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ISSN 1671-3710
CN 11-4766/R
主办:中国科学院心理研究所
出版:科学出版社

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    Conceptual Framework
    The behavioral and neural response patterns of growth mindset affecting learning process: A perspective from self-regulation learning theory
    JIA Xiaoyu, LI Ping, LI Weijian
    2024, 32 (12):  1947-1960.  doi: 10.3724/SP.J.1042.2024.01947
    Abstract ( 27 )   PDF (636KB) ( 25 )   Peer Review Comments

    The Program for International Student Assessment (PISA) identifies growth mindset as a crucial predictor of adolescents' academic achievement and social adaptation. Cultivating a growth mindset among adolescents is seen as a transformative change in reshaping the educational landscape and has become a significant topic in education. Recent large-scale studies have shown that growth mindset interventions enhance adolescents' academic performance and alleviate their stress, while several meta-analyses have reported minimal effects of such interventions on academic performance. Evaluating the true effectiveness of growth mindset interventions in improving adolescents' academic performance remains a challenging and cutting-edge issue in this field.

    Existing research has overly focused on learning outcomes, using academic performance as the primary measure of growth mindset and its intervention effects, while neglecting the behavioral aspects of the learning process. This oversight has obscured valuable assessment information, contributing to the current controversy. Therefore, this study explores the "behavioral and neural response patterns of how growth mindset influences the learning process," aiming to shift and innovate research perspectives, paradigms, and metrics in the following ways: (1) Process-Oriented Focus: This study emphasizes the process-oriented nature of learning and explores the effects of growth mindset and its interventions on various aspects of the learning process; (2) Metacognitive Framework: Based on self-regulated learning theory, this study adopts a metacognitive framework within a self-regulated learning paradigm to characterize the interactive patterns between growth mindset, motivation, metacognition, and self-regulated learning behaviors, thereby overcoming the limitations of previous research content and methods based on the social cognitive theory of motivation; (3) Comprehensive Assessment Tools: By constructing and integrating behavioral indicators, neural activity indicators, and brain plasticity indicators that reflect the influence of growth mindset on the learning process, this study provides multi-faceted assessment tools for scientifically evaluating the effectiveness of growth mindset interventions. This approach aims to mitigate the assessment bias caused by relying solely on learning outcome indicators.

    Learning is a continuously self-regulated process. This study addresses the key scientific question of whether growth mindset influences the learning process by utilizing a self-regulated learning paradigm within a metacognitive framework. Through behavioral experiments, event-related potentials (ERP), and functional magnetic resonance imaging (fMRI) experiments, the study reveals the behavioral and neural response patterns influenced by growth mindset in feedback learning contexts. In the study 1, we use a self-regulated learning paradigm to examine whether growth mindset influences behavioral performance in learning processes within task/ability feedback contexts, reflecting the effects of growth mindset and feedback on the learning process through behavioral indicators. In the study 2, ERP technology is employed to investigate whether growth mindset influences brain neural signals during the learning process within task/ability feedback contexts, providing objective neural evidence of the influence of growth mindset and feedback on the learning process. In the study 3, we aim to examine whether, after implicit activation (short-term intervention) of a growth mindset in individuals with a fixed mindset within a laboratory setting, their behavioral performance and neural activity during the feedback learning process converge with those of individuals with a growth mindset. Additionally, using fMRI technology, the study explores whether long-term growth mindset interventions can significantly alter gray matter volume in key brain regions and the connectivity strength between large-scale networks, and whether the latter mediates the relationship between growth mindset interventions and academic performance. This examination reveals the brain plasticity mechanisms by which growth mindset interventions influence feedback learning processes and outcomes.

    This study systematically explores the behavioral and neural response patterns influenced by growth mindset in the learning process, attempting to construct a theoretical framework for how growth mindset affects the learning process. Not only does it advance research on this topic from ongoing controversy towards greater clarity, but it also responds to the educational reform call for "strengthening process evaluation" in the new era. As brain plasticity-based growth mindset cultivation becomes widely applied in educational practice, clarifying the impact of growth mindset and its interventions on neural activity and brain plasticity during the learning process can provide a basis for accurately formulating and evaluating growth mindset cultivation programs for adolescents, promoting the scientific and standardized implementation of such programs. Moreover, integrating adolescents' growth mindset cultivation into supportive classroom feedback contexts is a direction that future educational practice could consider.

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    The double-edged sword effect of rivalry on decision-makers’ creativity recognition: An information processing perspective
    BAI Xinwen, QI Shuting, WANG Zhuojun, REN Siyu, SUN Wen
    2024, 32 (12):  1961-1979.  doi: 10.3724/SP.J.1042.2024.01961
    Abstract ( 13 )   PDF (652KB) ( 10 )   Peer Review Comments

    While leading organizations to engage in innovation, decision-makers constantly face fierce competition from counterparts in other organizations targeting the same markets, clients, suppliers, technologies, and/or regions. To survive and thrive amid intense competition, organizational decision-makers must identify the most promising and creative ideas and allocate limited resources for subsequent innovation stages. Existing research on decision-makers' creativity recognition has primarily focused on the interactions among creators, decision-makers, and the environment, examining how these subsystems collectively influence the ability to recognize truly creative ideas. However, studies have generally focused on a single decision-maker, overlooking the significant role of competition among decision-makers, thereby limiting the explanatory power for real-world phenomena.

    It is well-established that decision-makers often perceive each other as rivals when their respective organizations are closely matched and engaged in extended competition. As competition intensifies into rivalry, decision-makers become increasingly motivated to outperform their rivals. Rivalry theory posits that such rivalry can have a double-edged sword impact on decision-makers' effectiveness to identify truly innovative ideas. On one hand, rivalry may incentivize decision-makers to engage in systematic and in-depth analysis of innovation strategies of their own, thereby improving the efficiency and accuracy of creativity recognition. On the other hand, rivalry may induce tunnel vision, leading decision-makers to disproportionately focus on the creative potential of ideas under scrutiny by their rivals, while neglecting those ideas that fall outside their rivals' consideration.

    To gain a deeper understanding of the impact of rivalry on creativity recognition, the current study employs a mixed-methods design. Laboratory experiments test the causal relationship between rivalry and decision-makers' recognition efficiency, while field studies examine the external validity of experimental findings in real-world contexts. Specifically, Study 1 utilizes a laboratory experiment to manipulate competition forms and measure the cognitive processing depth and breadth of decision-makers in various competitive environments, investigating rivalry's impact on creativity recognition accuracy. Studies 2 and 3 explore how rivalry influences decision-makers’ creativity recognition through cognitive depth (systematic processing) and cognitive breadth (tunnel vision) pathways. Study 4 validates laboratory findings in real organizational contexts by analyzing mutual fund managers' investment decisions and examining how rivalry relationships among fund managers influence their identification and selection of corporate innovations.

    By integrating rivalry theory with the cognitive processing perspective, this study proposes a dual-pathway model to illustrate how rivalry influences decision-makers' creativity recognition. The model posits that rivalry exerts a double-edged sword effect on creativity recognition by affecting the depth and breadth of decision-makers' cognitive processing. Rivalry can catalyze more in-depth systematic processing, thereby enhancing the accuracy of creativity recognition. However, an excessive focus on competition may constrict cognitive breadth, inducing tunnel vision and the potential neglect of highly creative ideas. The principal theoretical contribution of this research lies in introducing the rivalry perspective into the domain of creativity recognition research. By delineating rivalry's effect on the cognitive mechanisms underpinning creativity recognition, our study provides a novel theoretical framework for understanding and improving organizational innovation management. Furthermore, it assists decision-makers in identifying cognitive biases within the innovation decision-making process, thereby facilitating more informed and rational innovation decisions.

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    The loss outweighs the gain: Myopic risk ignorance in sequential decision making
    CHEN Zhiqin, MA Jiatao, ZHANG Xueting
    2024, 32 (12):  1980-1989.  doi: 10.3724/SP.J.1042.2024.01980
    Abstract ( 25 )   PDF (537KB) ( 25 )   Peer Review Comments

    In real life, decision-makers often intentionally ignore “high probability, large loss” risks, leading to irreparable consequences. For example, in business, companies may prioritize short-term profits over long-term goals, disregarding accumulated risks. Similarly, in personal life, individuals often deliberately ignore and sacrifice long-term health for immediate pleasures, such as prolonged sitting, inactivity, or late-night gaming, despite knowing the risks.

    To explore the underlying scientific issues of this phenomenon, this project introduces the novel concept of “myopic risk ignorance.” Specifically, this concept refers to the difficulty decision-makers encounter in accurately perceiving or assessing the interdependencies among repeated similar decisions due to myopic evaluations and cognitive limitations. As a result, driven by the pursuit of immediate gains in individual decisions, decision-makers often sacrifice globally optimal goals and gradually ignore long-term risks. The phenomenon of myopic risk ignorance involves two consecutive choices in each round: first, whether to “execute” or “not execute” a certain risky behavior, and second, if they choose to execute, they need to decide the degree of execution. For the risky behavior, the decision to “execute” contains obvious “immediate small gains,” but it is also accompanied by “dynamic losses” that are often deliberately ignored. The objective probability and extent of these losses gradually increase with the degree of execution and the number of execution rounds. Choosing “not to execute” requires resisting immediate gratification, accurately assessing potential losses, and pursuing sustainable long-term goals.

    Myopic risk ignorance is a specific attitude within the context of sequential decision making, where individuals or organizations make a series of decisions over time to achieve optimal overall goals. Despite its prevalence, existing research primarily focuses on one-shot decisions, neglecting genuine behavioral patterns in sequential decision making. This limitation has impeded exploration of myopic risk ignorance. To address this gap, the project aims to uncover patterns and key characteristics of myopic risk ignorance within the framework of sequential decision making. It also seeks to develop a research paradigm to measure attitudes and explore the underlying mechanisms within decision processes and goals. This project is divided into three main studies: phenomenon revelation (Study 1), attitude measurement (Study 2), and mechanism exploration (Study 3).

    Study 1 aims to construct a scenario questionnaire to measure individuals’ myopic risk ignorance in daily decision making, verifying the phenomenon’s universality and robustness. Study 2, based on the characteristics of myopic risk ignorance - where individuals continuously choose to execute risky behavior or deepen the degree of execution, gaining “small gains,” but at the same time, they are accompanied by “dynamic losses with gradually increasing probability and magnitude” - will design a card-turning task as an abstract simulation of real-life decision making. Additionally, this study will use both the scenario questionnaire and the task paradigm to assess myopic risk ignorance attitudes, testing the consistency of these measurements. Study 3 intends to explore the underlying mechanisms by examining the relevance of decision processes and the multiplicity of decision goals in sequential decision making, laying the groundwork for future behavioral interventions.

    In summary, this project offers several contributions. It scientifically defines myopic risk ignorance, opening new theoretical perspectives for related research and expanding the fields of risky and intertemporal decision making. By analyzing decision characteristics over rounds, it provides a foundation for future research and new insights into behavioral decision theories. Moreover, exploring the mechanisms of myopic risk ignorance from both process and goal perspectives establishes a basis for prediction and intervention systems in related social phenomena. The research findings have practical applications, supporting the development of intervention strategies and sequential decision-making support systems that help individuals and organizations identify, assess, and mitigate long-term risks, ultimately enhancing long-term welfare.

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    Empowerment or disempowerment: The influence of using AI on creative personality
    WANG Hongli, LI Zhen, ZHOU Mengnan, CHEN Zhengren
    2024, 32 (12):  1990-2004.  doi: 10.3724/SP.J.1042.2024.01990
    Abstract ( 29 )   PDF (586KB) ( 26 )   Peer Review Comments

    Creative personality is often considered stable and unique. However, when artificial intelligence (AI) participates in creative tasks, the “digital authority” role of AI may cause automation bias in human use of AI, making it difficult for humans to maintain a leading role in creativity, even with a creative personality. Yet, significant research gaps persist. First, the organizational personality literature is dominated by the classic dispositional view that personality traits are stable. Second, despite calls to promote research on the impact of AI on personality traits, the field lacks theoretical and empirical research. Our knowledge regarding the effects of AI on human creative personality and its underlying mechanisms is notably limited.

    Considering the above calls and limitations, this study adopts a developmental perspective on personality to clarify the impact of using AI in creative work on creative personality. Specifically, it encompasses three distinct sub-studies. Study 1 reveals the mechanisms by which the use of AI mediates creative personality. By drawing on the concepts of "I can" and "I should", we examine the negative effects of using AI and automation bias on creative self-efficacy and creative role identity. Study 2 explores the long-term effects of using AI and automation bias on individual creative personality. Furthermore, study 3 investigates the effectiveness of self-leadership, focusing on how individuals defend their innovative subjectivity.

    This study makes three primary theoretical contributions. First, this study emphasizes the long-term effects of AI on creative personality. Although the potential influence of using AI on creativity has emerged as a prominent research topic, much of the focus has been on the impact of AI on the creative process, creative outcomes, and creative environment. Studies have shown that using AI can both foster and hinder creativity. Building on this, our research highlights a significant, yet potentially overlooked, drawback of using AI. It contributes to a more nuanced and complete picture of how emerging technologies can shape an individual's creative personality. This study posits that using AI may engender an individual's automation bias, which could disrupt the positive pathways of "I can create” and "I should create", ultimately diminishing individual creative personality. By doing so, we extend the literature on the negative effects of AI on creative personality and remind human beings of their unique roles as primary agents in creative work.

    Second, this study introduces self-leadership as an effective strategy for reaffirming humans as the central agents of creativity. Prevailing research often positions AI at the core of creative work, inadvertently obscuring the subjectivity of human beings. This study, however, asserts that although AI has a certain degree of autonomy, human beings remain the essential protagonists in creative work. To this end, this study proposes a strategy of internal control that reinforces the subject position of human creativity, fundamentally shifting from external organizational supervision to self-regulation. By embracing self-leadership, individuals can counteract the tendencies towards "cognitive saving" and social loafing, thereby preventing the degradation of creative personality that arises from using AI. In this way, this study reveals a pathway to counteract the negative effects of AI on creative personality, thereby optimizing the benefits of AI applications on creativity.

    Third, this study builds an overall theoretical model that encapsulates the impact of using AI on creative personality, the underlying mechanisms, and potential countermeasures. Prior research has predominantly examined how individuals with different personality traits respond to AI and the compatibility between personality traits and AI. However, there is still limited understanding about how AI affects individual personality traits as AI becomes more integrated into creative work. AI, with its exceptional capabilities, dynamism, and autonomy, stands out as a unique factor affecting creativity. Considering that particularity, there is an urgent need for a thorough and detailed theoretical framework. To this end, the theoretical model of this study encompasses the long-term effects of using AI on creative personality, elucidates the underlying mechanisms, and proposes effective coping strategies.

    In summary, our theoretical framework aims to provide scholars with a more comprehensive and profound understanding of how using AI influences individual creative personality, while also offering guidance on how to prevent the erosion of human creativity and avoid becoming subservient to AI.

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    Technical hollowing out of knowledge workers in the manufacturing industry in artificial intelligence context: The definition, formation and influence mechanism
    WANG Yongyue, HUANG Piaopiao, JIN Yanghua, BAI Xinwen, YUE Fengkai, ZHANG Fanying, GUO Zihao
    2024, 32 (12):  2005-2017.  doi: 10.3724/SP.J.1042.2024.02005
    Abstract ( 19 )   PDF (752KB) ( 22 )   Peer Review Comments

    The wave of intelligence has injected new impetus for China to transform from a manufacturing power to a manufacturing powerhouse and for the intelligent transformation of enterprises. However, at the same time, knowledge workers in the manufacturing industry face the challenge of reshaping the labor process with artificial intelligence. Previous studies mainly used labor process theory to analyze the impact of technological progress on the labor of “blue-collar workers” in manufacturing, while related research on knowledge workers in manufacturing is still in the conceptual discussion stage. Therefore, this study innovatively proposes the dynamic concept of technical hollowing out under the background of artificial intelligence to reflect the impact of the development and application of artificial intelligence technology on the labor process of knowledge workers in the manufacturing industry.

    This study constructs a theoretical study on the technical hollowing out of knowledge workers from three perspectives of sensemaking: cognition, behavior, and ability. This study has three research purposes: First, to explore the definition and dimensional structure of technical hollowing out from the perspective of “cognition-behavior-ability” sensemaking, and intends to extract two dimensions: executive skill hollowing and conceptual skill hollowing, technical hollowing out measurement scale was developed based on; second, based on the “cognition-behavior” interaction chain, we construct a two-stage model of “executive skill hollowing out” and “conceptual skill hollowing out” for the technical hollowing out of knowledge workers, and further explore the catalytic role of situational factors at the enterprise and employee levels; third, based on the capability-building perspective, the impact of technical hollowing out on knowledge workers’ dual innovation behavior and sustainable career development is explored. We intend to use case study methods to explore the definition, dimensional structure, measurement scale, and generation process of technological hollowing out. In addition, we use empirical research methods to analyze the impact mechanism of technological hollowing out on the multi-dimensional development of employees. Based on the above conception, this study attempts to construct a relatively systematic and complete theoretical framework of technological hollowing out through three closely related and hierarchical parts.

    This study takes knowledge workers in the manufacturing industry as the research object, expands the subject boundaries of existing AI in reshaping the labor process of workers, and grasps the research frontier of technological hollowing out of knowledge workers. The dynamic concept of technological hollowing out was innovatively proposed, and its dimensional structure and measurement scale were analyzed, deepening the dynamic research of technological hollowing out under the background of AI. At the same time, combining the sensemaking and labor process perspectives, the “double separation” model of employee skills and core science and technology is integrated based on the AI background, forming a theoretical model for the generation of technological hollowing out, which provides a new theoretical perspective for revealing the mechanism of AI’s reshaping of the labor process of knowledge workers. It makes up for the deficiency of labor process theory that focuses on the labor control of “blue-collar workers” from a static perspective. From the perspective of ability building in sensemaking, this study uses empirical analysis methods to reveal the impact path and boundary conditions of technical hollowing out on employees’ dual innovation behavior and sustainable career development by acting on their technological absorptive ability. It provides more evidence for a deeper understanding of the process of employees’ dual innovation behavior and sustainable career development. Also, it provides a new theoretical perspective for the cultivation and motivation of innovative and sustainable talents in the background of intelligent manufacturing. Moreover, the research conclusions can also provide practical inspiration for establishing harmonious and stable labor relations, as well as realizing long-term development and shared prosperity of enterprises and employees during the intelligent transformation of China’s manufacturing industry.

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    From conflict to integration: The theoretical construction of idiosyncratic deals to improve the relationship between individual and organizational goals
    LV Xiao
    2024, 32 (12):  2018-2030.  doi: 10.3724/SP.J.1042.2024.02018
    Abstract ( 18 )   PDF (589KB) ( 9 )   Peer Review Comments

    As the relationship between employees and organizations transitions from standard employment to mutually beneficial and symbiosis, organizations can no longer demand employees to obey organizational goals. Consistency and standardized human resource management practices based on organizational goals are challenging in satisfying employees' increasingly personalized and dynamic individual goals. Organizations face the dilemma of recruiting, employing, and retaining employees. Improving the relationship between individual and organizational goals has become essential in organizational management.

    Idiosyncratic deals, as a leading-edge construct in organizational behavior, offer rational approaches to express and satisfy employees' personalized and differentiated needs within the current framework of human resource management. Nowadays, the underlying assumption that employees are limited to passively accepting or rejecting organizational arrangements is challenged. When faced with conflicts between individual and organizational goals, employees express their needs while actively seeking cooperation with their organization. Similarly, organizations consider employees' individualized and differentiated needs to achieve their goals. More and more employees take the initiative to communicate or negotiate with their organization and obtain arrangements that satisfy their specific needs, referred to as idiosyncratic deals. Therefore, this study explores how employees can proactively enhance the relationship between individual and organizational goals through idiosyncratic deals based on cognitive-affective system theory.

    Firstly, this study identifies the speech strategies of idiosyncratic deal requests, which refer to employees actively articulating their requirements to organizations, and the conditions of idiosyncratic deal receipts, which refer to employees achieving personalized and differentiated human resources arrangements within the organization. As the employment relationship becomes more equal, employees not only imply their needs but also dare to put forward various requirements directly. Moreover, the relationships between different speech strategies (explicit or implicit) of idiosyncratic deal requests and receipts are affected differently by employees' human capital and social capital.

    Secondly, this study clarifies the function mechanism of idiosyncratic deals between the perception of individual-organizational goals conflict and integration. When employees face conflicts of individual-organizational goals, they attribute the cause to either self-responsibility or organizational responsibility, leading to the intention to seek help or the violation of psychological contracts. When employees face integration of individual-organizational goals, they can integrate their self-worth with their work and have harmonious relationships with organizations, leading to a sense of work psychological ownership and a harmonious employment relationship climate. Idiosyncratic deals can not only promote the transformation of individual-organizational goals from conflict to integration but also deliver constructive results of help-seeking intention and alleviate destructive results of psychological contract violation.

    Finally, this study explores the dynamic impact of idiosyncratic deals. As individual goals change or a deeper understanding of organizational goals is gained, conflicts between individual and organizational goals inevitably arise. However, when faced with these conflicts again, employees' past experiences of individual-organizational goals integrating stimulate more positive psychological perceptions. Furthermore, the successful experiences of idiosyncratic deals in the past also make employees more willing to express their needs and more likely to obtain new human resources arrangements. Thus, idiosyncratic deals provide an effective way to improve the relationship between individual and organizational goals continuously.

    The anticipated results of this study support the application of idiosyncratic deals in improving the relationship between individual and organizational goals. These promote the relevant research that shifts perspective from organization-centric to employee-centric and emphasizes consideration for employees' personalities and differing needs rather than solely demanding their commitment or identity. Additionally, this study delves into the mechanisms and dynamic impacts of idiosyncratic deals processes on improving the relationship between individual and organizational goals. These provide new approaches and suggestions for organizations to enhance individual-organizational goals relationship and promote organization-employee collaborative development.

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    Meta-Analysis
    A meta-analysis of work connectivity behavior after-hours and work-life conflict: Based on the work-home resources model
    HAN Zhiwei, CHENG Yanyuan, REN Zhishuai, WANG Danyang, LI Guojing
    2024, 32 (12):  2031-2049.  doi: 10.3724/SP.J.1042.2024.02031
    Abstract ( 15 )   PDF (1341KB) ( 21 )   Peer Review Comments

    With the continuous evolution of information and communication technologies, working through information and communication technologies during non-work hours and in non-work locations, referred to as work connectivity behavior after-hours (WCBA), has become increasingly prevalent. Given that WCBA represent a form of work behavior occurring outside of conventional work hours and locations, its association with work-life conflict has garnered significant attention in empirical research. However, existing empirical results regarding this association has not yet reached a consensus. Importantly, the inconsistency in existing empirical results has led to an unclear and incomplete understanding of the relationship between WCBA and work-life conflict. This ambiguity creates confusion for organizations and employees in managing WCBA, such as determining which measures to adopt to mitigate potential work-life conflict arising from WCBA. Therefore, this study focuses on examining the relationship between WCBA and work-life conflict, as well as the factors that influence this relationship.

    Drawing upon the work-home resources model, this study proposes a two-stage process theoretical model of how WCBA influence work-life conflict, and subsequently identifies factors contributing to the inconsistency in this relationship, including the manifestations of work-life conflict, tools utilized for WCBA, job positions, gender, marital status, parental status, and the economic conditions of the country or region. Additionally, beyond identifying the aforementioned factors from a theoretical perspective, this study also identifies several other potential factors, including the publication status of the literature, sampling methodology, research design, measurement methods of WCBA, employee age, employee organizational tenure, timing of WCBA, location of WCBA, and types of work-life conflict. The meta-analytic investigation, encompassing data from 67 independent samples comprising 30,498 participants, reveals a moderate positive correlation between WCBA and work-life conflict ( = 0.34). Furthermore, the strength of this correlation is contingent upon several factors, including the manifestations of work-life conflict, tools utilized for WCBA, marital status, parental status, sampling methodology, and measurement methods of WCBA. First, the correlation between WCBA and time-based work-life conflict is stronger than the correlation between WCBA and stress-based work-life conflict, as well as between WCBA and behavior-based work-life conflict. However, there is no significant difference between the correlations of WCBA with stress-based and behavior-based work-life conflict. Second, the correlation between WCBA and work-life conflict is stronger when using mixed tools compared to phone-based tools. Third, compared to married employees, the correlation between WCBA and work-life conflict is stronger among unmarried employees. Fourth, the correlation between WCBA and work-life conflict is stronger among employees without children than among those who have children. Fifth, the correlation between WCBA and work-life conflict is stronger when the sample is drawn from multiple organizations compared to when the sample is drawn from a single organization. Sixth, the correlation between WCBA and work-life conflict is stronger when WCBA was measured based on frequency rather than duration.

    The research results indicate a moderate positive correlation between WCBA and work-life conflict, suggesting that WCBA generally hinders employees' ability to effectively fulfill their life role demands. Additionally, the research results also indicate that the manifestations of work-life conflict, tools utilized for WCBA, marital status, parental status, sampling methodology, and measurement methods of WCBA all affect the relationship between WCBA and work-life conflict. Specifically, the identification of these factors not only offers insights for management practices but also provides clear directions for future research. For example, employees should consider leveraging external resources (such as family and financial resources) to meet life role demands during the WCBA process, thereby alleviating work-life conflict resulting from individual resources shortage. Furthermore, incorporating reports from significant others (such as spouse) and utilizing specific applications (Apps) to record employees' WCBA levels can contribute to more robust and precise research conclusions.

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    Research Method
    A profile-perspective on daily-life multi-situational individual differences assessment
    SHUI Xinyu, XIAO Yaheng, CHEN Jingjing, HU Xin, ZHANG Dan
    2024, 32 (12):  2050-2066.  doi: 10.3724/SP.J.1042.2024.02050
    Abstract ( 15 )   PDF (692KB) ( 22 )   Peer Review Comments

    The burgeoning field of psychological measurement has shifted its focus towards the situation-dependent nature of individual differences, spurred by the evolution of psychometric theories and methods. This paradigm shift acknowledges that the manifestation of individual differences is not consistent across various situations, necessitating a more nuanced approach to assessment that transcends the traditional laboratory setting. The pursuit is to achieve a comprehensive and accurate understanding of individual differences, which is essential for the optimal development of both individuals and society.

    Recent advancements in technologies, particularly the advent of smart sensors and wearable devices, have democratized the process of individual differences assessment, making it more accessible and efficient in everyday life. This technological leap has facilitated new strides in researching individual differences in real-world daily-life situations, encompassing subjective reports, behaviors, and physiological responses. The aggregation of such data has given rise to a novel perspective that centers on the analysis of high-dimensional data from an individual-centered viewpoint, known as the profile perspective.

    The profile perspective offers a radical departure from the variable-centered approach that has historically dominated psychological research. It posits that individual differences are best understood by examining the individual as a whole, within the context of various situations, rather than by isolating and measuring discrete variables. This approach recognizes the existence of distinct subgroups within a population, each characterized by a unique pattern of responses and behaviors across different situations. By aggregating multidimensional data on individual states and the interrelationships among these dimensions, the profile perspective aims to capture a more holistic representation of individual differences.

    The application of the profile perspective in the assessment of individual differences is gaining traction, with researchers employing a variety of methods to construct individual profiles. These methods include self-assessments, behavioral observations, and physiological measurements, each contributing to a richer understanding of the individual's psychological state and behavior. Self-assessments, while subject to biases and limitations, provide insights into an individual's subjective experience and emotional states within different situations. Behavioral observations, on the other hand, offer a more objective measure of an individual's actions and responses, unconfounded by self-report biases. Physiological measurements, a relatively objective form of data collection, have emerged as a powerful tool in the construction of individual profiles. They leverage the body's responses to capture the individual's reactions to various situations, offering a unique window into the person's psychological state. The use of wearable devices has made the collection of such data more practical and less obtrusive, allowing for continuous monitoring over extended periods.

    The integration of data from multiple sources and dimensions presents both opportunities and challenges. While it enriches the profile by providing a more comprehensive view of the individual, it also complicates the analysis due to the complexity of the interrelationships among variables. To address this, researchers have turned to sophisticated statistical models, such as structural equation modeling and machine learning algorithms, to uncover the underlying patterns and dynamics of individual differences.

    Looking ahead, the field of individual differences research stands at the cusp of significant advancements, propelled by technological innovations and the adoption of the profile perspective. This approach promises to unravel the intricacies of how individual differences operate within the fabric of daily life, offering insights that can inform personalized interventions and strategies for optimal development. However, this progress is not without its challenges. The complexity of daily situations and the dynamic nature of individual responses require sophisticated methods for situation classification and individual assessment. Moreover, the ethical implications of collecting and analyzing vast amounts of personal data, particularly in the context of wearable devices and digital health technologies, cannot be overlooked. The onus is on researchers to navigate these waters with care, ensuring that the benefits of these technologies are harnessed without compromising individual privacy or autonomy.

    In conclusion, the profile perspective on daily-life multi-situational individual differences assessment marks a significant shift in the way we understand and study human behavior. By embracing a holistic and individual-centered approach, researchers are poised to make strides in personalized psychological assessment and intervention, ultimately contributing to a more nuanced and effective approach to promoting individual and societal well-being.

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    The application of ecological momentary assessment in suicide research
    WU Caizhi, YUN Yun, XIAO Zhihua, ZHOU Zhongying, TONG Ting, REN Zhihong
    2024, 32 (12):  2067-2090.  doi: 10.3724/SP.J.1042.2024.0206
    Abstract ( 19 )   PDF (685KB) ( 19 )   Peer Review Comments

    Over the past 20 years, the application of ecological momentary assessment (EMA) in suicide research has grown exponentially, attracting significant interest from mental health professionals and clinical psychologists. EMA serves as a valuable data collection method in suicide research, utilizing technologies such as smartphones to monitor participants' real-time suicidal ideation, emotional states, and behaviors. This allows for a more fine-grained measurement in suicide risk (within hours) and effectively predicts short-term changes in suicidal ideation and behavior, playing a crucial role in the field of suicide research.

    The research design influences researchers' ability to effectively observe variables and accurately capture changes in suicide risk and related factors. Generally, In terms of study design, EMA employs event-contingent, time-contingent, or hybrid designs for data collection. To thoroughly understand the trends in suicidal ideation at different times, researchers may prioritize time-contingent designs to capture the dynamic characteristics of suicide risk. To examine temporal trends along with the specific contexts and influencing factors at the time of events, a hybrid design that combines time-contingent and event-contingent approaches can effectively reveal the mechanisms underlying suicidal behavior.

    EMA is suitable for both clinical and community populations, primarily focusing on adults, with limited research on adolescents and the elderly. Future EMA studies on suicide should emphasize demographic diversity while also considering mental health diagnoses and suicide-related features to identify daily risk factors for specific populations. By examining the trajectories of suicidal ideation and their links to future suicide tendencies among clinical patients with various mental disorders, researchers can identify key predictive factors for suicidal behavior.(77)In EMA suicide research among adolescents, daily diaries can reveal the trajectories of suicidal thoughts and behaviors during acute risk periods, capturing daily fluctuations in suicide risk. To explore the triggers of adolescent suicide-related events and variations in suicidal thoughts, it is crucial to enhance communication with schools and parents, coordinate adolescents' access to electronic devices, and address concerns about EMA participation. Additionally, to reduce technological challenges for older adults, wearable technology can unobtrusively collect continuous data on physiological, sleep, and activity levels, enabling real-time monitoring of suicide risk in this population.

    The application of EMA in suicide research requires careful consideration of feasibility. Compliance range from 44 to 90%, influenced by factors such as questionnaire length, assessment frequency, incentives, and the severity of suicidal ideation, which does not significantly affect compliance. Researchers can enhance feasibility by prioritizing frequent, brief assessments or using single-item indicators, adjusting the wording of questions, setting assessment prompts, and shortening prompt intervals. Developing a sampling schedule that balances time coverage with participant burden and using personalized feedback as alternative incentives can improve compliance and ensure the feasibility of EMA in suicide research.

    Safety is another critical consideration in EMA suicide research. While studies show no significant negative effects of EMA on individuals in short-term or long-term assessments, rigorous review by institutional review boards (IRBs) is still necessary. This review should address safety, privacy issues, and assess the crisis management and referral capabilities of the research team to ensure proper responses to potential crises. For safety management, researchers should conduct real-time reviews of participant data, especially regarding "high-risk" responses, and promptly contact participants for suicide risk assessment and intervention. To maximize benefits, researchers can implement a combination of preventive, staff-led, and supportive strategies as part of their safety management measures.

    To enhance short-term predictions of suicide risk, EMA should adopt innovative methods and technologies, utilizing digital technology and artificial intelligence for improved predictive capabilities. Additionally, it is crucial to address the legal and ethical issues related to EMA data in suicide research and to conduct localized studies within the context of Chinese culture.

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    Regular Articles
    The development of the correlation between visual-motor integration and reading
    ZHAO Yifan, LI Junjun, BI Hong-Yan
    2024, 32 (12):  2091-2099.  doi: 10.3724/SP.J.1042.2024.02091
    Abstract ( 15 )   PDF (449KB) ( 11 )   Peer Review Comments

    Visual-motor integration (VMI) refers to the coordination and integration of visual perception and fine motor skills, requiring individuals to perceive visual inputs and then plan and execute muscle movements accordingly. Numerous studies have shown that VMI ability is closely related to reading, with the degree of correlation being age-dependent. The development trajectory of the correlation between VMI ability and reading varies across different writing systems. In alphabetic writing systems, while the correlation between reading and VMI ability declines with age, it remains significant until secondary school. As for the reasons for this trend, considering the fact that as reading develops, the reliance on individually identifying letters and their order in words (which helps children sounding out the words) diminishes, giving way to a more automated process of direct retrieval. Consequently, the influence of VMI ability on reading performance diminishes with age. In Chinese writing system, mainland readers use simplified Chinese characters, while Hong Kong readers use traditional Chinese characters with more complex morphological structures (for example, the simplified Chinese character for tree is “树” and the traditional Chinese character is “樹”). Studies have shown that the correlation between simplified Chinese character reading and VMI ability increases with age, reaching a significant correlation in the upper grades of primary school (9 years and older). The lack of significance in the correlation between the two variables at a younger age may be attributed to the limited exposure of literacy instruction among younger children. During this developmental stage, there might not yet exist a stable correlation between their underdeveloped VMI ability and difficult Chinese character reading. For the traditional Chinese characters, there is a significant correlation between reading and VMI ability in preschool children. This difference in Chinese writing system can be attributed to the relatively easier nature of recognizing traditional Chinese characters and the relatively earlier literacy instruction received by Hong Kong children. Based on these reasons, their extensive practice in handwriting (which is the main way of learning Chinese characters) enhances their VMI and reading skills at a faster rate compared to mainland children. Consequently, a stronger correlation between VMI ability and reading may have been established among pre-school children in Hong Kong as opposed to those on the mainland. Additionally, studies focusing on developmental dyslexia (DD) groups with delayed reading skills have found that younger individuals exhibit more significant VMI deficits than older individuals across alphabetic writing systems, aligning with the developmental trajectory observed in typically developing children. In addition, research conducted on Chinese writing system has primarily focused on primary school students and has revealed that younger individuals with DD may not exhibit VMI deficits while older ones do, aligning with the developmental trajectory observed in Chinese typically developing children. Overall, it is evident that the correlation between VMI ability and reading performance is influenced by age and writing system. In light of the limitations of existing research, 1) future studies should adopt a multifaceted approach to measure VMI ability encompassing both process-oriented and outcome-based assessments. Most of the measurement of VMI ability in existing studies predominantly focus on the outcome, but ignore the process information. On the one hand, emphasizing process information can help improve the differentiation of the evaluation. On the other hand, disaggregating VMI performance into subcomponents such as latency and fluency can help clarify more clearly how VMI ability is involved in reading. 2) The emphasis on whether VMI ability serves as an essential foundation for supporting reading development constitutes a crucial aspect for future research. Specifically, these investigations should encompass several key dimensions. Firstly, longitudinal studies targeting the VMI ability of early children without reading experience can be conducted to distinguish the development sequence of VMI ability and reading ability from the temporal dimension. Secondly, conducting training studies on typically developing children can help elucidating whether VMI ability serves as a foundational precursor for reading development. Finally, by utilizing DD children who lag behind in reading ability, future studies can explore whether reading lag may due to VMI deficits. 3) Future researches should focus on elucidating the behavioral and neural mechanisms underlying the correlation between VMI ability and reading and its development. With regard to the internal mechanism through which VMI ability influences reading, previous studies have proposed hypotheses such as “the theory of internal models”, “the stroke processing hypothesis”, and “the visual analysis hypothesis”; however, empirical evidence remains insufficient to substantiate these hypotheses. Concerning the neural mechanism by which VMI ability impacts reading, prior research has suggested that the posterior parietal cortex may play a pivotal role; nevertheless, further exploration and verification from a developmental perspective involving participants across various age groups are warranted.

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    Emotional information processing in infants: Cognitive development and neural mechanisms
    MO Licheng, LI Qi, ZHANG Dandan
    2024, 32 (12):  2100-2108.  doi: 10.3724/SP.J.1042.2024.02100
    Abstract ( 10 )   PDF (413KB) ( 8 )   Peer Review Comments

    The emotional information conveyed through phonological prosody and facial expressions forms the foundation for human interpretation of others' emotions and facilitates interpersonal interactions. Investigating how infants perceive, discriminate, and evaluate emotions embedded in these two modalities deepens our understanding of their cognitive development and neural mechanisms. Infants’ emotional processing primarily relies on facial expressions, speech, and cross-modal sensory processing involving both visual and auditory inputs.

    In emotional facial processing, the temporal and frontal cortex are the core brain regions. Although emotional processing in infants involves both brain hemispheres, the right hemisphere appears to have an advantage. Remarkably, just 36 hours after birth, newborns can distinguish and imitate facial expressions, demonstrating their sensitivity and interactive ability with the surrounding environment. Two-day-old newborns can generally distinguish different facial expressions, such as happiness, sadness, surprise, and fear. By 3~4 months of age, infants can reliably differentiate between various facial expressions. At 5 months, they begin to distinguish different types and forms of facial expressions, including dynamic ones. After 6 months, infants exhibit classification perception of emotional facial expressions. By 7 months, they are very sensitive to dynamic facial expressions. By 8 months and beyond, infants start to show an understanding of emotional facial expressions, with positive emotions being understood earlier than negative ones. Although the global brain network for infant emotional facial perception is not yet fully mature at this stage, local specific brain networks have developed to a level almost equivalent to those of adults.

    In infants’ emotional speech processing, the temporal cortex is the core brain area. During the first week after birth, babies exhibit considerable sensitivity to emotional speech and can generally distinguish different emotional tones, which helps improve their interactions with others. By two months of age, infants can distinguish between happy and neutral speech, showing a greater sensitivity to happy voices. At 5 months, infants are able to differentiate between happy, angry, and neutral voices, again displaying a preference for happy voices. By 7 months, infants can distinguish between happy, sad, angry, and neutral voices, with sensitivity to angry and sad tones.

    Babies exhibit the ability to process emotional information across multiple modalities, demonstrated by their capacity to match and transfer emotional information across different sensory modalities. These abilities gradually improve with age. Compared to the processing of emotional speech and facial expressions, the development of cross-modal emotional processing in infants occurs later.

    Emotional bias manifests differently at various stages of infant development. Infants predominantly exhibit positive emotional processing in the first 6 months, but this gradually shifts to a stable negative bias after 6 months. Based on this observation, we propose the “Developmental Theory of Emotional Bias”: Human emotional processing biases change around six months of age, with positive biases observed in infants aged 6 months and below, and increasingly stable negative biases observed in infants aged 6 to 7 months and beyond. From a cognitive development perspective, the infants’ brain prioritizes processing stimuli relevant to their developmental stage. For infants aged 6 months and below, a more positive response to positive emotions may help establish strong connections with parents and ensure more care, thus favoring positive emotions. After 6 months, as infants develop motor abilities such as crawling, running, and jumping, they begin to actively explore the world. At this stage, they need to be more sensitive to threatening information to protect themselves from harm. Therefore, infants at this stage prefer negative emotions.

    Overall, as infants age, their ability to process emotions gradually improves, encompassing multiple levels from identifying and distinguishing emotions to capturing emotional changes and eventually understanding and applying emotions. Currently, research on visual, auditory, and cross-modal emotional information processing during infancy has made significant progress and established a relatively solid foundation. Future research needs to systematically investigate emotional processing from infancy through early childhood to construct a complete developmental timeline and reveal in-depth changes in infant emotional development. Additionally, specific experimental designs must rigorously control for additional variables and combine multiple research methods to provide more convincing evidence for understanding infant cognitive development and brain mechanisms.

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    The mechanisms and conditions for the occurrence of enviro-materialism
    CHEN Shouyong, LI Jing
    2024, 32 (12):  2109-2123.  doi: 10.3724/SP.J.1042.2024.02109
    Abstract ( 20 )   PDF (520KB) ( 13 )   Peer Review Comments

    Enviro-materialism refers to the phenomenon that individuals who hold materialistic values engage in pro-environmental behaviors. Unlike previous views on the contradiction between the materialistic values and pro-environmental behavior, the phenomenon emphasizes that the pursuit of material possessions can coexist harmoniously with concern for the natural environment. We systematically discuss the mechanisms and boundary conditions of enviro-materialism. Specifically, the psychological mechanisms underlying the phenomenon of enviro-materialism can be understood from five perspectives: crossvergence theory, costly signaling theory, impression management theory, compensatory ethics theory, and goal-framing theory. First, from the perspective of crossvergence theory, the emergence of enviro-materialism is the result of the interaction between cultural change and commercial ideology. Second, according to the cost signaling theory, pro-environmental behaviors that convey the signal of concern for the environment may be an effective means for materialists to gain high status and recognition from others. Furthermore, impression management theory suggests that the goal of pursuing high social status is closely related to the impression left by materialists on the audience, and they may choose pro-environmental behavior as a strategy for constructing positive impressions. In explaining the phenomenon of enviro-materialism, the compensatory ethics theory emphasizes that materialists’ pursuit of wealth and material goods has caused serious negative impacts on the environment, and in order to maintain moral balance, they may choose pro-environmental behaviors as compensation. Finally, the goal-framing theory states that if the materialists’ hedonic or benefit goal frame is activated, they may be guided to engage in more pro-environmental behaviors to achieve positive emotional experiences or personal gain. In addition, certain individual, situational and cultural boundary conditions are required for the enviro-materialism phenomenon to occur, including global cultural identity, environmental knowledge level, public-private attributes of decision-making situations, types of benefit appeals, nature contact, market context and generations. In other words, individuals who identify with global consumer culture or have a higher level of environmental knowledge are more likely to live in a materialistic mode while also maintaining concern for the natural environment. Second, materialists may exhibit their environmentally-friendly tendencies in public situations, when exposed to self-interest appeal messages, or when in contact with nature. Moreover, consumers living in emerging markets and younger generations are more likely to place equal importance on material possessions and environmental sustainability. By sorting out the connotation, occurrence mechanisms and boundary conditions of enviro-materialism, we make clear the fact that individuals holding materialistic values may also exhibit pro-environmental behaviors, which further deepens the academic understanding of the “green side” of materialism. At the same time, our work also provides new ideas for addressing the practical problem of the depletion of natural resources caused by materialistic consumption views. For instance, more environmental projects can be developed to stimulate materialists’ internal and external motivations (such as the pursuit of social status, good reputation, etc.) to encourage their pro-environmental behaviors. Also, contextual factors can be used to promote the green behavior of materialists, such as making environmental decisions in public places, engaging in more activities that involve exposure to the natural environment, and so on. However, there are still many issues that need to be addressed in future research regarding the emerging phenomenon of enviro-materialism. First, the connotation of enviro-materialism is relatively vague, and future research needs to further investigate whether the pro-environmental choices of this phenomenon are more likely to be reflected in indirect environmental behaviors such as green consumption. Second, it is necessary to explore more boundary conditions from the perspective of materialism, such as the socioeconomic status of the materialists themselves. Third, it is crucial to find ways to promote the stable occurrence of enviro-materialism, and we believe that focusing on “second-hand luxury goods” may be an effective strategy.

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    Human-AI mutual trust in the era of artificial general intelligence
    QI Yue, CHEN Junting, QIN Shaotian, DU Feng
    2024, 32 (12):  2124-2136.  doi: 10.3724/SP.J.1042.2024.02124
    Abstract ( 23 )   PDF (613KB) ( 27 )   Peer Review Comments

    With the advancement of technology, the dawn of artificial general intelligence is upon us, heralding a new era for human-machine interaction and relationships. Trust, as the linchpin of human-AI interaction, directly affects the success of the interaction and the user experience. Maintaining an appropriate level of trust can influence the outcomes of human-AI interactions. Currently, the trust relationship between humans and AI is undergoing transformation, yet existing research has not accurately grasped this new type of trust relationship. There are limitations in the understanding of human-AI trust, partly due to the unclear definition of human-AI trust, and partly because the focus has been solely on human trust in AI, neglecting the trust that AI places in humans, and lacking an understanding of the bidirectional trust process in interpersonal interactions.

    To address these deficiencies, this study first reviews the definitions of human-machine trust and automated trust from previous research and summarizes the current characteristics of human-AI trust: on one hand, the concealment of AI technology usage makes users unaware of AI's involvement; on the other hand, the current human-AI trust should include AI's trust in humans. In response to these characteristics, this study proposes a new definition of human-AI trust: that is, regardless of the awareness of the presence of AI algorithms, the attitude and confidence held between people and AI systems that believe the other party can help achieve specific goals, and the willingness to accept each other's uncertainty and fragility and bear the corresponding risks during the interaction process. The new definition extends the scope of human-AI trust to situations where users are not aware of AI's involvement and, for the first time, proposes a mutual trust relationship between humans and AI, which also implicitly reveals that human-AI trust is a dynamic process.

    Secondly, to overcome the limitations of previous trust models in explaining the dynamic and bidirectional trust relationship between humans and AI, this study, based on a comprehensive review of existing trust models (including the interpersonal trust model, the four-factor model of human-machine trust, the three-factor model of human-automation trust, and the general model for trust decisions), proposes a new human-AI mutual trust model for the new type of bidirectional trust interaction in the era of general artificial intelligence: the Human-AI Dynamic Mutual Trust Model. The model, for the first time, regards humans and AI as equal parties in trust establishment, constructing a dynamic mutual trust framework that includes three phases (initial phase, perception phase, and behavior phase) and two subjects (humans and AI). This framework encompasses various factors such as trust-related experience and trust propensity of the trustor and trustee in the initial phase, perceived factors such as perceived individual state and perceived system state in the perception phase, and result feedback and situational factors in the behavior phase, emphasizing the two important characteristics of “mutual trust” in the relational dimension and "dynamics" in the temporal dimension of human-AI trust.

    This study not only provides a clear definition of trust for the new type of trust relationship between humans and AI in the era of artificial intelligence but also proposes a brand-new theoretical model: the Human-AI Dynamic Mutual Trust Model, offering an in-depth theoretical explanation for the dynamic process of human-AI trust. Future research can explore within the framework of human-AI mutual trust how AI's trust in humans is established and maintained, how a quantitative model of human-AI mutual trust can be established, and what the process of human-AI mutual trust is in multi-agent interactions.

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