Institute of Psychology, Chinese Academy of Sciences
Institutional Repository of Institute of Psychology, CASNot a member yet
28529 research outputs found
Sort by
Relationship between paternal co-parenting conflict and adolescent non-suicidal selfinjury:chain mediating effect of maternal negative parenting and adolescent shame
No full text目的 探讨父亲共同养育冲突与青少年非自杀性自伤（non-suicidal self-injury, NSSI）的关系，以及母亲消极教养和青少年羞耻感在其中的中介作用。方法 采用共同养育关系量表、父母教养方式与维度问卷、中学生羞耻感量表和自伤行为量表，对548名青少年及其母亲进行调查。采用SPSS 26.0软件进行数据分析，使用AMOS软件构建链式中介模型并使用Bootstrap抽样方法进行中介效应检验。结果 相关分析结果显示，父亲共同养育冲突、母亲消极教养、青少年羞耻感和青少年NSSI，两两之间均呈显著正相关（均P<0.01）。中介效应分析结果显示：青少年羞耻感在父亲共同养育冲突与青少年NSSI之间的中介作用显著，效应值为0.089(95%CI:0.009～0.155)，占总效应的26.33%；母亲消极教养和青少年羞耻感在父亲共同养育冲突与NSSI之间的链式中介作用显著，效应值为0.080(95%CI:0.037～0.149)，占总效应的23.67%。结论 父亲共同养育冲突通过青少年羞耻感的独立中介作用，以及母亲消极教养与羞耻感共同产生的链式中介效应，影响青少年的NSSI行为。</p
Heterogeneous Graph Model for Psychological Support Oriented Towards Mental Health Detection
No full text在线心理健康论坛已经成为心理健康服务的重要载体，从海量帖子中检测出有心理健康问题的帖子是心理干预的基础.充分利用求助者的社交关系有利于判断其心理健康状态，然而，现有模型大都依赖显式的社交关系，没有关注医患（支持者和求助者）之间基于患者经历、症状成因、自我认知以及心理支持专长所形成的心理支持关系.以自杀意念为检测对象，提出帖子-用户交互心理支持异质图（post-user psychological support heterogeneous graph，PU-PSHG）来表示在线心理健康论坛中求助者和支持者发布的帖子语义和医患关系.基于PU-PSHG提出一种图增强的自杀意念检测模型（graph-enhanced suicide ideation detection，GSID）.首先，基于心理支持关系定义用户对用户、用户对帖子的2种元路径语义，构建包含用户和帖子的PU-PSHG，并采用DeepWalk算法从PU-PSHG中学习医患关系或社群关系.然后，通过关系表征学习心理支持关系的表示，基于异质关系融合帖子语义和医患关系.最后根据帖子的表示进行自杀意念强度分类.在CLPsych2017共享任务上的实验结果表明，GSID模型与现有的方法相比具有更好的性能.在Non-green F1，All F1，All Acc指标上相比于C-GraphSAGE基准模型提高7.8%，4.8%，1.4%.消融实验发现，去除PU-PSHG中帖子与帖子的回复关系、用户对帖子的心理支持关系、用户对用户的心理支持关系，Non-green F1分别下降3.04%，3.80%，6.17%.</p
Evidence of the application of the circle of security intervention in improving the mental health of parents and children
No full text基于依恋理论的安全感圆环(COS)干预在全球范围内广泛应用于不同文化和人口群体中，并取得显著成效。COS干预通过增强照顾者对儿童情感需求的敏感性和响应能力，不仅改善了儿童与照顾者的关系，增强了儿童的依恋安全性、社会情感功能和行为调节能力等，还显著增加了照顾者的敏感性，降低了其压力水平，改善了其情绪调节能力，提升了照顾者的自我效能感和反思能力等。鉴于此，结合中国的心理健康需求，推广本土化的安全感圆环干预对构建中国儿童安全型依恋和加强亲子关系具有重要意义。</p
Exercise addiction:prevalence and theoretical model
No full text运动通常被认为有益于身心健康，但过量运动也会增加成瘾的风险。相较于运动产生的诸多益处，其可能引发的不良后果往往未受到足够关注。该文在辨析“强迫运动”“运动依赖”“运动成瘾”相关概念的基础上，介绍现有运动成瘾的测量方式，并回顾了运动成瘾的发生率与地域、性别、年龄、运动类型和运动量的关系。此外，该文还梳理了运动成瘾的潜在发生机制，包括交感神经唤醒假说、认知评估假说和运动成瘾的四阶段理论模型。目前，国内对运动成瘾现象的认识尚显不足，有必要在未来的工作中提高大众对运动成瘾特征及其危害的认识。在理论研究方面，后续研究可以采用纵向研究设计，结合多种研究手段，进一步探究运动成瘾的发生率和可能危害。</p
High-vs.low-stake choices in life:How does modernization predict the multidimensional shifts of individualism in China
No full text个体主义的变迁一直广受学界关注。然而,现有文献中关于中国个体主义变迁的研究出现了矛盾的结果。本文指出,这可能是由于不同研究采用的个体主义测量指标不同所致。进一步,本文认为可将人们在日常生活中的个体主义实践分为两类：个体主义重选择(high-stake choices,涉及高机会成本)和个体主义轻选择(low-stake choices,涉及低机会成本),并认为现代化对个体主义重选择的影响大于对个体主义轻选择的影响。研究1通过一项问卷调查(N=312)检验中国民众对不同生活选择重大性的主观感知。结果发现,是否结婚、是否离婚、是否要孩子、是否与父母分开住等4项选择与给新生儿(男、女)取名等两项选择存在显著差异,显示出前者属于个体主义重选择,后者为个体主义轻选择。研究2通过分析中国26省30年的面板数据发现：1)中国各省的个体主义,包括重选择和轻选择,总体呈现上升趋势,且现代化显著正向预测两类个体主义;2)但相较于个体主义轻选择,现代化对个体主义重选择的预测力更强,预测趋势的省际差异更小。本研究通过将个体主义的测量分类,为重新审视中国内部乃至全球的个体主义变迁研究提供了一个新的理论视角。</p
系统推进社会心理服务体系建设
No full text当前，我国社会心理服务体系建设面临多重短板：资源分布不均，专业人才供给不足，服务成效受制于污名化、边缘化与形式化，本土化实证研究不足。为此，亟须推进社会心理服务体系的系统性建设：强化政策保障与顶层设计，构建多层次服务网络，“高度专业+深度融合”并举培养人才，将心理健康服务融入日常机制，提升国民心理健康素养特别是枢纽人群的能力，注重科学方法并加强效果评估。</p
热梗4:拒绝注目，“偷感”很重
No full text<正>生活实例李丽最近和朋友们一起去一处网红景点打卡。到了目的地，她迫不及待地想拍几张照片留作纪念。然而，当她准备拍照时，却发现周围人来人往，她顿时感到浑身不自在，原本想好的拍照姿势也变得僵硬起来。最后，她让朋友匆匆按了几下快门，便赶紧躲到一旁，仿佛自己做了什么见不得人的事。在办公室里，她也总是小心翼翼。每次和同事交流时，生怕自己的话引起别人的注意，即使是正常讨论工作，她也常常低着头，语速飞快。</p
Beyond the sound: Uncovering the distinct neural mechanisms of ERAN and MMN in music perception
No full textThe early right anterior negativity (ERAN) is an event-related potential commonly attributed to music-specific syntactic processing. An alternative account, however, regards ERAN as a subtype of mismatch negativity (MMN), a generalized neural response to auditory deviations. The present study employed time-generalized multivariate pattern analysis (MVPA) and representational similarity analysis (RSA) to examine whether ERAN and MMN-including physical MMN (phMMN) and abstract-feature MMN (afMMN)-reflect shared or distinct neurocognitive processes. Cross-condition decoding revealed that classifiers trained on afMMN data accurately classified phMMN trials and vice versa, whereas classifiers trained on ERAN failed to classify MMN trials (afMMN or phMMN) effectively. Additional RSA supported this dissociation, with theoretical models assuming independence between MMN and ERAN better fitting the neural data. These results convergently suggest that the ERAN is functionally and neurologically distinct from MMN, shedding light on the nature of musical syntactic processing. As well, by integrating MVPA and RSA, we introduce a novel methodological framework for investigating the neurocognitive processing of music.</p
Automating Social Science: LLMs vs. Human Experts in Variable Relationship Identification
No full textEmpirical research in social psychology centers on formulating testable hypotheses about variable relationships. However, the ability of human researchers to synthesize vast datasets and model intricate relationships is limited. Thus, this study evaluates the capacity of large language models (LLMs; Qwen2.5, Llama 3.1, and GPT-4) to identify variable relationships in social psychology, assessing their reasoning capabilities relative to both domain experts and non-domain experts. Therefore, we collected 56 meta-analyses of social psychology published in 2024, from which we extracted 247 variable relationships. We tasked LLMs and human experts to infer variable relationships based on variable definitions and compared their inferences with relationships reported in the meta-analyses, while also examining the impact of task difficulty, self-reported confidence levels, and relationship type on model performance. Our findings indicated that LLMs and domain experts performed similarly in identifying simple variable relationships (e.g., linear relationships and difference tests). However, the identification of more complex relationships, particularly moderating effects, presented a challenge for both. Furthermore, domain expertise significantly enhanced identification accuracy. Although a correlation was observed between model confidence and accuracy, it was not a strong predictor. Increased task complexity consistently reduced the performance of all LLMs. This study empirically examines the reasoning capabilities of LLMs, suggesting potential roles and limitations of algorithmic tools in social science, providing new evidence for data-driven academic practices
How Priority Incentives Impact Organ Donation Registration Intention and Related Behavior in China
No full textThe scarcity of human transplant organs in China underscores the need for improved public engagement in organ donation. In this study, we examined a cognitive-noncognitive dual pathway model of organ donation registration (ODR). Based on this model, we explored the efficacy and underlying mechanism of priority incentives, a strategy that gives priority to receive an organ to those who register to donate, in promoting ODR. Two online studies involving 1,632 non-donor Chinese adults were conducted. Study 1 used the dual pathway model to measure the effect of cognitive factors (CF) (i.e., attitude and subjective norm) and noncognitive affective factors (NF) (i.e., ick and jink) on ODR intention and related behavior. Study 2 manipulated priority incentives to examine its effect on ODR intention and related behavior and the cognitive-noncognitive pathways underpinning how it works. Both studies provided support for the structural validity of the dual pathway model. Study 1 found that ODR intention can be predicted by both CF and NF, while ODR-related behavior was solely predicted by NF. Study 2 showed that offering priority incentives can enhance ODR intention. Its indirect effect on ODR-related behavior was mediated through the path from CF to ODR intention. These results bridge a gap in understanding mechanisms of incentives toward ODR and have practical implications for improving ODR rates
Access Repository Dashboard
Do you manage Institutional Repository of Institute of Psychology, CAS? Access insider analytics, issue reports and manage access to outputs from your repository in the CORE Repository Dashboard!