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Analyses of Mediating Effects: The Development of Methods and Models WEN Zhonglin;YE Baojuan Advances in Psychological Science    2014, 22 (5): 731-745.   DOI: 10.3724/SP.J.1042.2014.00731 Abstract （3403）            Knowledge map    Mediation models are frequently used in the research of psychology and other social science disciplines. Mediation indicates that the effect of an independent variable on a dependent variable is transmitted through a third variable, which is called mediator. In most applied research, Baron and Kenny’s (1986) causal steps approach has been used to test mediating effect. In recent years, however, many methodological researchers questioned the rationality of the causal steps approach, and some of them even attempted to stop its use. Firstly, we clarify the queries on the causal steps approach one by one. Secondly, we propose a new procedure to analyze mediating effects. The new procedure is better than any single method that constitutes the procedure in terms of Type I error rate and power. The proposed procedure can be conducted by using observed variables and/or latent variables. Mplus programs are supplied for the procedure with observed variables and/or latent variables. Finally, this article introduces the development of mediation models, such as mediation model of ordinal variables, multilevel mediation, multiple mediation, moderated mediation, and mediated moderation. Related Articles | Metrics

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Statistical Remedies for Common Method Biases Zhou Hao,Long Lirong null    2004, 12 (06): 942-942~950.   Abstract （6986）            Knowledge map    The problem of common method biases has being given more and more attention in the field of psychology, but there is little research about it in China, and the effects of common method bias are not well controlled. Generally, there are two ways of controlling common method biases, procedural remedies and statistical remedies. In this paper, statistical remedies for common method biases are provided, such as factor analysis, partial correlation, latent method factor, structural equation model, and their advantages and disadvantages are analyzed separately. Finally, suggestions of how to choose these remedies are given. Related Articles | Metrics

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Network analysis and its applications in psychology CAI Yuqing, DONG Shuyang, YUAN Shuai, HU Chuan-Peng Advances in Psychological Science    2020, 28 (1): 178-190.   DOI: 10.3724/SP.J.1042.2020.00178 Abstract （1370）            Knowledge map    Network analysis models (or Network Psychometrics) have been widely used in psychology research in recent years. Unlike latent variable models which conceive observable variables as outcomes of unobservable latent factors, network analysis models apply the graph theory to construct a network to depict the associations among observable variables. The observable variables are treated as nodes and the associations between them are treated as edges. As such, network analysis models reveal the relationships among observable variables and the dynamic system resulted from the interactions between these observable variables. With indices reflecting individual nodes’ characteristics (such as centrality) and network structural characteristics (such as small-worldness), network analysis models provide a new perspective for visualization and for studying various psychological phenomena. In the past decade, network analysis models have been applied in the fields of personality, social, and clinical psychology as well as psychiatry. Future research should continue to develop and improve the methods of network analysis models, making them applicable to more types of data and broader research fields. Related Articles | Metrics

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The duality of attachment pattern: Trait attachment and state attachment JIA Chenglong, LIU Tingting, SUN Li, QIN Jinliang Advances in Psychological Science    2020, 28 (4): 626-637.   DOI: 10.3724/SP.J.1042.2020.00626 Abstract （1030）            Knowledge map    Traditional attachment theory suggests that an individual’s attachment-related psychological and behavioral patterns are relatively stable. However, from information processes or life-span development perspective, attachment patterns have trait-state duality, i.e. attachment patterns are both relatively stable and context-sensitive. An individual’s attachment pattern in a particular context is the consequence of his or her trait attachment and contextual feature interactions. The interaction patterns between trait attachment and attachment priming effects provide a window to understand the duality of attachment and their relationships. And the two-stages model of attachment activation offers a framework for integrating and understanding these patterns. Future studies should optimize the manipulation check of attachment priming, meanwhile, take the interaction between attachment avoidance and attachment anxiety in consideration. More attention should be paid to the individual differences in the high attachment anxiety group which may clarify the patterns of interaction between trait and state attachment. Moreover, the time course of how attachment coping strategies impact the effects of attachment priming should be concerned, which could reveal the mechanism of the interactions between trait and state attachment. Related Articles | Metrics

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Item Parceling Strategies in Structural Equation Modeling WU Yan;WEN Zhong-Lin null    2011, 19 (12): 1859-1867.   Abstract （2293）            Knowledge map    Item parceling is a technique using in structural equation modeling (SEM). Parceling can improve the quality of indicators and model fit. Bias that due to parceling was often neglectable and can be corrected. Parceling greatly enhances model parsimony, but it greatly reduces falsifiability of the tested model. It could be summarized that the prerequisites of parceling are unidimension and homogeneity, and the applicability of parceling is the analysis of structural models, rather than measurement models. Parcel-building algorithms and the number of parcels were discussed and recommended. A procedure for item parceling was proposed when the scale was unidimensional. If the scale was multidimensional, internal-consistency approach was recommended such that the items of the same dimension are parceled to one or three indicators for structural equation modeling. Related Articles | Metrics

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Affective Events Theory: Contents, Application and Future Directions DUAN Jin-Yun;FU Qiang;TIAN Xiao-Ming;KONG Yu null    2011, 19 (4): 599-607.   Abstract （3016）            Knowledge map    Research on affect in organization has begun to accumulate recently, while affective events theory (AET) proposes an integral framework for this field study. AET proposes that specific work events have impact on the arousal of affective reactions which, in turn, determine employees’ attitudes and behaviors. AET makes a clear separation of affective reactions and job satisfaction, as well as affect-driven behaviors and judgment-driven behaviors. Generally, AET is helpful to explain the importance of affect in the workplace. However, future studies should consider the team affect and its measurements. Lastly, more researches are needed for further validation and consummation for various persons under different cultures. Related Articles | Metrics

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Nudging goal attainment: The motivating effects of temporal landmarks ZHAO Xiaoying, LI Aimei, WANG Haixia Advances in Psychological Science    2019, 27 (7): 1275-1293.   DOI: 10.3724/SP.J.1042.2019.01275 Abstract （709）            Knowledge map    Temporal landmarks defined as any distinct event that stands out in the everyday humdrum of life, may be beneficial to goal-pursuit motivation. Specifically, when individual experience a current temporal landmark or expects a future temporal landmark, their levels of goal-pursuit motivation would be enhanced, and at the same time, their goal-related behaviors would be more likely to occur. In addition, temporal landmarks may increase individuals’ senses of psychological separation of temporal selves and then enhance goal-pursuit motivation through a series of mental processes such as increased self-efficacy, cognitive consistency, loss aversion and discrepancy-reduction. Future research should focus on examining the motivating effects and duration of temporal landmarks and its generalizability. Moreover, it is worth for future studies to investigate the potential mechanisms of temporal landmarks and to conduct a considerable amount of empirical studies to nudge decision making by manipulating temporal landmarks. Related Articles | Metrics

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A Meta-Analytic Review On The Correlation Of Children’s Aggression And Self Perceived Competencies Guo Boliang，Chang Lei null    2003, 11 (05): 529-533.   Abstract （1494）            Knowledge map    Meta-analysis based on multilevel modeling was used to review the latest 20 years of studies on the correlation between children’s aggression and self perceived competencies, the results showed significantly negative but lower level correlation between child aggression and general self worth and self perceived cognitive competency. No significant relationship was found between aggression and self perceived social competency, only 3 studies reported the correlation coefficient between aggression and self perceived physical competency, 2 negative and 1 positive. More studies in this area are needed to generalize the relationship between child aggression and self-perceived competencies and to study its correlates Related Articles | Metrics

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Motivated Information Processing Model: Theory and Applications WU Meng;BAI Xin-Wen Advances in Psychological Science    2012, 20 (11): 1889-1898.   DOI: 10.3724/SP.J.1042.2012.01889 Abstract （1924）            Knowledge map    Based on “groups as information processor perspective”, motivated information processing (MIP) model emphasizes that information processing and sharing depends on two types of motivations, epistemic motivation and social motivation, respectively. Epistemic motivation refers to the willingness to expend effort to achieve a thorough, rich, and accurate understanding of the world. It determines the depth of information processing. Social motivation is defined as the individual preference for outcome distributions between oneself and others. It influences which information will be processed. Epistemic motivation and social motivation, alone and in combination, interpret information processing at both individual and team level, and information sharing at team level. MIP model contributes to the industrial/organizational psychology literature by integrating the dual-process theory and groups as information processor perspective, and by providing a new perspective in the fields of negotiation, creativity, and team effectiveness. Limitations and implications for future study of MIP model are discussed. Related Articles | Metrics

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Task-switching training and plasticity of executive function Ziyu WANG, Ziye KONG, Rongjuan ZHU, Xuqun YOU Advances in Psychological Science    2019, 27 (10): 1667-1676.   DOI: 10.3724/SP.J.1042.2019.01667 Abstract （1514）            Knowledge map    The task-switching training is one of the approaches used to improve executive functions. Different paradigms are used to study the effects of training. While, few studies have investigated that the task-switching training could reduce switch cost and improve the performance of other cognitive tasks. On the other hand, the effects could be maintained for a certain period of time. However, some studies did not find significant transfer effect. Therefore, training efficiency is also affected by age, participation’s other executive function components, cognitive flexibility, and strategy. Moreover, task-switching training may improve the ability of set-shifting through three ways: improve the ability to resolve task-setting conflicts, increase the participation of the frontal-parietal network, and establish bottom-up automatic control. Future research should standardize the existing research methods and procedures, consider the task switching training from the unity and diverse perspective. Research also needs to look for more flexible training methods, such as tDCS. Related Articles | Metrics

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Intensive longitudinal data analysis: Models and application ZHENG Shufang, ZHANG Lijin, QIAO Xinyu, PAN Junhao Advances in Psychological Science    2021, 29 (11): 1948-1969.   DOI: 10.3724/SP.J.1042.2021.01948 Abstract （359）            Knowledge map    In the fields of psychology, education, and clinical science, researchers have devoted increasing attention to the intraindividual dynamics of behaviors, minds, and treatment effects over time, making personalized modeling a growing concern. Traditional cross-sectional and longitudinal studies only have a few measurement time points for each individual, which is not suitable for studying intraindividual dynamics. Intensive longitudinal design collects a set of measures from individuals at multiple time points with higher frequency over longer periods. With its strengths in more immediate, accurate, and authentic assessments, this design is more suitable to investigate the dynamics and mechanisms of intraindividual processes. With the development of mobile phones and other mobile devices, researchers can conveniently collect intensive longitudinal data for various aspects of psychology, including individual emotion, personality, cognition, and behavior patterns. The intensive longitudinal design has recently become one of the most prominent and promising approaches in psychological research, but most of these studies still relied on traditional analyzing methods. We first reviewed a conventional method of intensive longitudinal data analysis, the multilevel linear model (MLM), and discussed its limitations in analyzing intensive longitudinal data. We then introduced the principles, empirical applications, strengths, and weaknesses of two advanced modeling methods, dynamic structural equation model (DSEM) and group iterative multiple model estimation (GIMME). DSEM is a top-down approach of modeling intensive longitudinal data while GIMME is a bottom-up one, both being implemented in commonly used software. DSEM is one of the most promising methods for intensive longitudinal modeling and can be regarded as a multilevel extension of the dynamic factor model (DFM). It combines the strengths of various modeling approaches, including multilevel modeling, time-series modeling, structural equational model (SEM), and time-varying effects modeling (TVEM). GIMME is a dynamic network method initially proposed for functional magnetic resonance imaging (fMRI) data analysis and has recently been applied to intensive longitudinal data analysis. It combines individual- and group-level information to estimate network models at both levels, bridging nomothetic (population) and idiographic (individual) approaches to intensive longitudinal data analysis. By introducing these two advanced modeling methods, the current review can help deepen the understanding of the top-down approach and bottom-up approach and clarify their strengths and weaknesses in the intensive longitudinal data analysis. To help empirical researchers better understand the modeling of DSEM and GIMME and show the advantages of the two models compared with MLM, we provided a tutorial on how to analyze the intensive longitudinal data with the three models (i.e., MLM, DSEM, and GIMME), respectively. We presented the analyzing processes step by step and explained how to interpret the results of these models accordingly. By comparing the output results of the three models, the current review summarized the characteristics of each model. The corresponding Mplus and R codes were provided in the appendixes. Along with the three modeling methods mainly introduced in the current review, we also provided a general introduction of other common modeling methods in the intensive longitudinal data analysis. The current review summarized the popular models in the intensive longitudinal data analysis on their strengths and weaknesses and guided researchers to select suitable modeling methods in different situations. The current review contributes to the development and application of the advanced methods of intensive longitudinal data analysis and helps researchers better understand the dynamic process behind the intensive longitudinal data. Related Articles | Metrics

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Embodiment in Moral Judgment YE Hongyan; ZHANG Fenghua Advances in Psychological Science    2015, 23 (8): 1480-1488.   DOI: 10.3724/SP.J.1042.2015.01480 Abstract （1079）            Knowledge map    Moral judgment is a kind of evaluation and judgment about certain types of behaviors which individuals make to distinguish good from evil and right from wrong. With the rise of embodied cognition theory, the studies of embodiment in moral judgment are subsequently carried out. Researchers on embodiment in moral judgment mainly focus on three aspects, namely physical cleanliness and disgust, physical temperature and body movement. Researchers explain embodied effect in moral judgment from the perspective of Psychological Development proposed by Piaget and Vygotsky respectively, Conceptual Metaphor Theory and Evolutionary Psychology. Considering the fact that physical variables can influence moral judgment through emotion and cognition, future research should integrate embodied approach of moral judgment with existed theories of moral judgment. And researchers should make clear of the relationship between embodiment in moral judgment and moral intuition. Future research should further explore the timeliness and dynamic, discuss the relevant moderator variables and individual differences, and make cross-cultural comparisons under the perspective of embodied effect. Related Articles | Metrics

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How meteorological factors affect consumer behavior? The mechanism of meteo-marketing based on contextual marketing theory LI Chenxi, YAO Tang Advances in Psychological Science    2019, 27 (2): 191-200.   DOI: 10.3724/SP.J.1042.2019.00191 Abstract （2096）            Knowledge map    There is a growing body of literature investigating the significant impacts of meteorological factors on human behavior, ranging from individual emotion swings to the prosperity and decline of social economics. Based on contextual marketing theory, this study proposes the concept of meteo-marketing, which is particularly applicable for the era of big data. By identifying the meteorological factors that affect consumer’s psychology and behavior in the dynamic weather environment, this study proposes the influential mechanisms of the “meteorological factors-consumer psychology-consumption behavior” logical chain for further verification. The research mainly focuses on the three issues, i.e., the meteorological factors in contextual marketing, the impact of meteorological factors on consumer’s psychology and behavior and the interaction effect of meteorological factors and marketing strategies. Relevant research findings are expected to further extend and enrich the existing contextual marketing theory, and serve as a useful supplement to the discipline of environmental consumer psychology. Related Articles | Metrics

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Understanding mechanisms of prediction error cost in Chinese reading for older adults LI Lin, ZHAO Sainan, ZHANG Lijuan, WANG Jingxin Advances in Psychological Science    2022, 30 (1): 1-14.   DOI: 10.3724/SP.J.1042.2022.00001 Abstract （389）            Knowledge map    An important question for research on reading across the lifespan concerns whether mechanisms of cognitive processing undergo only quantitative changes or also qualitative changes with aging. To process written language effectively, readers use their existing knowledge to make predictive inferences about linguistic information. Quite often this will facilitate the processing of newly acquired information but will sometimes incur a processing cost due to predictive error. As Older adults appear to rely more heavily on lexical prediction during reading (Zhao et al., 2019, 2021). However, it is currently unknown whether, like young adults, they experience a processing cost due to predictive error, and whether the magnitude of this cost differs across age adult groups. Accordingly, the present research aims to understand the processing consequence of predictive error in both young and older adults, using methods that can shed light on both the behavioral and neural bases of these effects. This will be achieved using novel co-registration methods that synchronize the recording of electroencephalographic (EEG) signals with eye movements, so that behavioral and neural indices of language processing can be acquired simultaneously, in real-time, during natural reading. In particular, this approach will enable the analysis of fixated-related potentials (FRPs), which are averaged EEG waveforms time-locked to a fixation on a target word in a sentence during normal reading. Study 1 will manipulate whether a target word is predictable from the prior sentence context, using contexts in which the target word is predictable, ones in which it is unpredictable, and neutral contexts containing an unpredictable word. Crucially, comparisons of an unpredictable word in neutral compared to constraining contexts will provide a measure of prediction error, which is the cost incurred when the target word is unpredicted in a constraining context. The study will investigate the behavioral and neural correlates of this prediction error using a combination of eye movement measures and FRPs for target words. Moreover, by investigating age differences in these effects (i.e., for young compared to older adults) the study will reveal whether this prediction error differs across adult age groups. Study 2 will test these effects further by examining both the contribution to the prediction error cost of parafoveal information availability and individual differences in visual, cognitive and linguistic abilities. To examine the contribution of these individual differences, we will comprehensively assess the visual, cognitive and linguistic abilities of young and older adult participants prior their taking part in experiments. We will obtain information about participants' educational background, vocabulary knowledge and recent reading experience to match participants in terms of formal educational experience and to obtain indices of linguistic experience. In addition, we will assess processing speed, working memory, and inhibition as measures of cognitive capabilities. The data obtained will be used for the linear mixed-effects modelling of Study 3. Experiment 1 will use the boundary paradigm to investigate age differences in the prediction error cost when parafoveal information is available or not. The aim of this experiment is to establish whether limiting the availability of parafoveal information about an upcoming word differentially impacts lexical prediction by young and older adults. Experiment 2 will use masking text paradigm to investigate the aging effects on prediction error cost under high or low working memory load conditions. The aim of this experiment is to explore the effect of working memory load on prediction processing mechanism of young and older readers. Finally, in Experiment 3, the older adult participants will be divided into good and poor reading skill groups to examine whether there is a difference in the prediction error cost for older participants with good and poor reading skills as compared to skilled young adult readers. This will reveal how reading skills mediates predictive processing by older adults. Study 3 will use linear mixed-effects modelling and data-mining methods. All relevant factors will be included in the model analysis as covariates to investigate their effects on the prediction processing of older readers. Moreover, survival analysis and distribution analysis will be adopted to investigate the time course and individual differences of the above-mentioned effects (using data from Study 1 and 2). The findings from these studies will provide important insights into the nature of effects of cognitive aging and individual differences in visual, cognitive and linguistic abilities on neural and cognitive indices of word prediction in reading, and will form the basis for future models of these effects in Chinese reading. Moreover, the findings will shed light on the contribution of parafoveal processing, memory load, and reading skill on the predictive abilities of older adult readers. 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Common Method Variance Effects and the Models of Statistical Approaches for Controlling It XIONG Hong-Xing;ZHANG Jing;YE Bao-Juan;ZHENG Xue;SUN Pei-Zhen null    2012, 20 (5): 757-769.   Abstract （1372）            Knowledge map    Common Method Variance (CMV) refers to the overlap in variance between two variables because of the type of measurement instrument used rather than representing a true relationship between the underlying constructs. Researchers should give careful consideration to CMV although it may not surely bias the conclusions about the relationships between measures. CMV effect is often created by using the same method — especially a survey — to measure each variable. Procedural design and statistical control solutions are provided to minimize its likelihood in studies. A statistical control technique is a good solution if it can separate construct varience, method varience and error, and distinguish method bias at the item level from method bias at the construct level, and takes account of Method×Trait interactions. Thus, method-factor approaches are better than partial correlation approaches. It’s very important to understand the model of every method-factor approache for selecting statistical remedies correctly for different types of research settings. Etimating evaluate the effect of CMV within specific research domains and the effect of CMV on empirical findings within a theoretical domain should be concerned for further research. Related Articles | Metrics

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Resilience: The Psychological Mechanism for Recovery and Growth during Stress Yu Xiaonan,Zhang Jianxin null    2005, 13 (05): 658-665.   Abstract （2907）            Knowledge map    Resilience refers to the effective coping and adaptation although faced with loss, hardship, or adversity. This biological imperative for self-protection will be exhibited when people are faced with stress, threats, or life changes. Coping resources or protective factors on personal, family, and social aspects interact with each other into a dynamic system in order to resist the effect of adversity. The process model argues that resilience refers to the higher homeostasis than original level, and it is different from recovery. The hierarchy of resilience demonstrates its adaptive nature on different developmental stages, and the meaning of resilience varies according to the specific situations. Although there is no consensus on the measurement of resilience, some scales have been employed widely for their convenience and efficiency. The aim of resilience research is to examine strength and promote adaptation of people, and resilience interventions conducted by schools, clinical institutions, communities, and enterprises have been proven good effects. Related Articles | Metrics

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A Review of the Research on Moral Psychological Licensing SHI Wei null    2011, 19 (8): 1233-1241.   Abstract （1038）            Knowledge map    Moral psychological license may be defined as people’s perception that they are permitted to take an action or express a thought without fear of discrediting themselves. We present evidence that good behavior in one domain can license otherwise-discrediting behavior in the same domain or an unrelated domain. Observers are sometimes willing to extend license to actors on the basis of the actors’ behavioral history. The potential mechanisms behind licensing are moral credits and moral credentials which can be viewed as two independent routes. When one acts in domains that are relatively unimportant to one’s identity or can avoid appearing hypocritical, one’s behavioral history will liberate rather than constrain future behaviors. We also discuss remaining questions in the literature and propose avenues for future research, the questions including the relationship between self-licensing and person-licensing, verification fundamental assumptions of moral credits and moral credentials models, the desirable consequences of moral licensing. Related Articles | Metrics

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A Review on the Integrative Cognitive Model of Trait Anger and Reactive Aggression YANG Li-Zhu;DU Wen-Xuan;SHEN Yue null    2011, 19 (9): 1249-1258.   Abstract （1184）            Knowledge map    The integrative cognitive model (ICM) is an integration of several related theories, which explore the effect of individual differences in internal cognitive processes on a person’s level of trait anger from hostile situation inputs to reactive aggression. With considering the element of personality trait, it builds up a relational model among the three internal core cognitive processes, which are hostile interpretation, ruminative attention and effortful control. This model, with features of a clear and obvious structure and being easily controlled, enlightens integrative empirical researches of this area and opens a new path to reactive aggression theory exploration, and it also has great value of application. This theory still lacks further studies which multiple processing mechanisms of the ICM are assessed among the same set of participants, and some relevant neurophysiology studies and mental intervention exploration, which will be important topics for the future research. Related Articles | Metrics

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Underpinnings of Social Status Hierarchies YANG Shuai;HUANG Xiting;WANG Tong Advances in Psychological Science    2014, 22 (2): 250-258.   DOI: 10.3724/SP.J.1042.2014.00250 Abstract （484）            Knowledge map    Social status hierarchy is one of the basic principles in human society. N200 was found to be activated in the recognition of social status hierarchies, face recognition and visual attention. The recognition of social status hierarchies also at different levels involved brain regions of emotional expressions (e.g. prefrontal cortex, PFC), social and monetary rewards (e.g. striatum), empathy traits (e.g. anterior cingutate cortex, ACC), and numerical magnitude (e.g. bilateral intraparietal sulci, IPS). Social status hierarchy was founded dynamic by nature, and complicatedly interacted with genetic and environmental factors, such as serotonin neurotransmitter polymorphism (5-HTTLPR), glucocorticoid (GC), basal testosterone (T) and other factors of neuroendocrine system. These issues constituted the main focus points, and it would be an important approach to explore social status hierarchies by means of comprehensive research and system analysis in future. Related Articles | Metrics

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Basic psychological need and its satisfaction Cai-Zhi WU, Shuo RONG, Fang-Ting ZHU, Yan CHEN, Yong-Yu GUO Advances in Psychological Science    2018, 26 (6): 1063-1073.   DOI: 10.3724/SP.J.1042.2018.01063 Abstract （2918）            Knowledge map    Deci and Ryan proposed the concept of basic psychological needs based on previous studies and conceptualized basic psychological needs for autonomy, competence, and relatedness. Basic psychological needs originated from the Self-Determination Theory. Currently, measurement of basic psychological needs mainly employs the General Need Satisfaction Scale compiled by Gagné. The satisfaction of basic psychological needs is mainly affected by the surrounding environment, and closely related to the mental health of the individual; the thwarting of basic psychological needs will lead to anxiety and depression. The challenges of basic psychological needs are mainly focused on four aspects: the content of needs, the contradiction between needs, the stability of needs, and the universality of needs. Future research on basic psychological needs should focus on developing the measurement, carrying out in-depth studies on need thwarting, enhancing longitudinal studies, and conducting research on the strategies of meeting basic psychological needs. Related Articles | Metrics