An investigation of psychosocial factors related to changes in physical activity and fitness among female adolescents

Research examined the effects of a supervised physical activity program on potential psychosocial mediators and determined whether changes in these psychosocial variables predicted changes in physical activity and fitness. Sedentary adolescent females were assigned to an intervention (n?=?79) or comparison (n?=?67) group. Cardiovascular fitness (cycle ergometer), physical activity (3-Day Physical Activity Recall), and psychosocial variables related to physical activity (i.e., self-efficacy, perceived barriers, social support, enjoyment) were assessed at three time points over the 9-month study. An intention-to-treat analysis showed that the intervention did not impact any of the psychosocial variables, with the exception of perceived barriers, which increased in the intervention group. Longitudinal analyses showed that improvements in fitness were associated with positive changes in global self-efficacy and exercise enjoyment. Psychosocial variables did not mediate the program's effects on fitness or activity. However, individual level changes in psychosocial variables were related to changes in cardiovascular fitness.     

Mindfulness and integrative self‐knowledge: Relationships with health‐related variables

This study examined how mindfulness and integrative self‐knowledge were related to health‐related issues. Men in general population (n = 103) and coronary heart disease samples (n = 101) completed the Mindful Attention Awareness Scale, the Integrative Self‐knowledge Scale, the Type 2 subscale of the Interpersonal Reactions Inventory, the Perceived Stress Scale, and the Anxiety and Depression Scales. In both samples, there was a moderate positive correlation between mindfulness and integrative self‐knowledge and they were negatively correlated with all health‐related variables. However, only integrative self‐knowledge explained independent variance in health‐related variables. Specifically, in both samples, the relationship between mindfulness and health‐related variables was mediated by integrative self‐knowledge. Mindfulness and integrative self‐knowledge are related domains of self‐awareness that are associated with a range of health‐related variables. These relationships are robust across samples drawn from general population and patients with coronary heart disease. The finding that integrative self‐knowledge explained additional variance in the health‐related variables after the contribution of mindfulness had been accounted for suggests that reflective self‐awareness in integrative self‐knowledge may make a unique contribution to the explanation of individual differences in health variables.     

Measurement and comparative analysis of driver’s perception–reaction time to green phase at the intersections with and without a countdown timer

This paper proposes a method based on digital image processing for measuring drivers’ perception–reaction time (PRT) to the green phase. The detection of the onset of a green signal was based on the RGB color model. The detection of the start of the vehicle was based on the frame difference. The driver’s perception–reaction time was equal to the difference between the frame of the onset of the green signal and the frame of the start of the vehicle divided by the video frame rate. Drivers’ PRT with and without a countdown timer were comparatively analyzed. First, the means and variances of drivers’ PRT with a timer and without a timer were compared. Second, Normal, Lognormal, Gamma and Weibull distributions were used to fit the PRT data. Third, the fuzzy c-means clustering was utilized for PRT classification and comparison. The results show that the method for measuring drivers’ PRT based on digital image processing was effective. The drivers’ PRT was decreased from 2.12 s to 1.48 s with countdown signals. Weibull distribution appeared to best fit the PRT with No-Timer and Lognormal distribution appeared to best fit the PRT with Timer. The PRT data were classified into three groups: “Fast”, “Moderate” and “Slow”. Clustering centers without Timer were 1.16 s, 2.47 s and 3.98 s respectively. Clustering centers with Timer were 0.95 s, 1.64 s and 2.70 s respectively. The clustering centers can be regarded as reference values of drivers’ starting response for microscopic traffic simulation software.     

A latent class distance association model for cross‐classified data with a categorical response variable

In this paper we propose a latent class distance association model for clustering in the predictor space of large contingency tables with a categorical response variable. The rows of such a table are characterized as profiles of a set of explanatory variables, while the columns represent a single outcome variable. In many cases such tables are sparse, with many zero entries, which makes traditional models problematic. By clustering the row profiles into a few specific classes and representing these together with the categories of the response variable in a low‐dimensional Euclidean space using a distance association model, a parsimonious prediction model can be obtained. A generalized EM algorithm is proposed to estimate the model parameters and the adjusted Bayesian information criterion statistic is employed to test the number of mixture components and the dimensionality of the representation. An empirical example highlighting the advantages of the new approach and comparing it with traditional approaches is presented.     

第二类有中介的调节模型

心理学研究常用有中介的调节模型揭示调节作用通过中介变量间接实现的现象。介绍了第二类有中介的调节模型(meMO-II)的概念及优势; 将meMO-II与其它中介调节混合模型进行了辨析; 给出了meMO-II的建模方法和分析流程, 并用一个实例演示; 介绍了基于潜变量的meMO-II的分析方法、meMO-II建模方法的新进展以及meMO-II的变式。研究有助于推动调节机制研究的发展。     

Influence of school-level variables on aggression and associated attitudes of middle school students

This study sought to understand school-level influences on aggressive behavior and related social cognitive variables. Participants were 5106 middle school students participating in a violence prevention project. Predictors were school-level norms opposing aggression and favoring nonviolence, interpersonal climate (positive student–teacher relationships and positive student–student relationships), and school responsiveness to violence (awareness and reporting of violence and school safety problems). Outcomes were individual-level physical aggression, beliefs supporting aggression, and self-efficacy for nonviolent responses. School norms and both interpersonal climate variables had effects on all three outcomes in theorized directions. Only one of the responsiveness measures, awareness and reporting of violence, had theoretically consistent effects on all outcomes. The other, school safety problems, affected self-efficacy later in middle school. Evidence of gender moderation was generally consistent with greater influence of school-level factors on female adolescents. Discussion focuses on implications in light of previous research and intervention possibilities.     

Predicting Presidential Performance in the United States: Equation Replication on Recent Survey Results

Abstract

For more than 2 decades, researchers have tried to identify the variables that predict the overall performance of U.S. presidents. In 1986, there emerged a 6-variable prediction equation (D. K. Simonton, 1986c, 1987b) that has been replicated repeatedly. The predictors are years in office, war years, scandal, assassination, heroism in war, and intellectual brilliance. The author again replicated the equation on recent rankings of all presidents from George Washington through William Jefferson Clinton according to a survey of 719 experts (W. R. Ridings, Jr., & S. B. Mclver, 1997). The original 6-variable equation successfully predicted both the overall rankings as well as the 5 core components of the rankings (leadership qualities, accomplishment, political skill, appointments, character and integrity). The predictive value of the equation was illustrated for the presidencies of Ronald W. Reagan, George H. W. Bush, and Clinton.     

Mediation analysis and categorical variables: The final frontier

Many scholars are interested in understanding the process by which an independent variable affects a dependent variable, perhaps in part directly and perhaps in part indirectly, occurring through the activation of a mediator. Researchers are facile at testing for mediation when all the variables are continuous, but a definitive answer had been lacking heretofore as to how to analyze the data when the mediator or dependent variable is categorical. This paper describes the problems that arise as well as the potential solutions. In the end, a solution is recommended that is both optimal in its statistical qualities as well as practical and easily implemented: compute z_Mediation.     

Mediation with categorical variables compleat

This rejoinder addresses the thoughtful issues raised by the commentators. We hold to the analytical solution of fitting X → M (to obtain a and sa) and X&;M→ (to obtain b and sb) via regression or logistic regression, depending on whether M and Y are continuous or categorical. Then researchers compute za, zb, and ZMediation.