The dark and the bright sides of proactive work behaviour and situational constraints: Longitudinal relationships with task conflicts

We investigated relationships of a job stressor (situational constraints) and specific proactive behaviours with change in task conflicts over time. We introduced two distinct types of proactive work behaviour (promotion-oriented initiative and prevention-oriented initiative) and examined their positive but also negative relationships with change in task conflicts. Study 1 supported the construct validity of promotion-oriented initiative and prevention-oriented initiative for 363 student assistants: Confirmatory factor analyses indicated that both types of proactive behaviour were distinct constructs and also distinct from active coping; patterns of correlations were similar to those of a prior concept of proactive behaviour. Study 2 was a longitudinal online survey with 197 employees over 3 weeks. Consistent with our hypotheses, situational constraints and promotion-oriented initiative predicted an increase in task conflicts, whereas prevention-oriented initiative predicted a decrease in task conflicts.     

An introduction to Bayesian model selection for evaluating informative hypotheses

Most researchers have specific expectations concerning their research questions. These may be derived from theory, empirical evidence, or both. Yet despite these expectations, most investigators still use null hypothesis testing to evaluate their data, that is, when analysing their data they ignore the expectations they have. In the present article, Bayesian model selection is presented as a means to evaluate the expectations researchers have, that is, to evaluate so called informative hypotheses. Although the methodology to do this has been described in previous articles, these are rather technical and havemainly been published in statistical journals. The main objective of thepresent article is to provide a basic introduction to the evaluation of informative hypotheses using Bayesian model selection. Moreover, what is new in comparison to previous publications on this topic is that we provide guidelines on how to interpret the results. Bayesian evaluation of informative hypotheses is illustrated using an example concerning psychosocial functioning and the interplay between personality and support from family.     

Motor Programming as a Function of Constraints on Movement Initiation

Three experiments are reported that test the hypothesis that under certain conditions programming time is a function of the directional accuracy demand of a response, directional accuracy being quantified by the minimal angle subtended at the point of movement initiation by the circular targets within the response. Subjects in three simple reaction time experiments were required to tap a single target or a series of circular targets as rapidly as possible with a hand-held stylus. Experiments 1 and 3 showed that the subtended angle (SA) of a response can have a more powerful effect on programming time, as indexed by reaction time and premotor time, than the number of movement parts in the response. The results of Experiment 2 revealed that the locus of the directional accuracy effect was SA and not target size or movement distance. In all three experiments, response SA was a better predictor of programming time than was number of movement parts, target size, movement distance, movement time, and average movement velocity. The findings support the notion that constraints placed upon movement initiation by the directional accuracy demand of the task can play an important role in determining the length of the programming process.     

An Examination of Rapid Positioning Movements with Spatiotemporal Constraints

Unidirectional positioning movements with spatiotemporal-constraints were examined as a test of impulse-timing theory (Schmidt, 1976; 1980; Wallace, 1981). Movements were examined at the kinematic, kinetic, and neuromuscular levels in three experiments. In the first experiment, displacement was held constant while five different movement times were examined. Both amplitudes and durations of the EMG and the kinetic variables were related to movement time. The results generally support the impulse-timing model. In the second experiment, movements were performed to a target at each of four distances in a constant movement time. EMG and force amplitudes and, unexpectedly, accelerative-force duration were modulated to achieve changes in displacement when movement time was constant. In the third experiment, movement time and displacement were simultaneously varied resulting in four conditions with equal average velocities. The results of this experiment were not as clear and exhibited individual differences. EMG duration did not always vary with changes in movement time. The results of all three experiments could not be adequately accounted for by the impulse-timing model.     

A Gradual Effects Model for Single-Case Designs

Single-case designs are a class of repeated measures experiments used to evaluate the effects of interventions for small or specialized populations, such as individuals with low-incidence disabilities. There has been growing interest in systematic reviews and syntheses of evidence from single-case designs, but there remains a need to further develop appropriate statistical models and effect sizes for data from the designs. We propose a novel model for single-case data that exhibit nonlinear time trends created by an intervention that produces gradual effects, which build up and dissipate over time. The model expresses a structural relationship between a pattern of treatment assignment and an outcome variable, making it appropriate for both treatment reversal and multiple baseline designs. It is formulated as a generalized linear model so that it can be applied to outcomes measured as frequency counts or proportions, both of which are commonly used in single-case research, while providing readily interpretable effect size estimates such as log response ratios or log odds ratios. We demonstrate the gradual effects model by applying it to data from a single-case study and examine the performance of proposed estimation methods in a Monte Carlo simulation of frequency count data.     

Peer Substance Use and Homelessness Predicting Substance Abuse from Adolescence Through Early Adulthood

Adolescents who experience homelessness are at higher risk for abusing substances, and for being exposed to substance-using peers. The current study used a longitudinal design to track substance abuse, affiliation with substance-using peers, and episodes of homelessness among a sample of 223 adolescents who were housed at the baseline data collection and 148 adolescents who were housed at baseline. Participants were interviewed at six waves over 6.5 years, covering an age range from 13 to 25. Many participants experienced a recurrence of homelessness during follow-up, with 64.6 % of the baseline homeless group and 22.6 % of the baseline housed group reporting an additional episode of homelessness. Both alcohol abuse and other drug abuse symptoms showed an increase in adolescence followed by slowing in early adulthood. Recent homelessness and friend alcohol use predicted alcohol abuse symptoms, and the strength of the influence of friend use decreased over time. Recent homelessness and friend drug use predicted other drug abuse symptoms. Duration of the initial episode of adolescent homelessness showed no influence on substance abuse over time, or the effects of other predictors, highlighting the importance of conceptualizing the experience of homelessness as a recent stressor rather than an enduring personal characteristic.     

基于多元回归的调节效应分析

在心理学和其他社科研究领域,大量实证研究建立调节模型,以分析自变量对因变量关系的影响机制,但在基于多元回归的调节效应分析实践中仍存在不足。我们回顾了均值中心化在基于多元回归的调节效应分析中的作用,均值中心化不影响乘积项(即调节效应)的检验,仅对一阶项(即主效应)的检验有影响。讨论了简单斜率的检验方法,建议在调节变量为连续变量时,使用Johnson-Neyman法进行简单斜率检验;在调节变量为类别变量或研究者对某个调节变量值感兴趣时,使用选点法。并用一个实际例子演示如何进行调节效应分析。随后展望了调节效应检验的拓展方向。     

Using HLM to Explore the Effects of Perceptions of Learning Environments and Assessments on Students’ Test Performance

The study examines the role that perceptions or impressions of learning environments and assessments play in students’ performance on a large-scale standardized test. Hierarchical linear modeling (HLM) was used to test aspects of the Learning Errors and Formative Feedback model to determine how much variation in students’ performance was explained by students’ and school principals’ perceptions of learning environments and assessments. Results from sequential HLM testing indicated that students’ but not principals’ perceptions explained a significant, although modest, amount of the total variation in students’ test performance. These results suggest that when students perceive learning environments to be safe and valuable, and positive assessment activities to be taking place, they tend to perform better on standardized tests than when they perceive learning environments and assessment activities otherwise. These findings provide a rationale for investigating the variables that can help improve students’ perceptions in order to enhance their test performance.     

复杂问题解决中计算机模拟情境的逻辑框架

计算机模拟情境摆脱了实验室研究和现场研究的不足,满足了复杂问题解决的复杂性、动态性和模糊性等特征,受到研究者们的青睐.近年来,各种模拟情境在复杂问题解决研究中得到运用,其内部逻辑结构主要有线性结构方程和有限状态自动化,线性结构方程适用于等距数据,而有限状态自动化适用于称名数据.当前,对复杂问题解决的测量注重结果,而相对忽视过程.未来的模拟情境可以从问题特征、任务逻辑和测量方式来提高信度和效度.     

一种基于进化算法的概化理论最佳样本量估计新方法：兼与三种传统方法比较

概化理论在心理与教育测量领域应用较广。如何使测量程序在预算限制的情况下达到较优的可靠性是研究者需要考虑的重要问题, 这个问题可以转换为最佳样本量估计的问题。提出了一种基于进化算法的估计概化理论下最佳样本量的新方法——约束进化算法, 并采用模拟研究的方法比较了微分优化法、拉格朗日法、柯西不等式法等三种传统方法与约束进化算法的优劣。结果表明：在两侧面交叉设计、两侧面嵌套设计和三侧面交叉设计中都证明了约束进化算法更具优越性, 建议研究者在今后的研究中优先使用。