Applying a Family-Ecosystemic Model to Reunite a Family Separated Due to Child Abuse: A Case Study

Family reunification following the removal of a child due to child abuse is a challenging process. In this case study the authors demonstrate the success of a family-ecosystemic intervention for achieving the reintegration of an adolescent into her family following a court-imposed separation. The SET (Structural Ecosytems Therapy) model was used to: (1) repair family bonds, (2) build collaborations among the agencies involved in overseeing the child's welfare, and (3) build an alliance between the mother and agency personnel. This case study suggests that facilitating such collaborations can be helpful in the evaluation and follow-through of high risk cases.     

创造性科学问题提出材料的编制及效度研究

本研究通过对收集的科学发明创造实例进行整理,测量,访谈,再测量,建立拥有多项指标的创造性科学问题提出材料库,以期为研究创造性科学问题提出提供有效的测试工具。在材料库的建立过程中,对问题提出中的原型启发效应进行了探讨,结果表明,原型对创造性问题提出具有稳定的启发效应,并且这种启发效应在具有理科背景的个体上有更明显的效果。此外,创造性科学问题提出分数不仅与创造性成就倾向显著相关,且在企业环境中也显示出了对于不同创造力群体的有效鉴别     

Les cadres et les champs de l’intervention : vers une cartographie

The intervention is based on methodologies and theoretical conceptions of transformation processes. Intervention does not belong specifically to occupational psychology, but we will focus here on different approaches in this disciplinary field. First, the theoretical and methodological frameworks of ergonomics, psychodynamics, the activity clinical approach, psychosociology, socio-psychoanalysis, and systemic intervention will be presented. This mapping test will then seek to identify common fundamentals. It aims to highlight the contributions offered by these different attempts to model the intervention, which are often not well known to each other. Indeed, the plurality of approaches that can be mobilized constitutes an essential resource to support the confrontation with the challenges of reality in the course of the intervention and the challenges posed by “field” issues.     

形成性测量模型：结构方程模型的新视角

形成性测量模型(Formative Model, FM)是指标变异导致潜变量变异的模型, 反映性测量模型(Reflective Model, RM)是潜变量变异导致指标变异的模型。FM在模型界定、识别和估计、信效度评价以及模型应用等方面均与RM存在极大的不同。模型界定错误会使参数估计发生偏差, 影响统计结论的有效性, 应当审慎考虑指标和潜变量之间的关系, 选择恰当的测量模型。进一步揭示两者的区别和误用带来的偏差, 完善FM的识别和估计、信效度评价方法、对变量含义的解释以及高阶FM的理论解释和模型估计是未来的研究方向。     

Construct validity of global life-satisfaction judgments: A look into the black box of self–informant agreement

Life-satisfaction judgments are ubiquitously used as indicators of wellbeing. The construct validity of these judgments relies heavily on self–informant agreement. However, agreement is necessary, but not sufficient to claim that life-satisfaction judgments are valid. In addition, self–informant agreement should be based on the use of valid information about satisfaction with important life domains. An alternative possibility is that agreement is based on impressions about personality traits. We tested these two hypotheses in a model that predicted self-ratings and informant ratings of life satisfaction from shared perceptions of personality and satisfaction with life domains. In a round-robin study of families, we found that life-domains were the key predictor of self–informant agreement. However, the Depressiveness facet of Neuroticism had a small direct effect. In addition, it was indirectly related to self–informant agreement because it predicts lower satisfaction in important life-domains that were used to form life-satisfaction judgments.     

Affective structure,measurement invariance,and reliability across different experience sampling protocols

While affect is frequently measured with experience sampling methodology (ESM), the affective structure at the between- and within-person level has not been thoroughly investigated. We investigated the affective structure at the between- and within-person level, its invariance across different ESM protocols, and its reliability. Participants (N = 147) were randomly assigned to receive either a 30 or 60 item questionnaire three, six, or nine times per day, resulting in 72–75 participants per questionnaire length and 48–50 participants per sampling frequency. Momentary affect was assessed with 8 or 18 items. At both levels, a structure with two correlated factors showed the best fit compared to an orthogonal and a unidimensional model. A structure with additional freed residual correlations was invariant across protocols at the within-person level and showed high reliability. We observed indications of a more discrete affective structure within than between persons.     

Multimodal traffic safety concerns in a university population

Travelers have different concerns about traffic safety, which may affect their transportation choices and risk-taking behaviors as well as the overall safety performance of multimodal transportation systems. The objective of this study was to examine factors associated with stated concerns surrounding traffic safety among travelers using multiple transport modes. The analysis used data from an online questionnaire survey completed by over 2,000 students and employees at Utah State University in Logan, Utah, US. Four latent variables—concerns about pedestrians and cyclists, auto drivers, modal interactions, and roadway conditions—were confirmed using factor analysis from 16 questions about traffic safety concerns. These four types of safety concerns were then analyzed to understand their associations with mode choice, commuting behavior, and socio-demographics using a structural equation model. Results showed that safety concern varied systematically among different mode users and demographic groups. Auto drivers perceived interactions with pedestrians and cyclists as concerning, while non-auto users felt more concerned by automobile traffic. Commuters who were recently involved in a crash were especially concerned with non-motorized modes. Women, lower-income, and non-white road users were more concerned with traffic safety overall. Findings about multimodal traffic safety concerns provide insights into people’s perceptions, which can be useful in developing designs, plans, and policies for making a safer transportation system for all road users.     

Spiking neural networks and hippocampal function: A web-accessible survey of simulations,modeling methods,and underlying theories

Computational modeling has contributed to hippocampal research in a wide variety of ways and through a large diversity of approaches, reflecting the many advanced cognitive roles of this brain region. The intensively studied neuron type circuitry of the hippocampus is a particularly conducive substrate for spiking neural models. Here we present an online knowledge base of spiking neural network simulations of hippocampal functions. First, we overview theories involving the hippocampal formation in subjects such as spatial representation, learning, and memory. Then we describe an original literature mining process to organize published reports in various key aspects, including: (i) subject area (e.g., navigation, pattern completion, epilepsy); (ii) level of modeling detail (Hodgkin-Huxley, integrate-and-fire, etc.); and (iii) theoretical framework (attractor dynamics, oscillatory interference, self-organizing maps, and others). Moreover, every peer-reviewed publication is also annotated to indicate the specific neuron types represented in the network simulation, establishing a direct link with the Hippocampome.org portal. The web interface of the knowledge base enables dynamic content browsing and advanced searches, and consistently presents evidence supporting every annotation. Moreover, users are given access to several types of statistical reports about the collection, a selection of which is summarized in this paper. This open access resource thus provides an interactive platform to survey spiking neural network models of hippocampal functions, compare available computational methods, and foster ideas for suitable new directions of research.     

Macrointervention processes and strategies for leaders,changemakers, advocates,allies, and targets: A new framework to address macroaggressions in systems

The presence of macroaggressions, or obvious, overt, system-wide racial offensives and abusive acts evidenced in organizational systems and structures (e.g., confederate flags; signs in public places that read: “we only speak English”), have continued to penetrate American society at an unparalleled rate. The onslaught of violence toward racial, ethnic, and cultural minority citizens—in particular Black Americans and the disproportionate death rates of Black, Indigenous, and People of Color linked with the coronavirus disease 2019 (COVID-19) underscores an urgent need for broad-based systemic action. While microaggressions are well-documented in the psychological literature, less attention has been directed toward macroaggressions and how to address the ever-present forms of racism that propagate inequity within all aspects of organizations and larger systems (e.g., health care, legal, education). We propose a six-step conceptual framework to address macroaggressions evinced in these systems. Additionally, we introduce macrointervention strategies and illustrative examples that can be deployed and tested in diverse ecologies by institutional leaders, changemakers, advocates, allies, and targets of bias. We recommend well-designed empirical investigations to evaluate the proposed conceptual framework and to what extent it can affect changes at the macro-level.