ISSN 1671-3710
CN 11-4766/R


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    Research Method
    Examining societal change from the perspective of psychology: Research design and analytic techniques
    CAI Huajian, ZHANG Mingyang, BAO Han-Wu-Shuang, ZHU Huijun, YANG Ziyan, CHENG Xi, HUANG Zihang, WANG Zixi
    2023, 31 (2):  159-172.  doi: 10.3724/SP.J.1042.2023.00159
    Abstract ( 1127 )   HTML ( 61 )  
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    In recent years, impacts of societal changes on human culture and psychology have become a cutting-edge research area in cultural psychology. The research from the perspective of psychology mainly concerns psychological and behavioral changes as well as their potential drives, which often involves three kinds of effect, that is, age/maturation effect, period/time effect, and cohort/generation effect. Time effect refers to effects caused by socioecological changes in a certain period (e.g., the influences of modernization on Chinese people since 1980s). Age effect refers to development growth caused by individual maturation (e.g., developmental growth during a specific period). Cohort effect refers to effects associated with a specific born year (e.g., enduring effect of modernization on 1970 generation in China). Among these effects, time effect and cohort effect are related to socioecological change, whereas age effect usually constitutes a confounder.

    In examining psychological changes as well as their drives, widely used research designs includes cross-time comparison, cross-generation comparison, and cross-region comparison (or historical reconstruction). By examining psychology and behaviors of people in different times, cross-time comparison allows researchers to infer how surveyed psychology and behaviors have changed with time. This examination usually involves cross-temporal analysis of published data, archive data and survey data. The survey data may be resulted from diverse designs, including cross-sequential design, longitudinal design, revolving panel design, total population design and retrospective panel design. These designs vary in difficulty of data collection.

    Cross-generation comparison allows researchers to infer the changes of psychology and behaviors across time by examining differences across people born in different cohorts. The cohort can be decided based on special years (e.g., 1980s, 1990s and so on) or special events (e.g., China’s opening up and reform; China’s joining in WTO). In doing this, research can compare representative samples born in different cohorts. A special case is to compare grandparents, parents, and youngest generation within a family. Cross-generation comparison within a family also allows to examine similarities and dissimilarities of different generations.

    Cross-regional comparison allows researchers to infer the changes of psychology and behavior by examining differences across regions at different modernization levels. A typical example is to infer psychological changes by comparing people from rural areas with those from urban areas. In this case, rural areas represent the past or tradition, whereas urbane areas represent current or modern time. Thus, rural-urban differences can be mapped onto tradition-modern differences.

    In examining psychological changes as well as their drives, widely used data analysis methods includes classic correlation and regression analyses, and modern time series analysis. In exploring possible causal relationships, cross-lagged correlation analysis and Granger causal test are often used. In doing correlation and regression analysis, researchers usually use year or potential socioeconomic factors to predict targeted psychological outcomes, thereby inferring the psychological trends as well as their covariations with diverse socioecological factors. Cross-lagged correlation analysis allows us to infer the direction of the covariation. Granger causal test may provide further causality test while controlling for potential influences of autoregression. Vector autoregression has received increasing attention in recent years, which can be used to model multivariate time-series data. Despite salient advances in data analysis technique, how to decompose and estimate the age effect, period effect, and cohort effect is still a challenge. More studies are needed to tackle this issue.

    In summary, we summarized the main research designs and data analysis techniques in studying culture, psychology, and behavior changes. It is notable that each design has specific pros and cons, researchers need to choose suitable design in terms of research question and data collection possibility. If possible, it is highly recommended to pursue convergent evidence by conducting multiple studies with diverse research designs.

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    Exploring the neural representation patterns in event-related EEG/MEG signals: The methods based on classification decoding and representation similarity analysis
    CHEN Xinwen, LI Hongjie, DING Yulong
    2023, 31 (2):  173-195.  doi: 10.3724/SP.J.1042.2023.00173
    Abstract ( 685 )   HTML ( 46 )  
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    It is generally considered that the human brain will generate distinct neural representations corresponding to different mental processes. Exploring the differences of neural representations under various mental activities is one of the core issues in cognitive neuroscience. During recent decades, researchers have used different neuroimaging techniques to record brain activities involved in complex cognitive processes from the perspective of temporal or spatial measurement. Among these techniques, the non-invasive EEG/MEG with temporal resolution of millisecond has become a popular one to study the time courses of various cognitive activities. Due to the characteristics of EEG/MEG data (e.g., low S/N), in order to obtain relatively reliable results, traditional EEG/MEG studies mainly focused on the neural responses after group averaging, paying less attention to individual differences. Such method assumes that, for each subject, the amplitudes and directions of ERPs/ERMFs and their topographic maps in a specific time window of interest exhibit a consistent pattern under an experimental condition. In the case of poor consistency, the neural responses across subjects may cancel each other to a great extent after group averaging, which makes it difficult to get a reasonable interpretation.

    In recent years, researchers have introduced two techniques commonly used in fMRI studies, classification algorithms in machine learning (i.e., classification-based decoding) and representation similarity analysis, into the EEG/MEG data analysis. These two new techniques can overcome the shortcomings of traditional EEG/MEG data analysis based on averaging of voltage/magnetic flux density waveforms by taking individual differences into account, which could be used to reveal the coding of neural representation at individual level and provide a new idea to explore how the brain encodes specific neural representations dynamically. In the study of ERPs/ERMFs, classification-based decoding and representation similarity analysis can be used to explore not only the neural mechanisms that show consistent patterns along time among individuals, but also those that are significantly different across individuals but keep stable for a given individual. Thus, these two techniques are able to reveal specific neural representation patterns and even identify "brain fingerprints" at individual levels. Based on different methodological theories, these two techniques provide novel ways for EEG/MEG studies to compare representational differences of cognitive processes across time windows, tasks, modalities, and groups. Firstly, we systematically introduced the principles and operational processes of classification-based decoding and representation similarity analysis, together with a comparison with those traditional analysis methods of EEG/MEG. Then, the EEG/MEG studies to date using these two techniques are reviewed. Finally, some possible future research directions with regard to these two techniques are proposed.

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    Multiverse-style analysis: Introduction and application
    HUANG Shunsen, CHEN Haojie, LAI Xiaoxiong, DAI Xinran, WANG Yun
    2023, 31 (2):  196-208.  doi: 10.3724/SP.J.1042.2023.00196
    Abstract ( 931 )   HTML ( 39 )  
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    Multiverse-style analysis (e.g., the vibration of effects, multimodel analysis, multiverse analysis, specification curve analysis) proposes to report combinations of multiple analysis strategies during data analysis and to test the robustness of effects between relevant variables in all analytic strategies. The basic principles and applications of the multiverse-style analysis are described, and the operational steps are presented as an example of the relationship between smartphone use and smartphone stress. The strengths and limitations of the method are discussed, as well as future directions.

    Searching the Web of Science on the topic of multiverse-style analysis (e.g., the vibration of effects), we found that the number of papers rose from 9 in 2015 to 40 in 2021. Multiverse-style analysis is gradually being applied in psychology, behavioral sciences, neuroscience, psychiatry, and other fields. Most of these studies used self-reported data. Some neuroscience and biology-related studies used objective data (e.g. physiological indicators such as brain imaging data). Few studies combined self-reported and objective data. Most studies used cross-sectional designs. A few studies used longitudinal or cohort designs. In addition, multiverse-style analysis is gradually being combined with other psychological methods. For example, some researchers have combined it with mediation analysis to determine the robustness of mechanisms among variables. It has also been used with network analysis to reduce the instability of network centrality. People have combined multiverse-style analysis with meta-analysis to form the “combinational meta-analysis”. Finally, different studies have different preferences in the choice of combinations of analytic strategies. For example, some focus on different measurement approaches (self-report or objective measures), while others focus on different estimation methods or concentrate on the diversity of the datasets. In combining multiverse-style analysis with other methods, researchers usually emphasize the strengths of multiverse-style analysis to compensate for the weaknesses of other methods.

    Advantages of multiverse-style analysis: (1) It can include multiple data sets, multiple measurement methods and estimation methods, and then perform effect tests. (2) Multiverse-style analysis can be used to resolve controversial issues. Multiverse-style analysis not only has the advantages of meta-analysis but also can be applied to emerging areas where empirical studies are scarce and meta-analysis is not appropriate. Limitations of multiverse-style analysis: (1) As the combination of analysis strategies and sample size increases, it becomes more time consuming to make statistical inferences. (2) The method is still essentially a subjective selection process by the researchers. As such, there may be a potential risk of leading to the problem of "truly arbitrariness". (3) The statistical inference indicators of multiverse-style analysis are not stable. Conflicting results between different statistical indicators may arise. (4) It is difficult for the researcher to report all possible combinations of analytical strategies for an effect based on the available dataset. It is necessary to select the appropriate combination of analytical strategies and build an appropriate dataset based on the available theory and evidence before data analysis.

    Future directions: (1) Most existing studies demonstrate the robustness of interesting effects by simply describing all outcomes. Future applied research should consider implementing statistical inference. (2) Deepening the integration of multiverse-style analysis with other research methods, e.g. developing different criteria when integrating multiverse-style analysis with different methods. (3) Select stable statistical inference indicators, give more consideration to parameter estimation (e.g., BIC, AIC) and model estimation methods (e.g., Bayes, Monte-Carlo) when constructing combinations of analytic strategies, and include statistical inference in analytical software or software packages. (4) Combining multiple channels to jointly address the reproducibility crisis (e.g. future research could incorporate multiverse-style analysis during data analysis and pre-registration before data collection). (5) Hold a critical sight towards the different outcomes of different combinations of analytical strategies. There may not be a single standard law in the field of human psychology and behavior, which is influenced by multiple factors (e.g. genes, groups, environment, culture, etc.).

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    Conceptual Framework
    The impact of psychological detachment on work engagement: Promotion or inhibition?
    WAN Jin, ZHOU Wenjun, ZHOU Haiming, LI Pingping, SHI Kan
    2023, 31 (2):  209-222.  doi: 10.3724/SP.J.1042.2023.00209
    Abstract ( 1230 )   HTML ( 75 )  
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    Employees are the creators of organizations’ core competencies, and whether they can actively engage in work is critical to the development of organizations. So improving employees' work engagement is of great significance for both individual and organizational development. However, as competition intensifies and the pace of work accelerates, the boundary between work and non-work becomes increasingly blurred. It’s easier to physically get off work, but harder to mentally get off work, which can easily cause physical and mental exhaustion and reduce work engagement. Therefore, it is an important way to improve work engagement by helping employees to put down work during non-working hours which can avoid physical and mental exhaustion and replenish physical and mental energy as much as possible. Psychological detachment refers to the mental state in which an individual is detached from work during non-working hours, not being disturbed by work-related problems and stopping thinking about work. Mainstream studies believe that psychological detachment has a positive effect on work engagement, but there are contradictory conclusions regarding the impact of psychological detachment on work engagement. Therefore, there is still a lack of solid scientific evidence for psychological detachment as a means to improve employee work engagement.

    Based on the Job Demands-Resources Model, this study constructs a comprehensive model to investigate the effect, mechanism and boundary conditions of psychological detachment on work engagement, so as to provide an integrated explanation for previous contradictory conclusions. The theoretical contributions of this study are mainly reflected in the following aspects: First, the concept of psychological detachment behavior is introduced to emphasize the distinction between psychological detachment behavior and psychological detachment state. Psychological detachment in previous studies refers to the state of psychological detachment, but the existing measurement items are easily understood as psychological detachment behavior. Psychological detachment state can help individuals recover psychological resources, but psychological detachment behavior is an individual’s emotional and cognitive regulation behavior which needs to consume psychological resources. Therefore, this study defines the connotation of psychological detachment behavior and psychological detachment state, which is helpful to reveal the influence of the two on work engagement respectively, and can also provide a more accurate concept for subsequent research. Second, based on the job demand-resource model, an integrated multiple mediating and moderating model is constructed, which can explain the contradictory conclusions about the relationship between psychological detachment and work engagement in previous studies. This study believes that this contradictory conclusion is not only caused by the failure to distinguish psychological detachment behavior from psychological detachment state, but also that there are independent positive and negative mechanisms between psychological detachment and work engagement, and the relationship is moderated by work situations and personal characteristics. Therefore, based on the job demand-resource model, this study establishes an integrated explanatory model to deepen the understandings of the effect, mechanism and boundary conditions of psychological detachment, especially to reveal the negative mechanism of psychological detachment on work engagement. Third, it reveals the difference between psychological detachment after work and psychological detachment during work breaks. Most studies have investigated the influence of psychological detachment after work on the next day’s work engagement. In addition to using the experience sampling method to explore it, we also plan to investigate the influence of psychological detachment during work breaks on the subsequent work engagement of the same day by adopting the vignette experiment method. It can reveal the differences in the effects and mechanisms of psychological detachment during and after work breaks, and deepen the understandings of the effects and mechanisms of psychological detachment between the two periods.

    The conclusion can provide managers and employees with specific suggestions on psychological detachment according to different working situations and different individual characteristics, which can help employees maintain health and vitality, improve work engagement, and provide psychological capital for efficient operation and sustainable development of organizations.

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    The in-feed native advertising avoidance mechanism and re-targeting strategy based on user dynamic information processing mode
    ZHANG Hao, XIAO Bangming, HUANG Minxue
    2023, 31 (2):  223-239.  doi: 10.3724/SP.J.1042.2023.00223
    Abstract ( 476 )   HTML ( 20 )  
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    In the era of mobile Internet, the in-feed native advertising, which is more acceptable in the mobile news context, has become one of the primary forms of online advertisements. However, with the rapid development of in-feed native advertising, the ad avoidance problem has become prominent and brings unignorable harm to the platforms, advertisers, and users. Recent studies on in-feed native ad avoidance mainly focus on users' static, stable, and historical characteristics but neglect the dynamic, native, and reactive nature of in-feed platforms. The lack of a dynamic view on in-feed native advertising will inevitably lead to a wider gap between academic research and marketing practice. By applying the dynamic information processing perspective, this research breaks the limitation of traditional studies on in-feed native advertising that mainly focus on users’ static characteristics and explores the mechanisms of users’ ad-skipping and ad-blocking behaviors under varied information processing modes (convergent vs. divergent). The subsequent re-targeting strategies by the platform and their effectiveness are also discussed. This research consists of the following three sub-studies.

    In study 1, the authors propose a theoretical framework from a dynamic perspective and discuss the antecedents of in-feed native advertising avoidance based on users’ dynamic information processing states. First, following previous research on online advertising, the authors identify two typical ad avoidance types of ad-blocking and ad-skipping and delineate their differences and associations. Second, they explore the mechanisms through which the users avoid the in-feed native ads under different information processing states (i.e., convergent vs. divergent). Finally, they construct a multi-state hazard model to demonstrate the dynamic process of the users’ in-feed native ad avoidance. In study 2, the authors discuss how the platform should apply re-targeting strategies after the users actively block the in-feed native ads. The extant studies on ad avoidance have demonstrated that the ad-blocking behavior requires high cognitive and behavioral effort and therefore brings "residual impact" on improving the memory and cognition toward the blocked ads. Based on this theorem, the authors examine the signal value from the "residual effect" of the ad-blocking. Besides, the authors demonstrate whether and how the platform can leverage the "guided attribution" strategy to improve the users’ attitudes toward the subsequent ads. However, the authors further argue that the effectiveness of such re-targeting strategy is contingent. In study 3, the authors focus on the other parallel but fundamentally different ad avoidance behavior, i.e., the ad-skipping. The platform’s responsive re-targeting strategy is also discussed in this study. Due to the "learning effect" in the users’ continuous information processing, repetitive ad-skipping is more likely for users who have just skipped the ads. The increased arousal level can break such momentum during the users’ online browsings. Based on this theorem, the authors demonstrate whether and how the platform can apply the "prominence strategy" to decrease the likelihood of subsequent ad-skipping by the users.

    This research contributes to the present literature and marketing practice in several ways. First, it enriches the literature of ad avoidance by distinguishing two fundamentally different types of ad avoidance behaviors (i.e., ad-blocking vs. ad-skipping) in the in-feed native advertising context. The authors further discuss the varied mechanisms of ad avoidance based on users’ dynamic information processing states. Second, compared with the traditional and relatively static view on the in-feed native advertising, the authors build a theoretical framework from a dynamic perspective and discuss the mechanisms regarding how and when the dynamics of users’ online browsings affect their ad avoidances. Third, this research provides valuable and actionable suggestions on how the in-feed native advertisers and platforms should respond to the users’ ad avoidance appropriately to improve the overall market communication efficiencies.

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    Regular Articles
    Better to misidentify than to miss: A review of occurrence mechanisms and applications of face pareidolia
    CHEN Zi-Wei, FU Di, LIU Xun
    2023, 31 (2):  240-255.  doi: 10.3724/SP.J.1042.2023.00240
    Abstract ( 915 )   HTML ( 38 )  
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    In real life, people occasionally perceive an object as something non-existent, called pareidolia. Among all forms of pareidolia, people are more likely to recognize a face from an object. Face pareidolia has been widely utilized in art, advertising, and design, but its occurrence mechanisms remain unclear. Previous studies have used various paradigms to explore the occurrence mechanisms of face pareidolia. According to the different paradigms used, the occurrence mechanisms of face pareidolia have been deeply discussed from top-down and bottom-up visual signal processing pathways. However, due to the variety of paradigms, face pareidolia occurrence mechanisms and potential applications are still in their infancy. There has been no systematic theoretical construction either. Based on the two visual processing pathways, we categorize two types of paradigms: the pareidolia monitoring paradigm (face pareidolia in a bottom-up pathway) and the pareidolia discrimination paradigm (face pareidolia in a top-down pathway). To provide future research insights, we summarize the two paradigms from three perspectives, including stimuli, experimental procedures, and measurements. In addition, according to the perceptual prediction model, there are similarities and differences in the occurrence mechanisms of the two paradigms. Both paradigms have analogy, association, and prediction processes. However, the pareidolia monitoring paradigm focuses on rapid prediction generation through a single analogy and association process. The pareidolia discrimination paradigm focuses on the subjective expectation codes feedback to the analogy association process and then affects the subsequent prediction. In addition, the applications of facial illusions in clinical diagnosis, product, and advertising packaging are also listed. First, children with autism are less likely to produce face pareidolia than normal children, but they are still able to have face pareidolia. Moreover, there are connections between visual illusions and visual hallucinations in clinical diagnosis. Pareidolia could be used as a measurement of subclinical hallucinations. In commercial applications, the prominence of pareidolia elements in paintings, architecture, and advertising can attract consumers’ attention and facilitate their emotional or trait attributions to objects and consumer behavior. Future studies are suggested to develop new paradigms to explore further the interaction between top-down and bottom-up mechanisms of face pareidolia.

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    From induction to relief: Neurophysiological mechanisms underlying the curiosity feedback loop
    CHEN Nianqu
    2023, 31 (2):  256-273.  doi: 10.3724/SP.J.1042.2023.00256
    Abstract ( 681 )   HTML ( 27 )  
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    The curiosity feedback loop model considers the nature of curiosity as intrinsic motivation, regards information-seeking behaviors as an evoked outcome of curiosity, emotions as a concomitant product of curiosity, and emphasizes the dynamic and changing nature of curiosity. The model incorporates the expected value of control model and Bayesian reinforcement learning framework, and integrates research evidence from multiple functional brain systems such as the monitoring system, reward system, and control system. The model provides new ideas for understanding the neurophysiological mechanisms of curiosity.

    The curiosity feedback loop model decomposes a curious event into the following six processes: perceived information gap, curiosity generation, value assessment of control, information seeking, curiosity satisfaction, and information integration. Specifically, an individual develops a desire for information (reward) as a result of perceived information gap, and thus curiosity occurs. Subsequently, the individual performs a value assessment of control based on the current activity state or the expected outcome of potential behavior (e.g., information seeking). The decision to initiate information seeking is made by assessing how much control is needed to be exerted for the next behavior. Information seeking changes the information input, which in turn changes the individual state, and the new state becomes a cue for the value assessment of control, influencing a new round of information-seeking behavior. Information seeking corresponds to different outcomes: curiosity satisfied or curiosity unsatisfied. Curiosity satisfaction implies acquisition of information reward, which tends to increase the individual's estimate of the expected value of the new information and the validity of the behavior, which in turn reinforces information-seeking behavior. The further integration of information leads to the expansion of prior knowledge, and the expanded prior knowledge makes it easier for individuals to realize new information gap and stimulates new information-seeking behavior. This process creates a positive feedback loop that contributes to sustainable knowledge acquisition. Conversely, if information acquisition fails, the positive feedback loop will be interrupted.

    This dynamic loop of curiosity is embedded in the lifelong development of the individual, changing with the accumulation of experience and the development of brain. On the one hand, it is influenced and limited by various physiological changes in life development; on the other hand, the repeated consolidation of the curiosity loop also causes physiological changes that in turn affect an individual’s life development. In simple terms, the two curiosity-related systems - the dopaminergic and noradrenergic systems - contribute to short-term attention, memory, and information-seeking behavior, and are also beneficial for the long-term maintenance and improvement of cognitive function.

    Curiosity studies become increasingly multidisciplinary and cross-cutting, and therefore a unified concept and framework is needed as a basis for further scientific discussion. Regarding future curiosity research, increased attention could be given to: (1) strengthening the focus on curiosity satisfaction; (2) improving existing paradigms for curiosity research; (3) enhancing comparisons of the use of internal and external rewards; and (4) valuing the developmental aspects of curiosity research.

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    The effects of mindfulness-based interventions on different components of impulsivity: From the perspective of dual-process theories
    YANG Zhenzhi, ZENG Hong
    2023, 31 (2):  274-287.  doi: 10.3724/SP.J.1042.2023.00274
    Abstract ( 828 )   HTML ( 43 )  
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    Impulsivity is referred as a predisposition to act rashly on one’s first thoughts, which is usually characterized by little forethought, reflection, or consideration of the consequences of an action. According to the dual-process framework, components of impulsivity can be classified into affective impulsivity and action/cognitive impulsivity which then integrate into what is called a drive - control construct. These two types of impulsivities are dominated by the socioemotional system (driving force) and the cognitive control system (controlling force) respectively. The dual-process theories offer a novel explanation for the underlying mechanisms of impulsivity, and Mindfulness practices is a type of method that can effectively regulate impulsivity and be well explained by this theory framework.

    Mindfulness-based interventions (MBIs) emphasize the intentional awareness of individual’s physical and mental experience with a non-judgmental attitude. MBIs comprise both traditional contemplative practices from a few religions and the contemporary mindfulness approaches that form some cognitive-oriented psychotherapies. In recent years, clinical practitioners have proposed and developed a number of MBIs targeting impulsive individuals’ problematical behaviors. Researches into the effectiveness of these MBIs show significant outcomes among different populations, including attention deficit and hyperactivity disorders, substance abusers, adolescents with behavioral problems, and obese people with eating disorder.

    From the dual-processing approach, the positive impact of MBIs on impulsivity has two reasons: one is that MBIs can mitigate the action/cognitive impulsivity triggered by the cognitive control system, and the other is that MBIs can lower the affective impulsivity caused by the socioemotional system. More specifically, MBIs attempts to train individuals to be fully "exposed" to their immediate self-experience with positive attitudes, so as to reduce their reward expectation whilst improving the responsiveness to natural reward, and then realizing the adjustment and reshaping of their reward effects. Meanwhile, MBIs can enhance individual’s ability of “decentering” the feeling of stress and negative affect, thus reducing the perception of distress feeling and providing a necessary buffer to avoid impulsive behaviors. More essentially, MBIs-trained individuals are more sensitive to their own introspection and habitual responses, which helps to weaken the automatic driving force in impulsive behaviors. In addition, MBIs strengthen individuals’ cognitive control and inhibitory control, leading to decreases in the relevant impulsive performance in waiting impulsivity and action impulsivity.

    Due to differences in processing time and varied directionality between factors driving and controlling impulsivity, MBIs expand the buffer zone between receiving and responding to stimuli, with repeated practice focused on attention and positive attitudes including acceptance and non-response. MBIs not only weaken the motivation of driving factors, but also promotes the effective implementation and participation of controlling factors, thus reducing the confrontation between these two types of components and the interaction of these two factors could then make individual's underlying dynamic system more balanced. To sum up, supported by the dual-processing model and empirical evidence, MBIs can be considered as an effective intervention approach to reduce individual impulsivity.

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    An exploration of the continuum beliefs intervention on the stigma of mental disorders
    LI Chengzhe, SHI Yujing, ZONG Yahui, XIE Jiushu
    2023, 31 (2):  288-300.  doi: 10.3724/SP.J.1042.2023.00288
    Abstract ( 504 )   HTML ( 17 )  
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    The stigma of mental disorders indicates the prejudice or discrimination against patients with mental disorders due to their illness. The stigma of mental disorders not only seriously affects the recovery of patients with mental disorders but also seriously impedes their integration into society and harms their social functioning. Nowadays, due to the large number of people suffering from mental illnesses worldwide, the stigma of patients with mental disorders has led to a wide range of social impacts. Therefore, previous studies have proposed many theories to interpret the generation of the stigma of mental disorders and propose many intervention programs to eliminate the stigma. However, these theories hold the view that the generation of the stigma of mental disorders is mainly due to the lack of public social knowledge about mental disorders, unreasonable attribution, or lower moral level. Moreover, these theories had drastic debates. For example, the effects of these intervention programs based on these theories were not always stable. To reduce such debates, the present study interprets the stigma of mental disorders from the underlying cognitive system of the stigma. To this end, the present study proposes a new theoretical explanation of stigma from the perspective of social categorization and proposes corresponding intervention programs. Specifically, the present study believes that people’s stigma of mental disorders is derived from social classification. People spontaneously categorize patients with mental disorders as out-group members, which results in out-group bias and prevents people from maintaining objective and rational perceptions of patients with mental disorders, and eventually generates stigma. Based on the innovational theories above, the present study also extends the theoretical perspective of continuum beliefs and proposes an innovational stigma intervention system.

    The continuum beliefs intervention is a potential intervention method to eliminate the stigma of mental disorders, which has been tested widely. The continuum beliefs intervention attempts to blur the boundaries between people and patients with mental disorders. This approach intends to affect the instinct categorization processing of human beings to minimize stigma. The continuum beliefs intervention holds that there is no absolute difference between typical people and patients with mental disorders, which suggests that they are similar and cannot be separated. Therefore, continuum beliefs intervention focuses on the core mechanism of the stigma of mental disorders, i.e., social categorization. This approach helps people believe patients with mental disorders are similar to themselves, which will significantly reduce the stigma of mental disorders.

    The present study further extended the continuum beliefs intervention by proposing a social classification-based continuum beliefs intervention program, which highlights the role of social classification in the continuum beliefs intervention program. Furthermore, the present study constructs a social classification-based continuum beliefs intervention model. The social classification-based continuum beliefs intervention model holds that: (1) the intervention aim is reducing incorrect social categorization; (2) the contents of the intervention are used to eradicate incorrect social classification; (3) the one’s level of incorrect social categorization can be used as the indicator to measure the intervention effect. In addition, the effect of the classification-based continuum beliefs intervention depends on three factors: perceived threats, disease attribution, and personal traits. The present paper also interpreted how these factors improve or decrease the intervention effects of the classification-based continuum beliefs intervention. Furthermore, the present paper also interpreted how the classification-based continuum beliefs intervention changed social categorization and then influenced the generation of the stigma of mental disorders. Future studies should examine the theoretical model of the classification-based continuum beliefs intervention in cross-cultural situations. Meanwhile, future studies may develop online continuum beliefs intervention methods to extend the application of the continuum beliefs intervention. Furthermore, future studies may also develop individualized continuum beliefs intervention programs to improve the intervention effect.

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    Monism and pluralism in morality: Origins, connotations and debates
    ZHANG Haotian, YU Feng, XU Liying, XUAN Zheli
    2023, 31 (2):  301-314.  doi: 10.3724/SP.J.1042.2023.00301
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    The distinction between moral monism and moral pluralism has been reflected in the early vision of moral philosophy. Moral pluralism can be traced back to moral relativism, which holds that there is no universal moral principle. And any moral value applies only within certain cultural boundaries and individual value systems. However, moral universalism, a monistic ethical position, holds that there are universal ethics that apply to all people. In recent years, the above theoretical confrontations have entered the field of moral psychology. The dispute between monism and pluralism is one of the most active theoretical controversies in the field of moral psychology in recent years. Moral monism holds that all external moral-related phenomena and internal moral structures can be explained by one factor. The representative theories are stages theory of moral development and dyadic morality theory and so on. On the other hand, moral pluralism holds that morality cannot be explained by a single factor, but there are many heterogeneous moral dimensions, which are culturally sensitive. The representative theories include the triadic moral discourse theory, the relational model theory and the moral foundations theory and so on.

    Among them, the dyadic morality theory put forward by Kurt Gray et al. and the moral foundation theory put forward by Jonathon Haidt are the typical representatives of the disputes between monism and pluralism. Gray et al. argued that harm is the most powerful factor in explaining moral judgments and moral judgments about harm are more intuitive. Moreover, people with different political orientations reach a consensus that harm is the core of moral judgments. On the contrary, Haidt et al. believed that people of different political orientations, cultures and social classes is manifested with different moral foundations, and the moral foundations scale has good construct validity, discriminant validity, practical validity, etc. The disputes between the two theories mainly focus on the explanatory power of harm, the harmfulness of moral dumbfounding, modularity views and the problem of purity. Specifically, Gray et al. argued that moral dumbfounding stems from biased sampling that confounds content with weirdness and severity, rather than purity violation. They also believed that the so-called "harmless wrongs" can be explained by perceived harm. Importantly, purity cannot be regarded as an independent construct of morality. Moreover, there is few evidence to support the modular claims. Nevertheless, Haidt et al. believed that moral monism oversimplifies the connotations of morality. The different moral foundations are not " Fodorian modularity", but more flexible and overlapping "massive modularity". Furthermore, plenty of evidence supported purity as an independent moral foundation.

    Future research should be carried out in the following aspects. First of all, morality must need a clearer definition. To ensure the validity of moral research, future research should try to define moral concepts more clearly and should ensure that only one construct is tested at a time. Without ensuring that the situation clearly reflects a certain moral dimension, it is difficult for researchers to pinpoint which moral dimension influences people’s moral judgments. Secondly, in addition to paying attention to the disputes between monism and pluralism, we also need to separate from the disputes, take an objective view of the different characteristics of the controversies, learn from each other and complement each other, so as to promote the development of moral psychology. Specifically, moral monism emphasizes the simplicity of moral constructs and the accuracy of measurement, while pluralism emphasizes the understanding of the nature of morality among people in different cultures. These are two different theoretical constructs and explanations of the nature of morality. Future research should combine the advantages of moral monism and moral pluralism, and try to adopt realistic situations with high ecological validity, so as to construct a more perfect integrated theoretical model. Last but not the least, most previous empirical studies have been dominated by the "WEIRD (Western, Educated, Industrialized, Rich and Democratic)” sample. Future research should urgently consider the possibility of carrying out morality research indifferent cultures, especially based on the Chinese culture to explore the nature of morality.

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