An adaptive network model covering metacognition to control adaptation for multiple mental models

Learning processes can be described by adaptive mental (or neural) network models. If metacognition is used to regulate learning, the adaptation of the mental network becomes itself adaptive as well: second-order adaptation. In this paper, a second-order adaptive mental network model is introduced for metacognitive regulation of learning processes. The focus is on the role of multiple internal mental models, in particular, the case of visualisation to support learning of numerical or symbolic skills. The second-order adaptive network model is illustrated by a case scenario for the role of visualisation to support learning multiplication at the primary school.     

基于网络理论的物质成瘾新视角

物质成瘾是一种涉及生理、心理和环境等多因素的复杂现象, 但是当前基于生物还原论的解释对物质成瘾现象整体性的理解和康复研究造成了阻碍。网络理论聚焦于心理障碍变量之间相互作用形成的反馈环路, 从整体视角为研究物质成瘾提供了新的理论框架。将网络理论应用于物质成瘾的研究中将有利于:(1)理解症状之间的相互关系和影响; (2)理解症状网络的整体性和系统性动态变化过程; 以及(3)将多层次和多水平因素整合到统一的理论框架中。从网络理论视角来理解物质成瘾, 也将对未来的干预和治疗提供了理论支持。目前, 网络理论仍处于言语模型阶段, 未来需要进一步提出更具体、可验证的统计模型, 以完善对于物质成瘾机制的了解, 更加有效地推进物质成瘾的治疗与恢复。     

Attributional style of the mother as a predictor of aggressive behavior of the child

The association between the life orientation and attributional styles of a mother and the aggressiveness of her child were studied in 61 mothers and their children, 23 boys and 38 girls, mean age 6.6 years (range 4–13 years). The mother's life orientation and attributional styles were established during interviews using the life-style questionnaire, and a child's aggressiveness was evaluated by the mother using the Health Examination Survey. The factors assessing life orientation were lack of personal control, causal unstability, internal locus of causality, personal responsibility, and democratic educational attitudes. The mother's personal responsibility and internal causal attributions were related to nonaggressiveness in the child, whereas mothers with a lack of personal control were likely to have aggressive children. Educational attitudes were of no importance. The results showed no sex- or age-related variance.     

Sex differences in the perceived causal structure of date rape: A preliminary report

The present study examines the perceived causes of date rape by the use of network analysis. The 142 subjects in the study were presented with grids containing 9 causes listed by row and column. They were asked to indicate if they belived there was a causal link between each of the 72 causal pairings. The resulting network placed emphasis on male and female drunkenness, norms of dating, and society's attitude to date rape as distal causes of date rape. Misunderstanding of behavior by men, male attitude that date rape is unimportant, and need by males for dominance were seen as proximal causes. Further networks for each sex were constructed: these showed clear division of opinion on the causes of date rape. © 1995 Wiley-Liss, Inc.     

Is the news making us unhappy? The influence of daily news exposure on emotional states

There is evidence that exposure to negative news is making people feel bad, but not much is known about why this only affects some people or whether this also applies to everyday news exposure. This study examined the direct and indirect effects of daily news exposure on people's affective states. Using ecological momentary assessment (EMA), 63 respondents (24 men and 39 women) reported their news exposure and affective states five times a day for 10 days. In addition, personal relevance of the news and personality characteristics, neuroticism and extraversion, were assessed. Results showed that negative news perceptions were related to more negative affect and less positive affect, and these effects were moderated by personal relevance, but not personality characteristics. The implications of these outcomes are discussed.     

Making Americans Feel Great Again? Personal Significance Predicts Political Intentions of Losers and Winners of the 2016 U.S. Election

Reactions of losers and winners of political elections have important consequences for the political system during times of power transition. In four studies conducted immediately before and after the 2016 U.S. presidential elections, we investigated how personal significance induced by success or failure of one's candidate is related to hostile versus benevolent intentions toward political adversaries. We found that the less significant supporters of Hillary Clinton and supporters of Donald Trump felt after an imagined (Study 1A) or actual (Study 2) electoral failure the more they were willing to engage in peaceful actions against the elected president and the less they were willing to accept the results of the elections. However, while significance gain due to an imagined or actual electoral success was related to more benevolent intentions among Clinton supporters (Study 1B), it was related to more hostile intentions among Trump supporters (Studies 1B, 2, and 3).     

Quantifying the Interplay of Semantics and Phonology During Failures of Word Retrieval by People With Aphasia Using a Multiplex Lexical Network

Investigating instances where lexical selection fails can lead to deeper insights into the cognitive machinery and architecture supporting successful word retrieval and speech production. In this paper, we used a multiplex lexical network approach that combines semantic and phonological similarities among words to model the structure of the mental lexicon. Network measures at different levels of analysis (degree, network distance, and closeness centrality) were used to investigate the influence of network structure on picture naming accuracy and errors by people with Anomic, Broca's, Conduction, and Wernicke's aphasia. Our results reveal that word retrieval is influenced by the multiplex lexical network structure in at least two ways—(a) the accuracy of production and error type on incorrect productions were influenced by the degree and closeness centrality of the target word, and (b) error type also varied in terms of network distance between the target word and produced error word. Taken together, the analyses demonstrate that network science techniques, particularly the use of the multiplex lexical network to simultaneously represent semantic and phonological relationships among words, reveal how the structure of the mental lexicon influences language processes beyond traditionally examined psycholinguistic variables. We propose a framework for how the multiplex lexical network approach allows for understanding the influence of mental lexicon structure on word retrieval processes, with an eye toward a better understanding of the nature of clinical impairments, like aphasia.     

Age-Specific Effects of Lexical–Semantic Networks on Word Production

The lexical–semantic organization of the mental lexicon is bound to change across the lifespan. Nevertheless, the effects of lexical–semantic factors on word processing are usually based on studies enrolling young adult cohorts. The current study aims to investigate to what extent age-specific semantic organization predicts performance in referential word production over the lifespan, from school-age children to older adults. In Study 1, we conducted a free semantic association task with participants from six age-groups (ranging from 10 to 80 years old) to compute measures that capture age-specific properties of the mental lexicon across the lifespan. These measures relate to lifespan changes in the Available Richness of the mental lexicon and in the lexical–semantic Network Prototypicality of concrete words. In Study 2, we used the collected data to predict performance in a picture-naming task on a new group of participants within the same age-groups as for Study 1. The results show that age-specific semantic Available Richness and Network Prototypicality affect word production speed while the semantic variables collected only in young adults do not. A richer and more prototypical semantic network across subjects from a given age-group is associated with faster word production speed. The current results indicate that age-specific semantic organization is crucial to predict lexical–semantic behaviors across the lifespan. Similarly, these results also provide cues to the understanding of the lexical–semantic properties of the mental lexicon and to lexical selection in referential tasks.     

Subjectifying the Personality State: Theoretical Underpinnings and an Empirical Example

Recent developments in personality research highlight the value of modelling dynamic state-like manifestations of personality. The present work integrates these developments with prominent clinical models addressing within-person multiplicity and promotes the exploration of models centred on state-like manifestations of personality that function as cohesive organizational units. Such units possess distinct subjective qualities and are characterized by specific affects, behaviours, cognitions, and desires that tend to be co-activated. As background, we review both theory and research from the fields of social cognition, psychotherapy, and psychopathology that serve as the foundation for such models. We then illustrate our ideas in greater detail with one well-supported clinical model—the schema therapy mode model, chosen because it provides a finite and definite set of modes (i.e. cohesive personality states). We assessed these modes using a newly developed experience-sampling measure administered to 52 individuals (four times daily for 15 days). We estimated intraindividual and group-level temporal and contemporaneous networks based on the within-person variance as well as between-person network. We discuss findings from exemplar participants and from group-level networks and address cross-model particularities and consistencies. In conclusion, we consider potential idiographic and nomothetic applications of subjective states dynamic personality research based on intensive longitudinal methods. © 2020 European Association of Personality Psychology     

Searching for Prosociality in Qualitative Data: Comparing Manual,Closed-Vocabulary,and Open-Vocabulary Methods

Although most people present themselves as possessing prosocial traits, people differ in the extent to which they actually act prosocially in everyday life. Qualitative data that were not ostensibly collected to measure prosociality might contain information about prosocial dispositions that is not distorted by self-presentation concerns. This paper seeks to characterise charitable donors from qualitative data. We compared a manual approach of extracting predictors from participants' self-described personal strivings to two automated approaches: A summation of words predefined as prosocial and a support vector machine classifier. Although variables extracted by the support vector machine predicted donation behaviour well in the training sample (N = 984), virtually, no variables from any method significantly predicted donations in a holdout sample (N = 496). Raters' attempts to predict donations to charity based on reading participants' personal strivings were also unsuccessful. However, raters' predictions were associated with past charitable involvement. In sum, predictors derived from personal strivings did not robustly explain variation in charitable behaviour, but personal strivings may nevertheless contain some information about trait prosociality. The sparseness of personal strivings data, rather than the irrelevance of open-ended text or individual differences in goal pursuit, likely explains their limited value in predicting prosocial behaviour. © 2020 European Association of Personality Psychology