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Does classical music make you smarter? A meta-analysis based on generalized Mozart effect CHEN Lijun, HUANG Meilin, JIANG Xiaoliu, WANG Xinjian Advances in Psychological Science    2023, 31 (12): 2232-2262.   DOI: 10.3724/SP.J.1042.2023.02232 Abstract （5800）   HTML （305）    PDF （1262KB）（6619）       Knowledge map    Since the last century, scholars have increasingly focused on examining how Mozart’s music affects people’s cognitive performance, leading to rapid growth in the empirical literature on the Mozart effect. However, the effect size reported in empirical studies has been inconsistent. To address this, we conducted a meta-analysis based on a systematic and comprehensive review of studies on the impact of classical music, seeking to determine its influence on cognitive performance and the underlying mechanisms at work. We also investigated whether the characteristics of research participants (e.g., age group, gender, cultural context) and elements of experimental design (e.g., type of experimental design, types of control music, the order of music, cognitive task and cerebral hemisphere) moderate the magnitude of the Mozart effect. We identified studies by searching Web of Science, PubMed, ProQuest, WanFang, and China National Knowledge Infrastructure from 1993 to 2022 using the following terms: (“Mozart effect” OR “Mozart music” OR “music effect” OR “classical music”) AND (cognit* OR intellig* OR spati*). Our selection criteria were as follows: (1) the study reported original empirical findings; (2) at least two out of three possible treatments (listening to Mozart's Sonata KV 448, other classical music, or silence/other sounds) were administered to the groups; (3) the study involved the generalized Mozart effect and cognitive performance; (4) participants were the general public, excluding clinical or animal samples; (5) the study was written in either Chinese or English (the languages spoken by the authors). Ninety-one studies (with a total of 172 independent effect sizes and 7,159 participants) were included in the meta-analysis. Given that effect size could be influenced by participant characteristics (e.g., age, gender, cultural context), we applied a random-effects model. After coding the data, the “metafor” package (version 3.4.0) in R software was used to evaluate the total effect size of classical music and to analyze the publication bias test and moderating effects. The results showed that classical music improved cognitive task performance with a small effect (g = 0.36, 95% CI [0.24, 0.49]). The impact of publication bias was minimal, and the major findings remained valid. Additionally, the moderation analyses revealed that the strength of the relationship was moderated by age group, cultural context, type of experimental design, and dominant hemisphere of the brain. Specifically, the effect size of Chinese subjects was significantly larger than that of foreign subjects (g: 0.64 > 0.27, p = 0.018), and the effect size of preoperational stage children (3~6 years) was the largest (g= 1.10). Compared with the within-subject design, the between-subject effect was significantly greater (g: 0.48 > 0.22, p = 0.037). The right hemisphere also performed much better than the left (g: 0.44 > 0.08, p = 0.019). Moreover, gender interacted with age group, cultural context and cerebral hemisphere. The direct priming hypothesis received more robust support from this meta-analysis (g: 1.29 > 0.34, p = 0.045). To summarize, this study makes several important theoretical advances. First, this study systematically assessed the effects of listening to classical music on cognitive performance basing on a broad definition of Mozart effect, covering a wider range of musical genres and cognitive task types. It bridged the limitations of existing meta-analyses, clarified the debate on the reliability and scientific validity of the Mozart effect, and laid the groundwork for in-depth discussions. More importantly, this paper was the first to compare the effect sizes based on the "Direct Priming Hypothesis" and the "Arousal-mood Hypothesis", indicating the former to be more adept at explaining the Mozart effect. This provided a clearer theoretical guide for future researches. Finally, by examining the moderation effects of several factors, this paper explained why previous literature on the Mozart effect has reported inconsistent findings and provided more targeted design guidance for future studies. Beyond its theoretical advancements, the current paper’s results also have practical implications, such as the implications of age group differences and their interactions for children's cognitive development. The results can also aid in utilizing music education more effectively to boost cognitive performance. Future researches are encouraged to examine the long-term facilitative effect of classical music on cognitive performance, to explore the role of music preference in cognitive facilitation, and to explore more underlying moderators for the intervention effect size, such as subjects' personality traits, familiarity with music, and difficulty of the cognitive task. Table and Figures | Reference | Related Articles | Metrics

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Personality dynamics: The integration of process and trait WU Fan, HU Yueqin Advances in Psychological Science    2023, 31 (7): 1269-1287.   DOI: 10.3724/SP.J.1042.2023.01269 Abstract （5774）   HTML （180）    PDF （1011KB）（25814）       Knowledge map    Personality dynamics is a research perspective that focuses on intra-individual processes and their relationship with inter-individual personality traits such as Big Five. From the beginning, personality psychology has emphasized the dynamic nature of personality. Early theories of personality dynamics have been proposed but were not tested due to restrictions in methodology until the last two decades when the widespread use of intensive longitudinal analyses brought the personality dynamic approach back into focus. Theories of personality dynamics have several emphases: (1) distinguishing between stable and unstable components in the personality system; (2) the personality system is self-regulating; (3) situational and environmental factors are integral to understanding personality; and (4) personality is a multi-process system. While different theories of personality dynamics share the goal of explaining the underlying processes of observable personality traits, they can be further divided into personality process models and integrative models according to their different theoretical emphases. Personality process models focus on the influencing factors and mechanisms that produce behaviors in different contexts, i.e., why people behave differently in different situations. Prominent theoretical perspectives include theories that explain behaviors based on neurophysiology (e.g., the reinforcement sensitivity theory), the social-cognitive theories that explain behaviors via processes such as information processing, goal pursuit, and self-regulation (e.g., the cognitive-affective personality system model), and theories that emphasize the different types of interactions between persons and situations/environments (e.g, the person-environment relations model). In contrast, personality integrative theories attempt to integrate personality process models and trait models, focusing on explaining the causes of stable intra- and inter-individual personality structures by zooming in on the evolutional basis of human beings or the complex interactions of dynamic social-cognitive processes. Research questions include, for example, “What is the specific set of causal processes that underlie a specific trait?”, or “What are the causing forces underlying the inter-individual personality structures such as the big five personality traits?”. Representative theories addressing these issues include the whole trait theory, the knowledge-and-appraisal model of personality architecture, and the cybernetic big five theory. Empirical research on personality dynamics employs a range of methods designed to analyze the within-person multivariate dynamic functioning, the complex interrelationships therein, and the relationships between processes and traits. Intensive longitudinal design with the experience sampling method is commonly used. Intensive longitudinal data are usually analyzed using statistical models that can handle multi-level structures (e.g., multilevel models, multilevel structural equation modes), reciprocal relationship (e.g., dynamic structural equation models and group iterative multiple model estimation), multivariate network system analysis and visualization (e.g., graphical network analysis), and system-level feature extraction (e.g., dynamic system models). Based on these methods, applied personality research in organizational, educational, and clinical psychology has made progress on topics such as within-person variability in personality states and their correlation with variables of interest in the related field. Future research could address the following issues. Theoretically, researchers should pay attention to the distinctions and connections between intra-individual and inter-individual personality structures. Also, theories of personality dynamics, which focuses on the personality of normal individuals, can be integrated with the theory of psychopathology. In addition, future researchers can also consider how to incorporate temporal effects into theories. Empirically, future researchers could: incorporate different sampling methods, such as self-reports, others’ reports, behavioral indicators, and electronic footprints, to further sort out the sources of variance in personality states; measure multiple psychological processes simultaneously, such as the biological, cognitive, affective, and motivational processes underlying a particular trait; manipulate or measure personality states in a clearer and more precise manner to ensure that they are representative of the chosen personality, for example, measure personality facets rather than traits; and report reliability at the within-person level in multilevel analyses. Table and Figures | Reference | Related Articles | Metrics

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Conceptualization of time poverty and its impact on well-being: From the perspective of scarcity theory SUN Xiaomin, YANG Shuting, KONG Xiaoshan, LIU Zhenzhen, MA Rongzi, YUAN Yue, ZHANG Nan, JIANG Xinying, CAO Peiling, BAO Ruiji, LIN Yiqin, LI Ning, LI Zhihang Advances in Psychological Science    2024, 32 (1): 27-38.   DOI: 10.3724/SP.J.1042.2024.00027 Abstract （5750）   HTML （381）    PDF （716KB）（10013）       Knowledge map    In today’s fast-paced world, increasing numbers of individuals are facing time poverty, i.e., having too much to do and not enough time. It can impact people's cognitive processes and behaviors by affecting their attention. However, the extant literature provides only a limited understanding of the influence of time poverty and its effects on individual multi-faceted well-being. Therefore, a comprehensive investigation of the concept of time poverty and its impact on well-being is of great importance theoretically and practically. The current study intends to present a three-dimensional theoretical model for the construct of time poverty from an integrated perspective, aiming to explore its effects on multi-faceted subjective well-being and investigate the potential mechanisms by which time poverty reduces well-being based on scarcity theory. Specifically, the current study proposes a three-dimensional structure for the concept of time poverty, which includes length, intensity, and quality. Most researchers agree that spending an excessive amount of time on paid work or unpaid domestic work and having an insufficient amount of free time leads to time poverty. Moreover, the number of tasks to be completed per unit of time may be an independent source of pressure resulting in the perception of time poverty. The stressful pace caused by over-rapid task completion and too short intervals could increase the sense of time poverty. Lastly, the quality dimension of time poverty comprises time integrity, time autonomy, and time synchronization. Low time quality could worsen the perception of time poverty. Based on the three-dimensional model of time poverty, the current study aims to develop a time poverty scale and construct a large-scale Chinese time poverty database. This database is designed to collect demographic information as well as the level of time poverty of representative samples, aiming to explore the dominant type of time poverty for different demographic groups and trace the dynamic changes in time poverty over time. Furthermore, the current study proposes that time poverty can have a significant impact on people’s well-being. Time poverty can develop a scarcity mindset, leading people to focus on the scarcity of time. Consequently, they overemphasize productivity, resulting in a strong inclination of completing more tasks in a shorter amount of time. Such a mindset shifts people’s attention from the activity’s process to its results, reducing intrinsic motivation and, as a result, ruining people’s well-being. An excessive focus on productivity can also harm interpersonal and family well-being by underestimating the importance of investing time and energy in nurturing relationships, thereby lowering the quality of relationship-oriented interactions. Therefore, we argue that by promoting the over-productivity orientation, time poverty can adversely affect individual, interpersonal, and family well-being. Furthermore, time poverty in one spouse's workplace produces an over-productivity tendency which then spills over to the family environment and is conveyed to the other spouse in their daily interactions. Such processes are likely to negatively influence both parties’ well-being. Overall, the current project develops a three-dimensional time poverty theoretical model, based on which a time poverty scale will be developed. With the new scale, a large-scale database will be constructed. The project will explore the experiences of different groups of people with distinct characteristics in Chinese society, and how such experiences influence personal, interpersonal, and family well-being. The results of the current project are of great importance for not only the successful coping of time poverty for individuals but also for societies aiming to improve the well-being of their people. Table and Figures | Reference | Related Articles | Metrics

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“Rat Race” or “Lying Flat”? The effect of competition stress on psychological compensation WANG Wangshuai, YI Yanxi, LUO Zhiwei, LI Jie Advances in Psychological Science    2024, 32 (7): 1057-1072.   DOI: 10.3724/SP.J.1042.2024.01057 Abstract （5140）   HTML （422）    PDF （710KB）（17600）       Knowledge map    In the modern society with rapidly accelerating pace, competition has become ubiquitous and intense. No doubt that competition can lead to aversive psychological stress. Interestingly, in response to the competition stress, individuals choose two contradictory compensation strategies, as some go “Rat Race”, while others do “Lying Flat”. Why do individuals make contrasting choices? Does it result from different types of stress? What are the psychological mechanisms and boundary conditions of the “Rat Race” and “Lying Flat” effects, respectively? In the current literature, none of these questions has been answered. Therefore, the core concepts of this research are competition stress and psychological compensation; the central story is to reveal the relationship between different types of competition stress and psychological compensation. More specifically, this research distinguishes the multi-dimensional attributes of competition stress. Based on the theory of psychological compensation, we then explore individuals’ compensation strategies when faced with different types of competition stress. The paper is structured into three main sections: (1) competition stress is a multi-dimensional concept, encompassing both competition result stress and competition process stress; (2) competition result stress leads to the fluid compensation strategy, which is termed as the “Rat Race” effect. The psychological mechanism of this effect is self-esteem threat, and the boundary condition is self-affirmation; (3) competition process stress drives the escapism compensation strategy, which is termed as the “Lying Flat” effect. The psychological mechanism of this effect is well-being threat, and the boundary condition is social support. This study marks the first attempt to identify different types of competition stress and examines how they respectively affect individuals’ compensation strategies. The present paper significantly contributes to the existing literature on competition stress, psychological compensation, self-esteem, and well-being. Moreover, research findings can guide companies’ marketing activities, promote individual well-being, and assist public policy making. The research questions of this paper are rooted in practicality and real-world, and answering these questions in turn contributes to the extant literature in at least two ways. First, while existing research on competition stress has shed light on how it alters an individual’s physical and mental states, it portrayed competition stress as a unidimensional construct, overlooking its potential multidimensional nature. Moreover, prior studies have failed to explore individuals’ compensatory strategies under competition stress. Consequently, this research reveals the multidimensional attribute of competition stress, delineating it into competition result stress and competition process stress. Subsequently, how different types of competition stress lead to contrasting compensatory strategies are analyzed, including the “Rat Race” effect engendered by competition result stress and the “Lying Flat” effect prompted by competition process stress. Second, this paper contributes to the literature on self-esteem and well-being. Specifically, regarding self-esteem, while previous research has primarily examined its direct influence on individuals, this study uncovers that self-esteem serves as the underlying psychological mechanism driving the “Rat Race” effect. In terms of well-being, despite being frequently investigated in extant research, yet it received less attention in explaining psychological compensation. Therefore, findings from the present research enrich the literature on well-being, expanding our understanding of its connections with competition stress and compensatory behaviors. Aside from the theoretical contributions, the current research also provides practical implications in three ways. For enterprises, the psychological compensation behavior impelled by competition stress is shown to follow a traceable pattern, which can be leveraged for increasing market share and sales profits. For instance, product slogans aimed at individuals opting for “Rat Race” can aim to evoke their competitive mindset, while brands tailored to those embracing “Lying Flat” should emphasize concepts like escaping the “noise” and maintaining the inner peace. As for individuals, it is suggested that when faced with severe competition stress, individuals can restore psychological resources through recalling past successful experiences or seeking for the support from families and friends. Furthermore, for policymakers, given that over-competition may lead to negative outcomes, this research reminds policymakers to maintain a moderate competition level in the society and to make necessary interventions when necessary. Table and Figures | Reference | Related Articles | Metrics

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The relationship between anxiety, depression and social comparison in an era of digital media ZHAO Li, BAI Sha Advances in Psychological Science    2025, 33 (1): 92-106.   DOI: 10.3724/SP.J.1042.2025.0092 Abstract （4888）   HTML （477）    PDF （3140KB）（9244）       Knowledge map    The prevalence of anxiety and depression has escalated, prompting the current study to investigate the antecedents and coping strategies for these conditions in an era of digital media. A theoretical framework grounded in affective events theory and social comparison theory is built to elucidate the relationships between social comparison and anxiety and depression, acknowledging that such relationships are contingent upon the influences of the social media environment. This review unveils that negative social comparison (upward comparison and downward assimilation comparison) exerts a deleterious impact on anxiety and depression, with social networking applications catalyzing these adverse effects. Conversely, emotional comparison (i.e., social comparison of emotions) and downward contrast comparison are positively associated with alleviated anxiety and depression, as online health communities fostered a supportive milieu for emotional comparison, thereby helping to mitigate these conditions. This study extends social comparison theory in the realm of emotion and identifies the affordance of online health communities for coping with anxiety and depression. The implications for the principles of design, management, and operation of such communities are further discussed. Previous research on the relationship between social comparison and anxiety/depression has yielded divergent findings. Some studies have identified social comparison as a paramount factor in initiating, perpetuating, and exacerbating anxiety and depression. Conversely, others have demonstrated that emotional comparison may alleviate stress and anxiety. Unfavorable comparisons with others across various dimensions, such as interpersonal relationships, social status, abilities, accomplishments, careers, income, and appearance, can precipitate psychological disorders like anxiety and depression. However, emotional comparison contributes cognitive clarity, empathic comfort, prevention, and learning, proving to be a coping mechanism for individuals experiencing negative emotions like anxiety in threatening situations. By delineating the distinct subtypes of social comparison, this review elucidates, to some extent, the seemingly complex and contradictory findings in the extant literature on the relationship between social comparison and anxiety and depression, as well as the internal logic behind the dual impact of social comparison on anxiety and depression. Previous studies have underscored the markedly distinct role of online media environments in shaping the relationship between social comparison and anxiety/depression. On one hand, social networking platforms have expanded the scope of comparisons, diversified the targets of comparison, and increased the accessibility of social comparison information; consequently, the frequency of social comparisons has substantially escalated. Moreover, the editability of information on social networking platforms, the selective presentation of users, and the positive bias of self-presentation (i.e., individuals showcasing their best selves, exaggerating their self-importance, overstating their accomplishments and enjoyment of life, blatantly exhibiting, and even selectively displaying or altering photographs to enhance their appearance) exacerbate the deleterious impact of upward social comparisons, which can provoke anxiety and depression. On the other hand, the characteristics of online health communities (i.e., anonymity, homogeneity, normative, social, and on-demand availability) provide a conducive environment for emotional communication and social comparison, thereby facilitating the amelioration of anxiety and depression. The review delves into the intricate mechanisms of anxiety and depression within the within the digital media era. It elucidates the intrinsic link between anxiety/depression and social comparison as well as the affordances of online health communities. Furthermore, it conducts a comprehensive exploration of emotional comparison, which has the potential to advance social comparison theory within the emotional realm and broaden the scope of emotional comparison theory in the context of internet-based healthcare. The discussion of the bi-directional effects of social comparison on anxiety and depression underscores the self-reinforcing spiral of individual negative emotions, a notable consideration when addressing the emotional experiences of anxious and depressed groups. Given the pervasive, disseminated, and developmental affective states, coupled with the distinctive social comparison proclivity exhibited by anxiety-depression cohorts, it is imperative to investigate the emotional adversities (emanating from social interactions) of stigmatized groups through the theoretical lens of intergroup emotions. The ubiquity of self-disclosure, extensive accessibility, and traceability of information facilitated by online communities present opportunities to ameliorate mental health outcomes or manage emotional preoccupations. Subsequent empirical inquiries should delve into the efficacy of online communities in the identification, diagnostic processes, and therapeutic modalities for anxiety and depressive disorders, with particular emphasis on the delineation of online and offline domains, as well as the trade-off between the dichotomous effects of social comparison in digital spheres. Table and Figures | Reference | Related Articles | Metrics

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The influence of AI awareness on employee’s psychological and behavioral outcomes and its theoretical explanation WANG Tao, ZHAN Xiaojun, YU Wei Advances in Psychological Science    2024, 32 (7): 1195-1208.   DOI: 10.3724/SP.J.1042.2024.01195 Abstract （4419）   HTML （253）    PDF （609KB）（7239）       Knowledge map    AI awareness refers to an employee's perception that the use of AI affects their work attitude, behavior, well-being, and work environment. The fourth Industrial Revolution has arrived, and while AI improves employee performance, it also brings risks and uncertainties that have a huge impact on employees. Although many studies have explored the impact of AI awareness on employees' psychological and behavioral outcomes, due to scholars' academic background, current studies are more focused on the field of relative segmentation. At the same time, because the concept of AI awareness is relatively new, its name is not unified, and the ambiguity of the concept limits the public's in-depth insight into AI awareness. In addition, the action path and boundary conditions of AI awareness on employees' psychological and behavioral outcomes have not yet been clarified, and the lack of AI awareness research framework has hindered the understanding of how AI application affects employees' psychological and behavioral outcomes. In order to explore the specific impact of AI application on employees and its function explanation mechanism, firstly, the research on AI awareness was systematically reviewed, the concept connotation of AI awareness was clarified, and AI awareness was re-defined as employees' perception of the impact of AI application on their work attitude, behavior, well-being and working environment. This definition highlights the two-sided nature of AI awareness, that is, AI awareness has both positive and negative effects on employees, rather than just negative effects. Second, it reveals the effects of AI awareness, advancing the understanding of how AI awareness affects employee psychology and behavior. The positive and negative effects of AI awareness on employees' psychological state are explained from the three aspects of emotion, stress and cognition, and the positive and negative effects of AI awareness on employees' behaviors are explained from the two aspects of active and negative behaviors, so that organizations and academia can more clearly, comprehensively and systematically recognize the important effects of AI application on employees' psychological and behavioral outcomes. Promote research in related fields. Thirdly, the theoretical explanation mechanism of AI awareness is explained based on resource perspective (conservation of resources theory, JD-R model), pressure perspective (cognitive evaluation theory), psychological needs perspective (self-determination theory), and environment perspective (person-environment fit theory). Finally, the paper elaborates on five aspects: exploring the multi-level driving mechanism of AI awareness, enriching the action mechanism of AI awareness, mining the spillover effect of AI awareness and strengthening the interaction impact between AI and employees, and builds an integrated model diagram for future research on AI awareness, which will help promote local relevant research. By answering the above questions, it is expected to provide theoretical reference for the subsequent research of scholars, enhance the academic community's cognition and understanding of how the application of AI affects employees, and provide new ideas for promoting the development of AI research. At the same time, it is revealed that managers in the era of Industry 4.0 should re-examine themselves, understand, learn and trust AI technology, use AI technology to develop new skills to improve their management ability, help organizations adopt AI technology more effectively, prevent risks and promote the healthy development of organizations. Managers must clarify the use of AI technology, allow employees to participate in the process of developing and implementing AI systems, eliminate misunderstandings and mistrust, and conduct AI technology training for employees, so that employees have more understanding of AI, reduce the sense of rejection of AI, and recognize that coexistence with AI is an inevitable development of the times. At the same time, it also informs employees that the purpose of applying AI is to help rather than replace them, relieve employees' anxiety and sense of threat, reduce their fear of unemployment, enhance employees' positive cognition of the application of AI, and then reduce their negative evaluation of the application of AI, and help organizations maximize the positive side of AI and reduce the dark side brought by AI. Table and Figures | Reference | Related Articles | Metrics

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A meta-analysis of the impact of AI application on employees in the workplace JIANG Jianwu, LONG Hanhuan, HU Jieyu Advances in Psychological Science    2024, 32 (10): 1621-1639.   DOI: 10.3724/SP.J.1042.2024.01621 Abstract （4412）   HTML （206）    PDF （743KB）（8658）       Knowledge map    Given the widespread application of artificial intelligence (AI) technologies in workplaces, there has been a rapid increase in literature exploring AI-related themes. Scholars are increasingly focused on understanding how these applications influence employee behaviors and psychology. However, consensus on the direction, boundaries, and extent of these effects remains elusive. To address this issue, this paper conducts a meticulous review and selection of literature published from January 2017 to July 2023. A meta-analysis is performed on the 64 literatures (N = 150) to advance knowledge in three main areas: (1) Explore the strength and direction of the relationship between AI application and employees’ positive behaviors and psychological effects, as well as their negative behaviors and psychological effects. This aims to clarify the inconsistent conclusions and fill gaps in quantitative integration. (2) Based on the Job Demands-Resources model, this paper delineates the theoretical rationale underlying the impact of AI on employees’ behavior and psychology within an organizational context, upon its integration as a new technology, and elucidate specific pathways of its effects. (3) Investigate whether the effects of AI application on employee behavior and psychology are potentially influenced by the type of AI application, industry context, and measurement methods. Endeavor to furnish a clearer and more comprehensive overview of the correlation between AI and employee outcomes, thereby providing a theoretical foundation for tailored AI advantages in practical settings and methodological designs for subsequent empirical research in academia. The result finds that: (1) The application of AI in the workplace exhibits a “double-edged sword” effect, which can enrich employees' psychological resources as technical support and stimulate positive behaviors, may also threaten employees to consume psychological resources and cause negative behaviors. (2) The relationships between AI application and employee behaviors/psychological effects vary under different AI types. Assisted and augmented AI enhance employee job satisfaction by reducing task costs, thereby increasing work engagement, creativity, and productivity. Such abundance in work resources contributes to an uplift in employees' job satisfaction and happiness. Consequently, when employees experience greater job involvement, there is a notable increase in creativity and productivity. However, managerial and autonomous AI types, despite improving efficiency and autonomy to some extent, introduce stress due to their supervisory and controlling attributes, suppressing positive work experiences and fostering negative psychological states. (3) Variations in AI application effects on employee behaviors and psychological effects across different industry types are evident. Employees in labor-intensive industries, with structured work environments and lower occupational skills, perceive more negative effects from AI. Conversely, employees in knowledge-intensive industries benefit from more flexible and autonomous work environments enhanced by AI, demonstrating stronger abilities in receiving, learning, and adapting to new information and technologies. (4) The relationship between AI application and employee behavior, as well as psychological impacts, varies depending on diverse measurement of AI application. Studies using subjective evaluations tend to reveal more negative impacts of AI on employee behaviors and psychological effects compared to those using objective measurement methods. This study has made several theoretical contributions: (1) Systematically integrate and evaluate the fragmented research conclusions on the effects of AI application on employee behaviors and psychology, synthesizing empirical findings and responding to calls in the literature for understanding the personal impacts of automation technologies. (2) Within the framework of Job Demands-Resources model, this paper elucidates the diverse impacts of different types of AI application on employee behavior and psychology, expands the influencing factors that could augment the positive results of AI application, and further validates the concerns regarding potential adverse consequences. (3) Enrich the boundary conditions in the relationship between workplace AI application and employee behavior and psychology. This paper explores the moderating effects of the type of AI application, industry context, and measurement methods, responding to the scholarly calls for further examination of moderating variables of AI application affecting employee experience, thereby offering new insights for inconsistent research conclusions in the academic literature. Beyond theoretical advancements, the results of this study provide guidance for organizations to scientifically adjust the management strategies of AI, accurately direct employees perceptions, and effectively maximize its value. Table and Figures | Reference | Related Articles | Metrics

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The occurrence mechanism of short video indulgence from the perspective of human-computer interaction DONG Wanghao, WANG Weijun, WANG Xingchao, LI Wenqing Advances in Psychological Science    2023, 31 (12): 2337-2349.   DOI: 10.3724/SP.J.1042.2023.02337 Abstract （4401）   HTML （282）    PDF （721KB）（9461）       Knowledge map    Short video indulgence refers to an individual’s compulsive and uncontrollable consumption of short videos, leading to significant behavioral or attention impairments, and subsequently causing difficulties in interpersonal relationships, learning, and/or work adaptation. With the continuous expansion of the short video user base and the trend towards younger groups, threats of short video indulgence to users’ physical and mental health have aroused extensive attention. From a human-computer interaction perspective, we synthesized and delineated the relevant factors contributing to the occurrence of short video indulgence. The objective is to formulate a comprehensive framework delineating the intricate mechanism that underpins the phenomenon of short video indulgence, thereby shedding light on the intricacies involved in its developmental process. At first, in order to explore the delineation between short video usage and indulgence, we categorized short video usage into “instrumental” and “ritualistic” forms. Instrumental usage refers to user behavior driven by specific goals or needs, where short videos serve as tools or means to achieve particular objectives. Ritualistic usage refers to user behavior without a specific objective, where short videos become habitual behaviors associated with particular contexts, times, or situations. The transition from conventional utilization of short videos to the state of short video indulgence appears to encompass a notable shift in usage behavior, evolving from a utilitarian “instrumental” function to a more “ritualistic” engagement. After that, the present work formulates a conceptual framework delineating the mechanisms underlying the onset of short video indulgence, delving into the domains of human-computer interaction and susceptibility traits. The first section encompasses four facets: information technology, content provision, human-computer interaction, and user experience. Their salient characteristics encompass technological advancement, content richness, interactive efficiency, and user immersion. Furthermore, propelled by recommendation algorithms, users’ engagement with short videos becomes increasingly fortified. The second section systematically expounds the susceptibility factors contributing to short video indulgence. The four categories of unique susceptibility traits align with the four stages of interactive mechanisms, while the categories represented by common susceptibility traits have an inducing effect on general addictive behaviors. Considering the analogous nature of short video indulgence to general online indulgence, the unique and common susceptibility traits exhibit mutual intersection and overlap. Overall, the role of interactive mechanisms lies in arousing susceptibility traits, rendering individuals more susceptible to allure and ensnarement in a cycle of addictive behaviors. Simultaneously, susceptibility traits amplify users’ responsiveness and vulnerability to inducing factors. The multifaceted components within the realm of human-computer interaction, propelled by recommendation algorithms, intricately intertwine with users’ susceptibility traits, driving the transformation of users’ engagement with short videos from an “instrumental” to a “ritualistic” approach, ultimately leading to the emergence of short video indulgence. This framework seeks to illuminate the genesis and progression of short video indulgence, offering researchers in this domain a comprehensive conceptual structure to foster the scientific governance of short video indulgence. Subsequently, in order to achieve a deeper understanding of the mechanism behind short video indulgence, we offered theoretical interpretations of short video indulgence from cognitive, emotional, motivational, and social perspectives. The dual process theory, opponent process theory, uses and gratifications theory and social shaping of technology theory were employed to elucidate the process of short video indulgence formation. Finally, this study concludes by summarizing the existing shortcomings in the current field of research. The points are concluded as follows: 1) The research methods are limited, there should be a diversification of research perspectives; 2) Insufficient attention to technology emphasizes the need to emphasize improvements in technology that contribute to addiction; 3) The mechanism of formation is unclear, there should be a deepening of the research into the mechanisms of occurrence; 4) Inadequate research on user characteristics highlights the need to focus on susceptibility factor studies. Table and Figures | Reference | Related Articles | Metrics

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When AI learns to empathize: Topics, scenarios, and optimization of empathy computing from a psychological perspective HOU Hanchao, NI Shiguang, LIN Shuya, WANG Pusheng Advances in Psychological Science    2024, 32 (5): 845-858.   DOI: 10.3724/SP.J.1042.2024.00845 Abstract （4306）   HTML （273）    PDF （729KB）（16081）       Knowledge map    Empathy computing is an emerging research field that integrates artificial intelligence (AI) and big data technology to predict, identify, simulate, and generate human empathy. This field builds upon psychological studies in terms of concepts, measurements, neural foundations, and applications of empathy, and employs innovative computing approaches for analyzing and simulating empathy. This article critically reviews current research on empathy computing and discusses its future directions from a psychological perspective, with the aim of facilitating foundational research and practical applications in this field. The current research on empathy computing can be categorized into four themes based on different purposes and methods. On one hand, empathy computing primarily aims to analyze and comprehend empathy using computers. This endeavor can be further divided into two categories: (1) individual empathy assessment, which focuses on analyzing individual empathetic traits, and (2) empathetic content classification, which focuses on analyzing empathetic features in texts rather than individuals. On the other hand, research also focuses on simulating and expressing empathy through computing, which includes (3) the design of empathetic response systems and (4) the development of generative empathetic dialogue systems. The former provides users with a limited number of predefined rule-based responses and feedback to express empathy, while the latter utilizes AI to automatically generate a wide range of empathetic dialogues without relying on predefined rules. These four research streams are relatively independent yet complementary. Moreover, as research progresses, new directions will continue to emerge, such as improving the empathic capabilities of computers through brain-computer interface technology. Although research on empathy computing is still in its early stages, it has shown potential for innovative applications in scenarios such as mental health, education, business services, and public management. With the increasing prevalence of artificial intelligence, these fields, which involve substantial interpersonal interactions, are positioned to become the primary domains for human-computer interaction. As a result, they emerge as the key application scenarios for empathy computing. In the realm of mental health, empathy computing can assist in automatically evaluating and enhancing therapists' empathetic abilities. Additionally, it can provide personalized empathetic support and guidance through AI-driven chatbots. In the field of education, empathy computing can facilitate the learning process by employing empathetic AI tutors. Within the business sector, it enables organizations to deliver tailored customer experiences, thereby enhancing satisfaction and fostering loyalty through the generation of empathic dialogues. In public management, empathy computing can be used to generate empathetic discourse to counteract negative speech. Additionally, it facilitates policymakers to respond empathetically to citizens' needs and inquiries, thereby fostering trust between the government and the public. These four scenarios illustrate the vast potential applications of empathy computing. However, due to concerns related to safety and ethics, complete reliance on computers to perform empathetic tasks is currently not feasible. Instead, a collaboration between humans and computers is necessary. Empathy computing represents a transformative frontier, not only providing methods to measure and analyze empathy automatically on a larger scale but also enriching the theoretical landscape of empathy research. It extends traditional studies on empathy in interpersonal relationships to explore its emerging manifestations in human-AI relationships. This expansion raises novel questions about the universality of empathy and its potential evolution in human-computer interaction. Empathy computing holds the promise of serving as a cornerstone for a unified theory of empathy that encompasses diverse relationship dynamics, ranging from human-human to human-machine interactions and beyond. It is beneficial for comprehensively understanding empathy and effectively promoting it in the context of an intelligent society. Future research should focus on developing integrated theoretical models of empathy computing, establishing reliable psychological and behavioral datasets of empathy-related characteristics, and validating and refining empathy computing research through a human-centered approach. Psychologists play indispensable roles in leading, evaluating, and optimizing research and practice in this field. The collaboration of scholars in psychology and computer science is imperative to ensure that AI learns empathy effectively and ethically, thereby fostering people’s wellbeing in the forthcoming intelligent society. Table and Figures | Reference | Related Articles | Metrics

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The influence of loneliness on consumption behavior and its theoretical explanations LI Ting, KONG Xiangbo, WANG Fenghua Advances in Psychological Science    2023, 31 (6): 1078-1093.   DOI: 10.3724/SP.J.1042.2023.01078 Abstract （4290）   HTML （404）    PDF （933KB）（8878）       Knowledge map    Loneliness has become an increasingly common social phenomenon that is widespread at all ages and has an impact on people's daily lives in modern societies. Loneliness is a painful emotional experience that individuals subjectively perceive when the quality of intimate or social relationships does not meet ideal expectations or when they cannot satisfy their need to belong. Recent research findings regarding the impact of loneliness on consumption behavior have contributed greatly to the field of consumer behavior. However, the results of existing research are inconsistent and it is still unclear how loneliness affects consumption behavior. As a consequence, the field of consumer behavior is rather constrained in terms of research development and marketing strategy. In light of the importance of loneliness in the field of consumer behavior, this article systematically reviews the research findings of the influence of loneliness on consumption behavior in order to solve the above problems. First of all, this article summarizes and generalizes the widely used manipulation methods (including the feedback-evoked method, recall-evoked method, imagination-evoked method, and cue-evoked method) and measurement tools (i.e., the UCLA loneliness scale) for loneliness. Secondly, this article summarizes the effects of loneliness on consumption behavior from four aspects, including compensatory consumption behavior, avoidance consumption behavior, irrational consumption behavior, and uniqueness consumption behavior, respectively. Thirdly, this article analyzes and sorts out the triggering mechanisms and situational factors of loneliness-induced consumption behaviors, respectively. According to the Evolutionary Theory of Loneliness, this article contends that, the psychological needs (e.g., seeking social connection, restoring a sense of control, and seeking a sense of meaning in life) activated by transiently lonely consumers, who are influenced by the approach motive for restoring self-difference, will induce compensatory consumption behaviors. The social avoidance tendency activated by chronically lonely consumers, who are influenced by the avoidance motive for self-preservation in the short term, will induce avoidance consumption behaviors. At the same time, constant vigilance for social threats and the negative emotions it produces (e.g., anxiety) due to social avoidance may deplete lonely consumers’ self-regulatory resources, which will induce irrational consumption behaviors. The need for uniqueness activated by chronically lonely consumers, who are influenced by the avoidance motive for self-preservation in the long term, will induce uniqueness consumption behavior. In addition, loneliness motivates consumers to induce these above consumption behaviors will be influenced by factors such as consumers' intimacy status, marketing strategies, product attributes, and consumption contexts. Finally, the article explains the influence mechanisms of loneliness on various types of consumption behaviors based on different perspectives such as social surrogacy theory, sense of control theory, compensatory consumption behavior theory, self-regulation theory, and personality trait theory. Although many valuable results have been obtained from existing research on the effects of loneliness on consumer behavior, there are still some key issues that need to be addressed by future research. This article proposes that future research shall pay more attention to the impact of loneliness on altruistic consumption behavior (e.g., examining the effects of loneliness on pro-social consumption behavior or sustainable consumption behavior), the differential effects of type and degree of loneliness on consumption behavior (e.g., examining the differential effects of transient and chronic loneliness on consumption behavior), the potential moderators of loneliness-induced consumption behavior (e.g., exploring the boundary variables of loneliness-induced consumption behavior in terms of consumers' physiological activities, personality traits, and social characteristics), the internal mechanisms of loneliness-induced consumption behavior (e.g., attempting to explore the internal mechanisms of loneliness-induced consumption behavior from the cognitive-emotional dual processing path), as well as the reverse impact of consumption behavior on loneliness (e.g., clarifying the differential effects of consumption behavior on individual loneliness in the short and long term). Table and Figures | Reference | Related Articles | Metrics

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A meta-analysis of the relationship between perceived social support and student academic achievement: The mediating role of student engagement WU Jiahui, FU Hailun, ZHANG Yuhuan Advances in Psychological Science    2023, 31 (4): 552-569.   DOI: 10.3724/SP.J.1042.2023.00552 Abstract （4241）   HTML （317）    PDF （982KB）（8503）       Knowledge map    Academic achievement can be considered as a measure of student's knowledge level and adaptation to school. As a valid indicator for quantitatively assessing the effectiveness of national education, academic achievement has become a key concern for students, parents, schools, and society. While intrinsic motivation is important in the process of increasing academic achievement goals, extrinsic support is equally essential for students. In recent years, empirical studies based on social cognitive theory have analyzed the relationship between social support and academic achievement, revealing that perceived social support is more predictive and functional. With continuing advances in developmental psychology, current research is increasingly focusing on the mediating mechanisms between perceived social support and academic achievement. Student engagement is a specific indicator of student involvement in the learning process and an important measure of learning competence; thus, it can positively and significantly predict academic achievement. However, there are no uniform findings on how perceived social support and its sub-indicators affect academic achievement, and the extent to which both are influenced by student engagement factors has not thus far been definitively addressed. In addition, the current meta-analysis failed to comprehensively validate the correlation between perceived social support and academic achievement, exploring only the relationship between the three indicators of perceived social support and academic achievement, and the study tended to focus on a single dimension such as autonomy support. Moreover, current meta-analyses have not yet comprehensively revealed the mediating role of student engagement, with most studies focusing on integrating effect sizes and exploring possible moderating variables, using samples that do not involve mediating variables or the studies have devoted themselves to exploring the effects of multiple factors (e.g., individuals' cognitive and non-cognitive factors) and their chained relationships on academic achievement, with inclusion samples covering multiple mediating variables. In light of this, the current study classified perceived social support based on the microsystems that most directly influence student development in ecological systems theory and used meta-analysis to obtain reliable estimates of effect sizes, mediating effects of student engagement, and a range of moderating effects in conjunction with self-system processes theory. A total of 41 empirical research and 78 studies were included through literature retrieval. The results were as follows: (1) There was a significant positive correlation between perceived social support and its sub-indicators and academic achievement; however, because the effect values were small, a weak correlation was indicated, with perceived social support as a whole having the strongest correlation, followed by perceived teacher support, perceived parental support, and perceived peer support. In addition, perceived social support and its sub-indicators were found to be positively related to student engagement. The effect of perceived social support and its sub-indicators on student engagement was higher than academic achievement. (2) Student grade moderated the relationship between perceived teacher support and academic achievement only. Academic achievement indicators moderated the link between perceived social support and its sub-indicators and academic achievement, while the moderating effects of economic level and cultural background on the relationship between perceived social support and its sub-indicators and academic achievement were not significant. (3) The direct effect pathway between perceived social support and its sub-indicators and academic achievement showed a significant positive correlation. Student engagement partially mediated the effect of perceived social support and its sub-indicators on academic achievement. In addition, the partial mediating effect of student engagement was only significant for students in the junior high school group and not for the senior high school group. Table and Figures | Reference | Related Articles | Metrics

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Job replacement or job transformation? Definition, consequences, and sources of technology-driven job insecurity TU Yan, HAO Po, LONG Lirong Advances in Psychological Science    2023, 31 (8): 1359-1373.   DOI: 10.3724/SP.J.1042.2023.01359 Abstract （3958）   HTML （218）    PDF （799KB）（6052）       Knowledge map    During the digital transformation of Chinese enterprises, effectively alleviating and coping with employee job insecurity is crucial for building harmonious and stable labor relations. Although traditional job insecurity research has extensively examined the sources and consequences of job insecurity, it has paid little attention to the rapid development and application of artificial intelligence technology, which is an essential context for the current organizational management practice and research. This study innovatively puts forward a new concept of technology-driven job insecurity in the context of artificial intelligence, reflecting individual perceived job insecurity due to the development and application of artificial intelligence technology. Based on this, this study has three objectives. First, we theorize the definition and dimensionality of technology-driven job insecurity. Considering that artificial intelligence technology leads to two types of job changes (i.e., AI automation and AI augmentation), we distinguish job replacement insecurity from job transformation insecurity, thus expanding the research on the conceptualization and dimensionality of job insecurity. Second, we examine the impact of technology-driven job insecurity on employee work outcomes and career outcomes. Drawing upon signaling theory, we suggest that technology-driven job insecurity conveys information about employees’ career prospects and influences employee work and career outcomes via their perceptions of the occupational future (i.e., occupational future time perspective). Two dimensions of occupational future time perspective, namely focus on limitations and focus on opportunities, are examined. We expect that job replacement insecurity has negative indirect effects on work engagement, job performance, proactive career behavior, and career satisfaction via activated focus on limitations and deactivated focus on opportunities. In contrast, job transformation insecurity has negative indirect effects on work engagement, job performance, proactive career behavior, and career satisfaction via activated focus on limitations and in the meanwhile, has positive indirect effects on these outcomes via activated focus on opportunities. In addition, these effects are contingent on developmental human resource practices such that developmental human resource practices strengthen the positive indirect effects of technology-driven job insecurity and buffer its adverse indirect effects on employee outcomes. In doing so, this study can not only enrich the theoretical perspectives of job insecurity research but also reveal the unique consequences of technology-driven job insecurity. Finally, we investigate how job characteristics of the current job and technology-related personal characteristics impact employee technology-driven job insecurity. In light of cognitive appraisal theory, we suggest that high information-processing demands, low job complexity, and low problem-solving demands are associated with increased job automation expectations and subsequently heighten job replacement insecurity. Conversely, low information-processing demands, high job complexity, and high problem-solving demands are related to increased job augmentation expectations and subsequently heighten job transformation insecurity. Regarding employee personal characteristics, we expect that smart technology, artificial intelligence, robotics, and algorithms (STARA) awareness is associated with increased technology-driven job insecurity, while technology readiness is associated with decreased technology-driven job insecurity. Besides, job and personal characteristics have interactive effects on technology-driven job insecurity. Specifically, STARA strengthens the impacts of job characteristics on technology-driven job insecurity, while technology readiness mitigates these impacts. By revealing the opposite effects of the same job characteristic on job replacement and job transformation insecurity and identifying the boundary conditions for these effects, this study deepens the understanding of how job characteristics are associated with technology-driven job insecurity. Together, this study not only enriches the research on job insecurity in the context of artificial intelligence but also has implications for building harmonious and stable labor relations and improving employee well-being at work during the digital transformation of Chinese enterprises. Table and Figures | Reference | Related Articles | Metrics

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The relationship between parenting styles and positive development of Chinese adolescents : A series of meta-analytic studies TANG Tian, WANG Yu, GONG Fangying, SHI Ke, LI Xi, LIU Wei, CHEN Ning Advances in Psychological Science    2024, 32 (8): 1302-1314.   DOI: 10.3724/SP.J.1042.2024.01302 Abstract （3903）   HTML （297）    PDF （725KB）（6644）       Knowledge map    Objective: Positive Youth Development (PYD) is one of the most influential concepts in adolescent development research, which focuses on the potential advantages and plasticity of adolescent development trajectory, and emphasizes the important role of the interaction between individuals and the environment on adolescent development. Previous meta-analytic studies have mostly examined the effects of family parenting styles on single variables in the structure of positive adolescent development, and no study has examined the effects of family parenting styles on the holistic conceptualization of positive adolescent development. Methods: Based on the perspective of positive adolescent development, this study took Chinese adolescents as samples and included three variables: academic achievement, self-esteem and resilience to conduct a series of meta-analyses (206 articles, 1822 independent effect sizes, and the total number of subjects reached 109,968). Three databases including CNKI, Wanfang and VIP were selected for Chinese, and Web of Science Core Set, Wiley, Proquest, EBSCO and Elsevier databases were selected for foreign languages to search relevant studies on Chinese adolescents. For joint retrieval by keyword, such as "parenting/rearing styles" and "academiac achievemant/success/performance" or "self-esteem" or "resilience", At the same time, a large number of documents are included through subject search and full-text search. Retrieved on 22 December 2022. In the end, 206 articles met the above criteria, including 57 articles on academic achievement, 97 articles on self-esteem (including 3 articles in English), and 52 articles on resilience (including 1 article in English). The zero-order correlation coefficient r was used as the index of effect quantity. Comprehensive Meta-Analysis(CMA 2.0) was used to test the main effect and the moderating effect of the series of meta-analyses; meta-regression analysis was used to analyze the moderating effect of female ratio and publication year, etc.; subgroup analysis was used to analyze the moderating effect of education stage, publication type and measurement tools, etc. Results: Result: Different types of family rearing styles were significantly correlated with the three core indices of adolescents' positive development. Positive family parenting styles were moderately correlated with adolescents' positive development (r = 0.32), while negative family rearing styles were moderately correlated with adolescents' positive development (r = -0.13). The results confirm the relationship between family parenting style and the positive development of adolescents from a holistic perspective. Specifically, among the concrete constructs of adolescents' positive development, positive parenting style had the highest correlation with resilience (r = 0.43), followed by self-esteem (r = 0.318) and academic achievement (r= 0.18). Negative parenting styles were associated with higher levels of resilience (r = -0.17) and self-esteem (r = -0.16), and lower levels of academic achievement (r= -0.10). These results indicate that the effect of family rearing style on adolescent development is both holographic and different. In addition, meta-regression analysis and subgroup analysis found that the ratio of females in the continuous variable and the stage of education in the group variable had a significant moderating effect on the relationship between family parenting style and the indicators of adolescent positive development. Conclusion: In this study, three representative variables such as academic achievement, resilience and self-esteem were included in the core indices of adolescents' positive development. Based on the first-order and second-order meta-analysis, the relationship between the development resource of family parenting style and adolescents' positive development was investigated. In order to comprehensively and deeply understand the development resource value of family parenting style. It provides a theoretical perspective and new evidence for the holistic and differentiated effects on the positive development of adolescents. There is a close correlation between family parenting style and adolescent development variables, which confirms the important role of "family style parenting" in promoting the overall positive development of adolescents, and the holographic function of positive family parenting style in shaping adolescents' ability, self-worth and positive psychological character. It highlights the theoretical contribution and practical significance of this study under the background of Chinese excellent traditional family culture. Table and Figures | Reference | Related Articles | Metrics

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The effects of gender nonconformity on adolescent peer evaluation and related dynamics WEN Fangfang, KE Wenlin, FANG Zeming, WANG Yang, LEI Yatian, ZUO Bin Advances in Psychological Science    2023, 31 (8): 1331-1341.   DOI: 10.3724/SP.J.1042.2023.01331 Abstract （3792）   HTML （198）    PDF （874KB）（6357）       Knowledge map    Inherent gender is an important dimension of self-identity and social categorization, and has a huge impact on individual psychology, interpersonal relationships, intergroup behaviors and social development. Gender stereotypes, gender socialization and gender attitudes have been stable themes in disciplines, such as social psychology, developmental and educational psychology and sociology. Gender is the core component of the self-concept and an important dimension of social categorization. Gender Nonconformity is a psychological phenomenon in which individuals display gender norms that do not correspond or are inconsistent with their birth sex. In recent years, the phenomenon of Gender Nonconformity has become increasingly prominent among adolescents, and previous studies have shown that Gender Nonconformity adolescents face challenges in social adjustment such as peer relationships. Although some research paradigms and theoretical findings have been accumulated in the area of Gender Nonconformity and related areas, there are still limitations. Although some research paradigms and theoretical findings have been accumulated in the area of Gender Nonconformity and related areas, there are still limitations. Firstly, previous studies have mainly adopted the traditional binary approach of gender conformity and non-conformity; secondly, there is a lack of cognitive-motivational pathways to examine the prototypical matching and avoidance intentions of Gender Nonconformity in influencing adolescents' peer evaluations; thirdly, previous studies have mainly adopted a static perspective on gender-biased peer evaluations, ignoring the dynamic processes of gender-biased generation and evolution. To address these limitations, this study will break through the gender binary category and explain the psychological mechanisms of static effects and dynamic changes of Gender Nonconformity on peer evaluation from the perspective of the relationship between basic attributes and gender attributes, and provide possible interventions to change the negative peer evaluation of Gender Nonconformity individuals. The specific aims of the study include: firstly, to develop and provide neurophysiological evidence for the basic attributes of Gender Nonconformity; secondly, to reveal the cognitive-motivational dual-path mechanism of prototype matching and avoidance intention in the process of Gender Nonconformity influencing peer evaluation; and thirdly, to explore the dynamic evolutionary mechanism of Gender Nonconformity influencing peer evaluation. Focusing on the above three research aims, this study systematically examines the influence of Gender Nonconformity on peer evaluation and its evolutionary psychological mechanisms according to a progressive research hierarchy of "realization layer - algorithmic layer - computational layer". The study includes three aspects. (1) A polymorphic refinement examines the effects of Gender Nonconformity on peer evaluation, constructs a view of the underlying attributes of Gender Nonconformity and provides behavioral and neurophysiological evidence of the layers of realization. (2) A dual cognitive-motivational pathway mechanism for Gender Nonconformity to influence peer evaluation is revealed at the algorithmic level. The social cognitive paradigm is used to explore the cognitive activation of "prototype matching" and the motivational activation of "intention to avoid" in the process of Gender Nonconformity influencing peer evaluation through questionnaires, behavioral experiments and situational experiments. (3) Exploring the dynamic evolutionary mechanisms of Gender Nonconformity in peer evaluation from the abstract computational level. Using reinforcement learning paradigms, computational modelling, implicit measurement, contextual experiments and live experiments, the prototype formation process of Gender Nonconformity peer evaluations is simulated using reinforcement learning models based on a dual pathway of cognition and motivation to explore the dynamic evolutionary mechanisms of gender-biased peer evaluations and possible intervention pathways for negative peer evaluations of gender-biased individuals. The findings of this study can provide some managerial and educational insights into the effective promotion of youth gender development, peer relationships and mental health based on a gender perspective. Table and Figures | Reference | Related Articles | Metrics

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Honor culture and face culture: A comparison through the lens of the dignity, honor, and face cultural framework and indigenous social theory WEI Xindong, ZHANG Kaili, FU Xurong, WANG Fengyan Advances in Psychological Science    2023, 31 (8): 1541-1552.   DOI: 10.3724/SP.J.1042.2023.01541 Abstract （3534）   HTML （113）    PDF （597KB）（4836）       Knowledge map    Honor and face cultures attach great importance to regulating individual behavior by social expectations and cultural norms. However, the two cultural phenomena differ in several crucial aspects. The new cultural framework of dignity, honor, and face was proposed based on three different cultural logics and reveals that while both honor culture and face culture place importance on adhering to social norms, honor culture places greater emphasis on both self-awareness and external evaluations for self-worth, whereas face culture places more weight on external evaluations. Additionally, honor culture is characterized by an unstable social hierarchy prone to competition, violence, and virtue, while face culture prioritizes modesty, harmony, and cooperation within a more stable hierarchy. However, the framework does not fully explore the cultural practices and specific connotations that are locally relevant to each respective culture. From indigenous perspectives, the self-image and social image in honor culture are relatively consistent, and honor encompasses moral, gender, and family-related aspects that may be defended through violence. In contrast, self-image and social image in face culture tend to be incongruent, and face involves morality and social achievement, which is expressed through the dimensions of seeking face and avoiding losing face with an emphasis on status and authority. Combined with the above two perspectives, these core differences between honor and face cultures can be attributed to the moralization and instrumentalization of social cultural norms. Specifically, honor tends to moralize social and cultural norms by transforming descriptive norms into prescriptive norms, where majority and typical behaviors that exist in a culture are considered behaviors that group members should or must abide by. In contrast, face instrumentalizes social and cultural norms by using descriptive and prescriptive norms as means and tools to maintain relationships, demonstrate status, and uphold authority. This perspective provides new insights into cultural phenomena, such as the positive correlation between violence and virtue in honor cultures, where violence becomes a social norm that adapts to the honor culture environment and is moralized into a virtuous attribute. The social norm of harmony in face culture exists both as value-oriented harmony influenced by Confucian culture and instrumental harmony in daily life, leading to a dissonance between face and heart. This comparative analysis can help in developing new measurement models to test the core differences between the honor and face cultures and explore the impact of changing values and social ecological variables on the moralization and instrumentalization of social norms in the context of cultural change. Table and Figures | Reference | Related Articles | Metrics

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The big data analysis in cultural psychology WU Michael Shengtao, MAO Yunyun, WU Shuhan, FENG Jianren, ZHANG Qingpeng, XIE Tian, CHEN Hao, ZHU Tingshao Advances in Psychological Science    2023, 31 (3): 317-329.   DOI: 10.3724/SP.J.1042.2023.00317 Abstract （3516）   HTML （181）    PDF （876KB）（5779）       Knowledge map    With the further development of computers and big data technology, human society and its cultural forms are undergoing profound changes. The production and interaction of cultural symbols have become increasingly complex, and cultural members and their social networks have left numerous texts and behavior footprints, which makes it necessary to describe, predict, and even change the culture, so that computable cultural symbols and their interaction process have gradually become the research object of cultural psychology. In this vein, Computational Cultural Psychology (CCP), which employs big data and computation tools to understand cultural symbols and their interaction processes, has emerges rapidly, making large-scale or even full sample cultural analysis possible. The key variables of CCP are mainly about individualism and collectivism, and the analysis technologies include feature dictionaries, machine learning, social networks analysis, and simulation. New research avenues of CCP involve the cultural change effect from the temporal perspective and cultural geography effect from the spatial perspective. For the former, Google Ngram Viewer, Google News, Google Search, name archives, pop songs, and micro-blogs were used to analyze the cultural changes after the long-term historical development and the short-term economic transformation. For the latter, both social media (e.g., Twitter, Facebook, and Weibo) and large-scale survey were used to analyze the cultural differences of various countries or regions in different geographic spaces, as well as the relationship between culture and environment, such as cultural diversity along the "Belt and Road", person - environment fit and cultural value mismatch across different regions in a country or all over the world. It should be noted that there are several limitations in CCP, including decoding distortion, sample bias, semasiological variation, and privacy risk, although new methods and paradigms are provided. In future directions, theoretical interpretation of variables, cultural dynamics, interdisciplinary integration, and ecological validity should be seriously concerned. In particular, accurate definition and theoretical interpretation of big data measurement are needed; a variety of big data corpus (e.g., historical archives) should be used for the evolutionary analysis of dynamic cultures; deep integration, but not conflict, should be encouraged between culture psychology and the sciences of computer, communication, and history; and the "scenarios" of big data should be considered in promoting the ecological validity of cultural psychology. Taken together, a review of the emergence of CCP, as well as the empirical research on the big data analysis of cultural change and cultural geography, is helpful in understanding the advantages, limitations, and future direction of this new field, which sheds light on theoretical and methodological innovation of cultural psychology. Table and Figures | Reference | Related Articles | Metrics

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Dancing with AI: AI-employee collaboration in the systemic view YIN Meng, NIU Xiongying Advances in Psychological Science    2024, 32 (1): 162-176.   DOI: 10.3724/SP.J.1042.2024.00162 Abstract （3505）   HTML （219）    PDF （679KB）（16192）       Knowledge map    AI-employee collaboration is an interactive system composed of “AI-human-organization” with the goal of completing tasks efficiently. Promoting AI-employee collaboration is crucial for driving the deep integration of AI and the real economy, as well as the mental health and career development of employees in the digital era. However, the conceptual connotation of AI and AI-employee collaboration has not yet been systematically elaborated in the literature, which has led to ambiguity in the meaning of AI in organizations as well as confusion between concepts of different AI application. In addition, the research of AI-employee collaboration is fragmented and complex across disciplines, and the academic community lacks a comprehensive understanding of the current status and future direction of AI-employee collaboration research. Based on the above limitations, we conducted a comprehensive search of the literature related to AI-employee collaboration, coded the publication information, theoretical basis, core research conclusions and other contents of the literature, and organized the content of the paper based on a systemic review after reading the literature in depth. We first clarify the concept and dimensions of AI in the workplace, and then discuss the systemic view of AI-employee collaboration, and further clarify the conceptual connotation of AI-employee collaboration from the systemic view. This helps to unify the academic dialogue and lay the foundation for subsequent research on AI-employee collaboration. Then, based on the systemic view of AI-employee collaboration, the paper constructs a research framework of AI-employee collaboration using I-P-O paradigm, and describes AI-employee collaboration as input, process and output of a system in detail. At the input of the system, AI, employees, and organizations work together to drive the design, implementation, and use of AI. At the AI level, we review from three dimensions: physical attributes, mental attributes and ethical attributes. At the employee level, we review from four aspects: attitude, KSAs, personalities and demographic characteristics. At the organizational level, we review from three perspectives: organizational readiness, organizational support, organizational climate and culture. In the process of the system, actors operate around work tasks, and they influence the output by performing the tasks. Therefore, the process is a task configuration, including two aspects: task goal and interaction approaches. We further propose that optimizing AI-employee collaboration requires attention to the dynamic matching of interaction approaches and task goal. At the output of the system, we summarize the outcomes of three actors: employees, AI and organization. The research framework explicitly describes the components and internal mechanisms of AI-employee collaboration system, and provides a basic theoretical framework guide for further more in-depth research. Finally, based on the limitations of the research framework, we propose future research prospects from five perspectives. (1) Future research should emphasize the ethical issues in AI-employee collaboration system, providing more empirical and experimental evidence for the impact of ethical attributes on AI-employee collaboration. (2) Future research should develop objective measurements of the organizational consequences of AI-employee collaboration. (3) Future research should explore more individual factors that may influence AI-employee collaboration, such as prompt ability, cultural values, etc. (4) Future research should further elaborate the task configuration of AI-employee collaboration and examine the efficiency and effectiveness of AI-employee collaboration with different task configurations. (5) Future research should expand the research framework based on the new developments of I-P-O paradigm, such as feedback loops. Table and Figures | Reference | Related Articles | Metrics

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Can learning by non-interactive teaching promote learning? CHENG Meixia, KUANG Ziyi, LENG Xiaoxue, ZHANG Yang, WANG Fuxing Advances in Psychological Science    2023, 31 (5): 769-782.   DOI: 10.3724/SP.J.1042.2023.00769 Abstract （3413）   HTML （136）    PDF （978KB）（3196）       Knowledge map    As a generative learning activity, learning by non-interactive teaching refers to learners play the role of teachers and teach what they have learned to others, and the activity is designed to help learners actively engage in knowledge building and improve their academic performance. For example, learners face a video camera to explain the learning material to imaginary, non-present peers in their minds (i.e., recording an instructional video). Given the vastly different ways in which learning by non-interactive teaching was implemented (e.g., video, audio, and text), the effectiveness of learning by non-interactive teaching in facilitating learning might be different. By summarizing the relevant studies, it was found that learning by non-interactive teaching in oral form with a tutor figure (e.g. video) was more effective in improving learner’s performance (d immediate comprehension = 0.56, d delayed comprehension = 0.63, d immediate transfer = 0.35, and d delayed transfer = 0.76) compared with simple learning activities such as restudy and retrieval practice, which was probably a better implementation. Learning by non-interactive teaching in oral form (e.g. audio only, d immediate comprehension = 0.09 and d immediate transfer = 0.02) or written form (e.g. text, d immediate comprehension = -0.16, d delayed comprehension = 0.39, d immediate transfer = 0.08, and d delayed transfer = 0.19) without a tutor figure had a smaller positive effect on learning outcomes. Learners with non-interactive teaching also experienced higher motivation (d = 0.44) and enjoyment (d = 0.76) and were willing to invest more mental effort (d = 0.47). The retrieval practice hypothesis and the generative learning hypothesis focused on different subcomponents of cognitive processing (e.g., retrieval, generation, or monitoring) to explain the positive effects of learning by non-interactive teaching on learning, respectively. The social presence hypothesis emphasized that social presence might facilitate whole cognitive processing and thus improved learning. Our results supported these three hypotheses to some extent. In addition, the cognitive theory of multimedia learning (CTML) may provide a supplementary explanation for differences in the effectiveness of different implementations of learning by non-interactive teaching. On the one hand, learning by non-interactive teaching (e.g., video) might successfully create teaching situation that stimulated a moderate sense of social presence and leaded learners to be more engaged and think more deeply about the material, i.e., increased their essential processing and generative processing, and thus facilitated learning. On the other hand, learning by non-interactive teaching (e.g., text) might distract learners from focusing too much on the typos, the standardization and rigorousness of written language, i.e., increased their extraneous processing. Due to the inherently high demands for processing capacity in generative activities, too much extraneous processing might cause learners' limited processing capacity being insufficient for adequate essential processing and generative processing, which in turn impaired learning. While learning by non-interactive teaching in the audio-only format might neither successfully facilitate learning with essential processing and generative processing because of the weaker teaching situation created, nor hinder learning with extraneous processing because of the automated spoken language. Research is needed to test and integrate theories, identify boundary conditions, and enhance the effectiveness of learning by non-interactive teaching in the future. Table and Figures | Reference | Related Articles | Metrics

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Behavioral intervention strategies to nudge smoking cessation ZHANG Ning, WANG Anran Advances in Psychological Science    2023, 31 (4): 684-696.   DOI: 10.3724/SP.J.1042.2023.00684 Abstract （3393）   HTML （151）    PDF （863KB）（5008）       Knowledge map    Smoking is one of the major public health challenges around the world. Traditional tobacco control strategies, which include health education, taxes on tobacco products, and restrictions on smoking in public spaces, have greatly contributed to the reduction of smoking behavior around the world. However, these strategies are not always effective in helping smokers successfully quit smoking. As the traditional strategies do not consider the “irrational characteristics” of smoking behavior and its underlying mechanisms, their effects are usually discounted in real-world contexts. Recent advances in applied behavioral sciences during the past several decades provide new approaches for nudging smokers to quit smoking, which could be used to develop more effective tobacco control strategies at both the individual and population level. This article systematically reviews recent empirical research on behavioral intervention strategies to nudge smoking cessation according to the framework developed by Duckworth and colleagues for improving self-control. Specifically, behavioral nudge interventions for promoting smoking cessation could be classified by the people or organization implementing the intervention (e.g., smokers versus governments and public health agencies) and their underlying mechanisms (e.g., cognitively oriented versus context oriented). Context oriented interventions implemented by governments and public health agencies include reducing the accessibility of tobacco retail outlets in residence areas, restricting the display of tobacco products in stores and supermarkets, so as to reduce exposure of tobacco products, offering smaller size of cigarette products, and establishing separate smoking areas and removing tobacco-related irritants from the environment; cognitively oriented interventions implemented by governments and public health agencies include printing prominent warning pictures on cigarette packets, removing marketing information from cigarette packs, and increasing the usage of smoking cessation services; context oriented interventions implemented by smokers include making a public commitment to stop smoking and inviting important others to monitor one’s smoking behavior, using loss aversion to motivate quitting behavior among smokers; cognitively oriented interventions implemented by smokers include making specific, actionable smoking cessation programs, promoting a future-oriented time perspective, and cultivating incremental theories of smoking behavior. This framework makes it easier for governments and smokers to select appropriate behavioral nudge interventions. It also has implications for informing the development of culturally sensitive and adaptive behavioral intervention strategies for promoting smoking cessation in China, improving the efficiency and effectiveness of smoking cessation interventions, and contributing to the achievement of the “Tobacco Control Initiatives” of the “Healthy China 2030 Initiatives”. Although there is progress in developing effective behavioral nudge interventions for smoking cessation, future research is warranted to comprehensively evaluate the effects of these interventions, including both positive and negative effects, short-term and long-term effects, especially in real-world contexts. Future research is also needed to adopt behavioral change strategies in the development of stop-smoking APPs and digital smoking cessation services. By fully understanding the irrational characteristics of smoking behavior and its underlying mechanisms, we can develop tailored, targeted, context adaptable, and applicable smoking cessation intervention strategies. These types of interventions can greatly increase the effectiveness and efficiency of smoking cessation services. Future research is also needed to preclude the negative impacts of e-cigarettes and prevent the misuse of these behavior nudge strategies, especially among young children and adolescents who are vulnerable to the attraction of e-cigarettes. We believe that behavior science-informed interventions, if successfully implemented with the collaboration of governments, public health agencies, and smokers, can greatly contribute to safeguarding the health of both smokers and the general public. Table and Figures | Reference | Related Articles | Metrics

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Have gender stereotypes changed or not changed? Evidence from contents, methods, and consequences WANG Zhen, GUAN Jian Advances in Psychological Science    2024, 32 (6): 939-950.   DOI: 10.3724/SP.J.1042.2024.00939 Abstract （3387）   HTML （169）    PDF （559KB）（7140）       Knowledge map    Stereotypes have been defined as beliefs about the characteristics, attributes, and behaviors of people classified into social categories. Stereotypes are traditionally perceived as resistant to change. However, they may be changed under contexts of the impacts of societal changes on human culture and psychology. Given that gender stereotypes are expected to be more unshakable than other stereotypes (e.g., race stereotypes), it implies that there is a potential for changing other stereotypes, provided that gender stereotypes can be changed. Therefore, this article reviewed changes in gender stereotypes from their contents, methods, and consequences. According to the social role theory, gender stereotypes are built on social roles. Therefore, gender stereotypes are expected to change with the changes in the roles of men and women. Considerable studies have found that gender stereotypes have changed. Specifically, some studies have shown that women are perceived to increase their masculine characteristics (e.g., agency) over time, while men are not perceived to increase feminine characteristics (e.g., communion). Differently, others have indicated that both women and men are perceived to increase in counterstereotypical traits over time. However, in contrast to these findings depicting changes in gender stereotypes, several studies did not find significant changes, and they believed that gender stereotypes persist over time. One of the possible reasons for these conflicting findings is that different methods have been used in previous studies. The research methods of gender stereotype changes can be divided into traditional methods and new techniques. The traditional methods usually involve the past-present-future rating paradigm, cross-sequential design, and cross-temporal meta-analysis. Word embedding, as a new technique, has become increasingly important in recent years. All research methods have their relative advantages and disadvantages. The consequences of gender stereotype changes can be categorized into positive and negative outcomes. In terms of positive outcomes, gender stereotype changes increase the possibility of men being involved in more household labor, which may result in better relationship quality for the couple. Besides, the new male role in parental care for children generates many benefits, such as better academic performance, higher levels of self-esteem, and fewer behavioral problems in children. Additionally, gender stereotype changes can promote women’s economic independence and reduce the gender gap. However, there are also negative outcomes with the changes in gender stereotypes. Specifically, these changes intensify low fertility rates and birth rates. Notably, even if gender stereotypes towards targets become more and more positive over time, targets may not treat the stereotypes as compliments. On the contrary, they may perceive the stereotypes as a form of gender prejudice, eventually impairing interpersonal and intergroup relationships. Further research on gender stereotype changes can be discussed from the following aspects: first, it is important for researchers to conduct studies with diverse research methods in the future. Second, future research should pay attention to not treating gender stereotypes as a single construct. Instead, they should be investigated through the perspective of classification (e.g., descriptive and prescriptive gender stereotypes). Third, given that stereotypical gender characteristics seem to interact with each other to build gender stereotypes, future research should examine gender stereotype changes by treating gender stereotypes as a complex system from a network approach. Last, we should not ignore cultural impacts on gender stereotype changes. Given that China has undergone more unprecedented societal transformations than Western countries over the past decades, the social roles in China have undergone tremendous changes. Therefore, it is indispensable to investigate gender stereotype changes in China. Furthermore, not only the gender stereotype changes, future studies need to explore changes in stereotypes about other categories, such as race, ethnicity, age, sexual orientation, classes, and religion. Reference | Related Articles | Metrics