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CN 11-1911/B

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    25 August 2022, Volume 54 Issue 8 Previous Issue    Next Issue

    Reports of Empirical Studies
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    Reports of Empirical Studies
    Neural correlates of consciousness of emotional faces and the unconscious automatic processing: Evidence from event-related potentials (ERPs)
    SUN Bo, ZENG Xianqing, XU Kaiyu, XIE Yunting, FU Shimin
    2022, 54 (8):  867-880.  doi: 10.3724/SP.J.1041.2022.00867
    Abstract ( 224 )   HTML ( 26 )  
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    The neural correlates of consciousness (NCCs) are debatable due to the confounding effects of subjective reports. In addition, although previous studies have suggested that vMMN is relatively insensitive to the manipulation of visual attention, the relationship between vMMN and visual consciousness remains unclear. The inattentional blindness paradigm can not only effectively manipulate visual consciousness, but also explore the conscious processing without relying on subjective reports. Therefore, we used this paradigm to manipulate visual consciousness. Moreover, we introduced emotional (happy and fearful) faces, which are biologically and socially significant visual stimuli, to explore NCCs and the relationship between automatic detection of changes and visual consciousness.
    Fifty-six Chinese participants took part in the present study. We recorded electroencephalography (EEG) in three phases. In phase A, the participants needed to detect changes of the red dots. However, because they were not informed of the existence of emotional faces, 26 participants were unconscious of the task-irrelevant emotional faces. In phase B and C, all participants were informed about the emotional faces. Thus, they were conscious of the emotional faces. Specifically, in phase B, the participants still needed to detect changes of the red dots, and the emotional faces are task-irrelevant. However, in phase C, the participants were asked to detect changes of emotional faces, and thus emotional faces were task-relevant. To check the conscious state of emotional faces, participants were required to fill out an awareness questionnaire after completing phases A and B. Then the participants were divided into unconscious group and conscious group according to their conscious state of emotional faces in phase A.
    For NCCs, two analyses of ERP amplitude of standard stimuli in Phase A and B of the unconscious group were performed. First, for the ERPs at PO7 and PO8 electrodes, a three-factor repeated-measures analysis of variance (rANOVA) of Phase (A, B) × Emotion (Fear, Happy) × Hemisphere (PO7, PO8) was used. Second, for the ERPs at the three electrodes of FCZ, CZ and CPZ, a three-factor rANOVA of Phase (A, B) × Emotion (Fearful, Happy) × Electrodes (FCZ, CZ and CPZ) was adopted. Similarly, two three-factor rANOVA were used for the effect of task relevance. However, exploring the effect of task relevance requires an analysis of the ERPs of standard stimuli in phase B and C of all participants. For vMMN, we analyzed the ERPs at PO7 and PO8 electrodes during the 250~350 ms window of time.
    Results can be summarized as following. (1) For NCCs, the ERPs at PO7 and PO8 during the 200~300ms window of time were analyzed, which yielded a significant main effect of Phase [F(1, 25) = 16.385, p < 0.001, η2p = 0.396]. This showed that the emotional faces in phase B evoked stronger negativity than in phase A for the unconscious group, suggesting that the conscious processing of emotional faces evoked visual awareness negativity (VAN). The ERPs at PO7 and PO8 during the 400~600 ms window of time were analyzed, which yielded a significant main effect of Phase [F(1, 25) = 15.79, p = 0.001, η2p = 0.39]. This showed that the emotional faces in phase B evoked stronger positivity than in phase A for the unconscious group, suggesting that the conscious processing of emotional faces evoked late occipital positivity (LOP). Moreover, the ERPs at FCZ, CZ and CPZ during the 300~400ms window of time were analyzed, which yielded a significant main effect of Phase [F(1, 25) = 11.481, p = 0.002, η2p = 0.32]. This showed that the emotional faces in phase B evoked stronger positivity than in phase A for the unconscious group, suggesting that the conscious processing of emotional faces evoked late positivity (LP).
    (2) For the effect of task relevance, the ERPs on PO7 and PO8 in the 180~250ms interval were analyzed, which yielded a significant main effect of Phase [F(1, 55) = 20.93, p < 0.001, η2p = 0.28]. This showed that compared with the task-irrelevant condition (phase B), the emotional faces under the task-relevant condition (phase C) evoked stronger negativity, suggesting that task relevance evoked selection negativity (SN). The ERPs on PO7 and PO8 in the 400~500ms interval were analyzed and the main effect of Phase is significant [F(1, 55) = 6.12, p = 0.02, η2p = 0.1]. This showed that compared with the task-irrelevant condition, the emotional faces under the task-relevant condition evoked stronger positivity, suggesting that task relevance evoked LOP. Moreover, the ERPs on FCZ, CZ and CPZ in the 300~400ms interval were analyzed and the main effect of Phase is significant [F(1, 55) = 29.77, p < 0.001, η2p = 0.35]. The results showed that compared with the task-irrelevant condition, the emotional faces under the task-relevant condition evoked stronger positivity, suggesting that task relevance evoked LP that may reflect the post-perceptual processing. Therefore, this study provides evidence that LP and LOP are NCCs without the confounding effects of task relevance. In short, VAN may reflect the early perceptual process of emotional faces, LP and LOP may reflect the further process of classifying and recognizing the representations of emotional faces, such as assessing the emotional valence of faces.
    (3) For the relationship between vMMN and consciousness, we analyzed the data of phase A with a four-factor rANOVA of Stimulus-type (standard, deviant) × Emotion (Fearful, Happy) × Hemisphere (PO7, PO8) × group (conscious, unconscious). The rANOVA revealed that the main effect of Stimulus-type was significant [F(1, 54) = 9.43, p = 0.003, η2p = 0.149], and the interaction between Stimulus-type and other factors was not significant [ps > 0.05]. This showed that compared to standard emotional faces, deviant ones evoked stronger negativity in phase A. Importantly, the vMMN effect was observed for both the conscious and unconscious group in the phase A. Furthermore, no amplitude difference of vMMN was observed between the aware (phase B) and the unaware (phase A) conditions among unconscious group [t(25) = 0.14, p = 0.88], suggesting that the automatic processing of emotional faces is independent of visual consciousness. Compared with Chen (2020), this study provides evidence that the automatic processing of emotional faces is independent of visual consciousness under the condition that the unconsciousness level is manipulated more effectively.
    (4) In addition, we analyzed the vMMN effect with a ANOVA of Phase (A, B and C), which yielded a significant main effect of Phase [F(2, 110) = 5.24, p = 0.007, η2p = 0.087]. And compared with the task-irrelevant condition (phase B), the vMMN amplitude under the task-relevant condition (phase C) was larger (p = 0.003), suggesting that task relevance modulates the amplitude of vMMN and the attentional effect of task relevance promotes the automatic processing of emotional faces.
    The conclusions of this study can be summarized as following. (1) VAN is a NCC under the condition of avoiding confounding effects of visual attention, and LP and LOP are NCCs without the confounding effects of task relevance. (2) The visual awareness of emotional faces has different ERP indicators at different time stages. Specifically, VAN reflects the early perceptual experience, LP and LOP reflect the late conscious experience of non-perceptual information. (3) The automatic processing of emotional faces is independent of visual consciousness but is modulated by visual attention.

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    Semantic search during creative thinking: A quantitative analysis based on cumulative distribution and semantic similarity of responses
    CHEN Yanran, LIANG Zheng, ZHAO Qingbai, Huang Yu, LI Songqing, YU Quanlei, ZHOU Zhijin
    2022, 54 (8):  881-891.  doi: 10.3724/SP.J.1041.2022.00881
    Abstract ( 102 )   HTML ( 5 )  
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    The semantic search during creative thinking refers to the activation process of semantic information in long-term memory involved in creative activities. Influential theory has posited that the semantic activation process in free recall shows spreading activation within semantic network and is characterized by negative acceleration and clustering. Unlike the free recall, it is necessary to suppress the dominant response and to activate novel and distant information during creative thinking. Therefore, one might expect different semantic search processes during creative thinking, but such a hypothesis has not yet been directly tested. To explore the semantic search process during creative thinking, the present study described the quantitative dynamic characteristics of answer generation in a divergent thinking test using a series of parameters, such as cumulative response distribution and semantic similarity.
    The experiment employed a within-subject design with the task type (novel V.S. normal) as the independent variable. The experiment included two versions of alternative uses task (AUT): novel and normal AUT. In the novel AUT, 39 participants (30 females; aged 18 to 22) were asked to report novel and valid uses for the daily-life items presented on the screen as many as possible, while in the normal AUT they were only asked to think of valid uses for objects as many as possible. During the experiment, participants completed two normal AUTs, followed by two novel AUTs. Each AUT lasted for three minutes. The novelty of responses and semantic similarity of responses were scored by participants themselves. The time function of the cumulative number of responses was fitted by the hyperbolic function, and clustering analysis was conducted based on the semantic similarity of responses.
    The results showed that:
    (1) The cumulative response distribution in the novel AUT condition was negatively accelerating similar to semantic search during free recall, but the search speed in the novel AUT condition was slower than that of the normal AUT condition (Figure 1).
    Specifically, a nonlinear fit of $y~=~\frac{ax}{b+x}~$was performed on the answers time sequences generated by each subject in each AUT, and three answers sequences (two in the normal condition and one in the novel condition) were found to be non-convergent, which were removed in this section but retained in the semantic relationship analysis section. The average R2 of the remaining 153 trials successfully converged fits was 0.96, the RMSE was 0.38, and the average fitting curve was shown in Figure 1.
    The Kolmogorov-Smirnov method was used to test the normality of the fitted parameters a and b. It was found that they did not follow a normal distribution, so the median and the maximum values were used to represent the estimates of the fitted parameters. The Mann-Whitney U test was used to compare the differences of parameters a and b under different conditions (Table 1). The results showed that parameter a was not significantly different between the two conditions (p > 0.05), but parameter b was significantly higher in the novel condition than in the normal condition (p < 0.001).
    (2) In the novel AUT condition, the semantic similarity between participants’ responses (i.e., the answers) and the items (i.e., the questions) was low and significantly lower than that in the normal AUT condition.
    Specifically, we compared the semantic similarity between answers at each sequential position and questions in both conditions using an independent samples t-test. It was found that, except for position 6 and position 9, the semantic similarity between the answers and the questions in the normal condition was significantly higher than that in the novel condition (see Table 2).
    A third-order polynomial function was used to fit the semantic similarity between the answers at each position and the questions, as shown in Figure 2.
    (3) The responses in the novel AUT condition showed a significantly lower degree of clustering than that in the normal AUT condition. In the novel AUT condition, the semantic similarity between the clusterable and non-clusterable answers and the questions were low and not significantly different. Furthermore, there was no significant difference between the clusterable and non-clusterable answers in terms of novelty.
    Specifically, according to the scoring rules of semantic similarity, the semantic distance (d) less than or equal to 0.5 was taken as the clustering criterion, and the clustering degree of the answers under different conditions was calculated separately. Since there was a significant difference in the number of answers between the normal and novel conditions, the percentage of clustered answers to the total number of answers was used to represent the degree of clustering. Independent sample t-tests were used to compare the differences in the degree of clustering between the conditions. The results showed that the degree of clustering was significantly higher in the normal condition than in the novel condition, t (154) = 4.72, p < 0.001, Cohen’s d = 0.76, 95% CI: [0.11, 0.27].
    In addition, a 2 × 2 repeated-measures ANOVA was conducted with experimental condition (normal vs. novel condition) and clustering condition (clusterable vs. non-clusterable) as independent variables, and the mean novelty of answers and the mean semantic similarity between answers and questions as dependent variables (data from one subject who did not have clustered answers in the normal condition and seven subjects who did not have clustered answers in the novel condition were removed).
    The ANOVA results showed that the main effects of both the experimental conditions and clustering conditions on the mean novelty of answers were significant (experimental condition: F (1, 30) = 59.56, p < 0.001, partial η2 = 0.67; clustering condition: F (1, 30) = 27.03, p < 0.001, partial η2 = 0.47). The interaction was significant, F (1, 30) = 4.88, p = 0.035, partial η2 = 0.14. The results of the simple effects analysis showed that the novelty scores of the clusterable answers were significantly lower than those of the non-clusterable answers in the normal condition, F (1, 30) = 21.21, p < 0.001, partial η2 = 0.41; while in the novel condition, there was no significant difference between the novelty scores of the two types of answers (p > 0.05) (see Table 3).
    The main effect of both the experimental conditions and clustering conditions on the semantic similarity between answers and questions were also significant (experimental condition: F (1, 30) = 59.02, p < 0.001, partial η2 = 0.66; clustering condition: F (1, 30) = 23.09, p < 0.001, partial η2 = 0.44). The interaction was significant, F (1, 30) = 21.60, p < 0.001, partial η2 = 0.42. The results of the simple effects analysis showed that the semantic similarity between the clusterable answers and questions was significantly higher than that between the non-clusterable answers and questions in the normal condition, F (1, 30) = 37.13, p < 0.001, partial η2 = 0.55. In the novel condition, there was no significant difference between the clustered and non-clusterable answers in terms of semantic similarity to the questions (p > 0.05) (see Table 3).
    These findings indicated that the semantic search during creative thinking was partly in line with spreading activation theory of semantic search in free call. But the search speed was relatively slower. Furthermore, the novelty requirement prompted the participants to break up the semantic restriction of the item at the initial search and avoid nearby search. The participants tended to generate few ideas in each semantic field. However, when it is far away from the item in the semantic field, individuals might generate clustering ideas.

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    The relationship between preschoolers’ understanding of considerate socially-mindful actions and theory of mind
    ZHAO Xin, LI Dandan, YANG Xiangdong
    2022, 54 (8):  892-904.  doi: 10.3724/SP.J.1041.2022.00892
    Abstract ( 157 )   HTML ( 17 )  
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    We live in a highly interdependent world. Even if we do not directly interact with others, our own behaviors can have an indirect impact on others. One type of such behaviors that indirectly bring benefits to others are considerate, socially-mindful behaviors. In this study, we examined preschoolers’ evaluation of considerate socially-mindful actions; importantly, we also explored the underlying developmental mechanisms by examining its potential relationship to the development of theory-of-mind abilities. A total of 100 children aged 4~6 were recruited in this study. In the social mindfulness task, children were asked to compare two story characters, both of whom were to choose snack at snack time. One of the characters leaves a choice for the person waiting behind when she took a piece of fruit for herself (i.e., acts socially mindful), while the other character in a similar situation leaves no choice for the person waiting behind (i.e., does not act socially mindful). Children were then asked 1) which of these two characters was nicer and 2) who they would prefer to select as a friend. In addition, children were also administered theory-of-mind tasks (including the content false belief task, location false belief task, and hidden emotion task). We also measured children’s prosocial orientation (by a sharing task) and executive functioning capacity (by a Day/Night Stroop task). We found that, first, with age, children increasingly rated the socially-mindful character as nicer than the character who left no choice, and increasingly selected the socially-mindful character as a friend (r = 0.23, p = 0.20, see Figure 1). Second, when controlling for age, children's evaluations and friend preference in the social mindfulness task was significantly positively correlated with their theory-of-mind (r = 0.26, p = 0.008, see Figure 2), but was not correlated with their sharing behaviors or executive functioning. Such correlation remained significant when controlling for sharing and executive functioning. In summary, between the ages 4 and 6, children gradually develop an understanding and evaluation of social mindfulness, and such development is correlated with the development of theory-of-mind abilities. These findings provide insights for our understanding of children's social and moral evaluation and its underlying developmental mechanism.

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    The relationship among morphological awareness, character recognition and vocabulary knowledge in elementary school children: A cross-lagged model
    XIA Yue, XIE Ruibo, WANG Zhenliang, NGUYEN Thi Phuong, WU Xinchun
    2022, 54 (8):  905-916.  doi: 10.3724/SP.J.1041.2022.00905
    Abstract ( 100 )   HTML ( 8 )  
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    The present study aims to examine the relationship among morphological awareness, Chinese character recognition and vocabulary knowledge of elementary school students. Numerous studies on the language development of Chinese children show that as language learning progresses, an individual’s language system gradually develops and matures. Morphological awareness, Chinese character recognition and vocabulary knowledge play an important role in children’s language development. There is a solid one-to-one correspondence between syllables, morphemes and characters in Chinese. It is necessary to consider along with morphological awareness, Chinese character recognition and vocabulary knowledge simultaneously in the language development among elementary school children.
    Three follow-up tests were administered to 146 first-grade elementary school children over a 2-year period to examine changes in the developmental relationships between morphological awareness, Chinese character recognition, and vocabulary knowledge in elementary school children in grades 1 through 3. In addition, phonological awareness, rapid automatized naming of digits, orthographic awareness and intelligence were all measured as control variables at Time 1 (spring semester of Grade 1). A cross-lagged model was conducted to explore the relationship among children’s morphological awareness, character recognition and vocabulary knowledge at different time points.
    The results showed that the relationship among morphological awareness, Chinese character recognition and vocabulary knowledge varied across developmental stages after controlling the aforementioned control variables. (1) Chinese character recognition at Time 1 significantly predicted the homophone and homograph awareness at Time 2; (2) Vocabulary knowledge at Time 1 significantly predicted compounding awareness and Chinese character recognition at Time 2; (3) Chinese character recognition and vocabulary knowledge at Time 2 significantly predicted homophone, homograph and compounding awareness at Time 3. (4) Homograph awareness at Time 2 significantly predicted vocabulary knowledge at Time 3. The specific results are as follows.
    Table 1 presented means, standard deviations, and repeated measures ANOVA results of all measures used in this study. As seen in Table 1, elementary school children’s vocabulary knowledge, homophone awareness, homograph awareness, compounding awareness and Chinese character recognition all increased significantly over time: vocabulary knowledge F(2, 396) = 14.55, p < 0.001, η² = 0.68, homophone awareness F(2, 396) = 14.12, p < 0.001, η² = 0.63, homograph awareness F(2, 396) = 13.36, p < 0.001, η² = 0.48, compounding awareness F(2, 396) = 15.55, p < 0.001, η² = 0.88, and character recognition F(2, 396) = 25.33, p < 0.001, η² = 0.92.
    Table 2 presents the Pearson correlation matrix for all variables. As shown in Table 2, vocabulary knowledge, Chinese character recognition, homophone awareness, homograph awareness, and compounding awareness showed moderate stability between the three tests. Among the control variables IQ, rapid automatized naming, phonological awareness, and orthographic awareness were associated with some of the tests.
    The cross-lagged models were tested with good fit indices of χ2 / df = 1.22, RMSEA = 0.04, SRMR = 0.03, CFI = 0.99, TLI = 0.97. The specific results are shown in Figure1. Vocabulary knowledge at T1 can predict Chinese character recognition at T2 (β = 0.12, p < 0.05). Vocabulary knowledge at T1 can predict compounding awareness at T2 (β = 0.17, p < 0.05). Chinese character recognition at T1can predict homophone awareness and homograph awareness at T2 (β = 0.20, p < 0.05; β = 0.24, p < 0.01). Chinese character recognition at T2 predicted compounding awareness, homophone awareness, and homograph awareness at T3 (β = 0.18, p < 0.05 ; β = 0.35, p < 0.001; β = 0.28, p < 0.001). Vocabulary knowledge of T2 predicted compounding awareness, homophone awareness, and homograph awareness of T3 (β = 0.16, p < 0.05; β = 0.15, p < 0.1; β = 0.36, p < 0.001). Homograph awareness of T2 predicted vocabulary knowledge of T3 (β = 0.13, p < 0.1). In addition, T1’s morphological awareness had no significant predictive effect on T2’s vocabulary knowledge and Chinese character recognition. T2’s morphological awareness also had no significant predictive effect on T3’s Chinese character recognition.
    The results indicated that the relationship among different levels of morphological awareness, Chinese character recognition and vocabulary knowledge in Chinese elementary children has been changed over time. From Grade 1 to Grade 3, Chinese character recognition and vocabulary knowledge had stable predictive effects on morphological awareness, while the predictive effects of morphological awareness on Chinese character recognition and vocabulary knowledge changed with age.

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    The relationship between school assets and early adolescents’ psychosocial adaptation: A latent transition analysis
    HOU Qingqing, GUO Mingyu, WANG Lingxiao, LV Hui, CHANG Shumin
    2022, 54 (8):  917-930.  doi: 10.3724/SP.J.1041.2022.00917
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    Given a broad range of changes in cognitive, emotional, and social relationships, adolescence might mark the beginning of a period of significant fluctuations in psychosocial adaptation because it is a period of preparation for the future that requires special attention and protective measures. The developmental characteristics of different aspects of adolescents’ adaptation have been well studied. However, these previous studies, which have tended to explore various aspects of adolescents’ adaptation in isolation, have been unable to reflect the diversity of adolescents’ adaptation patterns and their variability over time. In addition, exploring and determining school situation-related predictors are essential for helping education professionals understand the relevant factors that affect various profiles and transition patterns of adolescents’ adaptation and, thus, formulate effective prevention and intervention programs to maintain and improve adolescents’ psychosocial adaptation. This study uses a person-centered approach to explore the profiles and transition patterns of early adolescents’ psychosocial adaptation and investigate gender differences and the protective role of school assets.
    A sample of 1012 junior middle school students was selected as participants and measured three times. The adolescents completed loneliness, depression, happiness, school assets scales, and peer nomination forms during the three measurements. The head teacher assessed the students’ prosocial and externalized problem behaviors. The descriptive statistics and multiple logistic regression were analyzed by SPSS 21.0. In this study, Mplus 7.4 was used to analyze the LPA first, and then the LTA. A series of cross-sectional LPAs were fitted using the samples at T2 and T3 to determine the number of classes to be used in the subsequent LTA.
    The results showed that early adolescents’ psychosocial adaptation had two profiles at T1: a well-adapted profile and an internalizing problem profile. Early adolescents at T2 and T3 were divided into four profiles: a well-adapted profile, an internalizing problem profile, an externalizing problem profile, and a peer rejection profile (see Figure 1).
    The LTA results are presented in Table 1. The diagonal of the transition matrix indicates the probability that the subject would maintain the original latent state at two adjacent time points. As shown, from T2 to T3, the well-adapted profile showed the highest stability, followed by the internalizing problem profile and the externalizing problem profile, across the one-year period. The peer acceptance profile showed the lowest stability.
    Of those students who exhibited instability from T2 to T3, adolescents who initially corresponded to the internalizing problem profile, externalizing problem profile, or peer rejection profile tended to gradually transition to the well-adapted profile over time. Adolescents corresponding to the well-adapted profile had the same probability of transition to the other three profiles.
    After district、SES and school type were controlled, at T1, a unit increase in school assets at T1 was associated with 62% (OR = 0.38, p < 0.001) decreases in the odds of membership in the internalizing problem profile at T1, compared to the odds of membership in the well-adapted profile at T1.
    At T2, girls were more likely to belong to the internalizing problem profile (OR = 1.78, p < 0.05) than to the well-adapted profile. Additionally, a unit increase in school assets at T2 was associated with 59%, 24%, and 47% decreases in the odds of membership in the internalizing problem profile, externalizing problem profile, and peer rejection profile at T2 (OR = 0.41, p < 0.001; OR = 0.76, p < 0.05; OR = 0.53, p < 0.001), respectively, compared to the odds of membership in the well-adapted profile at T2.
    At T3, a unit increase in school assets at T3 was associated with 61%, 45%, and 52% decreases in the odds of membership in the internalizing problem profile, externalizing problem profile, and peer rejection profile at T3 (OR = 0.39, p < 0.001; OR = 0.55, p < 0.001; OR = 0.48, p < 0.001), respectively, compared to the odds of membership in the well-adapted profile at T3.
    We further explored the influence of various factors on profile transitions. The subjects in the original latent state were used as the reference group. The occurrence ratio refers to the ratio of the probability of the subject's transition to another group and the change in the probability of maintaining the original group. As shown in Table 2, after district、SES and school type were controlled, from T2 to T3, a unit increase in school assets at T2 significantly decreased the odds of transfer from the well-adapted profile at T2 to the externalizing problem profile or peer rejection profile at T3 by 32% and 47%, respectively (OR = 0.68, p = 0.03, 95% CI [0.48 0.97]; OR = 0.53, p = 0.022, 95% CI [0.31 0.90], respectively). A unit increase in school assets at T2 significantly increased the odds of transfer from the externalizing problem profile or peer rejection profile at T2 to well-adapted profile at T3 (OR = 3.71, p = 0.01, 95% CI [1.40 9.83]; OR = 2.79, p = 0.01, 95% CI [1.33 5.85], respectively). Additionally, a unit increase in school assets at T2 significantly decreased the odds of transfer from the peer rejection profile at T2 to the internalizing problem profile at T3 by 60% (OR = 0.40, p = 0.01, 95% CI [0.20 0.79]).
    This study adds to the understanding of the diversity of the psychosocial adaptation development patterns of early adolescents and suggests the need for comprehensive screening and dynamic monitoring of adolescent adaptation and more complex intervention programs tailored to the specific characteristics of the relevant groups and boys and girls. In addition, identifying the protective role of school assets can help mental health professionals understand the supporting factors in the development of individual health, thereby promoting the positive development of adolescents. Moreover, this study provides a reference for school context-based assessment and intervention strategies.

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    The ancient behavioral immune system shapes the medical-seeking behavior in contemporary society
    WU Qi, WU Hao, ZHOU Qing, CHEN Dongfang, LU Shuai, LI Linrui
    2022, 54 (8):  931-950.  doi: 10.3724/SP.J.1041.2022.00931
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    Over the long course of evolution, in order to cope with the threat of pathogens, both animals and humans have evolved complex disease defense mechanisms, one of which is known as the behavioral immune system. The behavioral immune system is a complex suite of cognitive, affective, and behavioral mechanisms that ultimately help prevent pathogen transmission in the face of recurrent infectious disease threats. It functions by detecting threat-relevant cues in the environment and activating disgust-related responses aimed at diminishing those threats. However, in modern times, with advanced medical technology, the behavioral immune system may not always be beneficial to human disease control behaviors. Previous studies have found that, the social strategies that are designed to avoid infection in ancient times may lead to more serious health problems (e.g., the damage to the cardiovascular system) in modern society. These studies suggest that the behavioral immune system may be evolutionary mismatch in the modern and complex medical environment, which may have a negative impact on our medical-seeking behavior. Therefore, we hypothesized that in modern society, the activation of behavioral immune system will affect individuals' medical-seeking tendency, making individuals display more negative attitudes towards health-care and become more likely to delay their medical-seeking.
    This hypothesis was systematically tested by five different studies. In these studies, we used a well-validated medical-seeking attitude questionnaire and a computerized patient delay task to measure the individuals' medical-seeking tendency. Specifically, in Study 1A (223 participants) and Study 2A (218 participants), we investigated the relationship between trait activation level of behavioral immune system and individuals' medical-seeking tendency by employing the scales of Disgust Scale-Revised Chinese and Perceived Vulnerability to Diseases. In Study 1B (198 participants) and Study 2B (174 participants), we situationally activated the behavioral immune system by asking the participants to watch disease-salient primes in order to investigate the effects of external disease cues on the medical-seeking tendency. In Study 3, we investigated that whether the effects of the activation of behavioral immune system on the medical-seeking attitude and tendency were mediated by the perception of the risk of hospital infection.
    The results showed that: 1) core disgust (M = 27.83, SD = 6.36) negatively predicted the attitude of participants toward medical-seeking (M = 26.64, SD = 3.25), β = −0.20, SE = 0.09, t (203) = −2.27, p = 0.03, 95% CI = [−0.37, −0.03] ; 2) core disgust (M = 27.59, SD = 6.35) positively predicted the tendency of participants to delay medical-seeking (M = 6.46, SD = 5.88), β = 0.25,SE = 0.10, t (196) = 2.57, p = 0.01, 95% CI = [0.06, 0.43]; 3) situationally activating the behavioral immune system significantly affected the attitude of participants toward medical-seeking and the tendency of participants to delay medical-seeking, participants were found to be more likely to have a negative attitude toward medical-seeking (disease-salient: M = 26.96, SD = 3.63; control: M=28.05, SD=3.07; t(196) = −2.1, p = 0.04, d = 0.3, 95% CI = [−2.11, −0.07]) and delay their medical-seeking (disease-salient: M = 8.23, SD = 6.66; control: M = 6.12, SD = 5.79; t(172) = 2.23, p = 0.03, d = 0.34, 95% CI = [0.24, 3.98]) after watching the disease-salient primes; 4) the perception of the risk of hospital infection mediated the relationship between the activation of behavioral immune system and medical-seeking attitude and tendency, participants who had higher core disgust or received disease-salient primes were more likely to perceive the medical-seeking situations as infectious, which subsequently led the participants to adopt more negative attitude toward medical-seeking (indirect effect of disease prime: β = −0.03, SE = 0.02, 95% CI = [−0.08, −0.001]; indirect effect of core disgust: β = −0.04, SE = 0.03, 95% CI = [−0.11, −0.002]) and to display stronger patient-delay tendency (indirect effect of disease prime: β = 0.03, SE = 0.02, 95% CI = [0.004, 0.08]; indirect effect of core disgust: β = 0.05, SE = 0.04, 95% CI = [0.01, 0.17]) (see Figure 1).
    These results support our hypothesis, suggesting that the ancient behavioral immune system may have a negative effect on the medical-seeking behavior of contemporary society. These results are consistent with the evolutionary mismatch hypothesis and provide a new theoretical perspective for the further understanding of the medical-seeking behavior of modern human.

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    The effect of aging stereotypes on the quality of medical decision-making and the mediating role of attribution bias
    ZHANG Baoshan, JIN Dou, MA Mengjia, XU Ran
    2022, 54 (8):  951-963.  doi: 10.3724/SP.J.1041.2022.00951
    Abstract ( 88 )   HTML ( 8 )  
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    The quality of decision-making in older people decreases with age. In medical decision-making, poor medical decisions in older adults can have a range of adverse effects. Therefore, exploring the influencing factors of the quality of medical decision-making is necessary. Aging stereotypes are closely related to the quality of decision-making. Negative aging stereotypes will have a negative impact on the decision-making of older adults. However, the relationship between aging stereotypes and the quality of medical decision-making has not been fully studied, and the mechanism between the two remains unclear.
    As an important concept in social cognitive psychology, attribution bias is closely related to aging stereotypes and medical decision-making. When encountering behaviors or phenomena consistent with stereotypes, people are more inclined to attribute such behaviors internally to maintain the stereotypes. Furthermore, attribution bias is an important factor in decision-making, and the attribution bias of the older adults will have a significant impact on their subsequent treatment decisions. Nevertheless, the role of attribution bias in the relationship between aging stereotypes and medical decision-making in older adults remains unknown. Thus, this study attempts to clarify the relationship between aging stereotypes and medical decision-making and reveal the mediating role of attribution bias in the relationship between aging stereotypes and medical decision-making.
    This study has two experiments. Experiment 1 attempted to explore the relationship between aging stereotypes, attribution bias, and quality of medical decision-making in older adults. Experiment 2 attempted to further verify the relationship between the three by training attribution bias. Seventy-eight older adults were recruited as participants in Experiment 1 (see Table 1 for participants’ information). All participants were randomly assigned to the stereotypes threat group or the control group (see Table 1 for the results of t-test and Chi-square test of background variables between the two groups). Attribution bias and the quality of medical decisions in both groups were then measured.
    Eighty participants were recruited in Experiment 2 (see Table 2 for the detailed information). All participants were randomly assigned to the stereotypes threat group or the attribution bias intervention group (see Table 2 for the results of t-test and Chi-square test of background variables between the two groups). First, the aging stereotypes of all participants were activated. Participants in the stereotype threat group completed the same measurement as Experiment 1. Participants in the attribution bias intervention group completed attribution bias measurement and medical decision-making tasks after attribution bias training.
    SPSS 25.0 was used for the statistical analysis of the data. Experiment 1 found that the aging stereotypes negatively predicted the quality of medical decisions and increased the internal attribution bias. The internal attribution bias in the stereotype threat group was significantly higher than that in the control group, and the quality of medical decision-making was substantially lower than that in the control group (see Table 1 for the means and t-test results). The study also found that internal attribution bias was mediating in the relationship between aging stereotypes and medical decision quality. The results of the mediation effect test showed that aging stereotypes positively predicted the internal attribution bias, b = 0.60, SE = 0.09, t = 6.57, p < 0.001, 95% CI = [0.419, 0.784], internal attribution bias negatively predicted medical decision quality, b = −0.25, SE = 0.10, t = −2.43, p = 0.018, 95% CI = [−0.457, −0.045], aging stereotypes negatively predicted the medical decision quality, b = −0.52, SE = 0.10, 95% CI = [−0.725, −0.313]. Internal attribution bias mediated the relationship between aging stereotypes and medical decision quality, indirect effect = −0.15, Boot SE = 0.07, 95% CI = [−0.302, −0.033].
    Results of Experiment 2 show that the internal attribution bias of participants in the attribution bias intervention group was significantly lower than that in the stereotypes threat group, and the quality of medical decision-making was significantly higher than that in the stereotypes threat group (see Table 2 for the means and t-test results). That is, aging stereotypes negatively affected the quality of medical decisions, and internal attribution played a mediating role between the two. Furthermore, the control training of attribution bias can effectively alleviate the adverse effects of stereotypes in old age.
    This study enriches the previous research on the influence of stereotypes on decision-making. It has certain practical value for alleviating the negative effect of stereotypes in older adults and improving the quality of individual medical decision-making.

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    A multipath model of leader after-hours electronic communication expectations and employee job performance
    LI Xin, LIU Pei, LI Aimei, WANG Xiaotian, ZHANG Junwei
    2022, 54 (8):  964-978.  doi: 10.3724/SP.J.1041.2022.00964
    Abstract ( 94 )   HTML ( 8 )  
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    In the digital economy era, leaders exert influence during work hours and non-work hours, expecting employees to be available after work hours and responsive to work-related matters immediately via electronic communication devices, henceforth named “after-hours electronic communication expectations” (AECE). Previous studies have suggested the pros and cons of AECE on employees’ job performance. A comprehensive framework that explains the mixed findings, however, is missed. The current study, drawing upon conservation of resources theory, proposes that leader AECE may affect employees’ job performance through three resource paths. Specifically, in the resource gain path, leader AECE improves employees’ job performance through organization-based self-esteem. In the resource loss path, leader AECE reduces job performance through stress perception. In the resource threat path, leader AECE reduces job performance through reputation maintenance concerns. Furthermore, we consider employee self-leadership as an important boundary condition and suggest that it can strengthen the resource gain effect and weaken the resource loss and threat effects (see Figure 1).

    To verify the theoretical framework, we carried out an experimental study (Study 1) and a multi-wave, multi-source field study (Study 2). In Study 1, we recruited 224 full-time employees to participate in the experiment; 4 participants were dropped because they failed to pass the attention test or selected the same option for all items. Participants were randomly assigned to either the treatment group (i.e., high leader AECE group, n = 111) or the control group (i.e., low leader AECE group, n = 109). We first asked participants to imagine that they received a message from their supervisor at 9 PM. Then, different WeChat screenshots with AECE manipulation were provided. Specifically, in the treatment group (i.e., high AECE condition), leader sent three messages to express high AECE such as “Please respond ASAP”, as well as four unconnected voice calls. In the control group (i.e., low AECE condition), the leader sent two messages to express low AECE such as “Take your time, contact me when you are free”. After reading different screenshots, participants were instructed to complete measurements of a manipulation test, organization-based self-esteem, stress perception, reputation maintenance concerns, and demographic information.

    Study 1 revealed that compared to the control group, participants in the treatment group reported higher levels of organization-based self-esteem (Treatment group: M = 4.21, SD = 0.42; Control group: M = 3.68, SD = 0.49; t(218)= 8.67, p < 0.001, Cohen’s d = 1.17). Similarly, there were significant differences in stress perception among participants from different groups (Treatment group:M = 3.78, SD = 1.01; Control group:M = 2.97, SD = 1.02; t(218)= 5.94, p < 0.001, Cohen’s d = 0.80). In addition, participants in the treatment group experienced more reputation maintenance concerns (M = 4.06, SD = 0.70) than those in the control group (M = 3.40, SD = 0.64), t(218)= 7.26, p < 0.001, Cohen’s d = 0.98. This finding confirmed the causal relationship between leader AECE and three mediators.

    To improve external validity and test the full model, we conducted a multi-wave, multi-source field study. In Study 2, our sample comprised 418 full-time employees from state-owned enterprise in Guangdong Province and their direct supervisors initially. We collected data in three waves, with one month apart. In the first wave, the employees reported leader AECE, self-leadership, conscientiousness and demographic information. In the second wave, organization-based self-esteem, stress perception and reputation maintenance concerns were measured. In the third wave, we invited employees’ direct supervisors to report theses followers’ job performance. Finally, our sample included 346 employees, yielding a valid response rate of 82.78%.

    The means, standard deviations, correlations, and reliabilities among all variables are presented in Table 1. Study 2 supported the resource gain path; that is, leader AECE was positively related to subordinates’ organization-based self-esteem (b = 0.09, p = 0.047). Also, organization-based self-esteem was positively related to job performance (b = 0.23, p < 0.001). A significant indirect effect of leader AECE on job performance via organization-based self-esteem was found (b = 0.02, SE = 0.01, 95% CI = [0.002, 0.047]). In the resource loss path, employees who received AECE from the leader were more likely to experience stress perception (b = 0.16, p = 0.008). But stress perception was not significantly related to job performance (b = 0.01, ns). In the resource threat path, leader AECE was positively related to reputation maintenance concerns (b = 0.16, p = 0.008) and reputation maintenance concerns was negatively related to job performance (b = -0.17, p = 0.002). Results also found that reputation maintenance concerns played a significant mediating role (b = -0.03, SE = 0.01, 95% CI = [-0.066, -0.006]). Furthermore, self-leadership moderated the effect between leader AECE and reputation maintenance concerns (b= -0.24, p = 0.002), such that the effect was insignificant when self-leadership was high (b= 0.01, ns), whereas a positive relationship was found when self-leadership was low (b= 0.25, p < 0.001; see Figure 2). Also, self-leadership moderated the indirect effect of leader AECE on job performance via reputation maintenance concerns, such indirect effect was insignificant when self-leadership was high (b = -0.001, SE = 0.01, 95% CI = [-0.022, 0.019]), whereas the indirect effect was insignificant when self-leadership was low (b = -0.04, SE = 0.02, 95% CI = [-0.092, -0.013]).

    This study makes several important contributions. First, drawing on conservation of resources theory, we developed a new theoretical framework to investigate both the positive and negative effects of leader AECE on employees’ job performance, helping form a more comprehensive and dialectical understanding of the mixed effects. Second, by identifying the mediating mechanisms underlying the relationship between leaders’ AECE and job performance, this study explains why such a new phenomenon (i.e., leader AECE) has effects on employees. Third, the exploration of boundary condition is beneficial to provide guidance for mitigating the negative effects of leaders’ AECE.

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    Try something new together: Joint consumption fosters choice of unfamiliar products
    RAN Yaxuan, ZHANG Puyue, CHEN Siyun, XIANG Diandian
    2022, 54 (8):  979-995.  doi: 10.3724/SP.J.1041.2022.00979
    Abstract ( 101 )   HTML ( 13 )  
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    Joint consumption is pervasive in daily life, such as watching movies with friends, eating out with family, and shopping for communal kitchens with roommates. Comparing with individual consumption, decisions in joint consumption are distinct in various aspects. The number of existing studies on joint consumption is increasing year by year, but the research topics are too scattered to form a system. Previous research can be divided into three categories: driving factors, decision results and their influencing factors and subsequent consequences. However, very few studies have examined whether consumers would behave differently in the context of individual and joint consumption. In the current research, we extend the extent literature by examining how consumer respond to exploration behavior when shopping either individually or with others.
    Choosing between familiar and unfamiliar products is one of the most common forms of exploratory behavior. Perceived risk is an important factor affecting this choice. According to the risky shift theory, an individual in a group has greater risk-taking tendencies than when alone because sharing the decision result could weaken the perceived risk of each group member. In addition, there are researches showing mere being accompanied by others also decreases risk perception. Therefore, we inference that comparing with individual consumption, consumers in joint consumption would perceive less risk so that they prefer unfamiliar options. Nonetheless, the main hypothesis is limited. In the light of product category risk and impression management, this effect appears only when individuals face with low-risk products and are with close companions. The research framework is shown in Figure 1.
    Five studies were conducted to examine our hypotheses. As a lab experiment, Study 1a (N = 138) was a 2 (consumption situation: individual vs. joint) between-subjects design, which proved that participants in the joint condition (67.57%) were more likely to choose the unfamiliar product than those in the individual condition (50%; χ2 (1) = 2.94, p = 0.086, φ = 0.17; Figure 2).
    Study 1b (N = 263) repeated the main effect with a 3 (consumption situation: individual vs. joint with friends vs. joint with families) between-subjects design and also excluded the potential influence of relationship type on this effect. Comparison between groups showed (Figure 3) that comparing with participants consuming individually (45.2%), those consuming with friends (60.2%; χ2 (1) = 3.53, p = 0.060, φ = 0.15) and those with family members (60.7%; χ2 (1) = 4.23, p = 0.040, φ = 0.15) had higher preference for the unfamiliar restaurant. Meanwhile, there was no significant difference between the two joint consumption situations (p = 0.943).
    And by changing the manipulation and measurement method, Study 2 (N = 150) verified the mediating effect of perceived risk (indirect effect = 0.33, SE = 0.16, 95% CI: [0.0137, 0.6536]; Figure 4) with a 2 (consumption situation: individual vs. joint) between-subjects design. And it also ruled out the alternative explanation of emotional arousal (indirect effect = 0.088, SE = 0.071, 95% CI: [−0.0178, 0.2555]).
    Study 3 (N = 213) was 3 (consumption situation: individual vs. joint with a close friend vs. joint with a distant friend) between-subjects design. It identified two important moderating variables. On the one hand, by comparing individual and joint with a close friend situations, there was no significant difference in decision outcomes of high-risk products, such as movie (t(143) = 0.08, p = 0.934), movie theater (t(143) = 0.56, p = 0.580) and hand sanitizer (t(143) = 0.74, p = 0.458). We can only investigate the effect of joint consumption among low-risk products, such as popcorn (M individual = 4.93, SD = 1.42; M close friend = 5.36, SD = 1.20; t(143) = 2.00, p = 0.048, d = 0.33). On the other hand, shown in Figure 5, participants with close friends (M close friends = 5.36, SD = 1.20) were more interested in unfamiliar products than those consuming alone (M individual = 4.93, SD = 1.42; t(143) = 1.86, p = 0.048, d = 0.33) and those consuming with distant friends (M distant friend = 4.96, SD = 1.190; t(140) = 2.04, p = 0.044, d = 0.36). There was no significant difference between the latter two groups (p = 0.906). Additionally, it examined the mediating role of perceived risk (indirect effect = 0.04, SE = 0.03, 90% CI: [0.0013, 0.0864]) and excluded the alternative explanation of diffusion of responsibility (indirect effect = −0.01, SE = 0.01, 90% CI: [−0.0347, 0.0112]).
    Study 4 (N = 148) extended the scope of application of this main effect with a 2 (consumption situation: individual vs. joint) between-subjects design. The result showed that even when faced with daily choices in non-consumption situations, participants under joint consumption showed exploratory behavior (Mindividual = 1.17, SD = 1.08; Mjoint = 1.66, SD = 1.16; t(146) = 2.61, p = 0.010, d = 0.44).
    Our investigation suggests that joint consumption (vs. individual consumption) encourages consumers to try new and unfamiliar products/services through a decreased perception of consumption risk. This effect would be attenuated when consumers are shopping with distant companions or when consumers face the choice of high-risk products/services. Our findings supplement the literature on joint consumption, exploration behavior and risk-shift theory, while practically suggesting that managers can integrate the joint consumption context into the new product promotion process by defining product positioning.

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    A simple and effective new method of Q-matrix validation
    LI Jia, MAO Xiuzhen, WEI Jia
    2022, 54 (8):  996-1008.  doi: 10.3724/SP.J.1041.2022.00996
    Abstract ( 70 )  
    Cognitive diagnostic theory (CDT) can provide fine-grained and multidimensional process assessment results, which has important research and practical values. The Q-matrix that represents the relationship between items and attributes, is the basis of CDT. The accuracy of the Q-matrix is an important factor that affects the accuracy of items parameter estimation and participants' diagnosis. Therefore, it is of great significance to check the correctness of the Q-matrix or to validate it. A lot of studies have been carried out on the estimation or validation of Q-matrix, and a variety of methods have been proposed from different perspectives, each having their advantages and disadvantages. The methods based on model-data fit can provide rich test information without the need of complex parameter estimation and time-consuming and tedious calculation. Following this line of thinking, this study used Gini coefficient to express the purity of expected numbers proportion distribution, and constructed a simple and efficient Q-matrix validation method, called the optimization of response distribution purity (ORDP) method, which is suitable for both simplified model and saturated model.
    Residual index (R), root mean square error approximate (RMSEA) and hamming distance (HD) were compared to evaluate the performances with varied influencing factors, under the conditions of two different distribution of knowledge states (KS) (uniform distribution, multidimensional normal distribution), two different sample sizes (300, 1000), two different test lengths (20, 30), Q-matrix error rates (20%, 40%), item qualities ([0.05, 0.25], [0.05, 0.24]) and attribute hierarchical structures (independent structure, linear structure, convergent structure, and branched structure). The specific algorithm of Q-matrix validation is as follows. Firstly, the initial Q-matrix is represented by Q0. When validating the first item j, the initial q-vector of item j in Q0 is replaced with one of all possible q-vectors, leaving the rest of the items intact. Then, the EM algorithm is used to estimate the item parameters and the knowledge states of the participants. Lastly, the q-vector that minimizes ORDP, R, RMSEA, or HD for the q-vector of the item is selected.
    Simulation results demonstrate that: (1) The distribution of KS affects the performance of each method. Specifically, when the KS is uniformly distributed, ORDP method is superior to other methods, HD method is the next, followed by RMSEA and R methods; When the KS follows multivariate normal distribution, there is no significant difference between RMSEA and ORDP. RMSEA method is slightly better than ORDP method except independent structure, followed by HD and R method; (2) The validation effect of these methods under multivariate normal distribution is not as good as that under uniform distribution; (3) The validation rates of the four methods all affected by sample sizes, test lengths, Q-matrix error rates, item qualities and attribute hierarchical structures. If the smaller the number of respondents, the shorter the test length, the higher the Q-matrix error rates, or the lower the item quality, the worse the performance of each method will be, and vice versa; (4) The validation results based on the fractional subtraction data of Tatsuoka (1984) show that the Q-matrix modified by ORDP method has the best model-data fit.
    In this study, the ORDP index representing the purity of the expected numbers proportion distribution was constructed based on the Gini coefficient. Simulation and empirical studies show that this method has a high validation rate for Q-matrices under different conditions. On the whole, the new method proposed in this study validates the Q-matrix through data analysis, which can reduce the workload of experts and thus improve the correctness of the Q-matrix.
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