Child protection investigations: Discourse analysis and the management of incommensurability

This paper asks whether discourse analytic approaches in social psychology have yet produced methodologies adequate to the investigation of institutional ‘gaze’. Institutional language has been explored to the extent that state agencies construct members of the public by speaking about them in particular ways. This has often provided insight into the co-existence and competition of incommensurable discourses. However, studies of representation in the sense of speaking for have been notably absent from social psychology. It is argued that this aspect of discourse is a vital component in the study of contemporary governmental multi-agency strategy in the area of child protection, where recent legislation and policy aims at the coordination of incommensurable discourses. A methodology for studying this strategy is outlined through an account of the actor network approach in science studies, accounts of the State under the post-modern condition, and analyses of sections of interviews with social workers.     

对语义网络中概念非类属关系的实验研究

本研究包括三个实验。实验一在混和呈现条件下比较被试对隐喻句和类属句的加工时问,发现可理解性高的隐喻句的R_T不比类属句的慢。实验二在分组呈现条件下比较被试加工隐喻句与类属句的速度,结果与实验一基本相同。实验一、二中还发现类属概念的层次与语义加工时间没有必然联系。实验三比较了隐喻句对三类概念的启动作用,发现隐喻对自身的语义特征概念有明显的启动作用。根据三个实验的结果,我们提出了一种称为特征联结的语义网络结构模型。     

柯林斯语义层次网络模型的实验研究

应用语义验证法对柯林斯与奎利安的语义层次网络模型进行研究,结果表明:(1)柯林斯等人的语义层次网络模型不完全适用于人脑的信息加工;(2)被试对主语所指称客体的熟悉程度是决定语义验证时间的一个重要因素;(3)被试提取概念各属性的时间并非完全由属性储存的位置决定的。     

Clinicians and supervisors' experiences with developing practices of open dialogue in network meetings in public mental health services

Open Dialogue is a dialogical approach focusing on the perspectives of patients and their social networks on treatment and recovery processes. As part of a larger research project, this prospective cohort study explores what promotes and hinders the development of Open Dialogue in network meetings (ODNM) based on the experiences of thirty-seven clinicians and seven supervisors. Multistage focus group interviews were used to collect data and were analysed thematically. We generated two main themes: (1) togetherness and isolation and (2) challenging and evolving. The findings show that ODNM can be developed in public mental healthcare, but this leads to both challenges and opportunities at the organisational level, such as conflicting perspectives, the difficulty of maintaining interest in ODNM, the need for committed and involved leaders, and the growing change in the traditional view of treatment, which has made clinicians collaborate more with patients and their relatives.     

The organization of construal networks and functional adaptation

This review examined the association of construal network organizations with functional adaptation and psychological well-being. Recent neuropsychological research supports the presence of distinct construal networks in the brain that organize action at different levels of goals and tasks. Construal networks are sets of connected construals, or mental representations of objects, events, and behaviors. Little attention, however, has been given to how the organization of construal networks promotes functional adaptation. Cognitive processes, construal levels, personal meaning, cultures, and situations influence the configurations of construal networks. The reviewed evidence indicated that construal network organization facilitates functional adaptation and well-being, either though the coherence or fit of the assembled construals with each other or through the mediation of their fit with situations or contexts, like a culture. This review goes beyond previous studies by describing the constructive, creative, and hypothetical aspects of construal organizations and their effects on functional adaptation and psychological well-being.     

Acute exercise and children’s cognitive functioning: What is the optimal dose of cognitive challenge?

Acute bouts of exercise have the potential to benefit children’s cognition. Inconsistent evidence on the role of qualitative exercise task characteristics calls for further investigation of the cognitive challenge level in exercise. Thus, the study aim was to investigate which “dose” of cognitive challenge in acute exercise benefits children’s cognition, also exploring the moderating role of individual characteristics. In a within-subject experimental design, 103 children (M_age = 11.1, SD = 0.9, 48% female) participated weekly in one of three 15-min exergames followed by an Attention Network task. Exergame sessions were designed to keep physical intensity constant (65% HR_max) and to have different cognitive challenge levels (low, mid, high; adapted to the ongoing individual performance). ANOVAs performed on variables that reflect the individual functioning of attention networks revealed a significant effect of cognitive challenge on executive control efficiency (reaction time performances; p = .014, ƞ²_p = .08), with better performances after the high-challenge condition compared to lower ones (ps < .015), whereas alerting and orienting were unaffected by cognitive challenge (ps > .05). ANOVAs performed on variables that reflect the interactive functioning of attention networks revealed that biological sex moderated cognitive challenge effects. For males only, the cognitive challenge level influenced the interactive functioning of executive control and orienting networks (p = .004; ƞ²_p = .07). Results suggest that an individualized and adaptive cognitively high-challenging bout of exercise is more beneficial to children’s executive control than less challenging ones. For males, the cognitive challenge in an acute bout seems beneficial to maintain executive control efficiency also when spatial attention resources cannot be validly allocated in advance. Results are interpreted referring to the cognitive stimulation hypothesis and arousal theory.     

Eating Disorder Symptom and Fear Change Trajectories During Imaginal Exposure Therapy: A Slope Network Analysis

Eating disorders (EDs) are characterized by fears related to food, body image, and social evaluation. Exposure-based interventions hold promise for targeting a range of ED fears and reducing ED psychopathology. We investigated change mechanisms and optimal fear targets in imaginal exposure therapy for EDs using a novel approach to network analysis. Individuals with an ED (N = 143) completed up to four online imaginal exposure sessions. Participants reported ED symptoms and fears at pretreatment, posttreatment, and 6-month follow-up. We constructed networks of symptoms (Model 1), fears (Model 2), and combined symptoms and fears (Model 3). Change trajectory networks from the slopes of symptoms/fears across timepoints were estimated to identify how change in specific ED symptoms/fears related to change in other ED symptoms/fears. The most central changing symptoms and fears were feeling fat, fear of weight gain, guilt about one’s weight/shape, and feared concerns about consequences of eating. In Model 3, change in ED fears bridged to change in desire to lose weight, desiring a flat stomach, following food rules, concern about eating with others, and guilt. As slope networks present averages of symptom/fear change slopes over the course of imaginal exposure therapy, further studies are needed to examine causal relationships between symptom changes and heterogeneity of change trajectories. Fears of weight gain and consequences of eating may be optimal targets for ED exposure therapy, as changes in these fears were associated with maximal change in ED pathology. Slope networks may elucidate change mechanisms for EDs and other psychiatric illnesses.     

A Psychometric Network Perspective on the Validity and Validation of Personality Trait Questionnaires

This article reviews the causal implications of latent variable and psychometric network models for the validation of personality trait questionnaires. These models imply different data generating mechanisms that have important consequences for the validity and validation of questionnaires. From this review, we formalize a framework for assessing the evidence for the validity of questionnaires from the psychometric network perspective. We focus specifically on the structural phase of validation, where items are assessed for redundancy, dimensionality, and internal structure. In this discussion, we underline the importance of identifying unique personality components (i.e. an item or set of items that share a unique common cause) and representing the breadth of each trait's domain in personality networks. After, we argue that psychometric network models have measures that are statistically equivalent to factor models but we suggest that their substantive interpretations differ. Finally, we provide a novel measure of structural consistency, which provides complementary information to internal consistency measures. We close with future directions for how external validation can be executed using psychometric network models. © 2020 European Association of Personality Psychology     

Towards end-to-end likelihood-free inference with convolutional neural networks

Complex simulator-based models with non-standard sampling distributions require sophisticated design choices for reliable approximate parameter inference. We introduce a fast, end-to-end approach for approximate Bayesian computation (ABC) based on fully convolutional neural networks. The method enables users of ABC to derive simultaneously the posterior mean and variance of multidimensional posterior distributions directly from raw simulated data. Once trained on simulated data, the convolutional neural network is able to map real data samples of variable size to the first two posterior moments of the relevant parameter's distributions. Thus, in contrast to other machine learning approaches to ABC, our approach allows us to generate reusable models that can be applied by different researchers employing the same model. We verify the utility of our method on two common statistical models (i.e., a multivariate normal distribution and a multiple regression scenario), for which the posterior parameter distributions can be derived analytically. We then apply our method to recover the parameters of the leaky competing accumulator (LCA) model and we reference our results to the current state-of-the-art technique, which is the probability density estimation (PDA). Results show that our method exhibits a lower approximation error compared with other machine learning approaches to ABC. It also performs similarly to PDA in recovering the parameters of the LCA model.     

A multiplex view of leadership structure in management teams

In the hope of complementing the structural perspective in upper echelon research and advancing a fine-grained understanding of dyadic leadership influence in management teams, the current study combines two types of intrateam structures—leadership network and friendship network—to create a multidimensional conceptualization of leadership structure in management teams. Specifically, we propose that management teams with a denser singular leadership network (i.e., a network consisting of many leadership ties that are not coupled with friendship ties) should have lower management team cohesion, which subsequently renders worse business unit performance. To contrast, management teams with a denser multiplex network (i.e., a network consisting of many leadership ties that are coupled with friendship ties) should have higher management team cohesion, which subsequently renders better business unit performance. Guided by structural contingency perspective, we further propose that management team task interdependence will strengthen team cohesion's positive impact on business unit performance. To test the hypothesized model, we collected team-level social network data and multiple-wave survey data from 697 managers nested in 148 hotels (i.e., 148 management teams) owned by a large hospitality company. We also obtained objective performance data for each hotel (i.e., occupancy percentage rate and revenue per available room per day) as the criterion measure. The data supported our hypotheses. The theoretical and practical implications of our findings are discussed.