET on brain activity in acrophobic patients and to explore the potential mechanisms underlying its therapeutic action.</p>\u0000 <p><b>Method:</b> Fifty patients with acrophobia were randomly assigned to either an experimental group (25 patients) or a control group (25 patients) based on different treatments. The experimental group received VRET, while the control group received conventional IET. A mixed-design repeated-measures analysis of variance (ANOVA) was performed on the whole brain to identify brain regions affected by the intervention. Both groups of patients underwent treatment twice a week for 3 weeks. fMRI scans were performed for all patients at baseline and after treatment to facilitate a comparison of clinical effects at the end of the treatment period. The degree centrality (DC) values of the blood oxygenation level dependent signals across the entire brain were analyzed. A mixed-design repeated-measures ANOVA was conducted on the pre- and post-intervention data to identify brain regions affected by the intervention. The degree of symptom improvement was assessed using self-report measures, including the Acrophobia Questionnaire (AQ), the Attitude Toward Heights Questionnaire, the Behavior Avoidance Test, and the 7-item Generalized Anxiety Disorder Scale. These assessments were correlated with pre- and post-intervention differences in brain activity. Additionally, a functional connectivity (FC) analysis was conducted to identify any atypical connectivity patterns following the ET.</p>\u0000 <p><b>Results:</b> There was a significant positive correlation between the change in scores on the AQ and the right middle temporal gyrus (MTG) (<i>r</i> = 0.442, <i>p</i> = 0.045). After VRET, DC values in the right calcarine, MTG, cuneus, and precuneus were decreased (<i>p</i> &lt; 0.005), while DC values in the postcentral gyrus decreased after IET (<i>p</i> &lt; 0.05). Additionally, reduced FC between the right MTG and both the right medial superior frontal gyrus and the left MTG was observed in acrophobia patients following VRET. In the IET group, reduced FC between the left MTG and the left superior temporal gyrus was found (<i>p</i> &lt; 0.005).</p>\u0000 <p><b>Conclusion:</b> Preliminary results suggest that VRET may improve abnormal brain activity in acrophobia by modulating the activity of the default mode network and the primary visual cortex.</p>\u0000 </div>","PeriodicalId":55179,"journal":{"name":"Depression and Anxiety","volume":"2025 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/da/7823251","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143118813","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}