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The Influence of Proximity and Spatial Configuration on the Similarity Effect in Visual Working Memory 2021, (2): 258-265.  Abstract ( )   PDF   Visual working memory (VWM) performance can benefit from the Gestalt principles of similarity and proximity in the change-detection task. A fundamental issue in this field is how similarity together with proximity influences the VWM representations. One view postulated that the positive effect of similarity on VWM performance was constrained by proximity, such that similarity was effective only when the similar items were near each other in an ordered spatial configuration of memorized items. The other assumed that such effect of similarity could occur regardless of proximity of similar items in a random spatial configuration of memorized items. However, the order of spatial configuration, as a basic organization rule, was not controlled in previous studies of the effect of similarity and proximity in VWM. Such similarity effect might be influenced by the order of spatial configuration for memorized items. Therefore, a crucial test of such fundamental issue is how proximity and the order of spatial configuration influence the similarity effect. We examined how proximity influenced the similarity effect in VWM with the orderliness of spatial configuration of memorized items using a change detection task. Proximity of similar items was manipulated by the distance and the inserted other item between similar items. The proximal condition was the decreased distance between similar items without inserting other item. The non-proximity conditions were the decreased distance between similar items with inserting other item, as well as the increased distance between similar items with or without inserting other item. Furthermore, the present study employed ordered and random spatial configurations of memorized items in experiments 1 and 2, respectively. In Experiment 1, it investigated whether proximity influenced the similarity effect when spatial configuration was in order. Participants were asked to remember 6 colored circles that were located on an imaginary circle (i.e., ordered spatial configuration). In Experiment 2, it aimed to investigate whether proximity influenced the similarity effect when spatial configuration was random. Participants were required to remember 6 colored circles that were presented at random locations around the center of the screen (i.e., random spatial configuration). The hypotheses were that the increased distance and the inserted other item between similar items could impair the similarity effect when spatial configuration of memorized items was in order, and that such proximity could not influence the similarity effect when spatial configuration was random, given the salient cue of similarity in the random spatial configuration. The results showed that the accuracies of similar items were higher than those of dissimilar items in both ordered and random spatial configurations, regardless of proximity of similar items. Furthermore, inserting other item between similar items attenuated the similarity effect when the similar items were far from each other for the ordered spatial configuration, but not for the random spatial configuration. These results suggested that similarity could facilitate VWM performance regardless of the order of spatial configuration for memorized items. Such similarity effect on VWM performance was constrained by proximity only when the spatial configuration of memorized items was in order. Related Articles | Metrics

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The Role of Machine Learning in Solving Overfitting 2021, (2): 274-281.  Abstract ( )   PDF   Overfitting is the production of an analysis that corresponds too closely or exactly to a particular set of data, and may therefore fail to fit additional data or predict future observations reliably. There are modal overfitting and procedure overfitting in current psychology. An overfitted model is a statistical model that contains more parameters than can be justified by the data. The essence of overfitting is to have unknowingly extracted some of the residual variances (i.e. the noise) as if that variances represented underlying model structure. One of the ways to avoid overfitting is machine learning. Machine learning (ML) is the scientific study of algorithms and statistical models that computer systems use to effectively perform a specific task without using explicit instructions, relying on patterns and inference instead. Machine learning algorithms are used in email filtering, detection of network intruders, and computer vision. Here, we summarized the values and ways of machine learning in prediction. First of all, we describe the current state of psychology that explanation without prediction by introducing modal overfitting and procedural overfitting. In modal overfitting, if the researcher only pursues the high degree of goodness of fit of the model, it will lead to a decrease of prediction of the model in other samples. The practice of flexibly selecting analytical procedures based in part on the quality of the results they produce has come to be known as p-hacking or data-contingent analysis. This is mainly because the bias (not variance) of sample is incorrectly fitted to it. Secondly, we show the essential reason of overfitting: the viewpoint of ‘A model could interpret well does not mean that it could reliably predict human behavior’. Although explanation and prediction are relatively close in philosophy, they differ greatly from a statistical and practical point of view. From a statistical point of view, goodness of fit is an important indicator to measure how well the model fits the data generation process. The higher the goodness of fit of the model, the more variances can be explained, the closer it is to the real process of data generation. However, the variances contain meaningful variances caused by independent variables and meaningless variances caused by sampling. Theoretically, only meaningful variance needs to fit, but the existing tools cannot distinguish between each other in practice. This limitation directly leads to overfitting. Overfitting models have a high degree of explanation for sample data, but the prediction is poor in other samples. From a practical point of view, it is difficult to construct a model with good interpretation and prediction at the same time in reality. Thirdly, the logic of modeling and key technologies of machine learning were introduced. The two principles are: 1) Decomposing errors into bias and variances, we just fit variances to avoid the phenomenon of high variance of modeling; 2) Trading off biases and variances to minimize prediction errors. The three core technologies are cross-validation, regularization and big data. All of them guarantee the prediction of the model rather than explanation. At last, we use sample data and MATLAB code to illustrate the specific application process of machine learning in model fitting. We believe that psychology researchers should try to solving practical problems, using the method(s) of machine learning and building more accurate and robust prediction models. Related Articles | Metrics

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Interaction Between Semantic Priming and Stimulus Quality in Chinese Words of Single Character Yi-Xuan GUO Alisa 2021, (2): 282-289.  Abstract ( )   PDF   Previously, controversies are observed over the research approach for specifically stimulus quality interacted with?semantic priming during lexical decision tasks (LDTs), and generally between the Interactive Activation (IA) model and the Multistage Activation (MA) model. Both models involve three?stages of processing: feature, letter and word stages. According to the IA model, the processing in each stage feeds activation forward to other stages as soon as activation begins in the original stage (processing is cascaded),?accompanied with?feedback between adjacent stages. The cascaded activation?across representational stages can produce statistic interactions between?stimulus quality and semantic priming?even when?the?relatedness proportion (The?proportion of semantically related primes to targets)is low(0.25). Compared with forgoing IA model, each stage in MA model will not be activated, before the activation in the prior stage reaches?a?threshold or the prior processing stops. This model predicts interactions?as a result of a strategic?retrospective prime retrieval that influences early visual processing?only when the?relatedness proportion?is high. Given that semantic access of a visual word in Chinese system involves less phonological mediation, stimulus quality may possess greater impact on semantic processing via the cascade processing in Chinese than that in English. Thus, two experiments were performed to test the interactions between stimulus quality and semantic priming in different relatedness proportion during lexical decision tasks. Namely, they were to test if the interactions between stimulus quality and semantic priming occur regardless of relatedness proportion (i.e., 0.5 vs. 0.25). The experiments employed a 2 (semantic priming: related vs. unrelated) × 2 (stimulus quality: blurredness of level 5 vs. blurredness of level 6) design which comprised 4 treatment conditions. Four stimulus lists were created so that each condition has equal chance when every prime and every target character appeared by rotating the lists across?the student participants. The target characters were blurred with 66% and 51% proportion of image pixels masked for the levels 5 and 6, respectively. In Experiment 1, there were 35 real character trials in each condition, with an equal number of 140 pseudo-character trials. Experiment 2 shares the design solution with Experiment 1 only taking the exception of addition of extra (140?uncorrelated pairs of prime and characters) and (140?pairs of irrelevant characters and pseudo-characters) to the stimulus list with reduction of relatedness proportion?from 0.5 to 0.25. Overall, all experiments showed that the responses to both corresponding targets and slightly blurred targets initiated more quickly and accurately than those irrelevant and highly blurred?targets behaved. More importantly, as expected from the cascaded processing in the IA model, the experiments together indicate the interactions between stimulus quality and semantic priming on response times (RTs) rather than response accuracy regardless of the relatedness proportion. However, in contrast to previous studies, the designed experiments exhibited greater?priming effects on RTs for slightly blurred?stimuli?than?that of highly blurred?stimuli. Nonetheless, these discrepancies would not undermine the conclusion that the interactions, between?stimulus quality and semantic priming on RTs in Chinese reading, should consistently take place as well when the relatedness proportion?was very low. The interactions in Experiment 2 are not met the MA model prediction while the?strategic retrospective prime retrieval was invalidated in?low relatedness proportions. Meanwhile, these results suggest that the 0.5 ratio would not alter the amount of interactions between stimulus quality and semantic priming compared to the 0.25 one, and the relatedness proportion should not affect the interactions between stimulus quality and semantic priming in Chinese words processing. In conclusion, the results could be interpreted in terms of cascaded processing in the IA model but not applicable in the MA model. Related Articles | Metrics

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More Load, More Difficult in Shifting —— Evidence from a Digital Alternate Comparison Task 2021, (2): 290-295.  Abstract ( )   PDF   Working memory (WM) and cognitive flexibility are the two major components of executive function. Does working memory affect task shifting? This issue is still controversial. Some researchers had found that the switching cost was not affected by working memory, so working memory was not associated with cognitive flexibility. However, other researches had shown that working memory was closely related to task shifting and resource constraint of working memory was one of the main sources of switching cost. So far, most studies on the relationship between working memory and task switching have adopted the dual-task paradigm. The main reason of the contradictory results was that different investigators manipulated different components of working memory in the experiment. If the researchers increased the load on the central executive component of working memory in the experiment, it would have a significant impact on task switching.?On?the?contrary,?task?switching?cost?in?the?experiment would not be affected by working memory load when other components of WM are manipulated. To further test this hypothesis, a Digital Updating Task (DUT) was adapted into a Digital Alternate Comparison Task (DACT). The goal of the present study is to address the interaction between working memory and task shifting by using Digital Alternate Comparison Task (DACT). Fifty-six college students aged 18-24 were tested through the DACT. The task was divided into high working memory load and low working memory load. In the study phase, participants were presented with two or three initial items, one for each figure (hexagon, square or circle). Participants were instructed to memorize the number for each shape. Then, they would be displayed with a series of new items. For each new item participants had to compare the number for the same shape with initial item. Through the regulation of working memory load, observing the changing of switching cost under different working memory load level. According to previous researches on the correlation between working memory and task shifting. We hypothesized that the reaction time was longer under the switching condition and switching cost increased with the working memory load. The results showed that reaction time under switching condition was significantly higher than that under non-switching condition. The accuracy under switching condition was significantly lower than that under non-switching condition. This indicated that there was more significant accuracy and reaction time deficits under the switching condition. What's more, the reaction time in switching condition under high working memory load was significantly longer than that under low working memory load. The accuracy under high working memory load was significantly lower than that under low working memory load. And the switching cost under high working memory load was also significantly higher than that under low working memory load. This indicated that the switching cost increased along with working memory load. We discussed and analyzed the experimental?results?with?the?limited?theory?of?attention?resources?in?details. These?findings?suggested?that?switching?cost?existed?in?DACT.?The?bigger?the?working?memory load,?the?larger?the?shifting?cost?is.?That?is,?these?findings?further?confirmed?the?close?relationship between?working?memory?and?cognitive?flexibility. Related Articles | Metrics

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Analysis of the Specific Index of FN400 and LPC to Familiarity and Recollection Ming-Yang YU 2021, (2): 302-308.  Abstract ( )   PDF   Two cognitive processes contribute to memory recognition, namely recollection and familiarity. The Dual process theory supposed that recognition can be decomposed into two distinct processes that reflect the separate mnemonic mechanisms of familiarity and recollection. Previous electrophysiology researches commonly believed FN400 and LPC index to familiarity and recollection, respectively. The FN400 is more negative for new than old stimuli over front-centrally, between 300-500 ms, which has been associated with familiarity. The LPC is a later positive old/new difference maximal over centroparietal channels between 500-800 ms post-stimulus, which has been associated with recollection. The FN400 similarly to the N400 in timing and response pattern, however, some studies have proven that there are functional differences between the FN400 and N400. In the previous researches, the measurement of familiarity was mainly done by a recognition test, which was a measurement of explicit memory, ignoring the influence of implicit memory on recognition. There was a great overlap between familiarity and conceptual priming in the experimental operation. Therefore, the FN400 may also be the result of the co-occurrence of conceptual priming and familiarity. Therefore, to eliminate the interference of conceptual priming on FN400, the researchers used meaningless materials to separate familiar processing. It should be noted, however, that some researchers have recently posited that FN400 is an index of the interaction of conceptual priming and familiarity, and the specific role of the two in the production of FN400, remains to be further explored. In addition to the intense discussion on the significance of FN400, some researchers also believe that the LPC is related to familiarity. It is generally believed that only recollection supports source information retrieval, but studies have proven that familiarity is also beneficial to remember source information, which indicates that recollection and familiarity processing may be included in source information retrieval at the same time, hence LPC may be a mixed indicator of both. However, the recent research provided new insight into the precise functional utility of the LPC and recollection, they successfully replicated existing within-participant modulations of the magnitude of the LPC with recollection during old/new recognition, Remember/Know/Guess and source memory task in two large samples of healthy young adults. Critically, however, they also suggested that variation in the magnitude of the LPC doesn’t index memory performance as expected. The limitations in prior ERP studies of recognition memory are driven by the restrictions in the recording setup. In another research, there was no LPC when investigating neural correlates of remembering in more naturalistic settings. This indicates that the specific index of FN400 and LPC still needs debate, and the influence of factors, other than familiarity and recollection, should be fully considered when using FN400 and LPC as evidence of the dual process theory. There are three questions to issue in the future. Firstly, it is necessary to further clarify the preconditions for conceptual priming and familiarity to influence FN400 or not. Second, we must clarify the index of LPC while improving ecological validity and controlling extraneous variables. Third, further explore the interaction between familiarity and recollection in the recognition process. Related Articles | Metrics

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Being Bullied on College Students' Aggressive Behaviors: The Mediating Effect of Relative Deprivation and the Moderating Effect of Violence Exposure in Daily Environment 2021, (2): 309-315.  Abstract ( )   PDF   Aggressive behaviors, has always been widely concerned by scholars because it could do harm to others and society. Previous studies have shown that aggressive behaviors, can have a series of serious effects on individuals, such as severely affecting their physical and mental health, personality development, academic progress and social interaction. Researches have shown that being bullied can lead to some feelings such anxiety, depression and other mental symptoms, as well as some aggressive behaviors. Research has found that being bullied can predict behavioral problems such as aggressive behaviors. Therefore, in order to build a harmonious and stable campus environment, the researchers should pay more attention to external behaviors such as aggressive behaviors. Being bullied individuals tend to have strong sense of inferiority, while long-term social comparison can increase the level of relative deprivation. However, relative deprivation is harmful to the individual body and mind, even can trigger many other external problem like aggressive behaviors. Based on Bandura social learning theory, violence exposure in daily environment has drawn lots of researchers attention recently. It is believed that violence exposure in daily environment may result in aggressive behaviors . The present study aimed to explore the moderated mediation among being bullied, relative deprivation, violence exposure in daily environment and aggressive behaviors. The study not only examined indirect relations between being bullied and college students’ aggressive behaviors intention via relative deprivation, but also examined the extent to which violence exposure in daily environment moderated the indirect relations between being bullied and college students’ aggressive behaviors. 941college students (455 boys and 486 girls, Mage=20.21±1.37) were recruited in the study to complete self-report questionnaires. The self-report questionnaires used in this study included being bullied scale, relative deprivation scale, violence exposure in daily environment scale, and aggressive behaviors scale. Being bullied was measured with the being bullied scale which consists of 14 items. The respondents rated the extent to which they agreed with each statement on a 5-point Likert scale. Relative deprivation was measured with the relative deprivation scale which consists of 4 items. The respondents rated the extent to which they agreed with each statement on a 6-point Likert scale. Violence exposure in daily environment was measured with the violence exposure in daily environment questionnaire which consists of 8 items. The respondents rated the extent to which they agreed with each statement on a 5-point Likert scale. Aggressive behaviors was measured with the aggressive behaviors questionnaire which consists of 29 items. The respondents rated the extent to which they agreed with each statement on a 5-point Likert scale. The results indicated that: (1) Relative deprivation played a partial mediating role between being bullied and college students’ aggressive behaviors; (2) Violence exposure in daily environment moderated the two paths in the relationship between being bullied and college students’ aggressive behaviors at the same time. For low intensity violence exposure in daily environment, with the increase of being bullied, the relative deprivation had an obviously ascending trend (γ= 0.731, t =14.906, p＜0.001). For high intensity violence exposure in daily environment, with the increase of being bullied, the relative deprivation also show an obviously ascending trend (γ= 0.419，t = 8.758, p＜0.001). For low intensity violence exposure in daily environment, with the increase of relative deprivation, the college students’ aggressive behaviors had an obviously ascending trend (γ= 0.267, t =5.691，p＜0.001). For high intensity violence exposure in daily environment, with the increase of relative deprivation, the college students’ aggressive behaviors also show an obviously ascending trend (γ= 0.169, t = 4.615，p＜0. 001). Therefore, the effect of being bullied on college students’ aggressive behaviors was moderated mediating effect. The moderated mediating model significantly revealed the effect mechanism of being bullied on aggressive behaviors. These findings supported our model that the link between being bullied and college students’ aggressive behaviors was complex and dependent on other factors. The conclusion of the study had important reference value for controlling and preventing of college students’ aggressive behaviors. References | Related Articles | Metrics

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Parent-Child Technology Interference and Cyber-Relationship Addiction among Adolescents: Moderated Mediation Model Liu qinxue Qiong HU Di Qi 2021, (2): 316-323.  Abstract ( )   PDF   With the popularity of the Internet, people begin to establish and develop interpersonal relationship with others online. According to the newest report from China Internet Network Information Center, 95.6% Internet users accesses to social networking software, and adolescents aged 10-19 years old account for 17.5%. However, excessive reliance on online social networking may have serious negative effects on one’s physical and mental health. Therefore, exploring the factors and mechanisms of cyber-relationship addiction can be helpful for further prevention and intervention. Parent-child technology interference may be a crucial family factor in causing adolescent cyber-relationship addiction. Moreover, previous studies also indicated that relative deprivation was a potential mediator in the relationship between parent-child technology interference and cyber-relationship addiction. Meanwhile, internal-state-awareness can be the protecting factor for relative deprivation. According to the “attenuation” model, internal-state-awareness may interact with parent-child technology interference. In sum, this study constructed a moderated mediation model to reveal the relation between parent-child technology interference and cyber-relationship addiction. Specifically, we tested the relationship between parent-child technology interference and cyber-relationship addiction of adolescents, the mediating effect of relative deprivation, and the moderating effect of internal-state-awareness. A total of 1637 senior high school students (mean age = 16.19 years, SD = 3.82 year; 648 boys and 705 girls) were recruited to participate in this investigation. After given informed consents, they completed Parent-Child Technology Interference Scale, Cyber-relationship Addiction Questionnaire, Relative Deprivation Questionnaire and Internal-State-Awareness Scale. First, common method biases were examined. Then the overall relationships between the variables in the hypothesized model was obtained by correlation analysis. Finally, the proposed moderated mediation model was tested by AMOS. The correlation analysis showed that: parent-child technology interference was positively correlated with cyber-relationship addiction, and relative deprivation was positively correlated with parent-child technology interference and cyber-relationship addiction. After controlling for gender, the testing for moderated mediation model indicated that: (1) Parent-child technology interference significantly contributed to cyber-relationship addiction in senior high students; (2) Relative deprivation played a mediating role in the relationship between parent-child technology interference and cyber-relationship addiction; (3) Internal-state-awareness moderated the mediated path through relative deprivation, with the effect being stronger for adolescents with higher internal-state-awareness. Therefore, both mediating and moderating effects existed in the association between parent-child technology interference and cyber-relationship addiction. The present study revealed how and when parent-child technology interference affected cyber-relationship addiction of adolescents. These findings may contribute to the precaution and prevention of cyber-relationship addiction of adolescents. First, parents should reduce the frequency of using electronic devices during the interaction with their children. Meanwhile, parents should give appropriate response to their children. Second, parent-child technology interference can affect cyber-relationship addiction of adolescents through relative deprivation. The subjective experience of relative deprivation can be diminished through cognitive training. Thus, it is helpful to reduce the risk of adolescent cyber-relationship addiction by learning appropriate cognitive strategies. Related Articles | Metrics

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Using Demographic Information, Psychological Assessment Data and Machine Learning to Predict Students’ Academic Performance 2021, (2): 330-339.  Abstract ( )   PDF   Tracking college students’ academic performance and predicting students who will be likely to fail courses are important to providing early intervention and increasing retention rates. Previous studies have found that many psychological factors are correlated with academic marks, including personality, coping styles, mental health and academic and social motivational constructs. However, the traditional way of studying correlational factors often fails in providing an early prediction model since the mechanism underlying poor academic performance is generally complicated and sometimes the patterns are even implicit. Machine learning is an approach that detects implicit patterns via algorithms and statistical models in the big data, which can optimize exploratory analysis by providing internal cross-validation and is more robust to outliers. The present study aimed at utilizing a machine learning approach involving demographic information and the results of psychological assessments as input to classify students who have failed courses from those who have not failed courses in their first year at college. Six hundred and fifty-three participants from five universities in northern China were recruited. They were required to complete demographic information survey, Symptom Checklist 90, Rotter Internal-External Locus of Control Scale, Trait Coping Style Questionnaire and The Big-Five Personality Inventory-10. Those questionnaires measured mental health, coping styles, personality and generalized control expectations on internal-external locus respectively. Academic performance information was collected one year later. The low performing students were defined as having at least one course failed in their first year at college. Five machine learning algorithms including Random Forests (RF), K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Na?ve Bayes (NB) and Decision Tree (DT) were trained to build dichotomous classification model to detect low-performing students. The results showed that the highest classification f1 score was obtained by RF algorithms, with accuracy = 99.00%, precision = 95.86%, recall = 91.83% and f1 score = 93.80%. The feature importance analysis revealed that the features extracted from demographic information and psychological assessment questionnaires were both important in predicting a college student’s academic. The top 10 most important features in RF algorithm included age, gender, whether the student is the only child or not, internal-external locus control, neuroticism, positive coping, agreeable, general symptomatic index, openness and anxiety level. To avoid overfitting, which occurs when the model fits the peculiarities of the training dataset too much and does not find a general predictive rule, a new dataset (n=166) was collected and used to test the generalization performance of the predicting model in the present study. According to the results, the model showed a good generalization performance on the new dataset that was collected one year later with f1 score = 90.90%, accuracy = 97.84%, precision = 92.60% and recall = 89.26%. The study shows the potential of machine learning approaches in predicting students who will be likely to fail courses by using demographic and psychological assessment information. The results demonstrated that the RF algorithm could be used effectively to build a classification model that identifies low-performing students, indicating the applications in the future where early intervention for low-performing students is possible. Related Articles | Metrics

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The Differences of Leaders’ Gender Identity Ratings: An Empirical Analysis Based on the Implicit Leadership Theory 2021, (2): 340-346.  Abstract ( )   PDF   As a significant part of people’s self-concept, gender identity refers to people’s self-understanding of their gender based on social or cultural expectations. According to the two-dimension model of gender identity, masculinity and femininity are two independent dimensions of gender identity, and self-rating and subordinate-rating are two principal approaches using questionnaires (such as BSRI) to evaluate leaders’ gender identity, self-rating and subordinate-rating. However, by using these two rating methods, researchers often reach different result. Hence, this study firstly tried to find out whether there are any substantive differences between self-rating and subordinate-rating in leaders’ gender identity. In the studies of gender identity and leadership, gender role congruity perspective was always the choice of researchers as their theoretical basis. However, since both target stimulus’ (leader’) and perceivers’ (subordinate’) characteristics play important roles in leadership perception, it is insufficient to consider such research mainly from the target stimulus’s (leader’s) perspective. Thus, this study adopts the implicit leadership theory and stands on both leaders’ and subordinates’ sides to explore the influences of leaders’ sex and subordinates’ sex. Based on the implicit leadership theory, this study explores three differences in the evaluation of leaders’ gender identity, which are the differences between self-rating and subordinate-rating in leaders’ gender identity, the subordinate-rating differences between male leaders and female leaders in leaders’ gender identity, and the differences between male subordinates’ rating and female subordinates’ rating in gender identity of leaders. By using a matched questionnaire survey, this research collects 70 valid department samples (including 70 leader samples and 230 subordinate samples) from employees of the Chinese government and government-affiliated institutions. Specifically, leaders are asked to rate their own gender identity, while subordinates are asked to rate their department managers’ gender identity. The results are as follows: (1) subordinates tends to overestimate the masculinity component of leaders’ gender identity compared with leaders’ self-rating, while there is no significant difference between leader-rating and subordinate-rating in femininity dimension; (2) subordinates’ rating of male leaders’ masculinity is significantly higher than that of femininity, while there is no significant difference between masculinity and femininity when evaluating female leaders; (3) male subordinates rate higher than female subordinates in the masculinity component of leaders’ gender identity, while male and female subordinates’ evaluation of femininity is almost the same. In summary, this study explores three differences in leaders’ gender identity ratings based on the implicit leadership theory, which may not only contribute to theory development for future research but shed light on the internal mechanism exploration. Also, this study gives some suggestions to both leaders and organizations. For leaders, depending on their sexes and organizational types, they can shape their behaviors to make themselves match with subordinates’ prototype; for organizations, when they choose or promote a leader, they need to consider whether a candidate comprehensively fit with their organizations’ leadership prototype. Therefore, a leader or organization can be much more effective. Related Articles | Metrics

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The Dark and Bright Sides of Work Connectivity Behavior—— Moderation of Polytonicity 2021, (2): 347-354.  Abstract ( )   PDF   In the Internet era, the rapid development of mobile communication tools has made it common for employees to use electronic communication to handle work affairs during off-hours. In this context, a new way of work connectivity behavior has begun to attract the attention of scholars. Work Connectivity Behavior is based on the innovation of contemporary information technology, which means that individuals use mobile devices to complete work or deal with work-related affairs during off-hours. However, previous studies have shown that there is a paradox in the effect of job connectivity. Activists believe that work connectivity behavior promotes job resource flow among different fields and improves employees’ work output; negatives believe that work connectivity behavior makes employees' family life encroached and has a negative impact on individual family relations. Integrating the above two views, this paper puts forward the double-edged sword effect of job connectivity behavior, and reveals the moderating effect of employee's polytonicity on the double-edged sword effect. Based on the job demand-resource model, work connectivity behavior can not only promote the work goals progress and improve the job performance of employees (job resource process), but also increase the workload of employees and trigger work-family conflict (job demand process). Moreover, polytonicity respectively moderate the impact of work connectivity behavior on employees' job performance and work-family conflict. Specifically, when employees with high polytonicity, work connectivity behavior is more likely to bring work resources and promote the work goals progress; however, when employees with low polytonicity, work connectivity behavior is more likely to increase work demand and increase the workload. Based on 258 three-point leader-employee supervisor-employee dyads, Mplus7.0 was used to conduct path analysis to test the research hypothesis. The results show that: (1) Work connectivity behavior has a positive impact on employee performance through work goal progress. (2) Work connectivity behavior leads to work-family conflict through workload. (3) Polytonicity moderate the relationship between work connectivity behavior and job goal progress, and the indirect relationship between work connectivity behavior and job performance through work goal progress. For individuals with high polytonicity, work connectivity behavior has a more significant positive impact on work goal progress and job performance. (4) Polytonicity moderate the relationship between work connectivity behavior and workload, and the indirect relationship between work connectivity behavior and work-family conflict through workload. For individuals with low polytonicity, the negative impact of work connectivity behavior on workload and work-family conflict is more significant. By revealing the double-edged sword effect of work connectivity behavior and the regulatory role of multiple time orientations, the academia and industry have deepened their understanding of the advantages and disadvantages of work connectivity behavior, and provided enlightenment for how to play the positive role of work connectivity behavior and reduce the negative role. For employees with low polytonicity, when executing work connectivity behavior to deal with work affairs in off-hours, they should reasonably control the number of work, properly perform family duties, and reduce or avoid work-family conflicts. In addition, organizations can enhance employees' polytonicity through training, cultural construction and other activities, so as to give full play to the positive effect of work connectivity behavior. Related Articles | Metrics

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The Impact of the Promise Levels on Trust Decisions – The Mediation Effect of Cheating Notion 2021, (2): 355-361.  Abstract ( )   PDF   Trust refers to the beliefs about whether other people behave opportunistically in social and economic interactions. In terms of the rational signal theory, a person often makes social decisions (e.g. trust) based on perceived social information of others, such as language, gestures, and behaviors. Thus, people tend to make promises in order to convey social information that they are trustworthy and reliable. However, promises are characteristic of non-enforcement and non-binding, which may result in betrayal or deception. Previous studies found promises (vs non-promises) lead to more trust behaviors, however, it still remains unclear how promise levels impact trust decisions and what is the mechanism underlying this process. Therefore, the present study aimed to investigate the impact of promise levels on trust decisions. Next, we tested the mediation effect of cheating notion in the prediction of promise levels on trust behaviors. In order to test effects of promise levels on trust decisions, the current research conducted two studies using an adapted Trust Game (TG). In study 1, we recruited 46 college students who played as trustors completing 30 one-shot TG tasks with anonymous partners. Within each round, participants were informed the partner’s promise. The current study adopted three promise levels from previous studies: the high-level promises will return 14 yuan (70%), medium-level 10 yuan (50%), and low-level 6 yuan (30%). Next, they were allowed to decide whether to invest to their partners, then reported their social expectation for the anonymous partner. The results showed that participants were less likely to invest when they were informed high-level promises instead of medium- or low-level promises, suggesting high level promises inhibited trust decisions. In study 2, there were 28 college students participated in the similar experiment as study 1. Within this study, participants were additionally required to report the possibility of being deceived by their partners, which were regarded as indicators of cheating notion. The results not only consistently demonstrated the findings of study 1, but also found the cheating notion mediated the impacts of promise levels on trust decisions. Specifically, people perceived more cheating notion if their partner promised large payoffs rather than small or medium payoffs, thus resulted in distrust decisions. The present findings suggested cheating notion was critical in understanding the relationships between promise levels and trust decisions. In conclusion, people tend to trust the partners who promised small or medium payoffs instead of large payoffs. Given the non-binding nature of promises, individuals who promised large payoffs were more likely to deceive compared to people promised small or medium payoffs. Therefore, promises levels predicted trust behaviors through the mediation of cheating notion. The present study extended the previous findings by showing the impacts of promises levels on trust decisions, as well as the mediation effect of cheating notion underlying its process. References | Related Articles | Metrics

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How Does Attachment Influence Leaders’ Implicit Followership Theories? The Moderator Role of Gender Zhe-Ming XU Wei-Xi Zeng Jingzhen GAO 2021, (2): 362-369.  Abstract ( )   PDF   Leaders' expectations on followers have significant effects on subordinates, such as potential stimulation, work enthusiasm motivation and performance promotion. These expectations, also known as implicit followership theories(IFTs), aroused widespread concerns among scholars. In recent years, in order to have better understanding of the structure of IFTs, many researchers had investigated the antecedents to IFTs from various perspectives, including personality, emotion, and age, etc. However, while most of the studies revealed how intrapersonal factors could influence individuals’ IFTs, the interpersonal causes were ignored. Since leadership process happens based on social interaction, we supposed that leaders’ attachment system, which is activated by the emotional link between leaders and followers, will shape and influence their IFTs. According to the schema transference theory, the internal working model which developed in one’s early life would be activated and influences leaders’ opinions and attitudes to his/her subordinates in organizational contexts. In addition, since leaders often act as parents in workplaces, they preferred to build relationship with subordinates in a similar way which they had experienced in childhood. Based on connectionist network model, IFTs were distributed representations that could emerge their meaning only until the entire network was activated. Generally, such network would be influenced by both top-down and down-up contextual information processing mechanism. Therefore, we supposed that attachment, an emotion-related input, could have considerable impacts on IFTs. Moreover, since female are more susceptible to emotional factors compared with male, such as anxiety, depress and nervous, it is also worth to explore if the extent of the influence of attachment on IFTs would be different between male and female. We hypothesized that leaders’ IFTs would be predicted by their attachment, and their IFTs profiles would be different among diverse attachment styles. Besides, we supposed that gender would mediate the relationship between attachment and IFTs. The data were collected from 323 leaders of 10 organizations in China. In line with theoretical arguments, it showed that: (1) Attachment predicted IFTs significantly; (2) IFTs prototypes and anti-prototypes were different from various attachment styles. Secure attachment leaders preferred followers who were industrial and positive, while anxiety attachment leaders were fond of counterparts who were dull and affected, and avoidant attachment leaders favored effective and executive followers. (3) Gender moderated the relationship between IFTs and attachment. Female leaders’ negative expectations on followers were more likely to be influenced by attachment anxiety compared to male. Our findings provided significant theoretical implications. Firstly, the study expanded our understanding of antecedents to IFTs. By investigating how attachment shape leaders’ IFTs, we offered a new direction for future research. Secondly, the study deepened our understanding of IFTs of Chinese leaders with different attachment styles. Meanwhile, some practical implications were offered for organizations. Firstly, employers should consider attachment styles as important reference indexes in leader election. Secondly, employers could enhance person-job fit according to the different features of attachment styles. Thirdly, we should discard the prejudice that female leaders were more susceptible to emotional factors than male when judge subordinates, instead, evaluate them more objectively. Related Articles | Metrics

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Fear of Missing Out and Passive Social Networking Site Use Among College Students: A Two Wave Longitudinal Study 2021, (2): 377-383.  Abstract ( )   PDF   Fear of missing out and passive social networking site use have become widespread phenomena among college students, which would bring a series of detrimental outcomes, such as poor sleep, cognitive failures, decreased life satisfaction, and externalizing problems. Recently, some empirical studies have discussed the relationship between these two constructs among college students. However, the results based on cross-sectional designs are far from consistent. One group of researchers believed that fear of missing out might be a risk factor for the passive social networking site use based on the “Uses and Gratification Theory”, another group of researchers suggested that fear of missing out might be triggered by the passive social networking site use on the basis of “Replacement Hypothesis”, still other researchers hold that there may be a bidirectional association between fear of missing out and passive social networking site use based on “Reinforcing Spirals Model”. Therefore the direction of the relationship between these two constructs remains unclear, and longitudinal data is needed to clarify this issue. This study used a two-wave cross-lagged panel analysis to explore the reciprocal relationship between fear of missing out and passive social networking site use, and the moderating role of gender. In our study, four hundred and three Chinese college students completed questionnaires including fear of missing out scale and passive social networking site use scale twice with an interval of eight months. The data are analyzed using SPSS22.0 and AMOS23.0, including repeated measurement of variance analysis, correlation analysis and path analysis of the cross-lagged model. By testing autoregressive effects using longitudinal data, we found that fear of missing out and passive social networking site use in college students at an earlier time were important predictors for the same conditions at a later time. Moreover, the cross-lagged analyses revealed that the relationship between fear of missing out and passive social networking site use was bidirectional over the eight months. Additionally, the multiple-group analysis showed that there was no significant gender difference of the cross-lagged model. The findings of this study supported the view of the reinforcing spirals model, which indicated that higher level of fear of missing out predicts more frequent passive social networking site use over time and vice versa. The result reminds us that timely psychological counseling is needed even for college students who feel mild fear of missing out because it might lead to severe fear of missing out over time. In addition, we should also focus on educating college students about the proper usage of social network sites from an earlier age in order to prevent more frequent passive social networking site use in advance. More importantly, we should be aware that for both boys and girls, reducing fear of missing out is beneficial to the prevention of serious passive social networking site use and vice versa. Related Articles | Metrics

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The Effects of Negative Meta-stereotype Activation on CognitivePerformance among the elderly 2021, (2): 384-390.  Abstract ( )   PDF   With the degree of the aged phenomenon becoming more serious in our country, the health and cognitive problems of the elderly gradually become the focus of social attention. Previous studies found that not only the outgroup had negative stereotypes against the elderly, such as weak, obstinate and forgetful, but also the elderly themselves thought they were discriminated by outgroup because of their decline in memory, cognitive ability and creativity. That is to say that the elderly has negative meta-stereotypes. Meta-stereotype is the belief or awareness that ingroup members holds what outgroup members think of them. The valence of meta-stereotype is mostly negative, and meta-stereotype is more likely to be activated in the vulnerable group, for example, the elderly group. Previous studies have found that the activation of negative stereotypes will lead to negative cognitive effects, and the activation effect will be different under different difficulty cognitive tasks. Meta-stereotypes are more negative than stereotypes. Therefore, this study aims to explore the effect of activated negative meta-stereotype on cognitive performance among the elderly under two different difficulty N-back tasks. Our hypothesis was: (1) The activation of negative meta-stereotype will reduce the elderly’s cognitive performance. (2) When the negative meta-stereotype is activated, the performance among the elderly in different difficulty cognitive tasks is different. We tested the manipulation of the negative meta-stereotype among the elderly through a pilot study, and found that the activation of the negative meta-stereotype triggered significantly more irritability. We use another pilot study to test the applicability of the difficulty of cognitive load task among the elderly. Finally, the low cognitive load task (0-back task) and the high cognitive load task (1-back task) were selected to examine the cognitive effects of the activation of negative meta-stereotype among the elderly. In the formal experiment, 59 elderly people (mean age 72.87 years old, SD=7.75) were randomly assigned to a negative meta-stereotype group or a control group. A 2 (meta-stereotype manipulation: negative meta-stereotype activated group, the control group) × 2 (task difficulty: low cognitive load, high cognitive load) mixed-designed experiment was used in this study. Results showed that, 1) the average accuracy of participants in the negative meta-stereotype group was significantly lower than control group, and the average accuracy of high cognitive load task was significantly lower than low cognitive load task; 2) the average reaction time of negative meta-stereotype group was significantly longer than that of the control group, and the average accuracy of high cognitive load task was significantly longer than low cognitive load task; 3) the interaction effect between group and cognitive load level on reaction time was marginally significant, which suggested the reaction time of the negative meta-stereotype activated group was significantly longer than the control group in high cognitive load task while this difference was not significant in low cognitive load task. In general, the results show that the activation of the negative meta-stereotypes have negative cognitive effects among the elderly. Related Articles | Metrics

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The Promotion Effect of Monetary Reward on the Updating Function of Working Memory of Heroin Abstainers is Weakened 2021, (2): 391-397.  Abstract ( )   PDF   The n-back task with or without monetary reward was used to explore the effect of monetary reward on the refresh function of working memory in heroin abstainers. The mixed experimental design of 2 (subjects type: normal group, heroin withdrawal group) × 2 (task type: 1-back, 2-back) × 2 (reward type: no reward, monetary reward) was adopted, in which the subjects type was the inter group variable, task type and reward type was the intra group variable, and the dependent variable index was the reaction time and correct rate of correct response. Thirty two male heroin abstainers were selected from a compulsory isolation and rehabilitation center in Gansu Province, and 34 normal male subjects were recruited. There was no significant difference in age and years of education between the two groups. At the beginning of the program, the computer screen will display a guide to tell the subjects whether they will be rewarded after the task operation and the following tasks are completed. When the subjects fully understand the task and press "Q" key to start, a 500ms letter stimulus will appear in the center of the computer screen, followed by a 2000ms blank screen, followed by a 500ms letter stimulus. The subjects are required to judge the current thorns Whether the stimulation is the same as the last n stimulation? Press the "F" key. Otherwise, press the "J" key. Press the key quickly and accurately. No reward and monetary reward conditions adopt block design. If it is an n-back task under the condition of monetary reward, each time the subjects respond correctly, the experimental program will automatically record and add a point in the background, and the reaction error will not increase the point. The more points the subjects get, the more reward they will eventually get. In the process of task operation, the subjects are not ed whether the reaction is correct or not and the number of points obtained. Only during the break and after the experiment, the computer screen will display the current total number of points obtained; n-back tasks without reward will not be recorded or fed back. The results of repeated measurement analysis of variance showed that (1) the response time of all subjects under the condition of monetary reward was significantly shorter than that under the condition of no reward; (2) the difference between the response time of heroin withdrawal group under the condition of monetary reward or not was significantly smaller than that of the normal group under the condition of monetary reward or not; (3) in the 1-back and 2-back tasks, the correct rate of the normal group was significantly higher than that of heroin withdrawal group. The results show that monetary reward can promote the updating function of working memory of heroin abstainers, but the extent of its promotion is weaker than that of normal people; the updating function of working memory of heroin abstainers may be damaged. Related Articles | Metrics

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The nearer, the more tempting? The Effects of Perceived Spatial Proximity of Food on Desire for Consumption Quan-Cheng ZHANG 2021, (2): 398-404.  Abstract ( )   PDF   Abstract Exploring factors that influence desire for food and underlying mechanisms is important for preventing unhealthy eating behavior. From the mental simulation perspective, the current research investigates the effects of perceived spatial proximity of food on desire and the underlying mechanism. The authors propose that perceived spatial proximity negatively affects individuals’ desire through mental simulation. Limiting an individual’s perceptual resource (mouths) impedes mental simulation, and thus decreases the effect of perceived spatial proximity on desire. To test the above hypotheses, two experiments were conducted. The first experiment was conducted to test the effect of perceived spatial proximity on desire and the mediating role of mental simulation. This experiment was a one-factor (perceived spatial proximity: near vs. far) between-subjects design, and 95 college students participated in the experiment. The participants were randomly assigned into two groups (near vs. far). The stimulus was a print advertisement of a piece of cake. The perceived spatial proximity was manipulated as follows: The participants were told that the cake advertisement was from a store either near or far from their university. After viewing the advertisement, the participants indicated their desire and mental simulation on scales. The results of this experiment revealed that the participants in the near group reported a higher level of mental simulation and desire than those in a far group. Further analysis revealed that the mental simulation mediates the effect of perceived spatial proximity on desire. The second experiment was conducted to test the change of the effect of perceived spatial proximity on desire after limiting the individuals’ perceptual resource (mouths). In this experiment, the stimulus was an advertisement of an apple, and the perceived spatial proximity was manipulated by visually depicting the apple either near or far in the advertisement. This experiment was a 2 (perceived spatial proximity: near vs. far)ⅹ2 (perceptual resource limitation: limited vs. unlimited) between-subjects design. A total of 116 recruited college students participated in the experiment and were randomly grouped into four. To limit the participants’ mouths, they were asked to chew gum while viewing the advertisement. After viewing the advertisement, they reported their desire to eat the apple. The results showed that the mouth limitation decreased the desire through mental simulation for both the near and far groups, but the decrease effect was more significant for the near group than for the far group. The nearer an individual perceives the spatial proximity is, the more tempting the food is, and mental simulation mediates the relationship between spatial proximity and desire. Taking measures to limit the perceptual resources used when simulating mentally, the effect of spatial proximity on desire decreases. Theoretically, the current research is the first investigation to explore the effect of perceived spatial proximity on desire for food, and thus expands the scope of studies on eating behavior. Practically, the current findings provide insights into the manipulation of individuals’ desire for food. Key words desire for consumption, mental simulation, perceived spatial proximity Related Articles | Metrics

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The relationship between work during non-working hours and employees' life satisfaction: the mediating role of psychological detachment and the moderating role of motivation for phone use 2021, (2): 405-411.  Abstract ( )   PDF   Nowadays, in the era of "Internet +", the popularity and convenience of mobile phones make the process of communication and the spread of communication information more rapid and effective. Convenient mobile communication makes employees be in the state of "on the go, ready to work" all the time, even after work, blurring the boundary of work and family. Using mobile phones to work during non-working hours becomes a common state, which has brought about a series of positive or negative effects on employees. Previous studies have found that using mobile phones to work after working has a negative impact on employees' positive emotions, and a positive impact on emotional exhaustion and work-family conflicts. In addition, it will also interfere with the employees' recovery process and significantly reduce employees' happiness. Therefore, how to correctly deal with the official usage of mobile phones during non-working hours has become a problem that management scholars and enterprise supervisor must attach great importance to. Based on the theory of Job Demands-Resources model and Effort-Recovery model, this paper uses the diary method to explore the spillover effect of official usage of mobile phones during non-working time on employees’ life satisfaction. Using the job satisfaction scale, mobile phone usage behavior scale, psychological disengagement scale, and motivation for phones use scale, 968 valid data were obtained through an online diary study of 88 employees for 5 consecutive days. First, common method biases were examined by Harman single factor method. Then correlation analysis and regression analysis were conducted to acquire the overall relationships between variables in the hypothesized model. The results indicated as follows: (1) Using phones to work during non-working hours had a significant negative impact on employees’ life satisfaction; (2)The relationship between official phones usage during non-working hours and employee life satisfaction was mediated by psychological detachment; (3) The relationship between official usage of mobile phones during non-working hours and employees’ psychological disengagement was moderated by the motivation of mobile phones’ official usage.. It is concluded that the official usage of mobile phones during non-working hours had a negative impact on the normal psychological detachment process of employees after work, and had a negative spillover effect on life satisfaction. The autonomous motivation of using mobile phones to work could effectively alleviate the negative effects of official phones usage to work during non-working on life satisfaction. The psychological detachment level of employees who have high autonomous motivation of the official usage of mobile phones increased with the increasing of working frequency and duration of the official usage of mobile phones during non-working time. The conclusions drawn in this study expand the application scope of Effort-Recovery theory. At the same time, on the individual level, it provides a certain theoretical basis for individuals to effectively manage their cross-domain behaviors and adjust their own state; on the organizational level, practical advice is provided for organizations to improve employees’ job satisfaction and to create an organizational atmosphere which is more conducive to employees' active working. Related Articles | Metrics

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Not Fearing Inequality? The Psychological Explanations for Tolerance of Economic Inequality Yi DING 2021, (2): 412-418.  Abstract ( )   PDF   Economic inequality is one of the most pressing issues in many countries, not only in the developing but also in the developed countries. Thus, it has received growing public and scientific attention. Economic inequality is costly; however, people seem prefer somewhat inequality. For example, when asking people about the ideal distribution of wealth in their country, they actually prefer some unequal distributions. People also have policy debates ranging from taxation to welfare that aiming to reduce economic inequality. Why? What mechanisms explain this acceptance and tolerance of economic inequality? Based on the perspective of social psychology, in this review, we suggested a dual pathway model: how people perceive and evaluate economic inequality (i.e., cognitive path), and their anticipated benefits of inequality (i.e., motive path) could explain why they tend to tolerant inequality and to ignore the problems caused by economic inequality. In the cognitive path, first, people often estimate that their societies are far more equal than the actual level of economic inequality. The underestimated perception of (but not actual) inequality could predict more acceptance of economic inequality and less supportive of redistribution. Thus, we suggest that people underestimate the actual levels of wealth and income inequality, and this “underestimated inequality” can be regarded as a mechanism for why people are somewhat tolerant of economic inequality. Second, people tend to believe that inequality is fair, which comes from (a) a fair system and (b) individual differences in ability, personal effort, and success. Such beliefs would lead people to be insensitive to economic inequality, to consider current economic distribution as fair, and thus in turn to accept rather than oppose inequality. Indeed, evidence suggests that people are more likely to accept and maintain economic inequality when they have a tendency to legitimate the social system or when they attribute the inequality to personal characteristics, such as abilities, effort, or person choices. In the motive path, we suggested that people tend to anticipate that they would have more benefits from economic inequality, which leads them to be more likely to tolerant economic inequality. For example, evidence shows that people are more willing to tolerate inequality and to oppose to redistribution when they anticipate to have greater upward rather than downward income mobility for themselves and their children. Also, research on social class indicates that occupying advantageous positions on hierarchies related to resources, higher social class individuals tend to be less sensitive towards inequality and be more favorable to their own interests. Given this evidence, we suggest that the tolerance of economic inequality might be also motivated by selfish-related motivations. Before closing, we should briefly outline some potential avenues for future research. First, we should clarify whether people really concern about economic inequality rather than unfairness issue, poverty issue, or social conflicts stems from the inequality. Second, we should examine the relations between the cognitive and motive paths and to understand how these relations influence people’s attitude towards economic inequality. Third, we should explore interventions that would encourage people to support social policy that helps to reduce economic inequality. Related Articles | Metrics

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Is Learned Helplessness Learned: Comments on the Rethinking of the Theory of Learned Helplessness 2021, (2): 419-425.  Abstract ( )   PDF   In 1967, Seligman and Maier proposed the famous theory of learned helplessness based on animal experiments. They theorized that animals learned that outcomes were independent of their responses—that nothing they did mattered—and that this learning undermined trying to escape. In 2016, at the time when the theory was put forward for 50 years, Maier and Seligman reviewed the development of the theory, especially the biological mechanism of learned helplessness, and proposed their surprising rethinking: learned helplessness (passivity in response to shock) is not learned. It is a default, unlearned response to prolonged aversive events and mediated by the serotonergic activity of the dorsal raphe nucleus, which in turn inhibits escape. This passivity can be rescued by learning control, with the activation of the medial prefrontal cortex, which subserves the detection of control leading to the automatic inhibition of the dorsal raphe nucleus. So animals learn that they can control aversive events, but the passive failure to learn to escape is an unlearned reaction to prolonged aversive stimulation. For all researchers working in related fields, this rethinking is astonishing and worthy to be paid attention. Therefore, we briefly reviewed the origin and development of the theory of learned helplessness, and introduced the rethinking and the related neural mechanisms. Base on this review, we then discussed and commented on the rethinking. First of all, it is a good example for psychologists to test psychological theorization by using empirical data form neuroscience researches. Nevertheless, there are still some points in the rethinking need to be considered. First, there is still not sufficient evidence which Seligman and Maier employed in the rethinking to deny the existence of “learned” helpless. For example, it is truly evidenced that escapable shock but not exactly equal inescapable shock, increased the activation of projecting neurons in ventromedial prefrontal cortex (vmPFC), but it is still not clear whether vmPFC received the same amount of inputs under both escapable and inescapable shock conditions. Secondly, considering validity of the triadic experimental design, it is less proper to apply the original triadic design to laboratory rats in studies of learned helplessness, because laboratory rats unlikely have established expectation of control in their prior experience. Actually, the original design could not precisely reveal the psychological processes of learned helplessness, because expectation of subjects to control was not ensured. However, the expectation to control and loos of it induced by failure are the crucial ingredients for development of learned helplessness. Therefore, the neuroscience evidences with original design in rats could not strongly support the rethinking that learned helplessness is not learned. Finally, there is no doubt that learned helplessness exists in humans. When someone encounters prolonged aversive events which are uncontrollable, such as continuous failures in examinations, he/she will lose the expectation of success, give up trying, and even suffer from disorder like depression. Therefore, it is necessary to proceed to study learned helplessness, but a more appropriate experimental design is needed. In order to reveal the psychological processes and neural correlates of learned helplessness, we proposed a modified design based on the original triadic paradigm. One group of subjects was firstly exposed to a prolonged escapable stress treatment, which aims to establish the controllable expectation, and then to a prolonged inescapable treatment, accompanied with the yoked and na?ve groups. This modified design ensures the learning of controllability and then uncontrollability, while separates the effects of stressor per se by using the yoked and na?ve groups. The modified design highlights cognitive ingredient for learned helplessness, and thus have a better constructive validity for study of learned helplessness or learned depression in humans. Related Articles | Metrics

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The Association between Friend Support and Well–being for Undergraduates: The Mediating Role of Self-Efficacy and Moderating Role of Social Comparison Orientation 2021, (2): 426-432.  Abstract ( )   PDF   Well-being is an important goal for both life and education. As indicated by previous study, Chinese undergraduates’ ratings for present well-being were lower than their ratings for future well-being. It is necessary to understand the influence factors as well as the underlying mechanism of well-being to transform this high expectation into reality. The positive effect of social support on well-being has been confirmed by many empirical studies. And the main effect model of social support proposed by Cohen and Wills in 1985 identified that social support has a lasting impact on well-being. The model further indicated that social support can facilitate well-being because it provides a sense of predictability and stability in one's life situation and a recognition of self-worth. By definition, self-efficacy means someone's own assessment of how well one can carry out actions and interventions that are necessary for dealing with future situations. It reflects one’s personal action control as well as recognition of one’s competence. Hence, it might be self-efficacy which plays a mediating role between social support and well-being. Friend and family are the most important sources of social support for Chinese youth. However, many young people may migrate to other places away from hometown in pursuit of higher education. Being away from family decreases the protective effect of family support, which comparatively speaking makes friend support even more important. Therefore, this study focused on the influence of friend support and hypothesized that self-efficacy could play a mediating role between friend support and well-being for Chinese undergraduates. In addition, social comparison orientation also has some influence on well-being. As indicated by many studies, there is an interactive effect between social comparison orientation and factors related to self-concept such as self-esteem and self-certainty on psychological states. And an interactive effect of perceived control and social comparison orientation on well-being was also found by previous study. Because self-efficacy can also reflect one’s self-concept and has a close relationship with perceived control, the interactive effect may also be found between social comparison orientation and self-efficacy. Therefore, this study further hypothesized that social comparison orientation could moderate the relationship between self-efficacy and well-being. To test the hypotheses, the present study constructed a model to examine the mediating role of self-efficacy in the relation between friend support and well-being as well as the moderating role of social comparison orientation in the second path of the mediating effect of self-efficacy. 776 undergraduates completed a battery of self-report questionnaires measuring their friend support, well-being, self-efficacy and social comparison orientation. All the measures indicated good reliability in the study. And the following results were found: (1) Friend support was positively correlated with self-efficacy and well-being; self-efficacy was also positively correlated with well-being; social comparison orientation was negatively correlated with well-being. (2) Friend support exerted both a direct effect and an indirect effect on well-being; the indirect effect was through the mediation of self-efficacy. (3) Social comparison orientation moderated the second path of the mediating effect of self-efficacy. For undergraduate students higher in social comparison orientation, their self-efficacy had a significant ascending trend as the increase of friend support (bsimple=.14, t=3.39, p<.001); for undergraduate students lower in social comparison orientation, the ascending trend of their self-efficacy was more obvious as the increase of friend support (bsimple=.35, t=7.19, p<.001). (4) The indirect effect of self-efficacy was moderated by social comparison orientation, and the indirect effect was stronger for student lower in social comparison orientation. The study highlighted the mediation effect of self-efficacy and the moderation effect of social comparison orientation in the link between friend support and well-being. It contributes to a better understanding of the effect as well as the paths and conditions of social support on well-being for undergraduates. And it also provided constructive suggestions to facilitate the well-being of undergraduates. Related Articles | Metrics

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How Cognitive Style Influences Problem Solving in 4 to 8-year-old Children Xiu-Yan LI Zhen Wu 2021, (2): 433-439.  Abstract ( )   PDF   Cognitive style represents individuals’ consistence in information acquisition and information processing. It affects individual’s cognitive functioning, such as memory, attention, and problem-solving. To describe the developmental trend of children’s cognitive style and to investigate how cognitive style affects children’s problem-solving behaviors, we measured 98 4- to 8-year-old children’s wholistic-analytic dimension of cognitive style and the strategies they used in problem-solving. Participants were categorized into three age groups: preschoolers of the middle class and the senior class, as well as first-grade primary students. A computer program-based Cognitive Style Analysis (CSA) test was used to measure participants’ cognitive style. The stimuli were presented in a ThinkPad Yoga laptop with a resolution of 1920×1080. Participants were required to judge whether two figures were identical in the wholistic subtask and whether the simple figure was embedded in the complicated figure in the analytic subtask. Task order was counterbalanced among participants. Cube-based Puzzle Game was used to measure the participants’ problem-solving strategies. In the task, participants were required to build the same pattern as in the task card. First, regarding the cognitive style analysis test, we found that primary school children had higher accuracy and shorter reaction time in both the wholistic and the analytic subtasks than preschoolers, which indicates that cognitive ability grows with age rapidly. However, there was no significant difference between preschoolers of the middle class and the senior class. Second, we compared the cognitive style (wholistic-analytic ratio, calculated as the performance on the wholistic task divided by the performance on the analytic task) among children of the three age groups. One-way ANOVA showed that there was no significant age differences, and the average wholistic-analytic ratio was 1.84, suggesting that children aged 4 to 8 overall tended to be wholistic. Meanwhile, the analytic style gradually develops with age, as Pearson correlation results showed that age was significantly negatively correlated with the wholistic-analytic ratio. Finally, we divided participants into the high and low ratio group according to the median of the wholistic-analytic ratio. Mann-Whitney U Test results showed that the high ratio group (relatively wholistic style) used Subject Reference strategy (first complete the main part and then the background) more frequently than low ratio group (relatively analytic style), while low ratio group preferred Clue Inference strategy (complete the puzzle in the order of rows or columns strictly) and Local Positioning strategy( place the cube where it should be without obvious sequence). This study is one of the first research to explore how cognitive style develops in young children and how it influences the problem-solving strategy in early childhood. We found that 4- to 8-year-old children tended to be wholistic cognitive style; meanwhile, the analytic cognitive style increased with age. Importantly, cognitive style influenced children’s problem-solving strategies: children with relatively wholistic cognitive style tended to use Subject Reference strategy in problem-solving, while children with relatively analytic cognitive style tended to use Clue Inference strategy and Local Positioning strategy. The research facilitates our understanding of children's development of cognitive style and its effect on problem-solving behaviors. It may also provide theoretical evidence for early childhood parenting practices and education for children’s problem-solving. Related Articles | Metrics

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Item Selection Strategy Based on Gini index for Cognitive Diagnostic Computerized Adaptive Testing 2021, (2): 440-448.  Abstract ( )   PDF   Gini index which describes the impurity of data has been widely used in decision tree algorithms. In this paper, A new selection strategy based on Gini index for cognitive diagnositic computerized adaptive testing is developed, it is expected to ensure high test efficiency and uniformity of item bank usage. Two simulation studies aimed to investigate the efficiency of the Gini compared with SHE, PWKL, MPWKL, GDI, KL, Random select stratgies considering a variety of factors, namely, cognitive diagnostic model, and test termination rule. The pattern measurement rates(PMR), , test overlap rate(TOE), test average comsumed time(TC), test average length(TL) and its standard deviation were calculated based on the termination rules to compare the efficiency of the item selection indices. In the first simulation search, the indexes were computed using fixed-test lengths 20 and variable length test as a stopping rule for GDINA, DINA, DINO, RRUM, ACDM, LLM models on five attributes. In the second simulation search, the indexes were computed as same as the first one but only for GDINA on eight attributes. Some conclusions are concluded. (1) The four selection strategies of Gini, SHE, MPWKL and GDI have high measurement accuracy and have a little change under different CDM, so they are not sensitive to the cognitive diagnostic model and can be applied to the item banks of different mixed CDM in the actual test.(2) Compared with the PMR of SHE, MPWKL and GDI, those of Gini has little difference, but the uniformity of item bank usage of Gini is better than the three of them. Overall, Gini is more conducive to both measurement accuracy and the uniformity of item bank usage. (3) PWKL under different CDM, the fluctuation range of PMR is big, PMR of the PWKL with DINA model is as high as PMR of the Gini, SHE, MPWKL and GDI strategies, but under other models, PMR of the PWKL dropped about 5%, therefore, in practice ,adopting PWKL strategies should take the test of Goodness for Fit, besides DINA model, it is not recommended PWKL strategy. However, the utilization index of PWKL strategy in item bank is the best among the five strategies. With the DINA model, the index of Gini and PWKL strategy in item bank are basically the same, but the selection speed of Gini in item bank is about 37% faster than that of PWKL strategy. Therefore, if the actual data conforms to the DINA model, it is suggested to use Gini strategy instead of PWKL strategy.(5) although the measurement accuracy of MPWKL strategy is very high, it takes too much time to select next item, and the usage of item bank is the most uneven. Therefore, it is not recommended to use in the actual test.(6) when the number of attributes increases to 8, the measurement accuracy of each selection strategy declines rapidly, especially PWKL, test length is up to 30, PMR is less than 80%. Therefore, in CD-CAT, it is not recommended to measure too many attributes, but generally recommended about 6 attributes. Related Articles | Metrics

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Using GLMM to Unify GT and IRT Ming-Feng XUE Ping Chen Tour Liu Feng-Quan ZHEN 2021, (2): 449-456.  Abstract ( )   PDF   It is important to inspect the quality of psychometric tools (e.g., ability tests and personality scales) before they are applied. Due to the drawbacks of classical test theory, GT (generalizability theory) and IRT (item response theory) are becoming popular. Though some efforts have been made to combine GT and IRT, most of the researches continue to employ GT and IRT separately. That is because previous models such as GRIM (Generalizability in Item Response Theory Modeling) and HRM (Hierarchical Rater Model), are a little complicated and lack program to perform them. Therefore, this paper proposed GLMM (Generalized Linear Mixed Model) to unify GT and IRT. GLMM is an extension of Linear Mixed Model. By emploiting various link functions, response variables are no longer limited by continuous data in GLMM. Therefore, it is suitable to analyze discrete data such as dichotomous data. There are a lot of advantages to unify GT and IRT under the framework of GLMM. First of all, GLMM can provide variance components that are key components in GT as well as difficulty parameters that are necessary in IRT at the same time. Secondly, GLMM is simpler than previous models. In addition, we can perform GLMM in many programs such as lme4 package in R, HLM and so on. Last but not least, compared with EMS (Expected Mean Squares), traditional method to estimating variance components in GT, GLMM can avoid the violation of assumption of interval scale, which improves the reliability of analysis. To illustrate the feasibility and the strengths of GLMM, a simulation study and an empirical study were conducted. In the simulation study, σ_p^2=2×π^2/3, σ_i^2=1×π^2/3, and the reason why σ_p^2 and σ_i^2 were the multiples of π^2/3 was that the default residual variance of binominal GLMM using logit as linking function was π^2/3. Setting true parameters of variance component in this way provided us a simple proportional relationship. Person effect and item effect were randomly drawn from normal distribution with variance of σ_p^2 and σ_i^2 respectively, and the item effect was treated as easiness parameter. By exploiting the inverse logit function, the sum of person effect and item effect was transformed to the probability of a correct response. Then binary response was drawn from Bernoulli distribution with probability calculated from last step. GLMM was exploited to analyze the data. To make comparison, EMS and Rasch function in ltm package were also used. The results showed that GLMM provided more precise estimates of variance component, G coefficient and Φ coefficient than EMS did, while difficulty parameters estimated from GLMM were more precise than their counterparts from ltm package. Empirical data was LSAT dataset from ltm package with 1000 subjects, who answered 5 dichotomous questions. The results showed that the percentages of σ_p^2 from GLMM and EMS were close, but the percentages of σ_i^2 or σ_(pi,e)^2 were quite different between methods. In addition, difficulty parameters estimated through GLMM and traditional Rasch model were close. Compared with traditional GT and IRT, GLMM can produce reliable and precise results, especially no longer rely on the interval scale data assumption as EMS does. Therefore, it is appropriate to combine GT and IRT using GLMM to analyze psychometric tools which offers some special advantages. Related Articles | Metrics

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Research Progress in Polytomous Cognitive Diagnosis Model 2021, (2): 457-464.  Abstract ( )   PDF   Educational Assessments (education) is playing an increasingly important core role in assessing students' academic achievements. Traditional test theory can only provide students with a total score, and cannot provide specific information about students' internal knowledge structure and learning process. Cognitively diagnostic assessment (CDA) aims to measure learners of their cognitive strengths and weaknesses in assessed skills, so as to provide immediate diagnostic information for parents and schools, plan and guide subsequent improvement of teaching strategies and objectives. CDA is completely model-based. Currently, a large number of cognitive diagnosis models (CDMs) have been proposed to satisfy the demands of the CDAs. However, most existing CDMs are only suitable for dichotomously-scored items. In the case of the dichotomously-scored items, the test manager classifies the observed responses into two categories, correct and incorrect. In practice, there are lager polytomously-scored items/data in educational and psychological tests. It is common to use Likert-type items in questionnaires. For example, an item with four response categories, such as “Strongly Dislike”, “Dislike”, “Uncertain”, and “Strongly Like”, typically has scores of 0, 1, 2 and 3, respectively. In educational achievement test, it is also common to have polytomous items where a higher response category indicates higher ability to measure. It has been recognized that, polytomous items have several advantages over dichotomous items. For example, polytomous items can provide more information for inference, and some features are easier to measure with polytomous items such as personality, attitude, motivation, interest and more. Therefore, it is very necessary to develop CDMs for polytomous data. At present, only a few polytomous CDMs have been developed to deal with polytomous items. According to the models’ different order-preserving mechanisms in forming the dichotomies of response categories, the existing polytomous CDMs can be divided into three types: (1) graded response models, based on global (or cumulative) logit, (2) partial credit models that make use of the local (or adjacent category) category logit, and (3) sequential models, based on the continuation ratio logit. This paper briefly introduces the most commonly used polytomous CDMs, including their parameterization, the meaning of the models’ parameters, the model assumptions, the applicable scope of the model and relationships between these models, so as to provide a model reference for researchers and practical users. To explore the potential of these proposed polytomous CDMs, several future research directions can be identified. First, most CDMs assume that all students use the same strategy to solve problems. Multi-strategy CDMs take into account the differences of problem solving strategies among students and help to provide more diagnostic information. Therefore, it will be an interesting direction to study the polytomous CDMs for multiple strategies. Second, the current CDMs almost only utilize information on item responses and ignores an important source of information about a respondent's behaviour, namely response times (RTs) to items. It is also worth trying to develop a diagnostic model that utilizes both item responses and RTs. Third, an interesting topic for future research would be the applying these proposed polytomous CDMs to develop polytomous cognitive diagnostic computerized adaptive testing (CD-CAT) and computerized adaptive multistage testing (MST). Related Articles | Metrics

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Self-related processing in adult survivors of childhood psychological maltreatment Wei-Ming BAI LIU AiShu LIU Ming-Hui 2021, (2): 473-480.  Abstract ( )   PDF   Childhood psychological maltreatment has a negative impact on self-development, leading to the formation of a negative self, which can also affect individual behavior. Most previous studies had explored this effect using measurement rather than experimentation, which can be prone to bias and distortion. The self is the key point for individuals to construct their worlds and survive in them. Therefore, it is crucial to investigate the development of the self after psychological maltreatment. We undertook experiments to investigate whether childhood psychological maltreatment influences self-information processing and how emotional information affects the ability of the information process to reveal one’s self-development status. The current study used the Child Psychological Maltreatment Scale (CPMS) to screen participants. Thirty participants reporting histories of psychological maltreatment in childhood (experimental group) and thirty participants who did not report such histories (control group) were recruited for Experiments 1 and 2, respectively. A perceptual matching paradigm was utilized to assess the characteristics of self-related processing. This paradigm can overcome fundamental methodological problems in prior work by using self-names and -faces and providing a strong quantitative means to understand the self-integration function and its dysfunction. In Experiment 1, participants were asked to connect abstract geometric shapes to indicate either themselves (‘you’), or familiar other (‘friend’) or an unfamiliar other (‘stranger’). The task was to judge whether the sequential shape/label pairs matched or did not match. The main purpose of Experiment 1 was to examine whether the inclusion of abstract geometry into the self-system demonstrated a robust advantage of self-related processing. In Experiment 2, negative, neutral and positive emotional stimuli were embedded in the social-connection graph to explore whether the self-related processing of individuals is modulated by emotional information. It was then examined the self-integration function. The results of Experiment 1 showed that the response rate (RT/ACC) of self-related information judgements among the experimental and control groups was significantly faster than those of the friend (p<.001). Compared with the control group, the processing advantages of the friend in the experimental group were enhanced (p<.001). In Experiment 2, the response rate of self-related information judgements in the experimental group was significantly faster than that of the friend under a negative emotional condition (p=.003). There was no significant difference between positive and neutral conditions (ps>.10). In the control group, the response rate of self-related information judgements in the experimental group was significantly faster than that of the friend under both negative and positive emotional conditions (p<.001). In conclusion, through self-related information processing, individuals with or without histories of childhood psychological maltreatment had significant advantages of self-related processing. The self-integration function of psychologically-abused individuals is not stable. Negative emotions maintain the self-processing ability, while positive emotions weaken it. Moreover, there is an advantage of enhanced friend-related processing that is more likely to automatically associate friends with positive emotions. For individuals who are not psychologically abused, the self-integration function is stable and not easily disturbed by emotional information. The research verifies the constructivist self-development theory (CSDT), indicating that psychological maltreatment mainly thwarts the development of a self-benign positive appraisal. According to CSDT theory, we believe priming the secure attachment schema, or positive affect, can weaken inherently negative patterns in adults with histories of childhood psychological maltreatment. The research also suggested that we should pay more attention to children’s family growth environments, make the caregivers fully realise the importance of the child-caregiver relationship and provide children with a full sense of attachment and emotional support as they grow. These are critical to children’s self-adaptive development. Related Articles | Metrics

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Dialectical Behavior Therapy: Efficacy, Mechanism, and Prospect 2021, (2): 481-488.  Abstract ( )   PDF   Related Articles | Metrics

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Effective CBT intervention in social anxiety disorder: Neural predictors and machine learning applications 2021, (2): 489-495.  Abstract ( )   PDF   Objective: Social anxiety disorder (SAD) is a common chronic psychological disorder and an important cause of depression and autism. Cognitive behavioural therapy (CBT) is the gold-standard psychological treatment for SAD; however, some patients fail to respond to it. Therefore, identifying neurobiological predictors of the treatment response to CBT has implications for precision medicine. Methods: This paper systematically reviewed the relevant studies on neural predictors of individual responses to CBT in SAD in the core collection of Web of Science, MEDLINE, SciELO, PubMed and PsychoInfo databases from January 2013 to July 2020. The study samples met the diagnostic criteria for SAD in the diagnostic system of mental disorders. SAD was taken as the main symptom, and patients with other comorbid mood or anxiety disorders (such as mood disorders and generalised anxiety disorders) were not strictly excluded, but the participants had no history of major mental disorders (such as schizophrenia and bipolar disorder). Results: Preliminary evidence suggests that functional activation of the higher-order visual cortex (e.g. the dorsal and ventral occipito-temporal cortex and superior and middle temporal gyrus), the dorsal anterior cingulate cortex and parts of the prefrontal cortex (e.g. dorsolateral prefrontal cortex, dorsomedial prefrontal cortex and medial orbitofrontal cortex) may be potential predictors of the success of CBT treatment for SAD. In contrast, the predictive effects of activation of the amygdala and insula were not consistent across studies. The structural or functional connections between the amygdala and areas associated with emotional regulation, such as the prefrontal cortex, predicted therapeutic responses. There were few electrophysiological studies, and preliminary studies found that larger late positive potential (LPP) amplitude for aversive distractors is associated with more significant symptom improvement after CBT. No potential predictors were identified for brain structure, genetics, demography or clinical variables except for initial anxiety. Studies showed that neuroimaging predictors are superior to demographic and clinical indicators, which indicates the necessity of searching for neural predictors. Using machine learning methods, researchers made individualised-level predictions for the suitability of individuals with SAD for CBT therapy. Support vector machine and logistic regression were two of the most commonly used machine learning algorithms. The accuracy of prediction was between 69% and 92%, and the sample size was about 20–50 people. However, for most of the studies, feature selection or feature extraction methods were not combined to further optimise the classification performance of machine learning. In addition, most of the research used cross-validation to investigate the generalisability of the model. In this process, over-fitting caused by model comparison and parameter selection may also occur. Conclusion: Great progress has been made in the study of neural predictors for the treatment response to CBT for individuals with SAD, which will be helpful for the development of personalised treatment plans and the effective use of medical resources. Future research should consider cooperation and sharing among research institutions to obtain big data, conduct data collection under multi-modal and multi-task conditions, further enhance the ecology of experimental tasks and verify the effectiveness of individualised-level prediction in independent samples. Related Articles | Metrics

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Application of MPT Model in Recognition Heuristic 2021, (2): 496-503.  Abstract ( )   PDF   Abstract Recognition heuristic (RH) is frequently used when human make decisions. The RH as one of the simplest heuristics has attracted the attention of many researchers, it only uses recognition to make decisions. RH can be defined as follows: if only one of the two items is recognized, individuals infer that the recognized item hasstronger evidence therefore it should be chosen. For example, the individual is asked to judge whether City A or City B is larger. City A is recognized city, and City B unrecognized city. If the individual chooses the recognized City A as the larger city, it indicates that the individual uses the RH. Many measures have been used in RH. The measures included but not limited to are: adherence rate, discrimination index, hit rate and false alarm rate. These measures are limited in distinguishing the key concepts recognition and knowledge. To overcome this limitation, we introduce measures from a parametric multinomial model in this paper. The model is called Multinomial Processing Tree (MPT) model. MPT model is a family of effective statistical model measures and analyzes both explicit and implicit cognitive processes. MPT modeling methods have been successfully applied in many subject areas such as cognitive psychology, cognitive neurology game theory, sociology, artificial intelligence and artificial intelligence network. We have built a version of MPT model in this paper specifically for measuring relevant cognitive processes in RH. We name it r-model. The r-model introduce in this paper contains three sub-model with each of the models targeting three different cases: two objects are recognized (knowledge case), only one object is recognized (recognition case), and none of the objects is recognized (guessing case). The premise of using R-model is to use the pair comparison task as an experimental paradigm. After introducing the model, we explain how would one analyzes data using r-model. The strength of r-model is the capability of analyzing individual differences. Most existing methods can only analyze data at the group level therefore ignore individual differences. The degree RH used in human cognition highly individualized. RH researchers started to pay more attention to individual differences. Two methods are commonly used when considering individual differences in RH studies: Hierarchical Bayesian models and Hierarchical latent-class approach. Our proposed r-model is MPT implementation of the above mentioned two methods. The method of hierarchical modeling is used to define a separate MPT model and individual parameter estimates for each subject. It assumes that the individual parameter estimates for these individual MPT models come from a common distribution. The hierarchical latent-class approach is to use a finite hybrid model and assumes that the subject belongs to a limited number of potential classes and the same class of subjects have the same parameters. At the end of the paper, we propose the future research directions of using r-model in RH research. Specifically, we propose 1) how to modify model parameters to consider other measures such as response times and heuristic strategies; 2) How would one consider non-cognitive factors such as environmental conditions and individual characteristics. Keywords recognition heuristic; fluency heuristic; multinomial processing tree model; Bayesian hierarchical model Related Articles | Metrics

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The Traits-State of Wisdom: Debate, Integration and New Perspective Hao-tian ZHANG Zhe Feng Chao S.Hu 2021, (2): 504-511.  Abstract ( )   PDF   The debate between the trait- and state-theories of wisdom has always been a heated topic. The trait-theory of wisdom argues that wisdom is a stable personality trait that is difficult to be intervened through self-improvement or external efforts, and only the sages possess "true wisdom". Empirical studies basing on the trait theory have utilized self-report measurements and the nomination method. However, their theoretical basis and research methodology have two shortcomings: (1) The excessive pursuit of the "pure" trait-level of wisdom leads to the "utopia of wisdom"; (2) self-report measurements have inherent defects. The state-theory of wisdom holds that wisdom is not always a stable and invariable quality, but a state of mind that changes with the situation. Wisdom can be increased through one's efforts and external assistance. This theory inspires studies on wisdom intervention. In recent years, a considerable number of empirical studies have been conducted basing on the state-theory of wisdom, suggesting that wisdom is not an unattainable quality that only the sages can possess. Research of wisdom basing on the state-theory incorporates self-report, text analyses, event reconstruction, narrative analysis, and other state-of-art technologies. These studies are truly mixed-method studies, integrating qualitative and quantitative methodologies. Inspired by the density distribution theory of personality proposed by Fleeson (2001), Grossmann, Gerlach, et al., (2016) drew attention to the density distribution theory for studies of wisdom. They believe that wisdom could be defined as the density distribution of wise behaviors in specific contexts, and individuals show different levels of wisdom (trait expression) basing on situations (state expression). The traits of wisdom can be construed as the distribution of state expressions in specific situations. However, there is still space for improvement for the density distribution model. The shape of the distribution can be further specified, and distinctions can be made between people with different levels of wisdom. Given these issues, we put forward a new theoretical model: the trait-state normal distribution model. In this model, we try to categorize people into three groups (the high-level, medium-level, and low-level wisdom). According to the central limit theorem in statistics, we propose that trait-levels of wisdom are reflected through the mean levels of wisdom performances across different states, and the distributions of the mean level of wisdom among people fit the normal distribution. This new model attempts to integrate trait differences between individuals and state fluctuations within individuals, reflecting the individual wisdom accurately and objectively. Future studies should test this theoretical model empirically using the signal detection theory, longitudinal tracking, etc. Delineating the trait and state theories of wisdom facilitate further understanding of the concept of wisdom, and provides an important theoretical basis for wisdom fostering. Future studies should focus on the improvement of measurement methods of wisdom, the moderating effect of the importance of life problems on the stability of wisdom, and the cultural effects on the views of wisdom, which could then affect the fluctuation of wisdom in real life. Finally, the application of hybrid methods (e.g., Experience-sampling Methodology and Aggregation technology) is important for integrating trait- and state- theories of wisdom. Related Articles | Metrics