Next Issue

2026, Volume 34 Issue 7 Previous Issue   
---
Conceptual Framework
Meta-Analysis
Regular Articles


For Selected:

Download Citations EndNote Ris BibTeX

Toggle Thumbnails

Conceptual Framework

Select

From degradation to empowerment: Mechanisms of AIGC pollution and intervention strategies LIU Xiaochen, DENG Lingfei, WU Xianjiao, WU Ning 2026, 34 (7):  1109-1126.  doi: 10.3724/SP.J.1042.2026.1109 Abstract ( 106 )   PDF (872KB) ( 136 )   Peer Review Comments The rapid advancement of generative artificial intelligence (GenAI) has fueled an unprecedented surge of AI-generated content (AIGC) within the digital content economy. Accompanying this expansion, the large-scale diffusion of low-quality AIGC has given rise to a form of informational “pollution,” posing potential threats to platform credibility, user trust, and ecosystem sustainability. Although this phenomenon has attracted growing attention, its underlying psychological mechanisms and governance implications remain insufficiently theorized. Drawing on the psychological processes embedded in human-GenAI interaction and adopting a nested Stimulus-Organism-Response (SOR) framework, this study develops a multi-level theoretical account of AIGC pollution through a structured “cause-effect-intervention” logic across three interrelated sub-studies. The first sub-study theorizes how GenAI’s technological affordances may paradoxically contribute to low-quality content production. Rather than assuming that technological advancement inherently enhances output quality, this study argues that quality variance is primarily rooted in users’ psychological responses during the content creation process. In a content economy characterized by accelerated production cycles and traffic-driven monetization incentives, GenAI’s core affordances—ease of use, rapid generation, and iterative refinement—can be conceptualized as salient technological stimuli. These stimuli are theorized to reshape contributors’ cognitive evaluations and motivational orientations. Specifically, the study proposes that GenAI’s efficiency may intensify users’ pursuit of instant gratification while simultaneously elevating perceived self-efficacy. The heightened orientation toward immediacy may reduce willingness to invest additional effort in content refinement, whereas inflated self-efficacy may decrease perceived necessity for deep cognitive engagement. Together, these psychological dynamics are theorized to diminish contributors’ cognitive effort in content development, thereby increasing the likelihood of insufficient deliberation and low-quality AIGC production. This sub-study establishes the micro-foundational organism mechanism that is proposed to initiate the pollution cycle. Building on this foundation, the second sub-study conceptualizes low-quality AIGC, once disseminated, as a new environmental stimulus within the platform ecosystem. The framework theorizes its effects on two key actors in the content economy: content audiences and other contributors. For audiences, exposure to low-quality AIGC may violate technological expectations regarding GenAI’s reliability as well as social expectations concerning creators’ responsibility and value orientation. Such expectation violations are theorized to generate cognitive dissonance, which may subsequently influence information processing patterns, engagement intentions, and consumption decisions. These psychological and behavioral adjustments are expected to shape downstream outcomes in the content economy, particularly in marketing performance. For other contributors, the presence of low-quality AIGC may function as a social signal that activates perceived identity threat and perceptions of platform unfairness. These threat perceptions are theorized to influence subsequent content creation strategies, potentially leading contributors either to increase effort to differentiate their work or to conform to prevailing low-effort norms. The model further proposes that these responses are contingent upon contributors’ motivational orientations, such that intrinsic motivation is likely to encourage differentiation through higher cognitive investment, whereas extrinsic motivation may increase susceptibility to conformity. Recognizing the systemic implications of AIGC pollution, the third sub-study conceptualizes platform governance mechanisms as external stimuli capable of reshaping contributor cognition and behavior. First, official GenAI tools are theorized as guidance-based nudges. Compared with third-party tools primarily optimized for efficiency, official tools may be designed to scaffold structured creation and encourage more deliberate engagement. By embedding nudging mechanisms such as default quality templates, task simplification, and exemplary priming, platforms may enhance contributors’ cognitive investment and potentially improve content quality. Second, AIGC disclosure policies are conceptualized as social-norm nudges intended to strengthen accountability and creative responsibility. While disclosure may encourage contributors to invest greater effort to signal originality, it may also trigger audience bias that could dampen engagement incentives. To address the limitations of binary AI labels, this study proposes a multi-level disclosure framework that reflects varying degrees of human-AI collaboration (e.g., AI-assisted, AI-co-created, AI-dominated), supplemented by structured textual explanations. Such nuanced governance mechanisms are theorized to reinforce perceived creative ownership and responsibility, thereby increasing cognitive investment and ultimately contributing to higher-quality AIGC. Overall, this study develops a comprehensive, multi-level framework for understanding and governing AIGC pollution. By tracing the psychological trajectory from technological stimuli to individual cognition, ecosystem reactions, and governance interventions, the research advances theory on the unintended consequences of generative technologies and offers actionable guidance for platform managers and policymakers seeking to foster a sustainable and high-quality content ecosystem in the era of GenAI. References | Related Articles | Metrics

Select

Trust formation through experience transfer across different trust agents: A comparison between humans and artificial intelligence QI Yue, XIE Ran, YOU Shanshan, LI Tong 2026, 34 (7):  1127-1137.  doi: 10.3724/SP.J.1042.2026.1127 Abstract ( 91 )   PDF (543KB) ( 114 )   Peer Review Comments The rapid advancement of artificial intelligence (AI) has prompted a significant shift in the nature of human-AI interactions, transforming AI from a mere tool into a collaborative agent embedded in social contexts. As AI systems become more autonomous and interactive, the dynamics of trust in AI have evolved. Trust is no longer simply a one-way human trust toward machines, but also involves mutual trust between humans and AI, AI’s trust in humans, and even trust among AI agents themselves. Despite the growing importance of these complex relationships, there is a lack of comprehensive theoretical models that integrate human-human trust with human-AI trust, particularly in terms of how trust evolves, updates, and transfers across different agents and contexts. The proposed research aims to address these gaps by developing a novel experience-based framework for trust formation and transfer that integrates insights from social psychology and engineering psychology. Specifically, this proposal focuses on the dynamic nature of trust in human-AI interactions, where trust is not a static belief but a process that evolves over time through experience and is transferable across different agents and contexts. The core innovation of this framework lies in its dual-subject approach, treating both humans and AI agents as trustors and trustees, and in its focus on trust experience transfer. This allows for a unified theoretical model that explains how trust is not only learned through interactions but also transferred from one interaction partner to another, facilitating trust-building across human and AI agents. The research will explore three key research questions: (1) How do different trust subjects-humans and AI agents-learn trust through experience? (2) To what extent can trust-related experiences be transferred across agents, and what factors influence this transfer? (3) How do individual characteristics of the trustor and interaction characteristics moderate the learning and transfer of trust? By addressing these questions, the research will contribute to a deeper understanding of the mechanisms underlying trust formation in human-AI collaboration. The proposed model of trust experience transfer posits that trust is a dynamic, evolving process where individuals (or agents) update their trust beliefs based on feedback from previous interactions. This process is not confined to a single trust target, but rather extends across different agents, facilitating the transfer of trust from one relationship to another. For example, trust built through prior human-AI interactions may inform future human-human interactions or trust in other AI agents. Additionally, the model accounts for individual differences in trustors (e.g., age, anthropomorphism, AI characteristics, etc.) and contextual factors (e.g., interaction context and interaction relationship), which influence how trust is learned and transferred. To empirically test this framework, the research will employ an experimental paradigm involving both human participants and AI agents. This paradigm will manipulate the trust subject (human or AI agent) and the nature of their interaction, allowing for the examination of how trust develops and transfers between different agents. The experiments will use a combination of behavioral data and computational models to analyze trust-building processes in both human-human and human-AI interactions. The proposed methodology represents an innovation in trust research, as it explicitly incorporates AI as a trustor and allows for the examination of multi-agent trust dynamics in controlled settings. The anticipated contributions of this research are threefold: First, it will develop a unified model of trust that integrates human-human and human-AI trust, providing a comprehensive framework for understanding trust dynamics in mixed-agent systems. Second, the research will introduce the concept of trust experience transfer, demonstrating how trust can generalize across different agents and contexts, offering new insights into the adaptability and fluidity of trust. Finally, the study will provide empirical evidence regarding the role of individual and contextual factors in trust development and transfer, offering practical implications for the design of trustworthy AI systems. This research has significant implications for the design and deployment of AI systems, particularly in contexts where AI must interact with multiple agents and adapt to dynamic trust environments. By understanding how trust is built and transferred across human and AI agents, the research will inform the design of AI systems that can better calibrate trust, improve collaboration, and ensure the ethical deployment of AI in socially sensitive contexts. In conclusion, this proposal aims to advance the field of human-AI trust by providing a dynamic, experience-based framework for understanding how trust is learned and transferred across different agents. By integrating social psychology with engineering psychology, this research will offer both theoretical insights and practical guidance for the design of more reliable and trustworthy AI systems. References | Related Articles | Metrics

Select

The formation and mitigation mechanisms of cooperation dilemmas in hybrid employment teams: Balancing strategies under power asymmetry WANG Pengcheng, PENG Juan, QIN Chuanyan, LIU Shanshi 2026, 34 (7):  1138-1153.  doi: 10.3724/SP.J.1042.2026.1138 Abstract ( 53 )   PDF (725KB) ( 46 )   Peer Review Comments With the diversification of employment arrangements, hybrid employment teams have become an important organizational form for enhancing flexibility and integrating external resources. However, in practice, such teams do not necessarily realize the expected collaborative advantages; instead, they often encounter cooperation dilemmas, including coordination failures, insufficient knowledge sharing, and declining willingness to cooperate. Existing studies have largely explained these phenomena from the perspectives of institutional arrangements or contractual governance, while paying relatively limited attention to the micro-level collaboration between standard and non-standard employees. Addressing this gap, the present study adopts a power asymmetry perspective to examine the origins and formation mechanisms of cooperation dilemmas in hybrid employment teams and to explore feasible mitigation pathways. Drawing on power dependence theory, this study develops a multi-level analytical framework to systematically explain the formation and regulation of cooperation dilemmas from the team level, the individual level, and the level of intervention mechanisms. The core argument is that differences in employment status solidify structural power asymmetry, which reshapes task organization, interaction patterns, and psychological experiences, thereby generating cooperation dilemmas. Specifically, the study contains three key components. First, at the team level, structural power asymmetry produces cooperation dilemmas by distorting team work design. Power-advantaged members are more likely to dominate task boundaries and responsibility allocation, causing the task system to deviate from efficiency-oriented principles. This distortion manifests as task structure fragmentation, task content ambiguity, and task environment segmentation, making it difficult for team members to form clear shared responsibility. Coordination increasingly relies on procedures rather than relationships, and collaboration thus shifts from a stable cooperative system to constrained, transactional interaction. Work design distortion therefore serves as a crucial mediating pathway through which power asymmetry intensifies cooperation dilemmas. Second, at the individual level, the study shows how power asymmetry elicits differentiated behavioral responses across employment groups, thereby reinforcing cooperation dilemmas. For standard employees in power-advantaged positions, asymmetric dependence is more likely to activate dominant control behaviors, including excessive task intervention, restriction of information flows, unilateral decision-making, and boundary setting that favors their own interests. These behaviors may protect positional advantages but suppress mutual adjustment and shared learning. In contrast, for non-standard employees in power-disadvantaged positions, power asymmetry more readily induces defensive silence, reflected in reduced voice behavior, risk avoidance, and lower proactive engagement. Under asymmetric dependence, they are more likely to perceive higher interpersonal and career risks, which weakens psychological safety and the social foundation of cooperation. The dominant control of standard employees and the defensive silence of non-standard employees interact to form a self-reinforcing cycle, making distortions in work design difficult to correct. Third, in terms of intervention strategies, the study proposes a multi-level regulatory mechanism to mitigate the negative effects of power asymmetry. Structural empowerment and institutional design optimization help reduce power concentration stemming from employment status differences by clarifying authority boundaries, increasing procedural transparency, and strengthening safeguards for fair allocation. Social integration practices reshape team members’ cognitive perceptions of power and dependence, build shared identity, cross-status trust, and cooperative expectations, and weaken purely instrumental interaction. At the individual level, reducing standard employees’ perceived status threat can curb dominant control tendencies, while enhancing non-standard employees’ contingent self-esteem can reduce defensive silence and promote constructive voice. Working together across levels, these mechanisms transform asymmetric power relations into more functional interdependence, thereby improving cooperation in hybrid employment teams. By introducing power dependence theory into the context of hybrid employment teams, this study clarifies how structural power asymmetry influences collaboration through work design distortions and behavioral differentiation, extending prior research on teamwork and flexible employment that assumes power balance or emphasizes one-sided adaptation. The model integrates institutional structure, team work design, and individual behavioral responses to provide a more complete micro-level explanation. At the same time, the multi-level mitigation framework offers organizations a systematic path to identify and manage power asymmetry risks, underscoring that effective collaboration requires the joint operation of institutional design and relational integration rather than reliance on contractual control alone. These theoretical insights provide a stronger foundation for future research on the antecedents of power asymmetry, the evolution of cooperation mechanisms, and the boundary conditions of interventions, while offering actionable implications for managers seeking to maintain employment flexibility without sacrificing team cohesion and cooperative performance. References | Related Articles | Metrics

Select

How do zoom-in and zoom-out dynamic presentations shape consumers’ comparative decision making? An integrative framework from a dynamic psychological distance perspective MENG Lu, SHEN Qinchang, BIE Yongyue, XU Zibin 2026, 34 (7):  1154-1169.  doi: 10.3724/SP.J.1042.2026.1154 Abstract ( 69 )   PDF (734KB) ( 66 )   Peer Review Comments Dynamic product presentation has become a default design choice in short-video commerce and online retail interfaces, yet “dynamics” are typically treated as a monolithic feature (dynamic vs. static). This paper advances a more diagnostic and actionable account by theorizing zoom-in vs. zoom-out camera movements (i.e., zoom-in vs. zoom-out) as distinct dynamic distance cues that systematically reorganize consumers’ information processing during comparative decision making. We develop an integrative framework that explains why the same dynamic medium can generate divergent preference patterns, and we specify when these effects should strengthen or attenuate. Our central contribution is the dynamic distance-cue perspective, which treats zooming not merely as motion but as a directional change in perceived distance—from far-to-near (zoom-in) versus near-to-far (zoom-out). We argue that this directional cue alters (a) the viewer’s psychological stance toward the focal object, (b) the type of inferences drawn about brands, and (c) the comparison strategy used to evaluate competing options. Importantly, we unify evidence and theory streams that have largely evolved in parallel by mapping zoom direction onto three analytically distinct yet connected levels of comparison: product-level preferences, brand-level impressions, and attribute-level decision strategies. Product level: hedonic versus utilitarian preference via self-immersed versus self-distanced stance At the product level, we propose that zoom direction shapes whether consumers approach the decision through affective versus cognitive evaluation. A zoom-in sequence progressively concentrates attention on the focal product, producing a felt sense of moving “into” the scene. This fosters a self-immersed stance, amplifying experiential and affective reactions and thereby increasing preference for hedonic options in comparative choice. In contrast, a zoom-out sequence expands the field of view to include more contextual information and creates a sense of stepping back from the object, fostering a self-distanced stance that supports more deliberative, function-oriented evaluation and increases preference for utilitarian options. This mechanism clarifies not only whether dynamic presentation matters but also how specific shot movements can tilt consumers’ comparison criteria toward emotion-laden versus performance-relevant attributes. A key boundary condition is playback speed. We argue that the strength of perceived distance change depends on whether viewers have sufficient temporal bandwidth to register the unfolding movement. Slower zooming should heighten dynamic distance perception, strengthening the self-immersed/self-distanced experience and thus magnifying hedonic-versus-utilitarian preference divergence. Faster zooming, by reducing perceptual clarity and processing time, should attenuate these effects. Brand level: warmth versus competence inference via power orientation At the brand level, we extend the framework beyond product evaluation to explain how zoom direction reorganizes social inferences about brands. Drawing on the stereotype content tradition (warmth and competence) and power-orientation logic, we propose that zooming changes the consumer’s perceived relational stance toward the brand. Zoom-in signals psychological proximity and interpersonal closeness, which encourages more communal interpretation of intent and increases perceived brand warmth. Zoom-out increases perceived distance and can cue status, authority, and professionalism, thereby increasing perceived brand competence. This account specifies a visual route through which dynamic advertising can differentially advantage “warm” versus “competent” brand positioning in comparative contexts. We also identify a decision-focus boundary condition: choosing for oneself versus choosing for others. When choosing for oneself, viewers are more likely to use the self-relevant relational stance induced by zooming, allowing warmth/competence impressions to translate into choice. When choosing for others, comparative evaluation is less anchored in the decision maker’s own relational stance, and zoom-driven warmth/competence advantages should weaken. Attribute level: dimension-by-dimension versus holistic comparison strategy At the attribute level, we propose that zoom direction shapes the form of comparison itself. Zoom-in promotes a concrete, detail-focused mindset and increases attention to separable product components, making consumers more likely to adopt a dimension-by-dimension (attribute-wise) comparison strategy and to choose options that dominate on more individual attributes. Zoom-out promotes more abstract, global construal, encourages holistic processing, and increases reliance on overall (option-wise) evaluation, favoring options with stronger aggregate performance even if they do not win on every single attribute. This mechanism connects visual motion to choice architecture: zooming can effectively shift consumers between “counting wins” across attributes and “summing up” overall value. A further boundary condition is cognitive load. Because holistic evaluation is more resource-demanding, high cognitive load should reduce the advantage of zoom-out in promoting overall comparison, thereby shrinking the predicted divergence between zoom-in and zoom-out strategies. Implications Collectively, the paper contributes a multi-level, mechanism-based framework that (1) differentiates zoom-in vs. zoom-out as theoretically distinct dynamic cues, (2) integrates product preference, brand inference, and comparison strategy into a single explanatory architecture, and (3) specifies actionable moderators—playback speed, decision target (self vs. other), and cognitive load—that delimit when zoom-driven advantages should occur. For managers, the framework implies that “adding motion” is insufficient: effective dynamic creative should align zoom direction with the intended comparative goal (experience vs. function, warmth vs. competence, attribute-wise vs. holistic choice) and with platform contexts that vary in viewers’ time and attention constraints. References | Related Articles | Metrics

Meta-Analysis

Select

The relationship between family factors and children’s executive function: A series of meta-analyses XU Jie, HUANG Yinghang, GAI Xiaosong 2026, 34 (7):  1170-1188.  doi: 10.3724/SP.J.1042.2026.1170 Abstract ( 80 )   PDF (815KB) ( 139 )   Peer Review Comments Based on the family investment model and the family stress model, this study conducted a three-level meta-analysis to investigate the associations of family cognitive stimulation, parenting style, and parental psychological distress with children’s executive function. In addition, it compared the relative strength of these associations across family factors.Previous studies have typically examined the effects of a single category of family factors on children’s executive function from the perspective of either the family investment model or the family stress model. However, few studies have compared the strength of associations between different family factors and children’s executive function within a unified analytical framework. Consequently, it remains unclear which type of family factor is more closely associated with children’s executive function. To address this issue, the present study synthesized relevant empirical evidence to provide clearer support for understanding the relative roles of different family factors in the development of children’s executive function. A total of 154 studies comprising 612 effect sizes were included in the meta-analysis. The results indicated that family cognitive stimulation and positive parenting style were both significantly and positively associated with children’s executive function, whereas negative parenting style and parental psychological distress were both significantly and negatively associated with children’s executive function. Further comparisons showed that family cognitive stimulation (r = 0.146) and parenting style (positive parenting: r = 0.169; negative parenting: r = -0.128) were more closely associated with children’s executive function than parental psychological distress (r = -0.102). These findings suggest that, relative to parental psychological distress, family cognitive stimulation and parenting style may play a more direct or more prominent role in the development of children’s executive function. With respect to moderation effects, the measurement method of family cognitive stimulation significantly influenced the magnitude of its association with children’s executive function. Specifically, compared with questionnaire-based and video-based assessments, studies using home visits to assess family cognitive stimulation yielded larger effect sizes. This finding suggests that different measurement approaches may capture different aspects of the family environment, and that home-visit assessments may better reflect the actual level of cognitive stimulation available in the family context. In addition, the measurement method of children’s executive function also significantly moderated the observed associations. When executive function was assessed using indirect measures, the effect sizes linking parental psychological distress, positive parenting style, and negative parenting style to children’s executive function were all significantly larger than those obtained when executive function was assessed using direct measures. This result indicates that the strength of associations between family factors and children’s executive function may vary depending on the assessment approach adopted for executive function, and that such methodological differences should be taken into consideration when interpreting related findings. This study also examined the associations of different family factors with cool and hot executive function. The results showed that family cognitive stimulation, parental psychological distress, and parenting style were each significantly associated with both cool executive function and hot executive function. However, executive function type did not significantly moderate the associations between these family factors and children’s executive function. In other words, the patterns of association between family factors and children’s executive function were relatively consistent across cool and hot executive function. At the same time, variables such as age did not show significant moderating effects on the associations between family factors and children’s executive function, suggesting that these associations were generally stable across age groups. The significance of this study is reflected in two main aspects. First, by simultaneously examining and comparing the associations of family cognitive stimulation, parenting style, and parental psychological distress with children’s executive function within the same meta-analytic framework, this study provides evidence for a more comprehensive understanding of the relative roles of different family factors in the development of children’s executive function, and also offers empirical support for integrating the family investment model and the family stress model. Second, the findings have implications for family-based interventions targeting children’s executive function. Comparing the relative strength of associations between different family factors and children’s executive function may help identify which family factors warrant greater attention in intervention practice, thereby providing a basis for promoting the development of children’s executive function. References | Related Articles | Metrics

Regular Articles

Select

How the internal attention selection advantage emerges in visual working memory: Evidence from the retro-cue paradigm HU Aixin, MA Ying, HU Yuxin, TUO Min, ZENG Shuo, WANG Tingzhao 2026, 34 (7):  1189-1207.  doi: 10.3724/SP.J.1042.2026.1189 Abstract ( 92 )   PDF (649KB) ( 92 )   Peer Review Comments Visual working memory (VWM), constrained by limited capacity, requires flexible selection and prioritization of internal information, with the directional regulation of internal attention being essential to this process. Traditional research has primarily attributed VWM performance to limitations in encoding or storage capacity, overlooking the critical role of internal attention in managing information within VWM, such as the dynamic reshaping of representation priorities during the maintenance phase. While the retro-cue benefit (RCB) has garnered attention as a manifestation of the internal attention selection advantage, it is often explained through a single-mechanism lens, without a systematic integration of multiple mechanisms. This study, based on the retro-cue paradigm within the continuous resource model framework, synthesizes behavioral and neurophysiological evidence to present a theoretical framework for understanding the mechanisms and factors underlying the emergence of internal attention selection advantages in VWM. The main contributions of this work are as follows: The generation of RCB is not driven by a single factor but results from the interaction of three core mechanisms: consolidation sufficiency, sustained attention, and decision-stage information accumulation. Consolidation sufficiency is a prerequisite for the effectiveness of retro-cues, regulating early resource availability and stabilizing memory representations. Retro-cues can only effectively reallocate attention resources when memory representations have not yet reached full consolidation. Sustained attention plays a critical role in maintaining the internal attention selection advantage by resisting external interference, optimizing resource allocation, and preserving or reconstructing the prioritization of target representations. The accumulation of decision-stage information determines how this advantage translates into observable behavioral performance. This occurs by optimizing the efficiency of information accumulation, enhancing decision-making quality, and converting decision evidence into behavioral outputs. Thus, the formation of RCB can be understood as a continuous process of dynamic resource investment, maintenance, and transformation across different stages of VWM processing. The study also clarifies the four key categories of factors influencing the internal attention selection advantage: temporal progression, memory item changes, cue variations, and external interference. Temporal progression influences the protective effects of retro-cues on target representations, the sequencing of cognitive processing, and resistance to external interference, through three key sub-factors: Cue-Test Interval (CTI), Retro-cue Interval (RI), and Stimulus Onset Asynchrony (SOA). Memory item changes include memory load and the perceptual features of the items. Memory load alters the intensity of internal resource competition, while perceptual features influence the selective maintenance of internal attention by adjusting the processing weight of target and non-target features, thus impacting RCB. Variations in the number and type of retro-cues also play a crucial role: the number of retro-cues reshapes resource allocation strategies, while the type regulates attention distribution strategies. External interference, such as perceptual disruptions and dual-task interference, weakens the stability of attention maintenance and reduces internal attention control efficiency by depleting cognitive resources. Notably, these factors interact with the core mechanisms, dynamically influencing the emergence of internal attention selection advantages and shaping individual behavioral outcomes. A multi-level integrated cognitive model is proposed, which outlines, for the first time, the interactions and pathways between mechanisms and influencing factors. Each of the three core mechanisms is predominantly influenced by three of the four categories of factors and their sub-factors, with interactions among these factors creating a comprehensive regulatory effect. Moreover, by integrating cognitive neuroscience evidence, the study clarifies neural pathways formed by the collaboration of the occipital visual cortex, posterior parietal cortex (PPC), prefrontal cortex (PFC), and the striatum, providing a neural basis for the realization of internal attention selection and its advantages in VWM. In conclusion, this study offers a novel theoretical framework for understanding the emergence of internal attention selection advantages in VWM. Future research could combine neuroimaging and modulation techniques to explore active inhibition mechanisms, complex stimulus processing, and internal attention characteristics in populations with neurodevelopmental disorders, providing deeper insights into human cognitive processes. References | Related Articles | Metrics

Select

Minimal other minds: An ontogenetic investigation of animacy perception WANG Yong, DONG Da, CHEN Wei 2026, 34 (7):  1208-1218.  doi: 10.3724/SP.J.1042.2026.1208 Abstract ( 73 )   PDF (798KB) ( 93 )   Peer Review Comments Minimal Theory of Mind (MTM) has been regarded as a transitional form within the spectrum of the problem of other minds, situated between simple action perception and mature theory of mind. It is intended to explain the initial capacity for mindreading in infants, non-human animals, and other agents with limited cognitive resources. However, although MTM reduces the complexity of mental-state attribution, it still faces a fundamental theoretical difficulty: it presupposes that the target of cognition has already been identified as a social agent. Thus, MTM is minimal only at the level of mental-state representation, rather than at the ontogenetic point of departure for mindreading. To address this problem, this study argues that a minimal account of understanding other minds should trace the developmental trajectory further back and begin with a more primitive capacity, namely animacy perception. Before invoking psychological concepts such as beliefs and desires, animacy perception enables individuals to distinguish objects in the environment as animate or inanimate, thereby providing the most basic object condition for subsequent other-mind-directed processing. In this sense, animacy perception constitutes a prior ontological condition for access to other minds and offers a new entry point for addressing the question left unresolved by MTM: how minded objects are first distinguished. On this basis, this study proposes a new constructive framework for the minimal form of mindreading, namely, Minimal Other Minds (MOM) based on animacy perception. To support this proposal, this study reviews evidence on animacy perception from three aspects: visual cues, ontogenetic origins, and neural mechanisms. First, animacy perception can be triggered by both static and dynamic cues. Static cues include faces, eyes, body shapes, and texture-based appearance information. Face-like patterns, in particular, attract newborns’ attention and elicit early orienting responses in multiple species, indicating an early sensitivity to biologically relevant forms. Dynamic cues mainly include self-propelled motion, biological motion, and goal-directed motion. Even simple geometric figures may be perceived as animate if they display autonomous initiation, biological kinematic properties, or chasing-like relations. These findings suggest that animacy perception is not influenced by the perceiver’s own intentions or beliefs, but rather constitutes a highly rapid, spontaneous, and even irresistible perceptual process. Second, the ability to distinguish animate from inanimate entities emerges early in ontogeny. Existing explanations mainly include nativist, empiricist, and integrative accounts. Nativist accounts emphasize inborn sensitivities to faces, biological motion, and self-propelled motion. Empiricist accounts stress the role of domain-general learning from environmental regularities. Integrative accounts hold that early perceptual biases provide the initial scaffold for animacy perception and are progressively extended and reorganized through experience. Third, animacy perception relies on a distributed neural system involving the ventral occipitotemporal cortex, the lateral occipitotemporal cortex, and parietal regions associated with action understanding and goal processing. Particularly important is the neural model of animacy detection proposed by Shultz and colleagues. This model integrates three pathways responsible for static form cues, biological motion cues, and goal-directed motion cues, suggesting that animacy perception is a relatively independent processing system foundational for social cognition. On this basis, this study further develops the MOM framework from three dimensions: process, component, and structure. In process terms, the route to other minds should begin not with mental-state attribution, but with the prior detection of whether an object is animate and socially relevant. In component terms, MOM encompasses the full content of animacy perception and serves as a foundational part of the social-cognitive framework, preparing the ground for higher-level mentalizing. In structural terms, MOM is grounded in a hierarchical object space of animacy, organized along dimensions such as being alive, resembling an animal, moving autonomously, acting independently, and being unpredictable. Correspondingly, animacy-sensitive neural pathways preferentially process this object space, together forming the external object basis and internal neural architecture of minimal social cognition. The main contribution of this study lies in shifting the theoretical starting point of minimal mindreading from attenuated mental-state representation to prior animacy perception. By proposing MOM, this study reveals a theoretical gap in MTM at the ontogenetic level and provides a more fundamental framework for explaining how infants, animals, and other cognitively limited agents initially come to understand other minds. From this perspective, the genuinely minimal form of mindreading is not a weaker attribution of mental states, but the initial recognition that one is encountering a living, acting, and potentially minded other. More broadly, MOM helps bridge developmental psychology, comparative psychology, cognitive neuroscience, and philosophy of mind, while also offering a new reference point for research on direct social perception and computational modeling of early social cognition. References | Related Articles | Metrics

Select

Maternal anxiety-driven overprotective behaviors: An emotional-cognitive-behavioral closed-loop model TENG Yue, KONG Lingnan, LIU Lifen, YANG Bin, DANG Qi, GAO Jun 2026, 34 (7):  1219-1238.  doi: 10.3724/SP.J.1042.2026.1219 Abstract ( 127 )   PDF (683KB) ( 164 )   Peer Review Comments Maternal anxiety has become increasingly prevalent in contemporary parenting contexts; however, the mechanisms through which it drives and maintains overprotective behavior still lack a systematic theoretical explanation. To address this gap, the present review adopts a clinical perspective on maternal anxiety and synthesizes evidence from clinical, developmental, and neuroscientific research to propose an innovative “emotional-cognitive-behavioral closed-loop model” explaining the mechanisms underlying overprotective behavior. This model not only deepens our understanding of the relationship between maternal anxiety and parenting behavior but also offers new directions for theoretical innovation in integrated psychological, neural, and social interventions. The model proposes that maternal anxiety drives overprotective behavior through three interacting psychological components, rather than a simple linear causal chain. First, at the emotional level, maternal anxiety may trigger threat overamplification and emotional sensitivity dysregulation, causing individuals with maternal anxiety to perceive child distress or routine exploration as significant dangers. Second, at the cognitive level, individuals with maternal anxiety may display attentional bias toward threat cues and engage in catastrophic interpretation of ambiguous situations, while their cognitive reappraisal capacity may become impaired, potentially leading them to justify intrusive interventions as necessary protection. Third, at the behavioral level, overprotective actions (e.g., immediate soothing, activity restriction) produce rapid but temporary anxiety relief. Crucially, this relief functions may as a negative reinforcement signal, increasing the likelihood that overprotection will be repeated in similar future situations. These three levels may continuously feed back into each other: emotional amplification biases cognition, cognitive distortions justify more extreme protection, and behavioral relief reinforces both emotional and cognitive patterns, forming a self-perpetuating psychological closed loop. At the neural level, the model further attempts to elucidate how maternal anxiety drives overprotective behavior through three key pathways—threat amplification, cognitive dysregulation, and reward reinforcement—thereby achieving cross-level integration. Emotional triggering serves as the starting point of the model. Hyperactivation and heightened vigilance of the amygdala (AMY) correspond to the “emotional response” component of the closed loop, providing the initial driving force for the entire circuit. The connection between the medial prefrontal cortex (mPFC) and the AMY plays a key role in mediating fear and anxiety-like behaviors. Reduced regulatory function of the mPFC and its abnormal connectivity with the AMY lead to threat assessment bias and catastrophic thinking, which correspond to the “cognitive bias” component of the loop. The mPFC fails to effectively “brake”—that is, inhibitory control is weakened—resulting in amplified emotional signals that drive overprotective behavior. This altered neural functional state may lead individuals with maternal anxiety to adopt risk-avoidant decisions (e.g., early intervention or restriction) even in low-threat or uncertain situations—such as a child playing independently in a safe environment—as a preventive coping strategy. Such behaviors may eventually be marked as “effective” by the reward system (the Ventral Tegmental Area (VTA)-Nucleus Accumbens (NAc) dopamine pathway) and become consolidated into habitual actions through negative reinforcement. Thus, in the neural closed loop underlying maternal anxiety-driven overprotective behavior, the VTA-NAc reward pathway serves both as a reward pathway for emotional relief and as a reinforcement mechanism for behavioral consolidation, constituting a key downstream executive node of the loop. The three nodes described above do not operate in a linear cascade but instead form a dynamic interactive network, which may ultimately trap the entire system in a vicious cycle of “anxiety-protection-transient relief-increased vulnerability to anxiety,” making overprotective behavioral patterns increasingly stable and automatic. The formation of maternal anxiety-driven overprotective behavior does not stem from a single factor but may result from the dynamic coupling of psychological, neural, and social dimensions. Through a systematic review and synthesis of existing literature, this paper proposes an “emotional-cognitive-behavioral closed-loop model”, replacing fragmented factor-based accounts with a dynamic systems perspective. In addition, the model introduces “anxiety relief as reward” via negative reinforcement—a mechanism adapted from addiction and avoidance research—to explain why overprotective behavior becomes habitual and resistant to change, rather than merely attributing it to cognitive errors. Finally, it attempts to achieve cross-level integration by mapping psychological and neural levels onto each other, enabling future studies to test causal pathways rather than mere correlations. In conclusion, this review does not merely summarize existing knowledge but provides a mechanistic, integrative, and actionable theoretical framework that explains the formation, maintenance, and potential impact of maternal anxiety-driven overprotective parenting, thereby offering new directions for both basic research and clinical translation. References | Related Articles | Metrics

Select

The health hazards, mechanism and intervention paths of social jetlag on students’ physical and mental health GAO Chenghai, ZHANG Min, CAO Jing 2026, 34 (7):  1239-1255.  doi: 10.3724/SP.J.1042.2026.1239 Abstract ( 95 )   PDF (761KB) ( 113 )   Peer Review Comments Social Jetlag (SJL) refers to discrepancies existing in sleep-wake pattern between students’ school days and weekend days (or non-school days), which is mainly resulted by the misalignment of school schedules and circadian rhythms and characterized by a systematic shift in the midpoint of sleep. SJL is widespread among student populations worldwide. Despite growing attention to the adverse health effects of SJL, student-focused research remains fragmented and lacks systematic integration. This review synthesizes the literature on SJL across four domains: determinants, health outcomes, underlying mechanisms, and intervention strategies. Regarding etiology, this review categorizes the determinants of SJL into three broad domains: endogenous, exogenous, and institutional factors. Endogenous factors (e.g., nocturnal chronotypes, age, and sex) constitute the primary biological basis of SJL; exogenous factors (e.g., 24-hour electricity and internet availability, high-density indoor lifestyles, and the widespread use of electronic devices) provide an enabling environment for its development; and institutional factors (e.g., globally prevalent early school start times) act as key drivers of its emergence. The interplay of these internal and external influences disrupts circadian rhythms in students, ultimately giving rise to SJL and posing substantial risks to their physical and mental health. Regarding health outcomes, this review delineates the multifaceted impacts of SJL across two domains: physiological and psychological. Physiologically, SJL is significantly associated with obesity, elevated cardiometabolic risk, and diminished sleep quality. Psychologically, SJL is significantly correlated with symptoms of anxiety and depression, declines in cognitive functioning, poorer academic performance, and behavioral issues, including deficits in prosocial behavior, addictive behaviors, and disordered eating patterns. These associations exhibit variations based on gender and age, as well as characteristics of cumulative effects over time, and are particularly pronounced among individuals with nocturnal chronotypes and adolescents. Regarding mechanisms, circadian disruption induced by SJL first leads to dysregulated expression of core clock genes (e.g., CLOCK and PER), which in turn activates the hypothalamic-pituitary-adrenal (HPA) axis and the renin-angiotensin system, resulting in elevated cortisol levels and autonomic dysfunction. This central pathway further diverges into three downstream routes. At the metabolic level, increased ghrelin, decreased leptin, and reduced insulin sensitivity contribute to obesity and heightened cardiometabolic risk. At the neurobehavioral level, impaired prefrontal cortical functioning, heightened amygdala reactivity, and attenuated dopaminergic signaling jointly give rise to anxiety and depressive symptoms as well as behavioral problems. At the sleep level, delayed sleep phase and the accumulation of sleep debt disrupt slow-wave and rapid eye movement (REM) sleep, impede the restoration of synaptic homeostasis, and ultimately compromise memory consolidation and cognitive control. Regarding interventions, existing studies have addressed SJL among students from three single perspectives (endogenous, exogenous, or institutional) and have demonstrated modest effectiveness. However, these interventions reveal limited effect sizes, poor long-term sustainability, and insufficiently developed exogenous intervention strategies. To mitigate the progression and exacerbation of SJL in student populations at its source, a technology-empowered four-level intervention system, featuring systematic integration of collaboration among the “government, schools, communities, and families”, is proposed to establish a closed-loop management process comprising four stages: assessment, diagnosis, intervention and follow-up. This system aims to achieve the early identification, warning and intervention of Social Jet Lag among students. This study makes three primary contributions. First, it extends research on the adverse effects of SJL beyond single outcome variables to a comprehensive synthesis encompassing six domains: obesity, cardiometabolic risk, sleep quality, anxiety and depression, cognitive and academic performance, and behavioral problems, thereby revealing pervasive sex and age-related differences, as well as cumulative effects over time across these outcomes. Second, it elucidates how dysregulation of core circadian clock genes exerts effects via the neuroendocrine system, ultimately leading to widespread impacts on metabolism, sleep, cognition, and behavior. Third, it moves beyond single-component interventions by proposing a four-level intervention system based on collaboration among four key stakeholders. Collectively, this study not only broadens the psychological perspective on circadian health research but also provides a theoretical foundation and practical implications for optimizing school schedules and improving student sleep health policies. Future research should prioritize randomized controlled trials, longitudinal cohort studies, and more rigorous causal inference, while advancing context-specific intervention strategies tailored to the Chinese educational setting. References | Related Articles | Metrics

Select

The process and confines of mental budgeting constraints on expenditure decisions GAO Xu, XIN Ziqiang 2026, 34 (7):  1256-1268.  doi: 10.3724/SP.J.1042.2026.1256 Abstract ( 55 )   PDF (577KB) ( 59 )   Peer Review Comments Mental budgeting, a core component of mental accounting theory, refers to the cognitive process by which individuals allocate funds to specific mental accounts and track expenditures against these budgets. Although existing research has demonstrated that mental budgeting can constrain spending, the specific conditions under which such constraints succeed or fail require further theoretical exploration. To address this question, this paper proposes a constraint process model that delineates the cognitive mechanisms through which mental budgeting influences expenditure decisions and defines the boundaries within which it operates. The model consists of three sequential cognitive stages: cognitive labeling, expense identification, and budgetary reference. In the first stage, individuals assign cognitive labels to funds based on anticipated uses, thereby creating nonfungible mental accounts. This labeling process, rooted in basic human categorization, establishes the structural foundation for budget constraints. In the second stage, an expense must be noticed and matched to a preexisting mental account. If the expense is too small, too urgent, or otherwise fails to capture attention before the decision is made, it may escape budgetary scrutiny. In the third stage, once an expense is identified, the individual compares its utility against the remaining budget. If the perceived utility is sufficiently high, the decision may prioritize gain seeking over budget adherence, leading to intentional overspending. The model identifies three key boundary conditions that define the constraining confines of mental budgeting. The first is categorizability, which refers to whether an expense can be assigned to a mental account. The second is timing of identification, meaning whether the expense is recognized before or after the decision. The third is utility level, which concerns whether the perceived utility of the expense surpasses a threshold that triggers utility driven overspending. These conditions collectively determine whether an expense will be constrained by mental budgeting. The model thus helps explain why some expenditures, such as exceptional or low-cost items, are more likely to bypass budgetary control, and why individuals may strategically reclassify ambiguous expenses to alter their budget constraints. The model also addresses a theoretical tension in mental accounting research between the nonfungibility of mental accounts and the flexibility of expense categorization. By situating these phenomena in different cognitive stages: nonfungibility in the labeling stage and flexible categorization in the identification stage. This paper suggests that they are not contradictory but rather complementary mechanisms that together shape expenditure outcomes. This perspective advances the theoretical understanding of mental accounting and provides a more nuanced framework for analyzing consumer decision making under budget constraints. Beyond delineating constraints, this paper explores the adaptive value of mental budgeting. The system enhances decision efficiency in two ways. For identified expenses, it simplifies choice by providing budget references. For low stakes or urgent expenses, it allows for rapid decision making by bypassing elaborate deliberation. Furthermore, mental budgeting helps reconcile long-term and short-term benefits. The labeling and tracking mechanisms support future oriented goals, such as saving for significant purchases, while flexible categorization and post identification overspending enable individuals to pursue high utility opportunities without entirely abandoning the budget framework. This dual function perspective positions mental budgeting as a resource rational adaptation rather than merely a cognitive limitation. The paper concludes by suggesting directions for future research. Empirical validation of the model is needed across diverse contexts, using experimental paradigms that manipulate categorizability, identification timing, and utility levels. Neuroimaging techniques could further illuminate the neural correlates of the proposed stages, particularly the role of cognitive control regions in budget adherence versus overspending. Practical implications are discussed for consumer financial tools, marketing strategies, and public policy, highlighting how interventions might leverage the model's insights to promote adaptive financial behavior. By specifying the cognitive processes and boundary conditions that govern mental budgeting, this paper offers a comprehensive theoretical account of how and when budgets shape spending decisions. It provides a foundation for future research at the intersection of cognitive psychology, behavioral economics, and consumer science. References | Related Articles | Metrics

Select

A two-dimensional dynamic model of interpersonal co-opetition: The driving role of social comparison GAO Yuhui, LIU Feiyi, WANG Jinpeng, MENG Guangteng, LIU Xun 2026, 34 (7):  1269-1283.  doi: 10.3724/SP.J.1042.2026.1269 Abstract ( 90 )   PDF (964KB) ( 100 )   Peer Review Comments In human societies, competition and cooperation are not mutually exclusive phenomena but are instead deeply interdependent and dynamically intertwined. As global resource pressures continue to intensify, social comparisons among individuals play a pivotal role in shaping tendencies toward competition and cooperation, influencing the emergence, regulation, and transformation of co-opetition behaviors across multiple dimensions. While co-opetition has traditionally been conceptualized at the intergroup level, the ways in which these behaviors manifest and evolve dynamically at the interpersonal level remain inadequately understood, thereby highlighting a critical gap in current research. In this article, we first provide a comprehensive review of the relationship between competition and cooperation in interpersonal interactions and subsequently introduce an innovative two-dimensional dynamic model of interpersonal co-opetition. Unlike conventional approaches that conceptualize competition and cooperation as opposing ends of a single continuum, this model treats them as two independent dimensions, thereby establishing “co-opetition” as a distinct and central behavioral state. The model incorporates “social comparison” and “goal alignment” as key driving factors, illustrating how stable personality traits interact with situational and contextual variables to produce dynamic transitions among behavioral states, including cooperation, competition, co-opetition, and avoidance. This framework extends traditional social value orientation theories by emphasizing the importance of bidirectional motivational forces in shaping sequential decision-making processes across context-specific scenarios. It also aligns with evolutionary perspectives suggesting that competition and cooperation are adaptive strategies dynamically adjusted in response to relative payoffs and social cues. Building upon commonly used experimental paradigms for examining co-opetition, this article introduces the “Share Game” paradigm. In this design, participants allocate a fixed pool of resources according to their individual investment proportions. The paradigm generates dual motivational forces: on the one hand, individuals are incentivized to increase their investment to secure a larger share of resources, reflecting competitive tendencies; on the other hand, intrinsic constraints encourage participants to limit excessive competition and minimize resource wastage. Within this paradigm, interpersonal co-opetition behaviors can be quantified across multiple dimensions. First, investment levels are classified relative to the Nash equilibrium and the median strategy, distinguishing cooperation, co-opetition, competition, and extreme behaviors such as over-competition or zero investment. Second, social comparison is operationalized through the relative differences between individual and opponent outcomes, and further supplemented by real-time assessments of emotional valence and arousal. Third, goal alignment is evaluated by comparing the average investments of both parties to the median strategy, indicating the degree of shared objectives. Finally, dynamic variations in sequential decision-making facilitate the disentanglement of two underlying psychological mechanisms: consensus-based regulation and avoidance-driven restraint at the individual level. The study also examines the neural mechanisms underlying the effects of social comparison on co-opetition behavior. Future research is encouraged to integrate neuroimaging techniques with computational modeling. In particular, reinforcement learning approaches can be combined with social comparison metrics, such as upward and downward comparisons, as well as counterfactual reasoning. Such integrative approaches are expected to systematically reveal the computational neural mechanisms that govern interpersonal co-opetition decisions. In conclusion, this study provides systematic empirical support for a two-dimensional dynamic model of interpersonal co-opetition, demonstrating that competition and cooperation are not mutually exclusive but can coexist dynamically within individuals. By incorporating social comparison and goal alignment as core driving factors, the model reveals how stable personality traits interact with situational variables to produce dynamic transitions among cooperation, competition, co-opetition, and avoidance behaviors. The “Share Game” paradigm enables the quantification of co-opetition across multiple behavioral and psychological dimensions, offering a flexible and practical tool for experimental investigation. Furthermore, by integrating evidence from behavioral experiments, computational modeling, and neuroimaging, the study elucidates the neural and cognitive mechanisms underlying interpersonal co-opetition decision-making. This research offers a novel theoretical perspective on how individuals navigate trade-offs in complex social environments and points to three primary directions for future inquiry. First, future studies could investigate the influence of trait differences, such as social comparison tendencies and goal alignment preferences, on co-opetition behavior. Second, experimental paradigms with higher ecological validity could be developed to construct computational models that integrate multidimensional parameters. Third, combining neuroimaging with reinforcement learning, social comparison, and counterfactual reasoning could systematically reveal the computational neural mechanisms underlying co-opetition behaviors. References | Related Articles | Metrics

Select

The application potential, challenges, and implications of artificial intelligence in psychobiography SHU Yueyu, LI Chunjiang, REN Xiaoxiao, XIE Xia, ZHANG Yinxia, SONG Huan 2026, 34 (7):  1284-1298.  doi: 10.3724/SP.J.1042.2026.1284 Abstract ( 103 )   PDF (783KB) ( 98 )   Peer Review Comments This paper focuses on the application of large language models in psychobiographical research, systematically examining the efficiency revolution they bring and the profound crisis of researcher subjectivity they may induce, while innovatively proposing a comprehensive framework to address these challenges. Its core contribution lies in moving beyond the simplistic debate over “whether to use AI” and constructing a theoretical research framework for “how to facilitate human-machine collaboration.” The innovative aspects of this paper are mainly reflected in the following three areas: 1) Systematic and dialectical deconstruction of the application potential and inherent limitations of LLMs throughout the psychobiographical research process.For the first time, using the “puzzling question” analytical model in psychobiography as a framework, the paper meticulously analyzes the specific roles and boundaries of LLMs at each stage of the research process. Through case studies, it demonstrates how LLMs leverage their massive data processing and pattern recognition capabilities to significantly enhance research efficiency and expand researchers’ informational horizons in steps such as “rapidly identifying potential subjects,” “assisting in formulating puzzling questions,” and “collaboratively optimizing text.” However, the paper points out that behind these efficiency advantages lie fundamental epistemological limitations. The operation of LLMs is based on statistical probability rather than genuine understanding, which creates an insurmountable gap in the core aspects of psychobiography. For example, in the stage of “formulating puzzling questions,” LLMs can only generate lists of factual “irrationalities” but cannot achieve the creative leap from “behavioral anomalies” to “meaningful puzzles”—a leap that relies on the researcher's lived experience and existential engagement. This limitation stems from LLMs’ inherent constraints in semantic comprehension and meaning generation, which is also the root cause of superficial risks such as data bias and false content generation. 2) Explicitly propose and deeply elaborate on the core challenge of the “crisis of researcher subjectivity”, revealing its progressive manifestations. Building on an analysis of various technological risks, this paper suggests that the widespread application of LLMs may lead to the erosion and relinquishment of the researcher’s dominant role in meaning interpretation and theoretical creation. Researchers may progress from merely enjoying the efficiency of LLMs in data processing to developing dependence on them for core intellectual activities such as question formulation and theoretical framework selection, thereby outsourcing the creativity that should inherently belong to the researcher to algorithms. When confronted with the structured, professionally articulated analyses produced by LLMs, researchers may unconsciously suppress their own critical thinking, defaulting to the algorithm's “optimal solution,” which could result in a loss of the critical and creative essence essential to the humanities. The paper clearly states that addressing this crisis requires more than mere technical improvements; it demands systematic reconstruction across three levels: data foundation, ethical norms, and methodological processes. 3) Constructing a researcher-led framework to address the crisis. This paper proposes the development of specialized databases based on rich local historical materials (such as Chinese classical texts) and the training of domain-specific LLMs using these resources, thereby establishing a virtuous cycle of “local database——training specialized models——supporting local research——feedback for model correction.” This approach aims to ensure the accuracy and sensitivity of cultural interpretation from the data source, overcoming the cultural blind spots and biases of general-purpose LLMs. At the same time, the paper proposed ethical principles including Human Agency and Accountability, Fairness and Bias Correction, Privacy Protection and Data Security, and Risk Prevention and Dynamic Governance. These principles establish clear behavioral boundaries for responsible technology use. Finally, the paper designs and elaborates in detail an iterative, researcher-led human-computer collaborative research process. The core feature of this process is “the researcher defines the framework, the LLM executes the computations.” Key steps include: manual verification and purification of materials by the researcher; transforming psychobiographical theories into specific analytical dimensions and annotation rules, which are then “injected” into the LLM through fine-tuning or prompt engineering; the researcher ultimately determining the puzzling question based on resonance with the materials; and the researcher reviewing the theoretical fit of the LLM’s coding results. Throughout this process, the LLM consistently serve as “efficient assistants” for processing information, providing options, and generating drafts, while the power to ask questions, establish rules, make critical judgments, conduct in-depth interpretations, and construct theories remains firmly in the hands of researchers. In summary, the novelty of this work lies in providing psychobiography, and qualitative research more broadly, with a comprehensive theoretical framework and practical guide for effectively utilizing technological tools in the AI era while steadfastly upholding the core values of deep hermeneutic interpretation and theoretical innovation inherent to humanities scholarship. References | Related Articles | Metrics