Subjects: Psychology >> Cognitive Psychology Subjects: Psychology >> Social Psychology submitted time 2021-11-30
Abstract： " "
Peer Review Status:
Awaiting Review
Subjects: Psychology >> Psychological Measurement submitted time 2021-11-30
Abstract： Students' observed behavior (e.g., learning behavior and problem-solving behavior) comprises of activities that represent complicated cognitive processes and latent conceptions that are frequently systematically related to one another. Cognitive characteristics such as cognitive styles and fluency may differ between students with the same cognitive/knowledge structure. However, practically all cognitive diagnosis models (CDMs) that merely assess item response accuracy (RA) data are currently incapable of estimating or inferring individual differences in cognitive traits. With advances in technology-enhanced assessments, it is now possible to capture multimodal data, such as outcome data (e.g., response accuracy), process data (e.g., response times (RTs), and biometric data (e.g., visual fixation counts (FCs)), automatically and simultaneously during the problem-solving activity. Multimodal data allows for precise cognitive structure diagnosis as well as comprehensive feedback on various cognitive characteristics. First, using joint analysis of RA, RT, and FC data as an example, this study elaborated three multimodal data analysis methods and models, including separate modeling (whose model is denoted as S-MCDM), joint-hierarchical modeling (whose model is denoted as H-MCDM) (Zhan et al., 2021), and joint-cross-loading modeling (whose model is denoted as C-MCDM). Following that, three C-MCDMs with distinct hypotheses were presented based on joint-cross-loading modeling, namely, the C-MCDM-θ, C-MCDM-D, and C-MCDM-C, respectively. Three C-MCDMs, in comparison to the H-MCDM, introduce two item-level weight parameters (i.e., φi and λi) into the RT and FC measurement models, respectively, to quantify the impact of latent ability or latent attributes on RT and FC. The Markov Chain Monte Carlo method was used to estimate model parameters using a full Bayesian approach. To illustrate the three proposed models' application and compare them to the S-MCDM and H-MCDM, multimodal data for a real-world mathematics test was used. Data was gathered at a prominent university on the East Coast of the United States in an eye-tracking lab. An I = 10 mathematics items test was given to N = 93 university students with normal or corrected vision. The test included K = 4 attributes, and the related Q-matrix is shown in Figure 3. The data is divided into three modalities: RA, RT, and FC, which were all collected at the same time. The data was fitted to all five multimodal models. In addition, two simulation studies were conducted further to explore the psychometric performance of the proposed models. The purpose of simulation study 1 was to explore whether the parameter estimates of the proposed models can converge effectively and explore the recovery of parameter estimation under different simulated test situations. The purpose of simulation study 2 was to explore the relative merits of C-MCDMs and H-MCDM, that is, to explore the necessity of considering cross-loading in multimodal data analysis. The results of the empirical study showed that (1) the C-MCDM-θ has the best model-data fitting, followed by the H-MCDM and the S-MCDM. Although the DIC showed that the C-MCDM-D and C-MCDM-C also fitted the data well, the results were only for reference because some parameter estimates in these two models did not converge; that (2) the correlation coefficients between latent ability and latent processing speed and that between latent ability and latent concentration were weak, making it difficult to fully exploit the theoretical advantages of H-MCDM over S-MCDM (Ranger, 2013). By contrast, since the C-MCDM-θ can directly utilize the information from RT and FC data, the standard error of the estimates of its latent ability was significantly lower than that of the previous two competing models; and that (3) the median of the estimates of φi was less than 0, which indicated that for most items, the higher the participant’s latent ability is, the longer the time it will take to solve the items; and the median of the estimates of λi was higher than 0, which indicated that for most items, the higher the participant’s latent ability is, the more number of fixation counts he/she shown in problem-solving. Furthermore, it should be noted that the estimates of φi and λi do not always have the same sign for different items, indicating that the influence of latent abilities on RT and FC has different directions (i.e., facilitation or inhibition) for different items. Furthermore, simulation study 1 indicated that the parameter estimation of the proposed three models could converge effectively and the recovery of model parameters was good under different simulated test situations. The results of simulation study 2 indicated that the adverse effects of ignoring the possible cross-loadings are more severe than redundantly considering the cross-loadings. Overall, the results of this study indicate that (1) fusion analysis is more suitable for multimodal data that provides parallel information than separate analysis; that (2) through cross-loading, the proposed models can directly use information from RT and FC data to improve the parameter estimation accuracy of latent ability or latent attributes; that (3) the results of the proposed models can be used to diagnose cognitive structure and infer other cognitive characteristics such as cognitive styles and fluency; and that (4) the proposed models have better compatibility with different test situations than H-MCDM.
Peer Review Status:Awaiting Review
Subjects: Psychology >> Statistics in Psychology submitted time 2021-11-29
Abstract： Assessment datasets contaminated by non-effortful responses may lead to serious consequences if not handled appropriately. Previous research has proposed two different strategies: down-weighting and accommodating. Down-weighting tries to limit the influence of aberrant responses on parameter estimation by reducing their weight. The extreme form of down-weighting is the detection and removal of irregular responses and response times (RTs). The standard residual-based methods, including the recently developed residual method using an iterative purification process, can be used to detect non-effortful responses in the framework of down-weighting. In accommodating, on the other hand, one tries to extend a model in order to account for the contaminations directly. This boils down to a mixture hierarchical model (MHM) for responses and RTs. However, to the authors’ knowledge, few studies have compared standard residual methods and MHM under different simulation conditions. It is unknown which method should be applied in different situations. Meanwhile, MHM has strong assumptions for different types of responses. It would be valuable to examine the performance of the method when the assumptions are violated. The purpose of this study is to compare standard residual methods and MHM under a fully crossed simulation design. In addition, specific recommendations for their applications are provided. The simulation study included two scenarios. In simulation scenario I, data were generated under the assumptions of MHM. In simulation scenario II, the assumptions of MHM concerning non-effortful responses and RTs were both violated. Simulation scenario I had three manipulated factors. (1) Non-effort prevalence (π), which was the proportion of individuals with non-effortful responses. It had three levels: 0%, 20% and 40%. (2) Non-effort severity (π_i^non), which was the proportion of non-effortful responses for each non-effortful individual. It varied between two levels: low and high. When π_i^non was low, π_i^non was generated from U (0, 0.25); while when π_i^non was high, π_i^non was generated from U (0.5, 0.75), where “U” denoted a uniform distribution. (3) Difference between RTs of non-effortful and effortful responses (d_RT). The difference between RTs from two groups, d_RT, had two levels, small and large. The logarithm of RTs of non-effortful responses were generated from normal distribution N (μ,0.52), where μ=-1 when d_RT was small, μ=-2 when d_RT was large. For generating the non-effortful responses, we followed Wang, Xu and Shang (2018), with the probability of a correct response g_j setting at 0.25 for all non-effortful responses. In simulation scenario II, only the first two factors were considered. Non-effortful RTs were generated from a uniform distribution with a lower bound of exp(-5) and upper bound being the 5th percentile of RT on item j with τ=0. The probability of a correct response for non-effortful responses was dependent on the ability level of each examinee. In all the conditions, sample size was fixed at I = 2,000 and test length was fixed at J = 30. For each condition, 30 replications were generated. For effortful responses, Responses and RTs were simulated from van der Linden’s (2007) hierarchical model. Item parameters were generated with a_j~U(1,2.5), b_j~N(0,1), 〖 α〗_j~U(1.5,2.5)， β_j~U(-0.2,0.2). For simulees, the person parameters (θ_i,τ_i) were generated from a bivariate normal distribution with the mean vector of μ=(0,0)'and the covariance matrix of Σ=[■(1&0.25@0.25&0.25)]. Four methods were compared under each condition: the original standard residual method (OSR), conditional estimate standard residual (CSR), conditional estimate with fixed item parameters standard residual method using iterative purifying procedure (CSRI), and MHM. These methods were implemented in R and JAGS using a Bayesian MCMC sampling method for parameter calibration. Finally, these methods were evaluated in terms of convergence rate, detection accuracy and parameter recovery. The results are presented as following. First of all, MHM suffered from convergence issues, especially for the latent variable indicating non-effortful responses. On the contrary, all the standard residual methods achieved convergence successfully. The convergence issues were more serious in simulation scenario II. Secondly, when all the items were assumed to have effortful responses, the false positive rate (FPR) of MHM was 0. Although the standard residual methods had FPR around 5% (the nominal level), the accuracy of parameter estimates was similar for all these methods. Third, when data were contaminated by non-effortful responses, CSRI had higher true positive rate (TPR) almost in all the conditions. MHM showed lower TPR but lower false discovery rate (FDR), exhibiting even lower TPR in simulation scenario II. When π_i^non was high, CSRI and MHM showed more advantages over the other methods in terms of parameter recovery. However, when π_i^non was high and d_RT was small, MHM generally had higher RMSE than CSRI. Compared to simulation scenario I, MHM performed worse in simulation scenario II. The only problem CSRI needed to deal with was its overestimation of time discrimination parameter across all the conditions except for when π=40% and d_RT was large. In a real data example, all the methods were applied to a dataset collected for program assessment and accountability purposes from undergraduates at a mid-sized southeastern university in USA. Evidences from convergence validity showed that CSRI and MHM might detect non-effortful responses more accurately and obtain more precise parameter estimates for this data. In conclusion, CSRI generally performed better than the other methods across all the conditions. It is highly recommended to use this method in practice because: (1) It showed acceptable FPR and fairly accurate parameter estimates even when all responses were effortful; (2) It was free of strong assumptions, which meant that it would be robust under various situations; (3) It showed most advantages when π_i^non was high in terms of the detection of non-effortful responses and the improvement of the parameter estimation. In order to improve the estimation of time discrimination parameter in CSRI, the robust estimation methods that down-weight flagged response patterns can be used as an alternative to directly removing non-effortful responses (i.e., the method in the current study). MHM can perform well when all its assumptions are met and π_i^non is high, d_RT is large. However, some parameters have difficulty in convergence under MHM, which will limit its application in practice.
Peer Review Status:Awaiting Review
Subjects: Psychology >> Developmental Psychology submitted time 2021-11-27
Abstract： " Autism spectrum disorder (ASD) is a neurodevelopmental disorder that originates from childhood, and social deficits are core symptoms of ASD, which is closely related to social motivation deficits. Social motivation theory suggests that social motivation is a powerful driving force to guide individuals’ social behavior. The theory also highlights that social behavior is mainly manifested in social orientation, social reward and social maintenance. Studies had shown that individuals with ASD have deficits in the development of social motivation, they tend to pay less attention to social stimuli, they not able to actively seek and experience happiness brought by social interaction, and lack the strategies to maintain social relations. However, related research results were affected by factors such as individual characteristics, environment and experimental design. In the future, it is important to comprehensively consider these factors to strengthen the integrated research on the social motivation theory of individuals with ASD, so as to accurately understand the social motivation deficits of individuals with ASD. "
Peer Review Status:Awaiting Review
Subjects: Psychology >> Cognitive Psychology submitted time 2021-11-26
Abstract：自生物心理社会模型提出以来，利用心理因素预防和治疗疼痛备受关注，越来越多的研究表明抑制功能在疼痛发展和恢复阶段起关键作用。疼痛诱发的自我防御机制通过争夺认知资源影响抑制功能，反之低抑制功能个体在应对疼痛干扰中表现较差，进而影响着疼痛的预期和学习。现有关于抑制功能影响疼痛的研究主要基于相关设计，未来应进一步明确二者的因果关系。深入理解疼痛与抑制功能相互作用的认知机制有助于指导抑制功能对慢性疼痛的靶向干预。
Peer Review Status:Awaiting Review
Subjects: Psychology >> Management Psychology submitted time 2021-11-26
Abstract： "
Peer Review Status:Awaiting Review
Subjects: Psychology >> Social Psychology submitted time 2021-11-24
Abstract： Punishment decisions might be guided by the norm of punishment, that is, people will implement their own punishment according to perceived prevalence of punishment in a similar social midst. However, there may be differences between an individual’s perception of norms and actual norms, which is called normative misperception. This article uses four experiments to explore the existence, the direction, and the cause of the normative misperception in third-party punishment, as well as its influence on people’s own punitive behaviors. In Experiment 1, 449 participants were randomized in a four group factorial design (punishing before estimating, estimating before punishing, punishing only, and estimating only). Experiment 1 consisted of 6 rounds of dictator game, in which participants made punishment decisions for 6 offers and/or estimated the average punishment level of other participants in each offer. Experiment 2 aimed to establish the causal relationship between the normative misperception and the punishment by directly manipulating the normative misperception. Specifically, 134 participants were randomly divided into the overestimation group and underestimation group. After receiving the feedback, participants made punishment decision for an unfair offer and estimated the level of punishment of others in this offer. The purpose of Experiment 3 was to test the model of belief in a just world (BJW)-normative misperception-punishment, as well as the moderating effect of perceived social distance (PSD), with a within-participants design involving 164 participants. The procedure was similar to that of Experiment 1, except that we measured participants’ BJW and PSD before and after the game, respectively. In Experiment 4, we manipulated participants’ BJW through reading materials to test the causal relationship between BJW and the normative misperception. The results of Experiment 1 showed that there is an underestimated normative misperception in third-party punishment, which leads to a lower level of punishment. Experiment 2 proved that there exists a causal relationship between the normative misperception and punishment by directly manipulating the independent variables. Experiment 3 demonstrated that BJW might be an underlying cause of the normative misperception, while PSD moderates the effect of BJW on the normative misperception. Finally, Experiment 4 showed the causal relationship between BJW and the normative misperception, providing additional evidence to the results of Experiment 3. To sum up, we have found evidence of normative misperception in third-party punishment through 4 experiments. This underestimated misperception might be affected by dual reference points: BJW (internal) and PSD (external). It also shows to a certain extent that third-party punishment is a norm-maintaining behavior rather than a gain-based strategic behavior. "
Subjects: Psychology >> Medical Psychology submitted time 2021-11-24
Abstract： Maintaining optimal hand hygiene is an important strategy for infection control and prevention, but how to increase adherence to hand hygiene practices has been a major challenge to prevent infectious diseases and reduce hospital acquired infections (HAIs). Hand hygiene nudging intervention based on behavioral science transforms hand washing behavior into an automatic triggering habit in a more “imperceptible” way, which makes up for many limitations of traditional hand hygiene intervention based on knowledge sharing and health education. Given on different influential mechanisms, hand hygiene nudging strategies can be classified into four categories: providing decision information, optimizing decision options, influencing decision structure and reminding decision direction. The effectiveness of multi-facet nudging strategies has also been confirmed in practice, but there is still a lack of hand hygiene nudging intervention in Chinese sociocultural contexts. The future direction is to carry out such nudging interventions in hospitals, schools, communities and other public places in China based on the theory of behavioral sciences, so as to contribute to the prevention and control of infectious diseases and improve public health. "
Peer Review Status:Awaiting Review
Subjects: Psychology >> Cognitive Psychology Subjects: Psychology >> Experimental Psychology Subjects: Psychology >> Social Psychology submitted time 2021-11-23
Abstract：面孔知觉可能在区域尺度上发生多维信息整合，但迄今无特异性实验证据。本研究在两个实验中操纵面孔眼睛区域或嘴巴区域的单维构型或特征信息，测量人们觉察单维变化或跨维共变的敏感度，以此检测面孔区域尺度上的多维信息整合有何现象与规律，进而揭示面孔知觉的多维信息整合机制。实验获得三个发现：（1）正立面孔眼睛区域的信息变化觉察呈现出“跨维共变增益效应”，跨维信息共变觉察的敏感度显著高于任意一种单维信息变化觉察的敏感度；（2）“跨维共变增益效应”只在正立面孔的眼睛区域出现，在倒置面孔的眼睛区域、正立面孔的嘴巴区域或倒置面孔的嘴巴区域都没有出现，因此具有面孔区域特异性和面孔朝向特异性；（3）就单维信息变化觉察而言，眼睛区域的敏感度不会受到面孔倒置的损伤，但是嘴巴区域的敏感度会受到面孔倒置的显著损伤。综合可知，面孔知觉确实会发生区域尺度上的信息整合，而且它不是普遍性的信息量效应，是特异性的（只发生在正立面孔的眼睛区域）将单维信息分辨和全脸多维整合联系起来的整合加工；提示我们对全脸多维信息知觉整合的理解需要从传统的面孔整体加工假设（face holistic processing hypothesis）扩展到以眼睛为中心的层级化（hierarchical）多维信息整合机制。
Peer Review Status:Awaiting Review
Subjects: Psychology >> Psychological Measurement submitted time 2021-11-23
Abstract： The problem of missing data is common in research, and there is no exception for cognitive diagnostic assessment (CDA). Some studies have revealed that both the presence of missing values and the selection of different missing data processing methods would affect the results of CDA. Therefore, it is necessary to attach more attention to the problem in CDA and choose appropriate methods to deal with it. Although the problem in CDA has been explored before, previous studies did not consider multiple imputation (MI) and full information maximum likelihood (FIML), which are widely used in the field of missing data analysis. Moreover, previous studies neglected the comparison using empirical data and saturation models such as GDINA model. In summary, the main purpose of this study are to introduce MI and FIML into CDA, thus making a comprehensive comparison of different missing data handling methods, and further putting forward suggestions for handling missing data in practice. Simulation study considered six factors: (1) Sample size: 200 participants, 400 participants, and 1000 participants; (2) Test length: 15 test items and 30 test items; (3) Quality of items: high quality, medium quality, and low quality; (4) Missing data mechanisms: missing completely at random (MCAR), missing at random (MAR), and missing not at random (MNAR); (5) Missing rate: 10%, 20%, and 30%; (6) Missing data handling methods: zero replacement (ZR), MI-CART, MI-PMM, MI-LOGREG.BOOT, Expectation-Maximization algorithm (EM), and FIML. The GDINA model was used, and the analysis process was realized by the GDINA package in R software. Secondly, the PISA 2015 computer-based mathematics data were applied to compare the practical value of the proposed methods. The results of simulation study revealed that: (1) Missing data results in a decrease in estimation accuracy. The absolute value of Bias and RMSE both increased and PCCR values of all methods decreased as the sample size, test length and the quality of the items decreased and the missing rate increased; (2) When estimating item parameters, EM performed best, followed by MI. Meanwhile, FIML and ZR methods were unstable; (3) When estimating the KS of participants, EM and FIML performed best as the missing data mechanism was MAR or MCAR. When the missing data mechanism was MNAR, EM, FIML and ZR performed best. The empirical study results further supported the simulation research results. It showed that: (1) For all empirical indicators, EM, FIML, and MI-PMM perform best on one or more indicators; (2) The results obtained under the empirical study and simulation study under the MNAR mechanism are very similar; (3) EM performs well on all indicators, and ZR and FIML methods are slightly worse than EM, followed by MI-PMM, LOGREG.BOOT and MI-CART. In addition, based on the research results, the following suggestions were provided: (1) EM and FIML should be the first choice. However, if researchers do not want to get the complete data set, FIML could be used as a priority for missing data handling; (2) When the missing data mechanism was MAR or MCAR and the test length was not enough, researchers should avoid using the ZR method to deal with missing data. Finally, this paper ends with the prospects of future researches: (1) The multilevel scoring situation should also be studied; (2) The effectiveness of these methods should be tested in longitudinal research; (3) The performance of more methods of information matrix can be further compared in calculating the standard error to handle missing data; (4) Future research could focus on the missing mechanisms of data onto the real data. "
Peer Review Status:Awaiting Review
Subjects: Psychology >> Applied Psychology submitted time 2021-11-22
Abstract： Default–based nudge has been increasingly used in recent years to improve the public approval of social policies. However, its effectiveness has also been questioned by the public and some scholars. A meta-analysis was conducted to explore the effect of default options and the related variables that may affect its effectiveness. A total of 56 empirical research and 92 studies were included through literature retrieval. Results of the meta-analysis are as follows: (1) A considerable effect of default options was observed, (2) The moderating analysis of cultural background revealed that the nudging effect of default options under Western culture was better than that under Eastern culture, and (3) Lastly, the moderating analysis showed a significant difference of default effect between different domains and that the nudging effect of default options was greater in the money–related domain than in the health and environmental domains.
Peer Review Status:Awaiting Review
Subjects: Psychology >> Management Psychology submitted time 2021-11-22
Abstract： "
Peer Review Status:Awaiting Review
Subjects: Psychology >> Cognitive Psychology submitted time 2021-11-20
Abstract： Both inhibition of return (IOR) and emotion have the characteristics of attentional bias and improving search efficiency. Previous studies mostly used single modality presentation of emotional stimuli to investigate the relationship between the two, but the results of the research are not consistent. Existing studies have shown that the congruent emotion of audiovisual dual modality can be integrated into the perceptual stage, which is the same as the processing stage of IOR. Therefore, the present study adopted the cue-target paradigm and used audiovisual dual modality to present emotional stimuli to further investigate the interaction between emotion and IOR. Experiment 1 was a three-factors within-subject design. We mainly manipulated the presentation of cue validity (cued vs. uncued), target modalities (visual vs. audiovisual) and emotion type (negative vs. neutral). The task of the subjects was to identify the emotional stimuli of visual modality. Experiment 2 was similar to Experiment 1, but the emotional congruency was changed. The audiovisual dual modality presented incongruent emotion stimuli (visual negative face-auditory neutral sound; visual neutral face-auditory negative sound) to further investigate whether the impact of the audiovisual dual modality emotional stimulus on IOR was caused by the emotional stimulus of the auditory modality, that is, whether the emotional stimulus of the auditory modality has been processed. In Experiment 1, the responses in the cued condition were slower than those in the uncued condition, which suggested that IOR occurred. More importantly, the interaction between emotion type and cue validity in the condition of audiovisual dual modality, which showed that congruent negative emotion produces less IOR effect (11 ms) than neutral emotion (25 ms). At the same time, the audiovisual dual modality condition produced less IOR effect (18 ms) than the visual single modality condition (40 ms). We also found a larger multisensory response enhancement effect in the congruent negative emotion than in the neutral emotion. In Experiment 2, the results showed that there was no interaction between emotion and IOR under the condition of audiovisual dual modality, and there was no significant difference in IOR effect between single modality and audiovisual dual modality. This indicated that the IOR effect was not influenced by the presence of incongruent emotion in audiovisual dual modality. In summary, the present study showed that the IOR effect was influenced only when the audiovisual dual modality presented the same emotion. Our findings revealed that IOR and audiovisual dual modality congruent emotion in the same processing stage had a mutual influence. Audiovisual dual modality congruent emotion weakened the IOR effect and the differences between the negative emotion and the neutral emotion showed the adaptability of IOR. At the same time, this study further supported the perceptual inhibition theory of IOR. "
Peer Review Status:Awaiting Review
Subjects: Psychology >> Management Psychology submitted time 2021-11-20
Abstract： " In the past, researchers generally believed that that servant leadership had a positive effect on employees, teams, and organizations. However, recent studies have showed that servant leadership can also cause potential negative outcomes. This paper focuses on the negative effects of servant leadership. First, we review the concept and extant research of servant leadership. Then, based on role stress theory, resource allocation theories of self-control, conservation of resources theory, implicit followership theory, leader-member exchange theory and leadership prototypes theory, we explore the negative effects of servant leadership and its buffer mechanism from the perspective of leaders themselves and subordinates, respectively. Finally, we propose the future research from the aspects of research level, method, perspective, and content."
Peer Review Status:Awaiting Review
Subjects: Psychology >> Clinical and Counseling Psychology submitted time 2021-11-19
Abstract： " Substance addicts show significant impulsivity, which manifests as substance abuse and difficulty in withdrawing. In addition to the problems of inhibition and executive control, driving force from multiple psychological dimensions is also an important reason for impulsive substance use. This drive stems from a variety of sources, including reward effect, S-R related cue response through conditioning and sensation-seeking personality trait. Low levels of inhibition are insufficient to resist the effects of the drive. Consequently, this unbalanced state will lead to a habitual tendency in behaviour or compulsion to use substances under addicts’ craving. These two types of behavior are the manifestation of addictive impulsivity. "
Subjects: Psychology >> Other Disciplines of Psychology submitted time 2021-11-19
Abstract： "
Peer Review Status:Awaiting Review
Subjects: Psychology >> Social Psychology Subjects: Psychology >> Physiological Psychology Subjects: Psychology >> Cognitive Psychology submitted time 2021-11-19
Abstract： Recipients often reject unfair offers at the cost of their own interests in ultimatum games (UGs), reflecting their fairness preference. Yet fairness preference is not invariable. It is affected by various factors, among which empathy plays an important role. Individuals might, for example, sacrifice own interests to help others in need. This kind of behavior not only is contrary to the pursuit of self-interest maximization but also violates fairness principles. As individuals are not only concerned about fairness but also care for others, this study focuses on managing the relationship between the two potentially conflicting goals. We explored individuals’ behaviors and time dynamic processes of brain activities when fairness conflicted with empathy. It was hypothesized that empathy could modulate fairness-related decision making behaviors and ERPs. Thirty-seven college students (26 females, 21.00 ± 2.07 years) participated in this study and completed multiple ultimatum games. EEG signals were recorded during play. In the task, the proposers were underprivileged students (empathy condition) and ordinary children (non-empathy condition). Each proposer distributed 10 yuan between themself and one recipient. The participants played as recipients who would choose to accept or reject distribution offers (fair, unfair–disadvantageous, unfair–advantageous) by the proposers. The proposers and recipients would get the assigned money only if participants accepted the distribution offers. They received nothing if participants rejected the offer. The behavioral results showed that the acceptance rate in the empathy condition was greater than that in the non-empathy condition for the disadvantageous–unfair condition, while the opposite result occurred in the advantageous–unfair condition. The EEG results showed that in the non-empathy condition, the advantageous–unfair offer induced more negative anterior N1 (AN1) than it did in the empathy condition, but there was no difference between the disadvantageous–unfair versus fair conditions. In the advantageous–unfair condition, the P2 amplitude of the empathy condition was significantly more positive than that for the non-empathy condition, while in the disadvantageous–unfair condition, P2 amplitude of the non-empathy condition was slightly positive than that of the empathy condition. The disadvantage–unfair offer induced more negative medial frontal negativity (MFN) in the empathy condition, while no difference was found between fair versus unfair offers in the non-empathy condition. Additionally, the amplitude of P3 was larger in the fair versus the unfair conditions as it was not modulated by empathy. These findings suggest that experimentally-induced state empathy modulates fairness-related decision making behaviors and accompanying neural activity. Behavioral results indicate that state empathy takes priority in guiding people's behavior when it conflicts with the fairness criterion. For EEG results, empathy mainly modulates the early stage of the fairness concern and affects early attention and motivation as well as cognition and emotion. In later stages, the higher cognitive process represented by P3 is modulated only by fairness, not empathy. In conclusion, our study systematically explored and compared behavior patterns of fairness processing with temporal dynamic characteristics of brain activities by modulating empathy. The findings provide further insight into fairness-related decision making behaviors. They indicate the potential to influence individuals’ behaviors and cognition by manipulating empathy." "
Peer Review Status:Awaiting Review
Subjects: Psychology >> Psychological Measurement submitted time 2021-11-16
Abstract： Computerized classification testing (CCT) has been widely used in eligibility testing and clinical psychology since it can efficiently classify participants. As an essential part of CCT, the termination rule determines when the test is to be stopped and what category the participants are ultimately classified into, directly affecting the test efficiency and classification accuracy. The existing termination rules can be roughly divided into the likelihood ratio, Bayesian decision theory, and confidence interval rules. And their core ideas are constructing hypothesis tests, designing loss functions, and comparing the relative positions of confidence intervals, respectively. Based on these ideas, in different test situations, CCT termination rules have various specific forms. Future research can further extend Bayesian rules, construct rules for multicategory MCCT, integrate process data into termination rules, and build rules under the framework of machine learning. In addition, from the perspective of practical requirement, all three types of rules have the potential to be applied in the eligibility test, while the clinical questionnaire tends to choose Bayesian rules.
Peer Review Status:Awaiting Review
Subjects: Psychology >> Social Psychology submitted time 2021-11-16
Abstract： Algorithm aversion refers to the phenomenon of people preferring human decisions but being reluctant to use superior algorithm decisions. The three-dimensional motivational model of algorithm aversion summarizes the three main reasons: the doubt of algorithm agents, the lack of moral standing, and the annihilation of human uniqueness, corresponding to the three psychological motivations, i.e., trust, responsibility, and control, respectively. Given these motivations of algorithm aversion, increasing human trust in algorithms, strengthening algorithm agents' responsibility, and exploring personalized algorithms to salient human control over algorithms should be feasible options to weaken algorithm aversion. Future research could further explore the boundary conditions and other possible motivations of algorithm aversion from a more social perspective. " "
Subjects: Psychology >> Psychological Measurement submitted time 2021-11-15
Abstract： Abstract： Post-traumatic stress disorder (PTSD) has negative effects on children's development, even into adulthood. However, traditional diagnostic methods are difficult to quickly, objectively, and accurately identify and diagnose PTSD in children. Machine learning, as an emerging method to deal with a large number of variables and data, has gradually been applied to the research of early prediction, recognition, and auxiliary diagnosis of PTSD in children. Machine learning, with its advantages in performance and algorithm, can be applied to the recognition and prognosis of PTSD in children. Compared with self-reported diagnosis, the process of identifying and diagnosing PTSD in children through machine learning has unique advantages of high efficiency, objective accuracy, and resource-saving. Machine learning also has limitations in terms of hardware cost, algorithm selection, and prediction accuracy. In the future, researchers need to further improve the accuracy of machine learning diagnosis and recognition of PTSD in children and combine machine learning algorithms with traditional diagnosis methods for more exploration and application.
Peer Review Status:Awaiting Review
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