Subjects: Psychology >> Developmental Psychology submitted time 2024-04-08
Abstract： Parental coping socialization encompasses the interactive process through which parents impart cognitive, emotional, and behavioral strategies to their offspring, aiming to equip them with the essential abilities to effectively manage and navigate challenging situations. Empirical research, considering perspectives such as long-term developmental timelines, real-time contexts, and their integrations, has explored the implications of parental coping socialization, revealing its unique effects on the adjustment of children and adolescents. This study integrates these two models and proposes a dynamic process theory model of coping socialization based on a dynamic systems perspective. It refines the mechanisms of parental coping socialization in the adjustment of children and adolescents, considering both the long-term developmental and real-time situational timelines. This comprehensive model encompasses both the individual level of children and adolescents and the dyadic level of parent-child interactions. Future research can investigate the universality of parental coping socialization effects, delving deeper into the mechanisms by which parental coping socialization influences children and adolescents’ adjustment and their bidirectional relationships. This knowledge would provide a scientific basis for applying and promoting parental coping socialization in family education and clinical interventions.
Subjects: Psychology >> Cognitive Psychology submitted time 2024-01-14
Abstract： The spatial-numerical association of response codes (SNARC) effect is a phenomenon in which the leftward response is faster than the rightward response for smaller numbers, whereas for larger numbers, the rightward response is faster than the leftward response. Although the existence of the SNARC effect has been examined in many studies, most of these studies focused on the symbolic SNARC effect and neglected to explore the non-symbolic SNARC effect. Little is known about how symbolic and non-symbolic SNARC effects develop and whether there are differences in the cognitive mechanisms involved in these two effects. The present study aimed to simultaneously investigate the developmental characteristics and cognitive mechanisms of symbolic and non-symbolic SNARC effects to contribute to the understanding of number processing.
In Experiment 1, a large-sample cross-sectional method was used with four age groups to explore the developmental characteristics of symbolic and non-symbolic SNARC effects. Thirty-six 6- to 7-year-old children, 59 7- to 8-year-old children, 69 8- to 9-year-old children and 31 adults performed the symbolic and non-symbolic parity judgement task. Experiment 2 was based on dual coding theory and the findings from Experiment 1. In this experiment, 137 children aged 8 to 9 years, the key age at which symbolic and non-symbolic SNARC effects are observed, were selected as participants and followed longitudinally for six months to explore whether the two SNARC effects had similar cognitive mechanisms. Phonological ability, visuospatial ability, visual working memory and phonological working memory were measured at T1. At T2 (after 6 months), the participants' symbolic and non-symbolic SNARC effects were measured. The symbolic and non-symbolic SNARC effects at T1 were controlled.
The findings of this study were as follows. (1) The non-symbolic SNARC effect emerged in 6- to 7-year-old children, while the symbolic SNARC effect emerged in 8- to 9-year-old children. Thus, the non-symbolic SNARC effect emerged earlier than the symbolic SNARC effect. (2) There were no significant age differences in the symbolic or non-symbolic SNARC effects. (3) For 8- to 9-year-old children and adults with both symbolic SNARC effects and non-symbolic SNARC effects, these two effects were not significantly correlated. (4) Phonological ability and phonological working memory at T1 significantly predicted the development of the symbolic SNARC effect at T2 but not the development of the non-symbolic SNARC effect at T2. Visuospatial ability and visual working memory at T1 significantly predicted the development of the non-symbolic SNARC effect at T2 but not the development of the symbolic SNARC effect.
In conclusion, 8 to 9 years is the critical age at which symbolic and non-symbolic SNARC effects emerge simultaneously, and there is no significant difference in the size of the SNARC effects according to age. Furthermore, phonological ability and phonological working memory contribute to the symbolic SNARC effect, whereas visuospatial ability and visual working memory contribute to the non-symbolic SNARC effect. These findings suggest a difference in the cognitive mechanisms of these two SNARC effects. These findings support the hypothesis of the separation of symbolic and non-symbolic SNARC effects and extend dual coding theory.
Peer Review Status:
Awaiting Review
Subjects: Psychology >> Psychological Measurement submitted time 2023-12-21
Abstract： Situational Judgment Tests (SJTs) have gained popularity for their unique testing content and high face validity. However, traditional SJT formats, particularly those employing multiple-choice (MC) options, have encountered scrutiny due to their susceptibility to test-taking strategies. In contrast, open-ended and constructed response (CR) formats present a propitious means to address this issue. Nevertheless, their extensive adoption encounters hurdles primarily stemming from the financial implications associated with manual scoring. In response to this challenge, we propose an open-ended SJT employing a written-constructed response format for the assessment of teacher competency. This study established a scoring framework leveraging natural language processing (NLP) technology to automate the assessment of response texts, subsequently subjecting the system's validity to rigorous evaluation. The study constructed a comprehensive teacher competency model encompassing four distinct dimensions: student-oriented, problem-solving, emotional intelligence, and achievement motivation. Additionally, an open-ended situational judgment test was developed to gauge teachers' aptitude in addressing typical teaching dilemmas. A dataset comprising responses from 627 primary and secondary school teachers was collected, with manual scoring based on predefined criteria applied to 6,000 response texts from 300 participants. To expedite the scoring process, supervised learning strategies were employed, facilitating the categorization of responses at both the document and sentence levels. Various deep learning models, including the convolutional neural network (CNN), recurrent neural network (RNN), long short-term memory (LSTM), C-LSTM, RNN+attention, and LSTM+attention, were implemented and subsequently compared, thereby assessing the concordance between human and machine scoring. The validity of automatic scoring was also verified.
This study reveals that the open-ended situational judgment test exhibited an impressive Cronbach's alpha coefficient of 0.91 and demonstrated a good fit in the validation factor analysis through the use of Mplus. Criterion-related validity was assessed, revealing significant correlations between test results and various educational facets, including instructional design, classroom evaluation, homework design, job satisfaction, and teaching philosophy. Among the diverse machine scoring models evaluated, CNNs have emerged as the top-performing model, boasting a scoring accuracy ranging from 70% to 88%, coupled with a remarkable degree of consistency with expert scores (r= 0.95, QWK=0.82). The correlation coefficients between human and computer ratings for the four dimensions—student-oriented, problem-solving, emotional intelligence, and achievement motivation—approximated 0.9. Furthermore, the model showcased an elevated level of predictive accuracy when applied to new text datasets, serving as compelling evidence of its robust generalization capabilities.
This study ventured into the realm of automated scoring for open-ended situational judgment tests, employing rigorous psychometric methodologies. To affirm its validity, the study concentrated on a specific facet: the evaluation of teacher competency traits. Fine-grained scoring guidelines were formulated, and state-of-the-art NLP techniques were used for text feature recognition and classification. The primary findings of this investigation can be summarized as follows: (1) Open-ended SJTs can establish precise scoring criteria grounded in crucial behavioral response elements; (2) Sentence-level text classification outperforms document-level classification, with CNNs exhibiting remarkable accuracy in response categorization; and (3) The scoring model consistently delivers robust performance and demonstrates a remarkable degree of alignment with human scoring, thereby hinting at its potential to partially supplant manual scoring procedures.
Subjects: Psychology >> Developmental Psychology submitted time 2023-11-15
Abstract： Learning engagement, an important indicator of the learning process, has garnered extensive attention. Developmental contextualism and the integrative model of engagement posit that the interaction between individuals and environmental factors results in heterogeneous learning engagement development among individuals. Previous studies have demonstrated learning engagement heterogeneity among primary school students. However, in the context of the “double reduction” policy, the dynamic development of children’s learning engagement remains unclear. Moreover, positive parenting style, teacher-student relationships, and peer relationships, as important environmental factors, may predict children’s learning engagement transitions. Thus, this study adopts a people-centered research method to address these issues from a longitudinal perspective.
This study recruited participants from three ordinary public primary schools in Shandong Province, China. Participants at T1 (June 2021, before the implementation of the “double reduction” policy) were 378 children (164 boys; mean age: 9.97 ± 0.91 years old). Participants at T2 (December 2021, six months after the implementation of the policy) were 357 primary school students (155 boys; mean age: 10.50 ± 0.94 years old). Participants at T3 (June 2022, a year after the implementation of the policy) were 347 primary school students (147 boys; mean age:10.97 ± 0.91 years old). Students completed the Children’s Learning Engagement Scale (at T1, T2, and T3), Short−form Egna Minnen av Barndoms Uppfostran (at T1 and T2), Student Teacher Relationship Scale (at T1 and T2) and Children’s Peer Relationship Scales (at T1 and T2) during the three measurements. Latent profile analysis and latent transition analysis were employed in this study to explore children’s potential learning engagement subtypes and examine transitions between different subtypes across the three waves. Multiple logistic regressions were also used to investigate the impact of various environmental factors (i.e., positive parenting style, student−teacher relationships, and peer relationships) on the latent transitions of different learning engagement subtypes.
All data were analyzed by SPSS 26.0 and Mplus 8.0. The results revealed four distinct subgroups of learning engagement among primary school students: the “Low Engaged”, “Moderately Engaged”, “High Absorption with Vigorous Disengagement”, and “Highly Engaged” groups. In addition, due to the “double reduction” policy, students in the “Moderately Engaged” and “Highly Engaged” groups displayed relative stability, while those in the “Highly Disengaged” group tended to transition toward the “Moderately Engaged” group. Regarding the “High Absorption with Vigorous Disengagement” group, the findings indicated a higher likelihood of transitioning to the “Moderately Engaged” group from T1 to T2; however, from T2 to T3, these students were more likely to remain in their original subgroup. Moreover, the study identified the varying roles of different environmental factors in children’s learning engagement subgroups. Specifically, under the “double reduction” policy, positive parenting style and teacher–student relationships exhibited robust effects on children’s learning engagement transitions. The predictive effects of teacher-student relationships varied across different learning engagement subtypes among primary school students. Additionally, the study found that peer relationships had a positive influence on the transition of children within the “Moderately Engaged” group following the implementation of the “double reduction” policy.
This study provides the first evidence of heterogeneity and dynamic changes in learning engagement among Chinese primary school students, which indicates that following the implementation of the “double reduction” policy, family–school–collaborative education has made initial progress. These findings not only enhance our understanding of the dynamic development of learning engagement among primary school students but also provide empirical evidence regarding the effectiveness of the “double reduction” policy implementation.
Subjects: Psychology >> Statistics in Psychology submitted time 2023-10-07
Abstract： Hierarchical data, which is observed frequently in psychological experiments, is usually analyzed with the linear mixed-effects models (LMEMs), as it can account for multiple sources of random effects due to participants, items, and/or predictors simultaneously. However, it is still unclear of how to determine the sample size and number of trials in LMEMs. In history, sample size planning was conducted based purely on power analysis. Later, the influential article of Maxwell et al. (2008) has made clear that sample size planning should consider statistical power and accuracy in parameter estimation (AIPE) simultaneously. In this paper, we derive a confidence interval width contours plot with the codes to generate it, providing power and AIPE information simultaneously. With this plot, sample size requirements in LMEMs based on power and AIPE criteria can be decided. We also demonstrated how to run sensitivity analysis to assess the impact of the magnitude of experiment effect size and the magnitude of random slope variance on statistical power, AIPE and the results of sample size planning.
There were two sets of sensitivity analysis based on different LMEMs. Sensitivity analysis Ⅰ investigated how the experiment effect size influenced power, AIPE and the requirement of sample size for within-subject experiment design, while sensitivity analysis Ⅱ investigated the impact of random slope variance on optimal sample size based on power and AIPE analysis for the cross-level interaction effect. The results for binary and continuous between-subject variables were compared. In these sensitivity analysis, two factors regarding sample size varied: number of subjects (I=10, 30, 50, 70, 100, 200, 400, 600, 800), number of trials (J=10, 20, 30, 50, 70, 100, 150, 200, 250, 300). The additional manipulated factor was the effect size of experiment effect (standard coefficient of experiment condition= 0.2, 0.5, 0.8, in sensitivity analysis Ⅰ) and the magnitude of random slope variance (0.01, 0.09 and 0.25, in sensitivity analysis Ⅱ). A random slope model was used in sensitivity analysis Ⅰ, while a random slope model with level-2 independent variable was used in sensitivity analysis Ⅱ. Data-generating model and fitted model were the same. Estimation performance was evaluated in terms of convergence rate, power, AIPE for the fixed effect, AIPE for the standard error of the fixed effect, and AIPE for the random effect.
The results are as following. First, there were no convergence problems under all the conditions , except that when the variance of random slope was small and a maximal model was used to fit the data. Second, power increased as sample size, number of trials or effect size increased. However, the number of trials played a key role for the power of within-subject effect, while sample size was more important for the power of cross-level effect. Power was larger for continuous between-subject variable than for binary between-subject variable. Third, although the fixed effect was accurately estimated under all the simulation conditions, the width 95% confidence interval (95%width) was extremely large under some conditions. Lastly, AIPE for the random effect increased as sample size and/or number of trials increased. The variance of residual was estimated accurately. As the variance of random slope increased, the accuracy of the estimates of variances of random intercept decreased, and the accuracy of the estimates of random slope increased.
In conclusion, if sample size planning was conducted solely based on power analysis, the chosen sample size might not be large enough to obtain accurate estimates of effects size. Therefore, the rational for considering statistical power and AIPE during sample size planning was adopted. To shed light on this issue, this article provided a standard procedure based on a confidence interval width contours plot to recommend sample size and number of trials for using LMEMs. This plot visualizes the combined effect of sample size and number of trials per participant on 95% width, power and AIPE for random effects. Based on this tool and other empirical considerations, practitioners can make informed choices about how many participants to test, and how many trials to test each one for.
Subjects: Psychology >> Educational Psychology submitted time 2023-09-27
Abstract： Reading is important for children’s future academic success. Clarifying the mechanisms underlying reading ability has been a heated issue in reading research for decades. Most previous studies have focused solely on reading comprehension but scarcely paid attention to the mechanisms underlying reading fluency throughout elementary school. Reading fluency at the text level has been acknowledged as one of the indicators of children’s overall reading competence. Therefore, the present study aimed to clarify the shareability and specificity of the mechanisms underlying Chinese children’s reading comprehension and reading fluency across different developmental stages.
We recruited a total of 416 Chinese children in grades 2, 4 and 6 (lower, middle and upper stages) of elementary school and were then followed up for half a year. In the fall semester (Time 1), a series of tasks, including general cognitive ability; working memory; phonological, orthographic and morphological awareness; rapid automatized naming (RAN); word recognition accuracy; word recognition fluency and vocabulary knowledge, were administered. In the second or spring semester (Time 2), reading comprehension and reading fluency were administered. Three mediation models were fitted to the data with T1 morphological awareness and RAN as predictors, T1 word recognition accuracy, word recognition fluency, and vocabulary knowledge as mediators and T2 reading comprehension and reading fluency as outcomes. The remaining variables were controlled in all the three models.
Results indicated that morphological awareness and RAN significantly predicted reading comprehension and reading fluency at T2 via word recognition accuracy among children in the lower stage after controlling for the effects of T1 general cognitive ability, T1 working memory and T1 phonological and orthographic awareness. The mediating effect of T1 word recognition fluency in the contribution of T1 RAN to T2 reading fluency was also significant. However, in the middle and upper stages, the indirect effects of T1 morphological awareness and T1 RAN on T2 reading comprehension were not significant; for T2 reading fluency, the mediating role of T1 word recognition accuracy in the effect of T1 morphological awareness was significant in both stages, but the mediated role of T1 word recognition fluency was only significant in the middle stage. Moreover, T1 RAN contributed to it via T1 word recognition accuracy and fluency.
These findings attest to both the shareability and specificity in the mechanisms underlying reading comprehension and reading fluency across different developmental stages. These findings suggest that reading fluency should be incorporated as a legitimate index of children’s reading ability. They further imply that the developmental stages require consideration when exploring the mechanisms underlying the effects of morphological awareness and RAN on reading abilities (comprehension and fluency). This study provides empirical evidence for understanding the science of reading development among Chinese children and has important implications for future reading research and educational intervention.
Subjects: Psychology >> Social Psychology submitted time 2023-08-17
Sun, Xiaomin
Yang, Shuting
Kong, Xiaoshan
Liu, Zhenzhen
Ma, Rongzi
Yuan, Yue
Zhang, Nan
Jiang, Xinying
Cao, Peiling
Bao, Ruiji
Lin, Yiqin
Li, Ning
Li, Zhihang
Abstract： Time poverty is a pervasive sensation of having insufficient time in daily life, which is detrimental to physical and mental health and well-being. At present, the conceptual framework of time poverty remains unclear, and its association with well-being is inconsistent and lacks causal evidence and a comprehensive understanding of the underlying mechanisms. This study aims to disambiguate the meaning of time poverty, create a multidimensional theoretical model, devise an assessment scale, and establish a national database of time poverty in China. Drawing from scarcity theory, we examine the impact of time poverty on individual and interpersonal well-being and the possible mediating role of over-productivity orientation. Lastly, we investigate the impact of time poverty on family well-being and its underlying mechanisms based on the spillover-crossover model.
Subjects: Psychology >> Experimental Psychology Subjects: Psychology >> Cognitive Psychology submitted time 2023-06-30
Abstract： Signal detection theory (SDT) has been widely applied to explain the decision-making process in different types of cognitive tasks. However, one important limitation of classical SDT is that it is difficult to illustrate the mental mechanisms underlying the setting of response criterion. The current article discusses the decision rule in signal detection tasks from the perspective of Bayesian decision theory (BDT). I first introduce the basic idea of BDT based on the Bayes’ theorem. Next, I discuss how BDT explains the decision rule of ideal observer, and characterizes the deviation between actual participants and ideal observer in empirical signal detection tasks. I then discuss the difference between classical SDT and BDT in unequal variance signal detection model. Finally, I briefly introduce the empirical research evidence supporting BDT.
Peer Review Status:Awaiting Review
Subjects: Psychology >> Developmental Psychology submitted time 2023-04-11
Abstract： Given the high prevalence rate and its extensive possible adverse outcomes, a large number of theoretical and longitudinal studies have explored the development of social anxiety, but the research findings are inconsistent or even contradictory in preschool childhood, late childhood, and adolescence. In addition, there is still debate between trait theory and state theory of social anxiety, and there is also a lack of study on the age trend of social anxiety stability.
To clarify the above controversies and accurately characterize the age trend of the mean level and the stability of social anxiety, this study conducted a meta-analysis of longitudinal studies involving social anxiety. After pre-registering the study protocol on PROSPERO, we searched literature in six databases (CNKI, Wanfang Data, Web of Science, ProQuest, PubMed, andEBOSCO). In addition, we also backtracked the references cited in previous meta-analyses and reviews. Ultimately, a total of 192 independent samples (N = 170,192) from 173 longitudinal studies were included in the current meta-analysis. In order to quantify the trajectory of social anxiety more precisely, we divided the sample into 11 age groups according to the mean age of the sample between two adjacent measurement waves, and estimated the mean-level change and stability for each age group. The standardized mean difference (d) between two adjacent waves is used to estimate mean-level change, whereas the correlation coefficient (r) is used to estimate stability. Science most of the included studies reported multiple effect sizes, and these multiple effect sizes were most likely dependent, which violated the basic assumption of independent effect sizes in the conventional meta-analytic methods. We applied the three-level meta-analysis approach to handle such data-independency among effect sizes.
Results showed that: (1) The mean level of social anxiety showed a gradual decline from toddlerhood to early adulthood, with only slight increase in mid-adolescence. (2) In terms of rank-order stability, social anxiety rose slowly from toddlerhood to preschool childhood, then swiftly dropped to a low point in elementary childhood, recovered gradually after mid-adolescence, and stabilized at a high level in young adulthood. (3) The mean-level change of social anxiety was not affected by the study characteristics, the participant characteristics, and the variable characteristics. (4) The rank-order stability of social anxiety was moderated by written language, continent, culture, gender, and assessment mode. (5) The stability of social anxiety was a logarithmic function with time lag. Specifically, with the increase of time lag, the stability declined first quickly and then slowly, and almost reached a plateau after 6 years. (6) The results of moderator test for publication status, Egger's test, and Begg's test indicated the absence of publication bias in this meta-analysis.
This study makes a valuable contribution in characterizing the age-specific trends and stability of social anxiety from toddler to young adult by using the meta-analytic method. We conclude from this study that, in terms of mean level, the trajectory of social anxiety generally supports the personality maturation hypothesis. For stability, similar to personality traits, social anxiety tend to be a trait rather than a state construct. Overall, this study provides a new perspective for exploring the lifelong development of social anxiety.
Subjects: Psychology >> Statistics in Psychology submitted time 2023-01-31
Abstract： With the advancement of research depth in psychology and the development of data collection technics, interest in Mixed-Effects Location-Scale Models (MELSM) has increased drastically. When residual variances are heterogeneous, these models are able to add predictors in different levels, then help explore the relationship among traits and simultaneously investigate the inter- and intra-individual variability, as well as their explanatory variables. This study includes both simulated studies and empirical studies. In detail, the main contents of this project are: 1) Comparing and selecting candidate models based on Bayesian fit indices to construct MELSM; 2) Planning sample size according to both power analysis and accuracy in parameter estimation analysis for MELSM; 3) Extending the sample size planning method for MELSM to better frame the considerations of uncertainty; 4) Developing an R package for MELSM and illustrating the application of MELSM in empirical psychological studies. Based on the study, we hope these statistical models can be widely implemented. Moreover, the reproducibility and replicability of psychological studies will be enhanced finally.
Peer Review Status:Awaiting Review
Subjects: Psychology >> Management Psychology submitted time 2023-01-30
Abstract：
With the booming development of digital economy and digital technology, digital transformation has changed from an "optional" choice for some leading enterprises to a "mandatory" requirement for more enterprises. However, many companies face several problems in the digital transformation process such as slow performance growth and insufficient transformation sustainability. Among possible reasons for these problems, the misfit between employees' digital competencies, digital technologies, and digital job demands (i.e., individual-task-technology misfit) is the main one. Therefore, understanding how employees can proactively change the digital job environment and increase individual-task-technology fit to improve job performance has both theoretical and practical implications. Based on the job crafting research and individual-task-technology fit theory, this project proposes a new concept called digital job crafting and explore the mechanisms for the effect of digital job crafting on employees' job performance. Meanwhile, from the perspectives of colleagues, leaders, and organizational structure, this project will examine digital job crafting support, digital leadership, and
organizational formalization as potential boundary conditions of the relationship between digital job crafting and job performance. We intend to test our hypotheses using focus group interviews, case studies, multi-source and multi-wave surveys, and daily diary surveys. This project will contribute to expanding digital job research from a proactive adaptation perspective and initiate new research themes for job crafting research. It also provides theoretical guidance and practical intervention plans for employees to proactively adapt to digital transformation and gain digital intelligence dividends.
Peer Review Status:Awaiting Review
Subjects: Psychology >> Cognitive Psychology submitted time 2023-01-18
Abstract：
How semantics are represented in human brain is a central issue in cognitive neuroscience. Previous studies typically address this issue by artificially manipulating the properties of stimuli or task demands. Having brought valuable insights into the neurobiology of language, this psychological experimental approach may still fail to characterize semantic information with high resolution, and have difficulty quantifying context information and high-level concepts. The recently-developed natural language processing (NLP) techniques provide tools to represent the discrete semantics in the form of vectors, enabling automatic extraction of word semantics and even the information of context and syntax. Recent studies have applied NLP techniques to model the semantic of stimuli, and mapped the semantic vectors onto brain activities through representational similarity analyses or linear regression. A consistent finding is that the semantic information is represented by a vastly distributed network across the frontal, temporal and occipital cortices. Future studies may adopt multi-modal neural networks and knowledge graphs to extract richer information of semantics, apply NLP models to automatically assess the language ability of special groups, and improve the interpretability of deep neural network models with neurocognitive findings.
Peer Review Status:Awaiting Review
Subjects: Psychology >> Educational Psychology submitted time 2023-01-03
Abstract：
Elementary school students are at a critical stage of learning to read, and their language abilityand cognitive development require a large amount of reading materials that are appropriately difficult andconducive to comprehension. Current leveled reading mainly relies on shallow and quantitative text indicators, such as characters, words, and sentence level lexical properties, which is less suitable for thecharacteristics of Chinese ideographs and children's cognitive development needs. This study first usedmeta-analysis to glean eight qualitative cognitive indicators, including genre, theme, character, storyline, language feature, text structure, background knowledge, and life experience. Then we used the SOLOtaxonomy to develop a standardized grading description for each indicator that satisfied the developmental stages of children’s cognitive ability. Finally, we constructed the Qualitative Grading Standard for ChineseChildren’s Books and its operation manual. The follow-up empirical study showed that the qualitativeindicators had high discriminability, raters’ consistency reliability and predictive validity, and thus couldbeused to evaluate children’s books in an objective, reliable and valid way. In short, our Standard will helpschool teachers, book editors, and parents determine the appropriate grade level for children's books anduse Chinese leveled reading to promote children's language and cognitive development so that theycanachieve independent reading as early as possible.
Commenting
Commenting
Dispute
Subjects: Psychology >> Cognitive Psychology submitted time 2022-07-15
Abstract：
Learning and memory constitute the basis of individual survival and development. Improving learning and memory is the focus of psychology and neuroscience. Many recent studies have revealed that the reward and memory systems are structurally and functionally connected and that rewards can promote memory. The midbrain dopamine system and the hippocampal system are related in terms of structure and function. Rewards affect memory via encoding and consolidation by reference to different mechanisms. During the memory encoding stage, a reward can activate the reward system and the attentional control system and can cause more cognitive resources to be allocated to reward-related information, thus promoting memory with respect to reward information. During the memory consolidation stage, a reward can increase the release of dopamine that acts on the processing of reward-related information in the hippocampus, thus producing better memory in the context of reward information. Future research can focus on the complex patterns exhibited by the influence of rewards on behavior and that of intrinsic rewards on learning and memory.
Peer Review Status:Awaiting Review
Subjects: Psychology >> Psychological Measurement Subjects: Psychology >> Clinical and Counseling Psychology submitted time 2022-01-26
Abstract：
Symptoms of Autistic Spectrum Disorders (ASD) manifest as early as infancy, and the earlier detection and intervention can lead to better therapeutic results. The traditional tools of early screening and diagnosis of autism have limitations in evaluation methods and procedures, which cannot meet the needs of large-scale screening and diagnosis. With the rapid artificial intelligence technological advancement, using an intelligent approach for large-scale non-inductive early screening and diagnosis of autism has become possible. In the past decade, a myriad of research findings on intelligent detection technology of autism were generated domestically and internationally in six aspects: behaviors in classic tasks, facial expressions and emotions, eye gaze data, brain imaging, motor control and movement patterns, and multimodal data. Future research should focus on constructing a domestic intelligent medical screening and diagnosis system for early autism, developing screening tools for infants and young children, constructing an automated recognition model for autistic infants by integrating multimodal data, establishing a refined autism diagnosis method combined with brain imaging technology, and other aspects.
Peer Review Status:Awaiting Review
Subjects: Psychology >> Psychological Measurement submitted time 2021-12-04
Abstract： Computer-based problem-solving tests can record respondents’ response processes in real time as they explore tasks and solve problems and save them as process data. We first introduce the analysis process of process data and then present a detailed description of the new advances in feature extraction methods and capability evaluation modeling commonly used for process data analysis with respect to the problem-solving test. Future research should pay attention to improving the interpretability of analysis results, incorporating more information in feature extraction, enabling capability evaluation modeling in more complex problem scenarios, focusing on the practicality of the methods, and integrating and drawing on analytical methods from different fields.
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 >> Social Psychology submitted time 2021-11-04
Abstract： Disparagement humor refers to communication that contains denigration but elicits amusement. Relief theory, superiority theory, incongruity-resolution theory, and benign violation theory attempt to explain the psychological mechanism. Humor does not always arise from disparagement. The humorous effect is influenced by the group identity and attitude of the receiver, the psychological distance between the receiver and the target of disparagement, and the receiver’s personality and cultural background. Disparagement humor could contribute to the release of prejudice and the legitimation of social dominance orientation, but has inconsistent effect on interpersonal relations. The proposed Integrative Process Model of Disparagement Humor describes the mechanisms, precursors, and consequences of disparagement humor in tandem and could serve as a scaffold for future research. Future research should also devote more attention to the negative social impacts of disparagement humor and the corresponding interventions, the potential positive effects of disparagement humor on intergroup relations and social equity, as well as the disparagement humor emerging from Chinese socio-cultural background. " " "
Peer Review Status:Awaiting Review
Subjects: Psychology >> Psychological Measurement submitted time 2021-08-06
Abstract： The rapid development and application of artificial intelligence technology has promoted the intelligentization of mental health assessment. Being intelligent could solve the issues of traditional mental health assessment methods and decrease the rate of misdiagnosis and improve diagnosis efficiency, which is critical to the general investigation and early warning of mental health problems. Currently, an intelligent mental health assessment is in the initial stage of development. Related studies have explored the field mainly driven by data, in which researchers use online behavioral data and data from portable devices, aiming to achieve a higher prediction accuracy. However, the interpretability of assessment results is not yet ideal. In view of these problems, more emphasis should be laid on the knowledge and experience in the field of psychology, by which the research could be more pertinent, refined, reliable, and valid. These are essential directions for the further development and application of intelligent mental health assessment.
Subjects: Psychology >> Cognitive Psychology submitted time 2021-07-30
Abstract： Auditory word recognition involves complex cognitive processing. Blind people have certain advantages of auditory compensatory in word processing. However, due to the lack of visual input, the blind suffer more challenges in auditory word processing related with visual perceptual experience (e.g., color terms). Future research should focus on (1) the word categorization based on the relationship with visual experience; (2) the multifaceted effects and neuropsychological mechanisms of factors in auditory word recognition, including phonology, orthography, and semantics, in order to develop the special model of spoken word processing conforming to the perceptual characteristics of the blind; (3) developmental studies in different ages. Finally, to reveal the overall mechanism of the effect of blindness on auditory word recognition of the blind.
Peer Review Status:Awaiting Review
Hits
YES
Hits
Downloads
Comment