Journal of affective disorders最新文献_第5页

Machine learning and SHAP-based interpretation of dietary antioxidants’ impact on comorbid MDD and suicidal ideation 机器学习和基于shap的饮食抗氧化剂对共病性重度抑郁症和自杀意念影响的解释

IF 4.9 2区医学 Q1 CLINICAL NEUROLOGY

Journal of affective disorders

Pub Date : 2026-05-15 Epub Date: 2026-01-26 DOI: 10.1016/j.jad.2026.121252

Zhiwei Xu , Jintao Wang , Ting Chang , Yajing Li , Hongling Jia , Xuecheng Zhang

Objective

To develop and validate a machine learning model for predicting major depressive disorder (MDD) with suicidal ideation (SI) by incorporating dietary antioxidants, and to elucidate the specific contribution of these antioxidants in the prediction.

Methods

Data were obtained from NHANES 2007–2010. Dietary antioxidants, including vitamins, minerals, and polyphenols, were the primary predictors. Demographic, lifestyle, and health-related variables were also included. Collinear variables were removed, class imbalance was corrected, and data were normalized prior to modeling. Twelve machine learning algorithms were compared using a systematic benchmarking protocol within the sklearn framework: Random Forest (RF), LightGBM, AdaBoost, XGBoost, Extra Trees, CatBoost, Gradient Boosting Decision Trees, Support Vector Machine, Decision Tree, Gaussian Naïve Bayes, Stochastic Gradient Descent, and K-Nearest Neighbors. SHapley Additive exPlanation (SHAP) values were calculated to interpret feature contributions within the best-performing model.

Results

A total of 9306 participants were included, of whom 247 with MDD comorbid with SI. After preprocessing, 31 dietary antioxidants and 9 demographic and health-related variables were retained for modeling. The RF classifier achieved the highest performance with an accuracy of 83%, precision of 0.825, recall of 0.838, area under the ROC curve of 0.927, and F1 score of 0.831. SHAP analysis identified vitamin C, kaempferol, myricetin, peonidin, luteolin, eriodictyol, hesperetin, pelargonidin, and zinc as the most influential predictors.

Conclusion

The RF model exhibited superior predictive capability for comorbid MDD and SI. SHAP analysis highlighted the critical roles of dietary antioxidants, particularly vitamin C and kaempferol, in predicting these outcomes.

目的建立并验证一种结合膳食抗氧化剂预测重度抑郁症（MDD）合并自杀意念（SI）的机器学习模型，并阐明这些抗氧化剂在预测中的具体作用。方法数据来源于NHANES 2007-2010。饮食抗氧化剂，包括维生素、矿物质和多酚，是主要的预测因素。人口统计、生活方式和健康相关变量也包括在内。共线性变量被删除，类别不平衡被纠正，数据在建模之前被归一化。在sklearn框架内使用系统基准协议比较了12种机器学习算法：随机森林（RF）， LightGBM, AdaBoost, XGBoost, Extra Trees, CatBoost，梯度增强决策树，支持向量机，决策树，高斯Naïve贝叶斯，随机梯度下降和k -近邻。计算SHapley加性解释（SHAP）值来解释最佳表现模型中的特征贡献。结果共纳入9306例受试者，其中重度抑郁症合并SI 247例。预处理后，保留31种膳食抗氧化剂和9种人口统计学和健康相关变量进行建模。RF分类器的准确率为83%，精密度为0.825，召回率为0.838，ROC曲线下面积为0.927，F1得分为0.831，达到了最高的性能。SHAP分析发现，维生素C、山奈酚、杨梅素、芍药苷、木犀草素、周周醇、橙皮苷、天竺葵苷和锌是影响最大的预测因子。结论射频模型对MDD和SI合并症有较好的预测能力。SHAP分析强调了饮食抗氧化剂的关键作用，特别是维生素C和山奈酚，在预测这些结果。

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引用次数: 0

The longitudinal association between living in socially fragmented neighbourhoods and psychological distress among middle aged adults in Brisbane, Australia 在澳大利亚布里斯班的中年人中，生活在社会支离破碎的社区和心理困扰之间的纵向联系。

IF 4.9 2区医学 Q1 CLINICAL NEUROLOGY

Journal of affective disorders

Pub Date : 2026-05-15 Epub Date: 2026-01-31 DOI: 10.1016/j.jad.2026.121318

Vincent Learnihan , Nasser Bagheri , Gavin Turrell

Objective

Addressing social determinants of affective disorders is increasingly recognised as a major priority in mental health. This longitudinal study aimed to examine the effect of neighbourhood social fragmentation on psychological distress among mid-to-older aged (40–65 yrs) community dwelling men and women over time.

Methods

We analysed changes in psychological distress across four time points (2009–2016) using data from HABITAT, a population-representative longitudinal study of adults aged 40–65 in Brisbane, Australia. The analytic sample included 2902 men and 3950 women who completed the Kessler 6 scale. A novel longitudinal neighbourhood social fragmentation index was developed using Australian census data. Sex-specific mixed effects regression models were used to assess associations, adjusting for individual, household, and neighbourhood-level covariates.

Results

Men living in more socially fragmented neighbourhoods had higher mean scores of psychological distress (β = 0.66, 95% CI: 0.28 to 1.04). The effect of neighbourhood social fragmentation on psychological distress among men was stable over time. A trend of higher distress scores for women occurred as the level of neighbourhood social fragmentation increased, however this was not found to be statistically significant (β = 0.25, 95% CI: −0.11 to 0.60).

Conclusion

In the context of ageing populations and rising mental health burden, neighbourhood social fragmentation may be a key factor in developing targeted mental health prevention strategies. Our findings suggest differences between men and women in the relationship between neighbourhood social fragmentation and psychological distress; these differences may reflect gendered social experiences. Promoting community cohesion in more socially fragmented areas may help to reduce psychological distress, particularly among men.

目标：解决情感障碍的社会决定因素日益被认为是精神卫生的一个主要优先事项。本纵向研究旨在研究社区社会分裂对中老年（40-65 岁）社区男性和女性长期心理困扰的影响。方法：我们使用来自生境的数据，分析了四个时间点（2009-2016）心理困扰的变化，生境是一项针对澳大利亚布里斯班40-65岁成年人的人口代表性纵向研究。分析样本包括完成Kessler 6量表的2902名男性和3950名女性。利用澳大利亚人口普查数据开发了一种新的纵向邻里社会碎片化指数。使用性别特异性混合效应回归模型来评估相关性，调整个人、家庭和社区水平的协变量。结果：生活在社交更分散的社区的男性心理困扰的平均得分更高（β = 0.66,95% CI: 0.28至1.04）。随着时间的推移，邻里社会分裂对男性心理困扰的影响是稳定的。随着社区社会分裂程度的增加，女性的痛苦得分呈上升趋势，但这在统计学上并不显著（β = 0.25,95% CI: -0.11至0.60）。结论：在人口老龄化和心理健康负担增加的背景下，社区社会分裂可能是制定有针对性的心理健康预防策略的关键因素。我们的研究结果表明，男性和女性在社区社会分裂与心理困扰的关系上存在差异；这些差异可能反映了社会经历的性别差异。在社会较为分散的地区促进社区凝聚力可能有助于减少心理困扰，尤其是男性的心理困扰。

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引用次数: 0

Association between striatal gray matter volume and suicidal ideation in patients with major depressive disorder: Evidence from the REST-meta-MDD project 重度抑郁症患者纹状体灰质体积与自杀意念之间的关系：来自REST-meta-MDD项目的证据

IF 4.9 2区医学 Q1 CLINICAL NEUROLOGY

Journal of affective disorders

Pub Date : 2026-05-15 Epub Date: 2026-01-31 DOI: 10.1016/j.jad.2026.121262

Luyao Xia , Dongmei Wang , Huixia Zhou , Xiang Yang Zhang

Background

Suicidal ideation (SI) is a common complication of major depressive disorder (MDD), but its neural mechanisms remain unclear. Striatum (STR) is abnormal in patients with MDD and may serve as a biomarker for SI. The aim of this study was to investigate the potential of gray matter volume (GMV) as a biomarker of SI, for which no similar study exists.

Methods

Based on the REST-meta-MDD project, this study included 235 healthy controls (HCs) and 246 MDD patients, of whom 123 had SI and 123 did not. We analyzed magnetic resonance imaging (MRI) data using two-sample t-tests and Pearson's correlation. Analyses were corrected for multiple testing using 1000 permutations and threshold-free cluster enhancement (TFCE) correction. Depressive symptoms were assessed using the 17-item Hamilton Depression Rating Scale (HAMD).

Results

GMV in the right STR of MDD patients was significantly smaller than that of HCs (p < 0.05). GMV in the right STR was higher in MDD patients with SI than in those without SI, and this difference remained significant after adjustment for multiple covariates (p < 0.05). GMV in bilateral STR was associated with SI, and SI was included in the regression equation for SI-related GMV in all clusters (p < 0.05).

Conclusions

Our study suggests a statistically significant correlation between GMV in STR and SI, suggesting that this structural feature may be valuable for studying SI in MDD patients.

背景：自杀意念（SI）是重度抑郁症（MDD）的常见并发症，但其神经机制尚不清楚。纹状体（STR）在重度抑郁症患者中是异常的，可能作为SI的生物标志物。本研究的目的是探讨灰质体积（GMV）作为SI生物标志物的潜力，目前还没有类似的研究。方法：基于REST-meta-MDD项目，本研究纳入235名健康对照（hc）和246名MDD患者，其中123名患有SI， 123名未患SI。我们使用双样本t检验和Pearson相关分析磁共振成像（MRI）数据。使用1000个排列和无阈值聚类增强（TFCE）校正对多次测试进行分析校正。采用17项汉密尔顿抑郁评定量表（HAMD）评估抑郁症状。结果：MDD患者右侧STR的GMV明显小于hcc （p ）。结论：本研究提示STR的GMV与SI之间存在显著的统计学相关性，提示这一结构特征可能对MDD患者SI的研究有价值。

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引用次数: 0

Effects of aerobic exercise on depression-like behaviors and hippocampal transcriptomics in CSDS-induced adolescent mice 有氧运动对csds诱导的青春期小鼠抑郁样行为和海马转录组学的影响。

IF 4.9 2区医学 Q1 CLINICAL NEUROLOGY

Journal of affective disorders

Pub Date : 2026-05-15 Epub Date: 2026-01-31 DOI: 10.1016/j.jad.2026.121280

Linna Sha , Rong Xiang , Ting Yu , Jinyu Zhou , Tao Han , Yangdan Zhong , Qin Deng , Jiaojiao Hou , Bin Yang , Xiaomeng Li , Lishi Zhang , Jinyao Chen , Xia Jiang

Background

Adolescence is a critical period of vulnerability to depression, yet most evidence for the antidepressant effects of exercise derives from adult models. This study aims to investigate the effects of aerobic exercise and identify its associated molecular changes in the adolescent depression mouse model.

Methods

A chronic social defeat stress (CSDS) model was established in adolescent male C57BL/6J mice to induce depression-like behaviors. Thirty-six mice were randomly assigned to three groups: control (CG), model (MG), and model plus exercise (ME). MG and ME mice were subjected to CSDS for two weeks (days 7–20), while ME mice additionally received three weeks of aerobic treadmill training covering the whole CSDS period (days 0–20). Behavioral tests were conducted on days 21–26, followed by the collection of serum and hippocampal tissues for molecular, histological, and transcriptomic analyses.

Results

CSDS induced significant depression-like behaviors in adolescent male mice, including social avoidance, anhedonia, and behavioral despair, all of which were effectively alleviated by aerobic exercise. Aerobic exercise appeared to mitigate CSDS-induced neural damage and maintain hippocampal tissue integrity. Moreover, aerobic exercise increased serum levels of serotonin. Transcriptomic analysis identified 587 differentially expressed genes (DEGs). Among these genes, 59 overlapping DEGs were regulated by both CSDS and exercise, and were enriched in carbohydrate metabolism and cholinergic signaling pathways.

Conclusions

Aerobic exercise alleviates depression-like behaviors in adolescent male mice, possibly by modulating hippocampal gene expression – especially in cholinergic and carbohydrate metabolism pathways – which provides potential clues to how exercise could influence peripheral monoamine levels and hippocampal structural integrity. These putative mechanisms require further investigation.

背景：青春期是易患抑郁症的关键时期，然而大多数关于运动抗抑郁作用的证据来自成人模型。本研究旨在探讨有氧运动对青少年抑郁症小鼠模型的影响，并确定其相关的分子变化。方法：建立青春期雄性C57BL/6J小鼠慢性社会失败应激（CSDS）模型，诱导抑郁样行为。将36只小鼠随机分为对照组（CG）、模型组（MG）和模型加运动组（ME）。MG和ME小鼠进行为期两周（第7-20天）的CSDS，而ME小鼠在整个CSDS期间（第0-20天）进行为期三周的有氧跑步机训练。在第21-26天进行行为学测试，随后收集血清和海马组织进行分子、组织学和转录组学分析。结果：CSDS诱导青春期雄性小鼠出现明显的抑郁样行为，包括社交回避、快感缺乏和行为绝望，这些行为均可通过有氧运动有效缓解。有氧运动似乎可以减轻csds引起的神经损伤并维持海马组织的完整性。此外，有氧运动增加血清血清素水平。转录组学分析鉴定出587个差异表达基因（DEGs）。在这些基因中，59个重叠的DEGs受到CSDS和运动的共同调控，并且在碳水化合物代谢和胆碱能信号通路中富集。结论：有氧运动减轻了青春期雄性小鼠的抑郁样行为，可能是通过调节海马基因表达——尤其是胆碱能和碳水化合物代谢途径——这为运动如何影响外周单胺水平和海马结构完整性提供了潜在的线索。这些假定的机制需要进一步调查。

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引用次数: 0

Alcohol misuse as dysfunctional affect regulation: a network analysis of psychopathology across adulthood 酒精滥用作为功能失调的影响调节：成年期精神病理的网络分析。

IF 4.9 2区医学 Q1 CLINICAL NEUROLOGY

Journal of affective disorders

Pub Date : 2026-05-15 Epub Date: 2026-01-28 DOI: 10.1016/j.jad.2026.121290

Marina Zeldovich , Jürgen Fuchshuber , Elke Humer , Human-Friedrich Unterrainer

Background

Alcohol misuse is increasingly understood as a maladaptive form of affect regulation. This study examines the interplay between alcohol misuse, mental health symptoms, and age in a representative sample of Austrian adults, using network analysis to model these associations.

Methods

Data from 2007 participants (49% women; average age of 48.2 ± 16 years), representative of the general Austrian population in terms of age, gender, federal state, and educational level, were analyzed using validated instruments: the CAGE questionnaire for alcohol misuse, PHQ-9 for depression, GAD-7 for anxiety, ISI-7 for insomnia, and PSS-4 for stress. Network analysis using a regularized Gaussian graphical model was conducted to explore interrelations among these variables alongside age. Centrality, stability, and gender-based network comparisons were assessed.

Results

Overall, 21% of participants screened positive for alcohol misuse (CAGE ≥2). Bivariate analyses showed that individuals with suspected alcohol dependence reported higher levels of depression, anxiety, stress, and insomnia, and were younger. The regularized network analysis revealed a robust connection between alcohol misuse and depressive symptoms. Depression and anxiety emerged as central nodes in the network, while age was negatively associated with both alcohol misuse and psychopathological burden. No significant gender differences in network structure or global strength were found.

Conclusions

Findings support the conceptualization of alcohol misuse as a dysfunctional affect regulation strategy, particularly in relation to depressive symptoms. These results align with transdiagnostic models of emotional dysregulation and reinforce the need for preventive interventions focused on emotion regulation skills, particularly among younger adults and individuals with comorbid mental health conditions.

背景：酒精滥用越来越被理解为一种情绪调节的不适应形式。本研究在奥地利成年人的代表性样本中考察了酒精滥用、心理健康症状和年龄之间的相互作用，使用网络分析来模拟这些关联。方法：2007年参与者的数据（49%为女性，平均年龄为48.2 ± 16 岁），在年龄、性别、联邦州和教育水平方面代表了奥地利的一般人群，使用经过验证的工具进行分析：酒精滥用的CAGE问卷，抑郁的PHQ-9，焦虑的GAD-7，失眠的si -7和压力的PSS-4。使用正则化高斯图形模型进行网络分析，以探索这些变量与年龄之间的相互关系。评估中心性、稳定性和基于性别的网络比较。结果：总体而言，21%的参与者酒精滥用筛查呈阳性（CAGE≥2）。双变量分析显示，疑似酒精依赖的个体报告的抑郁、焦虑、压力和失眠水平更高，而且年龄更小。规范化网络分析揭示了酒精滥用与抑郁症状之间的紧密联系。抑郁和焦虑是网络的中心节点，而年龄与酒精滥用和精神病理负担呈负相关。在网络结构和整体强度方面没有发现显著的性别差异。结论：研究结果支持酒精滥用作为一种功能失调影响调节策略的概念化，特别是与抑郁症状有关。这些结果与情绪失调的跨诊断模型相一致，并加强了对情绪调节技能的预防性干预的需求，特别是在年轻人和患有共病精神健康状况的个体中。

{"title":"Alcohol misuse as dysfunctional affect regulation: a network analysis of psychopathology across adulthood","authors":"Marina Zeldovich , Jürgen Fuchshuber , Elke Humer , Human-Friedrich Unterrainer","doi":"10.1016/j.jad.2026.121290","DOIUrl":"10.1016/j.jad.2026.121290","url":null,"abstract":"<div><h3>Background</h3><div>Alcohol misuse is increasingly understood as a maladaptive form of affect regulation. This study examines the interplay between alcohol misuse, mental health symptoms, and age in a representative sample of Austrian adults, using network analysis to model these associations.</div></div><div><h3>Methods</h3><div>Data from 2007 participants (49% women; average age of 48.2 ± 16 years), representative of the general Austrian population in terms of age, gender, federal state, and educational level, were analyzed using validated instruments: the CAGE questionnaire for alcohol misuse, PHQ-9 for depression, GAD-7 for anxiety, ISI-7 for insomnia, and PSS-4 for stress. Network analysis using a regularized Gaussian graphical model was conducted to explore interrelations among these variables alongside age. Centrality, stability, and gender-based network comparisons were assessed.</div></div><div><h3>Results</h3><div>Overall, 21% of participants screened positive for alcohol misuse (CAGE ≥2). Bivariate analyses showed that individuals with suspected alcohol dependence reported higher levels of depression, anxiety, stress, and insomnia, and were younger. The regularized network analysis revealed a robust connection between alcohol misuse and depressive symptoms. Depression and anxiety emerged as central nodes in the network, while age was negatively associated with both alcohol misuse and psychopathological burden. No significant gender differences in network structure or global strength were found.</div></div><div><h3>Conclusions</h3><div>Findings support the conceptualization of alcohol misuse as a dysfunctional affect regulation strategy, particularly in relation to depressive symptoms. These results align with transdiagnostic models of emotional dysregulation and reinforce the need for preventive interventions focused on emotion regulation skills, particularly among younger adults and individuals with comorbid mental health conditions.</div></div>","PeriodicalId":14963,"journal":{"name":"Journal of affective disorders","volume":"401 ","pages":"Article 121290"},"PeriodicalIF":4.9,"publicationDate":"2026-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146093187","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}

引用次数: 0

Longitudinal changes in smoking habits over 20 years and late-life depressive symptoms: The Singapore Chinese Health Study 20 年以上吸烟习惯的纵向变化与晚年抑郁症状：新加坡华人健康研究

IF 4.9 2区医学 Q1 CLINICAL NEUROLOGY

Journal of affective disorders

Pub Date : 2026-05-15 Epub Date: 2026-01-12 DOI: 10.1016/j.jad.2026.121177

Huiqi Li , Aizhen Jin , An Pan , Woon-Puay Koh

Objectives

Its uncertain how rapidly the detrimental effects of smoking on depression decline after cessation. Hence, we investigated the association between changes in smoking habits and late-life depressive symptoms.

Methods

We used data from 5247 men in the Singapore Chinese Health Study. Smoking was assessed at baseline (mean age of 52.5 years; 1993–98), follow-up 1 (mean age of 58.7 years; 1999–2004), follow-up 2 (mean age of 65.5 years; 2006–10) and follow-up 3 interviews (mean age of 72.8 years; 2014–16). Participants were categorized according to smoking status at baseline and subsequent follow-ups. Late-life depressive symptoms were measured using the 15-item Geriatric Depression Scale at follow-up 3. Logistic regression models were used to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) of depressive symptoms.

Results

Compared to never-smokers, while the multivariable-adjusted OR (95% CI) for depression was 2.19 (1.78–2.70) in persistent smokers, this risk was reduced progressively with increasing duration of cessation. Specifically, the OR (95% CI) was 1.39 (1.03–1.88) in those quitting for <10 years and substantially reduced to 1.11 (0.86–1.44) in those quitting for ≥30 years. Expectantly, earlier age at cessation was associated with a greater reduction in the likelihood; the OR (95% CI) was 1.39 (1.08–1.79) in those quitting 60 years and older, whereas it was 1.06 (0.79–1.43) in those quitting before 40 years old compared to never-smokers.

Conclusions

The deleterious effects of smoking on late-life depression were substantially reduced only after sustained quitting for ≥30 years or quitting before 40 years old.

目的：目前还不确定戒烟后吸烟对抑郁症的有害影响下降的速度有多快。因此，我们调查了吸烟习惯的改变与晚年抑郁症状之间的关系。方法：我们使用新加坡华人健康研究中5247名男性的数据。在基线（平均年龄52.5 岁；1993-98年）、随访1次（平均年龄58.7 岁；1999-2004年）、随访2次（平均年龄65.5 岁；2006-10年）和随访3次（平均年龄72.8 岁；2014-16年）进行吸烟评估。参与者根据基线时的吸烟状况和随后的随访情况进行分类。在随访3时使用15项老年抑郁量表测量晚年抑郁症状。采用Logistic回归模型估计抑郁症状的比值比（ORs）和95%置信区间（CIs）。结果：与从不吸烟者相比，持续吸烟者抑郁症的多变量校正OR （95% CI）为2.19(1.78-2.70)，随着戒烟时间的延长，这种风险逐渐降低。具体来说，戒烟者的OR （95% CI）为1.39（1.03-1.88）。结论：只有持续戒烟≥30 年或在40 岁之前戒烟，吸烟对晚年抑郁症的有害影响才会显著降低。

{"title":"Longitudinal changes in smoking habits over 20 years and late-life depressive symptoms: The Singapore Chinese Health Study","authors":"Huiqi Li , Aizhen Jin , An Pan , Woon-Puay Koh","doi":"10.1016/j.jad.2026.121177","DOIUrl":"10.1016/j.jad.2026.121177","url":null,"abstract":"<div><h3>Objectives</h3><div>Its uncertain how rapidly the detrimental effects of smoking on depression decline after cessation. Hence, we investigated the association between changes in smoking habits and late-life depressive symptoms.</div></div><div><h3>Methods</h3><div>We used data from 5247 men in the Singapore Chinese Health Study. Smoking was assessed at baseline (mean age of 52.5 years; 1993–98), follow-up 1 (mean age of 58.7 years; 1999–2004), follow-up 2 (mean age of 65.5 years; 2006–10) and follow-up 3 interviews (mean age of 72.8 years; 2014–16). Participants were categorized according to smoking status at baseline and subsequent follow-ups. Late-life depressive symptoms were measured using the 15-item Geriatric Depression Scale at follow-up 3. Logistic regression models were used to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) of depressive symptoms.</div></div><div><h3>Results</h3><div>Compared to never-smokers, while the multivariable-adjusted OR (95% CI) for depression was 2.19 (1.78–2.70) in persistent smokers, this risk was reduced progressively with increasing duration of cessation. Specifically, the OR (95% CI) was 1.39 (1.03–1.88) in those quitting for <10 years and substantially reduced to 1.11 (0.86–1.44) in those quitting for ≥30 years. Expectantly, earlier age at cessation was associated with a greater reduction in the likelihood; the OR (95% CI) was 1.39 (1.08–1.79) in those quitting 60 years and older, whereas it was 1.06 (0.79–1.43) in those quitting before 40 years old compared to never-smokers.</div></div><div><h3>Conclusions</h3><div>The deleterious effects of smoking on late-life depression were substantially reduced only after sustained quitting for ≥30 years or quitting before 40 years old.</div></div>","PeriodicalId":14963,"journal":{"name":"Journal of affective disorders","volume":"401 ","pages":"Article 121177"},"PeriodicalIF":4.9,"publicationDate":"2026-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145984626","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}

引用次数: 0

Secular trend of self-injurious behaviors in PTSD and the impact of the COVID-19 pandemic: A quasi-experimental study 创伤后应激障碍患者自伤行为的长期趋势及新冠疫情的影响：一项准实验研究

IF 4.9 2区医学 Q1 CLINICAL NEUROLOGY

Journal of affective disorders

Pub Date : 2026-05-15 Epub Date: 2026-01-30 DOI: 10.1016/j.jad.2026.121316

Kwanghyun Kim

Introduction

This study aims to assess the secular trend of self-injurious behavior (SIB) in PTSD and evaluate the effect of the COVID-19 pandemic on SIB in PTSD.

Methods

The Nationwide Inpatient Sample (NIS) database 2017–2022 was used to analyze the secular trend of SIB in PTSD (N = 35,892,123). The ICD-10-CM code was used to define PTSD, suicide attempts, non-suicidal self-injury (NSSI), and psychiatric comorbidities. Logistic regression was used to estimate the odds ratio of SIB in PTSD and assess the association between potential covariates and SIB. An interrupted time series analysis (ITSA) model was applied to assess the long-term and short-term effect of the COVID-19 pandemic on SIB. Stratification by age was conducted to compare the secular trend of SIB by age.

Results

Both suicide attempts and NSSI were more prevalent in PTSD patients than in control. Logistic regression showed that patients with PTSD had higher odds of SIB, which were significantly attenuated after adjusting for covariates. A constant decline in the prevalence of suicide attempts was detected, but the rate of decrease was attenuated during the COVID-19 pandemic. In contrast, the prevalence of NSSI acutely increased after the onset of COVID-19 but gradually regressed to the baseline prevalence as time progressed. The changes in SIB during the pandemic were most prominent in participants aged 17 or younger.

Discussion

The COVID-19 pandemic had both immediate and sustained effects on SIB in PTSD. SIB in younger generations was most prominently influenced by the pandemic.

前言：本研究旨在评估PTSD患者自伤行为（SIB）的长期趋势，并评估COVID-19大流行对PTSD患者自伤行为（SIB）的影响。方法：采用2017-2022年全国住院患者样本（NIS）数据库分析PTSD患者SIB的长期趋势（N = 35,892,123）。ICD-10-CM代码用于定义PTSD、自杀未遂、非自杀性自伤（NSSI）和精神合并症。采用Logistic回归估计创伤后应激障碍中SIB的优势比，并评估潜在协变量与SIB的相关性。采用中断时间序列分析（ITSA）模型评估COVID-19大流行对SIB的长期和短期影响。按年龄分层，比较按年龄SIB的长期趋势。结果：PTSD患者的自杀企图和自伤发生率均高于对照组。Logistic回归结果显示，PTSD患者发生SIB的几率较高，调整协变量后显著降低。发现自杀企图发生率持续下降，但在2019冠状病毒病大流行期间下降速度有所减缓。相比之下，自伤发生率在COVID-19发病后急剧上升，但随着时间的推移逐渐回落到基线患病率。流感大流行期间SIB的变化在17岁或以下的参与者中最为突出。讨论：COVID-19大流行对PTSD患者的SIB有直接和持续的影响。年轻一代的SIB受大流行的影响最为显著。

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引用次数: 0

Higher physical activity is associated with reduced odds of depressive symptoms among university students: A meta-analysis of over 66,000 participants 一项对66,000多名参与者进行的荟萃分析显示，大学生中更多的体育活动与抑郁症状的几率降低有关。

IF 4.9 2区医学 Q1 CLINICAL NEUROLOGY

Journal of affective disorders

Pub Date : 2026-05-15 Epub Date: 2026-01-30 DOI: 10.1016/j.jad.2026.121319

Aline Josiane Waclawovsky , Jênifer de Oliveira , Carolina Piccolo de Carvalho , Maria Eduarda Adornes , Eduarda dos Santos , Sebastian Wolf , Carlos Cristi-Montero , Megan Teychenne , Brendon Stubbs , Andrea Camaz Deslandes , Felipe Barreto Schuch

Depression is highly prevalent among university students, who also exhibit low levels of physical activity. Although physical activity is associated with a lower likelihood of depressive symptoms, the magnitude of its effect in this population has not been systematically assessed. This study reviewed and performed a meta-analysis of the association between physical activity and depressive symptoms in university students. The Embase, PubMed, Web of Science, PsycINFO, and SPORTDiscus databases were searched from inception to January 24, 2025, for relevant studies. Random-effects meta-analyses were used to calculate adjusted (aOR) and unadjusted (OR) odds ratios for depressive symptoms based on physical activity levels. The protocol was registered in PROSPERO (CRD42024591429). Twenty-two studies, involving 66,683 students (median age: 21 years, 56.5% female), were included. Students with higher levels of physical activity had lower odds of depressive symptoms compared to those with lower levels (adjusted OR = 0.614, 95% CI: 0.540–0.698, I² = 47.5%). Subgroup analyses revealed no differences between studies conducted during or outside the COVID-19 pandemic. Among students in health sciences programs, higher physical activity was associated with a 34% lower likelihood of depressive symptoms (adjusted OR = 0.66, 95% CI: 0.49–0.88, I² = 33.2%). These findings indicate that increased physical activity is associated with a lower likelihood of depressive symptoms in university students, supporting its promotion as a mental health intervention.

抑郁症在大学生中非常普遍，他们也表现出低水平的体育活动。虽然体育活动与抑郁症状的可能性较低有关，但其在该人群中的影响程度尚未得到系统评估。本研究回顾并进行了大学生体育活动与抑郁症状之间关系的荟萃分析。检索了Embase、PubMed、Web of Science、PsycINFO和SPORTDiscus数据库，从项目启动到2025年1月24日进行相关研究。随机效应荟萃分析用于计算基于身体活动水平的抑郁症状的调整（aOR）和未调整（OR）优势比。该协议已在PROSPERO （CRD42024591429）中注册。纳入22项研究，涉及66,683名学生（中位年龄：21 岁，56.5%为女性）。体育活动水平较高的学生与体育活动水平较低的学生相比，出现抑郁症状的几率较低（调整后OR = 0.614,95% CI: 0.540-0.698, I2 = 47.5%）。亚组分析显示，在COVID-19大流行期间或之外进行的研究之间没有差异。在健康科学专业的学生中，较高的体育活动与抑郁症状的可能性降低34%相关（调整后的OR = 0.66,95% CI: 0.49-0.88, I2 = 33.2%）。这些发现表明，增加体育活动与大学生抑郁症状的可能性降低有关，支持其作为一种心理健康干预措施的推广。

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引用次数: 0

Right orbitofrontal cortex rTMS targets anxiety, not depressive, symptoms in first-episode schizophrenia 右眼窝额叶皮层rTMS针对首发精神分裂症的焦虑症状，而不是抑郁症状。

IF 4.9 2区医学 Q1 CLINICAL NEUROLOGY

Journal of affective disorders

Pub Date : 2026-05-15 Epub Date: 2026-01-29 DOI: 10.1016/j.jad.2026.121300

YiYi Yang , Qiang Hu , Xiong Jiao , YanYan Wei , HuiRu Cui , XiaoChen Tang , LiHua Xu , YingYing Tang , HaiChun Liu , Jin Gao , LingYun Zeng , ChunBo Li , JiJun Wang , TianHong Zhang

Background

Anxiety is highly prevalent and undertreated in first-episode schizophrenia(FES), but repetitive transcranial magnetic stimulation(rTMS) data for this comorbidity are scarce. The orbitofrontal cortex(OFC) is a key anxiety-regulating node, supporting its potential as a target. This study aimed to explore 1-Hz right OFC-rTMS's symptom-specific effects on FES mood.

Methods

This is a secondary analysis of a randomized controlled trial. Participants were drug-naive FES patients randomized to the active rTMS group(n = 51) or sham group(n = 45). All completed 20 intervention sessions, 20 sessions of active OFC-rTMS or sham, with 4-week follow-up, initiating oral olanzapine(10–20 mg/day) concurrently with the first rTMS session. Mood symptoms were assessed using the 24-item Hamilton Depression Rating Scale(HAMD) and the 14-item Hamilton Anxiety Rating Scale(HAMA). Psychopathological symptoms were assessed using the Positive and Negative Syndrome Scale(PANSS). The main outcome was the changes in HAMD and HAMA scores from baseline to 2 weeks and 4 weeks.

Results

The active group showed greater PANSS total(t = −3.260, p = 0.002; Cohen's d = 0.672) and subscale improvements vs. the sham group. Repeated-measures ANOVA(controlling for covariates) revealed significant Time×Group interactions for HAMA total(F = 4.698, p = 0.010; partial η² = 0.059) and psychic anxiety(F = 5.735, p = 0.004; partial η² = 0.072), but not somatic anxiety. For HAMD, only anxiety/somatization(F = 8.397, p = 0.031; partial η² = 0.099) and cognitive impairment(F = 6.240, p = 0.002; partial η² = 0.076) showed interactions, with no specific effects on overall depressive symptoms. In the sham group, HAMD anxiety/somatization correlated with all PANSS subscales(r = 0.311–0.477, p < 0.05), but this correlation was absent in the active group(all p > 0.05).

Conclusions

Right OFC-rTMS improves FES anxiety (not depression), supporting it as a targeted non-pharmacological option.

背景：焦虑症在首发精神分裂症（FES）中非常普遍且治疗不足，但重复经颅磁刺激（rTMS）治疗这种合并症的数据很少。眼窝前额皮质（OFC）是一个关键的焦虑调节节点，支持其作为目标的潜力。本研究旨在探讨1 hz右OFC-rTMS对FES情绪的症状特异性影响。方法：这是一项随机对照试验的二次分析。参与者是未使用药物的FES患者，随机分为活跃rTMS组（n = 51）或假手术组（n = 45）。所有患者均完成了20次干预，20次OFC-rTMS或假rTMS，随访4周，在第一次rTMS治疗的同时开始口服奥氮平（10-20 mg/天）。采用24项汉密尔顿抑郁评定量表（HAMD）和14项汉密尔顿焦虑评定量表（HAMA）评估情绪症状。采用阳性和阴性综合征量表（PANSS）评估精神病理症状。主要结局是HAMD和HAMA评分从基线到2 周和4 周的变化。结果：与假手术组相比，治疗组PANSS总分（t = -3.260,p = 0.002;Cohen’s d = 0.672）和亚量表改善明显。协变量重复测量方差分析(控制)透露大量的时间×组交互哈马总(F = 4.698,p = 0.010;部分η2 = 0.059)和精神焦虑(F = 5.735,p = 0.004;部分η2 = 0.072),但不是躯体焦虑。仅供HAMD、焦虑/躯体化(F = 8.397,p = 0.031;部分η2 = 0.099)和认知障碍(F = 6.240,p = 0.002;部分η2 = 0.076)显示交互,没有特定的对整体抑郁症状的影响。假手术组HAMD焦虑/躯体化与PANSS各分量表相关（r = 0.311-0.477,p  0.05）。结论：右OFC-rTMS可改善FES焦虑（而非抑郁），支持其作为有针对性的非药物选择。

{"title":"Right orbitofrontal cortex rTMS targets anxiety, not depressive, symptoms in first-episode schizophrenia","authors":"YiYi Yang , Qiang Hu , Xiong Jiao , YanYan Wei , HuiRu Cui , XiaoChen Tang , LiHua Xu , YingYing Tang , HaiChun Liu , Jin Gao , LingYun Zeng , ChunBo Li , JiJun Wang , TianHong Zhang","doi":"10.1016/j.jad.2026.121300","DOIUrl":"10.1016/j.jad.2026.121300","url":null,"abstract":"<div><h3>Background</h3><div>Anxiety is highly prevalent and undertreated in first-episode schizophrenia(FES), but repetitive transcranial magnetic stimulation(rTMS) data for this comorbidity are scarce. The orbitofrontal cortex(OFC) is a key anxiety-regulating node, supporting its potential as a target. This study aimed to explore 1-Hz right OFC-rTMS's symptom-specific effects on FES mood.</div></div><div><h3>Methods</h3><div>This is a secondary analysis of a randomized controlled trial. Participants were drug-naive FES patients randomized to the active rTMS group(<em>n</em> = 51) or sham group(<em>n</em> = 45). All completed 20 intervention sessions, 20 sessions of active OFC-rTMS or sham, with 4-week follow-up, initiating oral olanzapine(10–20 mg/day) concurrently with the first rTMS session. Mood symptoms were assessed using the 24-item Hamilton Depression Rating Scale(HAMD) and the 14-item Hamilton Anxiety Rating Scale(HAMA). Psychopathological symptoms were assessed using the Positive and Negative Syndrome Scale(PANSS). The main outcome was the changes in HAMD and HAMA scores from baseline to 2 weeks and 4 weeks.</div></div><div><h3>Results</h3><div>The active group showed greater PANSS total(<em>t</em> = −3.260, <em>p</em> = 0.002; Cohen's d = 0.672) and subscale improvements vs. the sham group. Repeated-measures ANOVA(controlling for covariates) revealed significant Time×Group interactions for HAMA total(<em>F</em> = 4.698, <em>p</em> = 0.010; partial η<sup>2</sup> = 0.059) and psychic anxiety(<em>F</em> = 5.735, <em>p</em> = 0.004; partial η<sup>2</sup> = 0.072), but not somatic anxiety. For HAMD, only anxiety/somatization(<em>F</em> = 8.397, <em>p</em> = 0.031; partial η<sup>2</sup> = 0.099) and cognitive impairment(<em>F</em> = 6.240, <em>p</em> = 0.002; partial η<sup>2</sup> = 0.076) showed interactions, with no specific effects on overall depressive symptoms. In the sham group, HAMD anxiety/somatization correlated with all PANSS subscales(<em>r</em> = 0.311–0.477, <em>p</em> < 0.05), but this correlation was absent in the active group(all <em>p</em> > 0.05).</div></div><div><h3>Conclusions</h3><div>Right OFC-rTMS improves FES anxiety (not depression), supporting it as a targeted non-pharmacological option.</div></div>","PeriodicalId":14963,"journal":{"name":"Journal of affective disorders","volume":"401 ","pages":"Article 121300"},"PeriodicalIF":4.9,"publicationDate":"2026-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146097003","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}

引用次数: 0

Development and multi-center validation of a school-home integrated machine learning model for early screening of attention-deficit/hyperactivity disorder in school-aged children 学龄儿童注意缺陷/多动障碍早期筛查的学校-家庭集成机器学习模型的开发和多中心验证

IF 4.9 2区医学 Q1 CLINICAL NEUROLOGY

Journal of affective disorders

Pub Date : 2026-05-15 Epub Date: 2026-01-29 DOI: 10.1016/j.jad.2026.121247

Chunbo Wang , Zhijuan Li , Jiangling Su , Mo Wang , Gaofu Zhang

Background

Attention-deficit/hyperactivity disorder (ADHD) is frequently under-identified in community settings, delaying necessary intervention. This study aimed to develop and validate a multidimensional Early Screening Prediction Model (ESPM-ADHD) for children aged 6 to 18 years, integrating school-home collaborative data.

Methods

A large-scale cross-sectional survey was conducted from January to December 2023 across three distinct regions in China. The dataset was divided into a development cohort (Chongqing, n = 15,085) and two independent external validation cohorts (Shaanxi, n = 7435; Yunnan, n = 4206). Machine learning algorithms, including Random Forest, XGBoost, LightGBM, and Logistic Regression, were trained using 15 selected features. The best-performing model was deployed as a web-based tool.

Results

A total of 26,726 valid questionnaires were analyzed, with an overall ADHD risk prevalence of roughly 2%. Among the tested algorithms, the Random Forest model demonstrated the most robust performance. In external validation, the model maintained high discriminatory power across diverse populations. Specifically, it achieved an AUPRC of 0.298 and an AUROC of 0.929 in the Shaanxi cohort, and an AUPRC of 0.253 and an AUROC of 0.907 in the Yunnan cohort. SHAP analysis identified antisocial behavior, academic performance (native language and math), and daytime sleepiness as the top predictors.

Conclusions

The ESPM-ADHD, constructed using the Random Forest algorithm, effectively identifies children at risk for ADHD by leveraging easily assessable demographic, academic, and somatic indicators. The developed online calculator provides a practical, objective triage tool for clinicians and guardians to facilitate timely referral and diagnosis.

背景：注意缺陷/多动障碍（ADHD）在社区环境中经常被低估，延误了必要的干预。本研究旨在整合学校-家庭协作数据，为6 - 18岁 儿童建立并验证多维早期筛查预测模型（ESPM-ADHD）。方法：于2023年1月至12月在中国三个不同地区进行大规模横断面调查。数据集分为一个开发队列（重庆，n = 15085）和两个独立的外部验证队列（陕西，n = 7435；云南，n = 4206）。机器学习算法，包括随机森林，XGBoost， LightGBM和逻辑回归，使用15个选定的特征进行训练。性能最好的模型被部署为基于web的工具。结果：共分析了26,726份有效问卷，总体ADHD风险患病率约为2%。在所测试的算法中，随机森林模型表现出最强的鲁棒性。在外部验证中，该模型在不同人群中保持较高的歧视性。其中，陕西队列的AUPRC为0.298，AUROC为0.929；云南队列的AUPRC为0.253，AUROC为0.907。SHAP分析发现，反社会行为、学习成绩（母语和数学）和白天嗜睡是最重要的预测因素。结论：使用随机森林算法构建的ESPM-ADHD通过利用易于评估的人口统计学、学术和躯体指标，有效地识别出ADHD风险儿童。开发的在线计算器为临床医生和监护人提供了一个实用、客观的分诊工具，以促进及时的转诊和诊断。

{"title":"Development and multi-center validation of a school-home integrated machine learning model for early screening of attention-deficit/hyperactivity disorder in school-aged children","authors":"Chunbo Wang , Zhijuan Li , Jiangling Su , Mo Wang , Gaofu Zhang","doi":"10.1016/j.jad.2026.121247","DOIUrl":"10.1016/j.jad.2026.121247","url":null,"abstract":"<div><h3>Background</h3><div>Attention-deficit/hyperactivity disorder (ADHD) is frequently under-identified in community settings, delaying necessary intervention. This study aimed to develop and validate a multidimensional Early Screening Prediction Model (ESPM-ADHD) for children aged 6 to 18 years, integrating school-home collaborative data.</div></div><div><h3>Methods</h3><div>A large-scale cross-sectional survey was conducted from January to December 2023 across three distinct regions in China. The dataset was divided into a development cohort (Chongqing, <em>n</em> = 15,085) and two independent external validation cohorts (Shaanxi, <em>n</em> = 7435; Yunnan, <em>n</em> = 4206). Machine learning algorithms, including Random Forest, XGBoost, LightGBM, and Logistic Regression, were trained using 15 selected features. The best-performing model was deployed as a web-based tool.</div></div><div><h3>Results</h3><div>A total of 26,726 valid questionnaires were analyzed, with an overall ADHD risk prevalence of roughly 2%. Among the tested algorithms, the Random Forest model demonstrated the most robust performance. In external validation, the model maintained high discriminatory power across diverse populations. Specifically, it achieved an AUPRC of 0.298 and an AUROC of 0.929 in the Shaanxi cohort, and an AUPRC of 0.253 and an AUROC of 0.907 in the Yunnan cohort. SHAP analysis identified antisocial behavior, academic performance (native language and math), and daytime sleepiness as the top predictors.</div></div><div><h3>Conclusions</h3><div>The ESPM-ADHD, constructed using the Random Forest algorithm, effectively identifies children at risk for ADHD by leveraging easily assessable demographic, academic, and somatic indicators. The developed online calculator provides a practical, objective triage tool for clinicians and guardians to facilitate timely referral and diagnosis.</div></div>","PeriodicalId":14963,"journal":{"name":"Journal of affective disorders","volume":"401 ","pages":"Article 121247"},"PeriodicalIF":4.9,"publicationDate":"2026-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146097011","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}

引用次数: 0