Grain Size and Parameter Recovery with TIMSS and the General Diagnostic Model

The purpose of this study was to explore the degree of grain size of the attributes and the sample sizes that can support accurate parameter recovery with the General Diagnostic Model (GDM) for a large-scale international assessment. In this resampling study, bootstrap samples were obtained from the 2003 Grade 8 TIMSS in Mathematics at varying sample sizes from 500 to 4000 and grain sizes of the attributes from a unidimensional model to one with ten attributes. The results showed that the eight-attribute model was the one most consistently identified as best fitting. Parameter estimation for more than ten attributes and samples less than 500 failed. Furthermore, the precision of item parameter recovery decreased as the number of attributes measured by an item increased and sample size decreased. On the other hand, the distributions of latent classes were relatively stable across all models and sample sizes.     

经济决策中人际信任博弈的理论模型与脑机制

信任是指个体在缺乏足够信息来判断他人动机、意图和行为的情况下,将社会资源交给对方处置并承担相应风险的意愿。作为一种基本的社会信号机制,信任对于发展和维持良好社会关系具有重要作用。借助信任博弈范式,研究者揭示了人际信任的认知神经机制并建构了多种理论,包括背叛厌恶理论、社会规范理论、道德规范理论和默认行为模型。脑成像研究发现信任行为主要涉及内侧前额叶、尾状核、杏仁核和脑岛等脑区,其中内侧前额叶主要参与心理推理、情绪认知与调控等过程,尾状核参与同伴值得信赖性的习得与编码,杏仁核和脑岛则主要参与风险、不确定性和背叛恐惧加工。今后研究应侧重不同理论之间的补充与整合,强化不同脑区之间的功能连接与整体性,并注重信任行为中的个体差异。     

Family incivility and counterproductive work behavior: A moderated mediation model of self-esteem and emotional regulation

Drawing from the work–home resources model, we examined the relations of family incivility, counterproductive work behaviors (CWB), state self-esteem, and emotional regulation. Results from three-wave lagged data (N = 284) indicated that family incivility was positively correlated with counterproductive work behaviors, and this relationship was mediated by state self-esteem. In addition, emotional regulation mitigated the relationship between family incivility and state self-esteem. The findings suggested that family incivility, as an emotional contextual demand in the home domain, is related to negative outcome (deviant behavior) in the work context (i.e., CWB) through the depletion of the personal resource—state self-esteem, while emotional regulation is a key resource that mitigates this relationship. This paper discusses the implications of these findings with respect to applications and developments of the work–home resources model.     

Personality change via work: A job demand–control model of Big-five personality changes

Based on the job demand–control model and Gray's biopsychological theory of personality, the author proposed a model to suggest that time demand and job control can drive changes in Big-five personality traits, especially neuroticism and extroversion, by shaping an individual's stress experiences at work. Five waves of data from 1814 employees over a five-year period from the Household, Income and Labor Dynamics in Australia Survey were analyzed. Time demand, job control and job stress were measured in all five waves, and Big-five personality was assessed in the first and last waves. The results showed that time demand and job control shaped job stress positively and negatively at a given time; and over time, an increase in time demand predicted an increase in job stress, which subsequently predicted an increase in neuroticism and a decrease in extroversion and conscientiousness. Results also showed that an increase in job control predicted an increase in agreeableness, conscientiousness, and openness directly, but did not predict change in neuroticism and extroversion. Finally, the buffering effect of job control on the association between time demand and job stress was only observed in two of five waves and such buffering effect was not observed in a change process. The implications on personality development and work design research are discussed.     

Impact of School Psychological Environment Variables on Happiness of Korean Youths

Abstract: This study analyzed the structural relationships between school‐related psychological variables (teacher support, learning flow, friendship) and the happiness of Korean youths, and compared structural equation models for middle and high schools. Questionnaire data were collected from students in middle and high schools in 10 cities and provinces of Korea. The final data set from 870 students was analyzed with Amos 20.0. Goodness of fit indices for the hypothetical model were good, and all paths were significant. That is, a model incorporating indirect and direct impact of school‐related psychological environment variables, such as teacher support, learning flow, and friendship, on the happiness of Korean youths is valid. Second, structural equation models for middle and high schools demonstrated significant differences. Therefore, different types of assistance are needed to increase the happiness of students in middle schools and high schools.     

A home-based approach to understanding the effect of spatial autocorrelation on seat belt non-use

Roadside observations indicate that seat belt use rates are often spatially correlated with nearby areas. However, very few studies have examined the effects of spatial autocorrelation on seat belt use. This study used exploratory spatial data analysis (ESDA) to explore spatial autocorrelation in Tennessee, which has a lower seat belt use than the United States national average. We geocoded home-addresses of vehicle occupants involved in traffic crashes between 2014 and 16 (n = 1,251,901) and projected them to the census tract corresponding to their home address. This projection reveals information about the spatial distribution of seat belt non-use and socioeconomics of the areas surrounding the crash victim's home. The presence of highly spatially correlated observations (i.e., a significant positive Moran’s I) suggests that seat belt non-use is not produced solely by the internal structural factors represented in the non-spatial models. ESDA reveals a distinctive regional imprint for spatial autocorrelation, in which Southern-metropolitan areas’ (Southern-MPOs) in Tennessee census tracts have higher than average seat belt non-use compared to Non-Southern-MPOs (16% vs. 9%). The spatial error model was suitable for Non-Southern-MPOs, whereas the spatial lag model was more suitable for Southern MPOs. Comparison of the estimated models indicates that in the Non-Southern MPOs, percentage of the White population, percentage of the population with Bachelor's degree, median household income, vehicle ownership, and population density are significant predictors of seat belt non-use. On the other hand, median household income, vehicle ownership, and percentage of population aged between 16 and 42 years old predict seat belt non-use in Southern MPOs. The study results could be used to identify seat belt non-use clusters at the state level and identify seat belt non-use hot zones. Furthermore, this analysis indicates that the relationship between demographic variables and seat belt non-use varies across regimes. Failing to consider the spatial regimes in the analysis would lead to falsely prioritizing groups prone to seat belt non-use.     

Consequences of autonomous vehicles: Ambivalent expectations and their impact on acceptance

Connected and autonomous vehicles (CAVs) are within reach of widespread deployment on public roads, but public perceptions are ambivalent. The objective of the present research was to assess expectations about the consequences of CAV introduction. These expectations should explain CAV acceptance, but their relative importance is poorly understood. We conducted a survey with a representatively drawn panel sample (N = 529) from France, Germany, Italy, and the UK. The survey consisted of a large item pool of expected consequences from CAV introduction, as well as general and affective evaluation of CAVs, ease of use, and behavioral intention to use CAVs. Exploratory factor analysis revealed four facets of expected consequences: road safety, privacy, efficiency and ecological sustainability. On average, expectations were mostly positive for ecological sustainability and safety, but negative for privacy. At the same time, substantial variance existed between respondents and between countries. For safety and efficiency, improvement was expected by a third of respondents, while another third expected worsening. Respondents from Italy expected more positive consequences for safety, while respondents from both France and Germany expected more negative consequences for privacy. To different degrees, all four facets predicted the intention to use CAVs in a structural equation model, primarily via affective evaluations. For policy makers, manufacturers, and service providers, understanding the trade-offs inherent to different CAV solutions will be central to ensure citizens’ needs are respected.     

Analysis of advanced driver assistance systems in police vehicles: A survey study

Few studies have examined the impact of advanced driver-assistance systems (ADAS) on police officers to improve driver safety and prevent crashes. This is in spite of police officers having higher driving-related mortality rates than average civilians. To fill this gap, a survey study was conducted on 73 police officers to assess their opinions on various ADAS features as well as their recommendations for improvement. Results of the correlation analyses indicated that officer behavior and opinion on ADAS features were influenced by the trust officers had in the available ADAS systems among other key factors such as ADAS training and perceived usefulness. On this basis, guidelines for future research and development of ADAS were provided to improve officer driving safety in police operations. The guidelines need to be further validated in future driving simulation or naturalistic studies.     

Modeling the influence of mobile phone use distraction on pedestrian reaction times to green signals: A multilevel mixed-effects parametric survival model

Understanding and modeling the influence of mobile phone use on pedestrian behaviour is important for several safety and performance evaluations. Mobile phone use affects pedestrian perception of the surrounding traffic environment and reduces situation awareness. This study investigates the effect of distraction due to mobile phone use (i.e., visual and auditory) on pedestrian reaction time to the pedestrian signal. Traffic video data was collected from four crosswalks in Canada and China. A multilevel mixed-effects accelerated failure time (AFT) approach is used to model pedestrian reaction times, with random intercepts capturing the clustered-specific (countries) heterogeneity. Potential reaction time influencing factors were investigated, including pedestrian demographic attributes, distraction characteristics, and environment-related parameters. Results show that pedestrian reaction times were longer in Canada than in China under the non-distraction and distraction conditions. The auditory and visual distractions increase pedestrian reaction time by 67% and 50% on average, respectively. Pedestrian reactions were slower at road segment crosswalks compared to intersection crosswalks, at higher distraction durations, and for males aged over 40 compared to other pedestrians. Moreover, pedestrian reactions were faster at higher traffic awareness levels.     

Factors affecting motorcyclists’ behavior in car-following condition

Car-following (CF) maneuver plays an important role in both traffic flow analysis and road safety assessment. However, many studies on this issue have focused on the drivers’ behaviour, neglecting the different driving behaviour of the motorcycle riders and the vulnerability of this type of user. The aim of the present paper is to analyse the factors affecting the riders’ behaviour in CF condition, by using two surrogate safety indicators, Time Headway (TH) and Time To Collision (TTC). A field experiment was conducted to collect data. Twenty young motorcyclists participated in the study driving their own motorcycles, which were instrumented with a camera and a global positioning system device (GPS). A digital image processing algorithm was used to obtain CF related indicators. The results of the study showed that Time Headway (TH) and Time To Collision (TTC) are independent of each other, extending the result obtained in the literature for the four wheeled vehicles to the motorcycles. TTC and TH were therefore analyzed separately. As for TTC, it was observed that only in few cases (0.8%) the riders were found in risky condition (TTC < 5 s), confirming the role of this parameter for the detection of an impending risk. On the other hand, TH gives information about a potentially risky situation, and 99% of the riders were found in such condition (TH < 2 s). Due to the few cases in TTC risky conditions, only TH was further modelled by using the hazard-based duration analysis. Accelerated Failure Time (AFT) model specification was used, and the Weibull distribution provided the best fit of the data. The model identified four covariates affecting TH and all of them had the effect of reducing TH, increasing the collision risk. The time spent on CF condition, the speed of the motorcycle, the willingness of overtaking and the engine size of the motorcycle were the factors that reduced TH.The findings of this study could be considered in the development of microsimulation models; the factors that were found affecting the motorcyclists’ behavior in car-following condition could be considered for a more realistic simulation of the riders’ choice of Time Headway.