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The influence path of sleep dimension on depression and anxiety in adolescents: the mediating role of academic pressure and the moderating effect of psychological resilience
No full text青少年时期是心理功能迅速发展且精神障碍高发的关键阶段。近年来，睡眠问题与抑郁、焦虑等负性情绪的关系日益受到关注，尤其在学业压力显著增强的社会背景下，这一关系更为复杂。然而，现有研究多采用变量中心的方法，仅揭示变量之间的平均趋势，忽视了青少年内部存在的情绪异质性与个体化差异。本研究基于中国 23,581 名青少年的大样本横断数据，系统探讨睡眠与情绪困扰之间的多路径作用机制，融合聚类分析、潜在剖面分析与结构方程建模等方法，揭示睡眠、学习压力与心理健康之间的交互关系及其调节机制。
首先，研究分析了不同学段青少年在睡眠、情绪困扰（抑郁与焦虑）以及学习压力方面的整体水平与变化趋势。结果表明，随着学段升高，睡眠质量逐渐下降，抑郁与焦虑检出率显著升高，尤其高中生群体呈现出最高风险水平。聚类分析进一步识别出多个具有代表性的睡眠模式，其中严重睡眠问题群体在情绪困扰水平上显著高于其他群体，提示睡眠特征在情绪健康中的重要区分价值。
为进一步刻画青少年情绪问题的群体差异，研究采用潜在剖面分析对抑郁与焦虑症状进行联合分型，识别出低风险组、轻抑郁组、中度抑郁焦虑组以及高风险共病组。多分类逻辑回归显示，主观睡眠质量差、入睡困难、睡眠时间短、日间功能障碍与睡眠障碍是预测高风险情绪状态的重要睡眠指标，尤其夜间觉醒与白天精神困倦对共病组的预测力最强。
在揭示个体心理机制方面，研究构建有调节的中介模型，检验睡眠问题是否通过学习压力影响情绪困扰水平（抑郁与焦虑得分），并进一步引入心理韧性作为调节变量。路径分析结果显示，睡眠问题不仅直接显著预测抑郁与焦虑水平，也通过提升学习压力间接加重情绪困扰。此外，心理韧性对“学习压力→情绪困扰”的路径具有显著负向调节作用，高韧性个体在相同压力下表现出更低的情绪反应，表明其在风险-保护机制中的缓冲效应。简单斜率分析进一步揭示，在低韧性群体中，学习压力对情绪困扰的影响显著增强，提示心理韧性缺乏会加速睡眠问题向情绪障碍的风险转化。
综上所述，本研究从发展阶段、群体类型与个体机制三个维度，综合揭示了青少年睡眠问题与情绪困扰之间的复杂关联路径。结果强调应关注睡眠质量在心理健康中的早期预警价值，学习压力在其中的桥梁作用，以及心理韧性作为关键保护因素的干预潜力，为识别高风险群体、优化多元干预路径提供了实证依据与理论支持。</p
Proactive and Reactive Control and Their Electrophysiological Mechanisms in Patients with Obsessive-Compulsive Disorder
No full text认知控制功能障碍可能是强迫症发病和症状维持的重要因素，具体可分为主动控制和反应控制两方面。主动控制涉及个体在任务执行前预先维持目标并抑制无关信息，而反应控制则是在冲突或干扰出现时，根据情境需求动态调整认知资源以抑制干扰。目前，多数研究通过传统的反应抑制任务评估反应控制，但关于强迫症患者是否存在反应控制缺陷的结论尚未统一。此外，主动控制的研究相对较少，且结果存在不一致。同时，强迫症患者主动控制和反应控制的神经机制尚未明确。因此，本研究以中国强迫症人群为对象，系统探讨其在主动控制和反应控制功能上是否存在损伤，及其背后的神经机制。
研究一采用条件性停止信号任务分离主动控制和反应控制的行为指标，并结合耶鲁-布朗量表评估其与强迫症症状的相关性。结果显示，与健康对照组相比，强迫症患者的主动控制和反应控制能力均存在损伤，且两者之间存在相互促进的关系，即主动控制损伤越严重，反应控制损伤也越明显。然而，这些损伤与强迫症症状严重程度、抑郁及焦虑水平无显著相关性。
研究二通过脑电技术探讨额叶中线 θ 振荡在强迫症患者认知控制损伤中的作用。研究发现，与健康对照组相比，强迫症患者在主动控制相关的早期额叶中线 θ 振荡水平显著较弱。此外，尽管两组在反应控制相关的额叶中线 θ 功率水平上无显著差异，但其神经-行为关联存在显著差异。健康对照组中，额叶中线 θ 功率与抑制率呈正相关，与停止信号反应时间呈负相关；而在强迫症组中，这种关联显著减弱或消失。
综上所述，本研究初步揭示了中国强迫症人群主动和反应控制损伤的行为特征及其神经机制，发现额叶中线 θ 振荡模式异常可能是其损伤的神经基础。研究结果为揭示强迫症认知控制损伤的病理机制提供了新的实验依据，为后续研究奠定了理论基础，并为深入理解强迫症的病理生理机制提供了重要线索。</p
Data-driven classification of narrative speech characteristics in stroke aphasia distinguishes neurological and strategic contributions
No full textNarrative speech deficits are common in post-stroke aphasia, resulting in negative influences on social participation and quality of life. Speech rate, complexity, and informativeness deficits all contribute to narrative speech. Research studies typically (implicitly) assume that these aspects of narrative speech production are a result of cognitive/ neurological impairment, but they may also result from strategic choices made as individuals with aphasia attempt to produce narrative speech. Here, we used data-driven methods to classify aphasic narrative speech patterns and evaluated their predictability from lesion patterns. 76 stroke aphasia patients completed 11 narrative speech production tasks. Quantitative Production Analysis (QPA) and Correct Information Unit (CIU) analysis were used to measure their structural and functional properties. Based on prior work, we selected QPA measures of speech rate (words per minute) and complexity (mean sentence length, inflection index, and auxiliary index) and four CIU measures of informativeness (#CIU, CIU/min, %CIU, #nonCIU). These measures produced two orthogonal dimensions with four orthogonal participant clusters. Comprehensive comparison between clusters revealed that speech rate and complexity were strongly associated with general aphasia severity and total lesion volume, and were predicted by frontoparietal grey matter and dorsal pathway white matter damage. In contrast, informativeness was independent of other behavioral and neurological deficits, and was not predictable from lesion patterns, suggesting that it reflects communication strategy rather than specific neurological impairment. These results provide an important step toward distinguishing neurological and strategic aspects of narrative speech deficits in post-stroke aphasia, with potential implications for treatment approaches that target communication strategies. (c) 2025 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).</p
Achievement Motivation and Performance in Wargames: Creativity as a Mediator
No full textComputer-based wargames provide an experimental platform for studying cognitive antecedents and behavioral outcomes in dynamic scenarios. Our study examines how achievement motivation influence wargame players' performance through the mechanism of creativity. In Study 1, we simplified the achievement motivation scale and revised the creativity scale for wargame contexts in China. After collecting data from students and wargame players (N1 = 300, N2 = 347), we validate their reliability and validity using exploratory and confirmatory factor analyses. Study 2 (N3 = 171) applied these validated scales to analyze the mechanism of creativity between achievement motivation and wargame performance. The results in Study 1 demonstrated that the refined two scales exhibited strong reliability and structural validity. The findings of Study 2 revealed that two types of motivation had different influences on wargame performance. The motivation of hope of success indirectly enhanced wargame performance through increased creativity. In contrast, the motivation of fear of failure reduced creativity and then negatively influenced overall results. Our study advances understanding of achievement motivation in dynamic gaming environments, suggesting that enhancing motivation of hope of success, decreasing motivation of fear of failure, and improving creativity may optimize performance to be more effective.</p
Sensorimotor simulation and distributed processing of biological motion: Insights from healthy and paraplegic adults
No full textThe processing of biological motion (BM), particularly the local motion cues tracing the movements of crucial joints, is vital for social interaction and human survival. While numerous studies have focused on the brain mechanisms underlying BM processing, the contribution of sensorimotor simulation at peripheral effectors remains unclear. In this study, we examined healthy adults and paraplegic spinal cord injury participants to investigate this issue. For healthy adults, both intact BM stimuli and local BM cues without global configuration induced a temporal dilation effect when sitting (sensorimotor simulation accessible), but not when standing (sensorimotor simulation temporarily hindered). In contrast, for participants with permanently hindered sensorimotor simulation, the temporal dilation effect was observed only with intact BM stimuli but not with local BM cues, indicating a robust reliance on sensorimotor simulation during the processing of local BM cues and a selective compensation based on global configuration cues for the permanent loss of sensorimotor simulation. These findings highlight the role of embodied cognition in the distributed processing of biological motion and suggest the importance of selective compensation under damaged sensorimotor circuits
Rapid audiovisual temporal recalibration across children and adults
No full textAudiovisual temporal integration ability, reflected by the size of the temporal binding window (TBW), plays an important role in reading. The audiovisual TBW is not fixed, but dynamically changes during the integration process, this is referred to as rapid temporal recalibration. To investigate the rapid audiovisual temporal recalibration ability across age and its correlation with reading, the present study conducted simultaneity judgment (the index includes Delta PSS and Delta TBW) tasks involving speech (Experiment 1; children: Mage = 10.70, adults: Mage = 24.52) and non-speech (Experiment 2; children: Mage = 10.19, adults: Mage = 24.26) audiovisual stimuli in native Mandarin-Chinese-speaking child and adult groups (n = 36 in each group). Results showed that children's Delta PSS and Delta TBW for speech stimuli were comparable to those of adults. However, when examining trial-by-trial changes in TBW during the integration process, a gap between children and adults was evident. Besides, for non-speech stimuli, children significantly differed from adults in both Delta PSS indicators and the integration process. Moreover, for both children and adults, the correlation and regression analysis showed that the rapid audiovisual temporal recalibration ability of both speech and non-speech stimuli explained reading fluency uniquely after controlling TBW, age, and gender
A study on anxiety and Depression symptoms in women undergoing IVF treatment and their group Hypnosis intervention
No full textThe Association Between College Students' Lifestyle and Anxiety Emotion: A Multidimensional Quantitative Analysis and Validation Based on Machine Learning Models
No full text近年来，大学生心理健康问题日益凸显。世界卫生组织（WHO, 2023）最新数据显示，全球约 35%的大学生存在临床可诊断的焦虑情绪症状，较十年前上升了 40%，中国大学生存在焦虑情绪的风险为 45.28%（青少年心理健康服务扫描报告，2023）。鉴于此，针对大学生焦虑情绪问题实施干预举措已刻不容缓 。
美国生活方式医学学会提出的健康生活方式六大支柱（全食物植物性饮食、 规律身体活动、压力管理、风险物质避免、充足睡眠和积极社交），与大学生日常的生活模式紧密相连、高度契合。基于大学生对这几类生活方式存在客观依存性，探究具体哪些生活方式会影响大学生焦虑情绪，并且影响机制和路径如何，遂成为本研究的科学问题。本研究采用混合研究方法，通过―现象描述→模型验 证→因果推断‖的递进式研究设计，系统考察六大生活方式与大学生焦虑情绪的关系及其动态变化规律。
研究一通过横断面调查，对来自 19 所高校的 32,227 名大学生样本，采用饮 食习惯及行为题项、身体活动等级量表（Physical Activity Rating Scale-3,PARS-3）、 健康促进生活量表（Health Promoting Lifestyle Profile,HPLP）、烟酒使用情况和手机成瘾量表（Mobile Phone Addiction Scale-8, MPAS-8）、匹兹堡睡眠质量指数(Pittsburgh sleep quality index,PSQI)、社会支持评定量表（Social Support Rating Scale, SSRS），分别获取大学生 6 大生活方式数据，用广泛性焦虑情绪障碍量表 （GAD-7）测试大学生的焦虑情绪得分，探讨大学生生活方式因素与大学生焦虑情绪的关系。研究二采用机器学习方法，在算法实现中采用 7:3 的比例对数据集进行分层随机划分，其中训练集包含 22,559 例样本，测试集包含 9,668 例样本，确保模型在不同地域特征的子群体中均具备稳健的预测效能。运用支持向量机（Support Vector Machine-SVM）、逻辑回归（Logistic Regression-LR）、朴素贝叶斯（Naive Bayes-NB）、随机森林（Random Fores-RF）及轻量级梯度提升机(LightGBM)，五种算法构建大学生焦虑情绪预测模型，识别出预测大学生焦虑情绪的风险因子，验证研究一的结果。研究三采用纵向追踪设计，对同一批大学 生的部分样本(N=853)在 2 个月后再进行同样的数据调查，使用向量自回归模型、交叉滞后模型和前后测数据的差值分析，探讨生活方式重要变量对大学生焦虑情绪的因果影响及其动态变化。
研究一发现，睡眠质量（反向计分，得分越高表示睡眠质量越差）、手机依赖与大学生焦虑情绪显著正相关，饮食偏好和行为、规律身体活动、压力管理和社会支持均与大学生焦虑情绪显著负相关。二元逻辑回结归果显示睡眠质量（OR=1.627）和手机依赖（OR=1.071）是大学生焦虑情绪发生的风险因素，睡眠质量得分每增加 1 分，大学生焦虑情绪可能增加 62.7%，手机依赖组的大学生焦虑情绪是非依赖组的近 2 倍（k=1.98）；而压力管理（OR=0.982）和社会支持 （OR=0.981）对大学生焦虑情绪有显著保护作用，高水平的压力管理能力可使大学生焦虑情绪降低 53.8%（焦虑情绪得分从 4.98→2.40）。研究二的结果表明， 基于机器学习的大学生焦虑情绪识别模型中，随机森林算法最优且适合本研究。手机依赖、社会支持、日间障碍、睡眠障碍、压力管理以及主观睡眠质量，均为预测大学生焦虑情绪的关键因素。其中，日间障碍、睡眠障碍和主观睡眠质量属于睡眠质量的子维度。综合来看，睡眠质量对大学生焦虑情绪的预测具有重要作用，贡献度约为 19%。此外，手机依赖（贡献度 11%）、社会支持（贡献度约 8%）以及压力管理（贡献度约 6%）同样是预测大学生焦虑情绪的关键因素， 这与研究一的结果一致。研究三显示，睡眠质量、手机依赖、压力管理、社会支持以及大学生焦虑情绪均呈现出显著的时间稳定性（β 取值范围为 0.222 - 0.521）。在这些因素中，大学生焦虑情绪的自我延续性最为突出，其 β 值达到 0.519 。睡眠质量与大学生焦虑情绪存在双向强化关系，睡眠质量既是大学生焦 虑情绪的强预测因子，也是大学生焦虑情绪的结果（即大学生焦虑情绪导致失眠），手机依赖单项促进大学生焦虑情绪，而社会支持通过增强压力管理（β=0.10）和 健康饮食（β=0.14）可缓解大学生焦虑情绪。
基于上述研究结果，得出如下结论：（1）睡眠质量、手机依赖、压力管理与社会支持显著影响大学生焦虑情绪。（2）睡眠质量和手机依赖是风险因素，压力管理和社会支持为保护因素。这四项因素对大学生焦虑情绪的预测贡献度分 别为：睡眠质量约 19%、手机依赖约 11%、压力管理约 6%、社会支持约 8%， 是大学生焦虑情绪的主要预测因子。（3）而手机依赖（β=0.22）和大学生焦虑 情绪的自我强化效应构成主要风险路径。睡眠质量与大学生焦虑情绪存在双向强化关系，睡眠质量既是大学生焦虑情绪的强预测因子，也是大学生焦虑情绪的结果，社会支持通过增强压力管理（β=0.10）和健康饮食（β=0.14）发挥保护作用。
本研究在大学生群体中探究生活方式多维因素与大学生焦虑情绪的关联机制，旨在为高校在预防大学生焦虑情绪以及临床干预大学生焦虑情绪方面提供科 学视角。</p
Influence of climate change beliefs on adolescent food saving behavior mechanisms mediating environmental concerns
No full textClimate change is a global environmental issue, and climate change beliefs have a substantial infuence on adolescent pro-environmental behavior. Ensuring sustainable consumption and production models (Goal 12) and taking urgent action to address climate change and its infuence (Goal 13) are explicitly stated in the United Nations Sustainable Development Goals. In this research, we make a large-sample survey in middle schools, Beijing. As a result of convenience sampling, 2016 valid questionnaires were collected (male students = 993, aged between 12 and 14 years). Multiple linear regressions and mediation models were used to test the efect of climate change beliefs (climate change occurrence, climate change attribution, and climate change risk perception) on adolescent food saving behavior and the intermediation of environmental concerns. The research fnding that (1) climate change beliefs signifcantly and positively predicted adolescent food saving behavior in these areas: climate change occurrence, climate change attribution, and climate change risk perception, and (2) environmental concerns mediated the efect of climate change beliefs on the food saving behavior of secondary school students. The fndings have enlightenment for policymaking and the education sector. The education sector should enhance adolescents’ correct understanding of climate change by adopting certain activities and educational strategies, thereby reducing food waste behavior, cultivating a sense of conservation, and further enhancing adolescents’ sense of social responsibility to contribute to environmental protection and sustainable development.</p
TTFNet: Temporal-Frequency Features Fusion Network for Speech based Automatic Depression Recognition and Assessment
No full textRelated studies have revealed that the phonological features of depressed patients are different from those of healthy individuals. With the increasing prevalence of depression, objective and convenient early screening is necessary. To this end, we propose an automatic depression detection method based on hybrid speech features extracted by deep learning, dubbed as TTFNet. Firstly, to effectively excavate the intrinsic relationship among multidimensional dynamic features in the frequency domain, the Mel spectrogram of raw speech and its related derivatives are encoded into quaternion representation. Then, the innovatively designed quaternion VisionLSTM is utilized to capture their synergistic effects. Simultaneously, we integrate sLSTM with the pre-trained wav2vec 2.0 model to fully acquire the temporal features. In addition, to further exploit the complementarity between temporal and frequency features, we design an XConformer block for cross-sequence interactions, which ingeniously combines self-attention mechanisms and convolutional modules. The designed XCFF fusion module, based on the XConformer block, enables multi-level interactions between frequency-domain and temporal-domain, thereby enhancing generalization ability of the proposed model. Extensive experiments conducted on the AVEC 2013, AVEC 2014, DAIC-WOZ and E-DAIC datasets demonstrate that our method outperforms current state-of-the-art methods in both depression recognition and severity prediction tasks.</p
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