EFFECTS OF CONTEXTUAL COMPETENCE ON SOCIAL INITIATIONS

The frequency of social initiations and satisfaction with interactions in three dyads, each consisting of 1 student with disabilities and 1 nondisabled peer, were assessed under two alternating conditions: Condition 1 assessed the interactions around a set of four trained computer games, and Condition 2 assessed interactions when students were playing a set of four untrained computer games. Training was conducted with a multiple baseline design across participants and was followed by social interaction probes using an alternating treatments design. The results indicated greater frequencies of social initiations by 5 of 6 participants, higher degrees of game satisfaction by all participants, and equal or higher degrees of peer satisfaction by 5 of 6 participants when playing trained games in comparison to untrained games.     

The effects of videotape modeling and daily feedback on residential electricity conservation, home temperature and humidity, perceived comfort, and clothing worn: Winter and summer

Two studies were conducted in all-electric townhouses and apartments in the winter (N = 83) and summer (N = 54) to ascertain how energy conservation strategies focusing on thermostat change and set-backs and other low-cost/no-cost approaches would affect overall electricity use and electricity used for heating and cooling, the home thermal environment, the perceived comfort of participants, and clothing that was worn. The studies assessed the effectiveness of videotape modeling programs that demonstrated these conservation strategies when used alone or combined with daily feedback on electricity use. In the winter, the results indicated that videotape modeling and/or feedback were effective relative to baseline and to a control group in reducing overall electricity use by about 15% and electricity used for heating by about 25%. Hygrothermographs, which accurately and continuously recorded temperature and humidity in the homes, indicated that participants were able to live with no reported loss in comfort and no change in attire at a mean temperature of about 62 degrees F when home and about 59 degrees F when asleep. The results were highly discrepant with prior laboratory studies indicating comfort at 75 degrees F with the insulation value of the clothing worn by participants in this study. In the summer, a combination of strategies designed to keep a home cool with minimal or no air conditioning, in conjunction with videotape modeling and/or daily feedback, resulted in overall electricity reductions of about 15% with reductions on electricity for cooling of about 34%, but with feedback, and feedback and modeling more effective than modeling alone. Despite these electricity savings, hygrothermograph recordings indicated minimal temperature change in the homes, with no change in perceived comfort or clothing worn. The results are discussed in terms of discrepancies with laboratory studies, optimal combinations of video-media and personal contact to promote behavior change, and energy policies that may be mislabeled as sacrificial and underestimate the effectiveness of conservation strategies such as those investigated in these studies.     

Simulation of Preference Information in an Interactive Reference Point‐Based Method for the Bi‐Objective Inventory Routing Problem

In the research area of multiple criteria decision making, very few publications exist that explicitly design the simulation of a decision maker (DM) in an interactive approach. For this reason, we outline some methods widely used in the literature to identify common assumptions of simulating the DM's responses and the required input preference information. Our paper aims at covering the identified gap by introducing experimental concepts. Such concepts are used for theoretical analyses of a combined search‐and‐decision‐making procedure. Simulating the DM is a fruitful idea because the algorithm can be tested without integrating a human decision maker. Finally, we conduct experiments based on the proposed settings for a multiobjective inventory routing problem, which is a relevant and challenging logistic problem. Copyright © 2014 John Wiley & Sons, Ltd.     

Performance of Mental Health Counselors in Integrated Primary and Behavioral Health Care

Integrated primary and behavioral health care (IPBH) is becoming a preferred mode of service delivery in the United States. Integrated care includes the participation of medical and mental health professionals, such as mental health counselors. The clinical outcomes of these professionals need to be studied to determine their effectiveness in such settings. We examined the performance of 10 mental health counselors on the clinical outcome of 1,747 clients treated in an IPBH center. Analyses using growth curve modeling and pre‐post test design revealed that mental health counselors were effective overall, but they differed in client dropout rates and efficiency in reducing clients' initial symptoms. We used the analyses to rank order counselors based on their effectiveness. Counselors who were the most effective varied in their efficiency but demonstrated the lowest client dropout rates. Implications for future research and counseling practice were discussed.     

Computer‐based training to teach observers to accurately score problem behavior using fast forwarding at 5x normal speed

The current study evaluated whether a computer‐based training program could improve observers' accuracy in scoring discrete instances of problem behavior at 5x normal speed using a multiple‐baseline design across subjects. During pretraining and posttraining, observers attempted to score multiple examples of problem behavior at 5.0x without feedback. During training, participants scored multiple examples of problem behavior at 5.0x with automated feedback. Researchers measured omission (missing problem behavior) and commission (scoring other behavior as problem behavior) errors and the total duration of scoring time to determine the observers' accuracy and efficiency, respectively. After training, all participants scored instances of problem behavior with less than 11% error using 5.0x. The time required to score the videos across 90‐min observations was reduced by 66%. Results extend previous evaluations of fast forwarding by demonstrating that the training program could be used to teach observers to accurately score problem behavior using a speed faster than 3.5x.     

Comparing computer‐based training and lecture formats to teach visual analysis of baseline‐treatment graphs

Accurate analysis of data is vital to the validation of interventions. As such, there has been a recent increase in studies evaluating visual analysis training procedures. However, past investigations have not evaluated direct and indirect visual analysis training methods with matched instructional content that was systematically designed. Furthermore, training has rarely included assessment of generalization and maintenance of visual analysis skills. The purpose of the current dissertation study was to compare the effectiveness and efficiency of (a) computer‐based training, (b) lecture formats with and (c) without the opportunity to pause, and (d) a no‐training group to teach visual analysis of AB graphs to university students. To make these formats directly comparable, the instructional content was equated by ensuring information and examples were identical across the three training procedures. Eighty‐three students were randomly assigned to one of the four groups. Results showed that all three training formats produced increases in accurate responding compared to the no‐training group. Visual analysis skills generalized to novel graphs and maintained approximately 2 weeks following all trainings. These results suggest that structured approaches that are carefully designed to train visual analysis are effective and lead to gains that generalize and maintain in the absence of training.     

Factorial validation and measurement invariance of the French version of the multidimensional competitive orientation inventory (FVMCOI) in the sport field

IntroductionLittle is known about the importance of the adaptive, maladaptive and neutral facets of competitive orientations among French athletes.ObjectiveThe aim of this study is to test the factorial validation and measurement invariance of the French version of the multidimensional competitive orientation inventory (FVMCOI) from the original version (MCOI, Orosz et al., 2018), which included 12 items and four factors (i.e., hypercompetitive orientation, self-developmental competitive orientation, anxiety-driven competition avoidance, and lack of interest toward competition).MethodA series of three complementary studies was carried out with a total sample of 891 competitors.ResultsFollowing cross-cultural validation methods a preliminary version of the FVMCOI was constructed and the clarity of its items was established (study 1). Then, exploratory structural equation modeling (ESEM) confirmed that the four-factor model for the FVMCOI was factorially valid, and consistent with the model of the original version. As such, the multiple-group invariance tests showed that the FVMCOI was partially invariant across both age and gender and fully invariant across type of sport, level of competition and over time (study 2). Finally, the concurrent validity of the FVMCOI was demonstrated through its expected relationships with achievement goals, competitive aggressiveness and anger in sport (study 3).ConclusionThe establishment of the FVMCOI extends the research in sport psychology by allowing an extensive psychometric study of the MCOI in the sport domain and providing deeper insights into the healthy, unhealthy, and neutral nature of competitive orientation in this context. The FVMCOI's potential practical applications in sport context, with some limitations and perspectives of this study, are also discussed.     

Autonomous vehicle safety: Understanding perceptions of pedestrians and bicyclists

Autonomous vehicle (AV) technologies have been rapidly advancing. One benefit of AVs is that the technology could eliminate many driver errors and also mitigate many pedestrian and bicyclist collisions. Real-world AVs have been tested in many cities. Five companies are running around 50 AVs in Pittsburgh, following the autonomous testing guidelines. BikePGH, a non-profit organization located in Pittsburgh, Pennsylvania conducted a follow-up survey in 2019 (the first survey was conducted in 2017) to understand non-motorists’ opinions of AVs. This study examined how pedestrians and bicyclists perceived AV safety based on their understanding and experiences. At first, this study performed a comparison group test to determine which questions vary by participants’ AV safety rating. The responses were later analyzed with a data mining method known as ‘association rules mining.’ A new performance measure, known as the rule power factor, was then used to identify the significant patterns in the form of rules. The participants also provided their thoughts in responses to the open-ended questions. Using Latent Dirichlet Allocation (LDA), a topic modeling algorithm, 40 topic models were developed based on five open-ended questions. The findings show that the non-motorists showed comparatively fewer negative opinions towards AVs than positive assessments. The results also show that perception patterns vary by the participant’s rating on AV safety. Findings of this study would be beneficial for the AV stakeholders in making AVs and roadways safer for non-motorists.     

计算模型视角下信任形成的心理和神经机制——基于信任博弈中投资者的角度

人际信任渗透在社会交互的各个方面, 是促进和维持合作的重要基石。以往研究者借助信任博弈范式, 主要探讨了人际信任的理论模型、生物基础和影响因素等方面。近年来, 研究者开始将计算模型应用于信任博弈的数据分析中, 深入挖掘人际信任行为背后的心理机制, 将计算模型与神经影像技术结合, 加深对信任行为背后脑机制的理解。目前将计算模型应用于信任博弈范式中的研究主要针对“信任是如何形成的”这一科学问题, 未来要进一步发展计算模型方法, 结合非侵入性脑刺激技术, 应用于精神疾病人群中, 以深入理解正常和异常信任形成的心理和神经机制。     

The danger of conflating level-specific effects of control variables when primary interest lies in level-2 effects

In the multilevel modelling literature, methodologists widely acknowledge that a level-1 variable can have distinct within-cluster and between-cluster effects, and that failing to disaggregate these can yield a slope estimate that is an uninterpretable, conflated blend of the two. Methodologists have stated, however, that including conflated slopes of level-1 variables in a model is not problematic if substantive interest lies only in effects of level-2 predictors. Researchers commonly follow this advice and use methods that do not disaggregate effects of level-1 control variables (e.g., grand mean centering) when examining effects of level-2 predictors. The primary purpose of this paper is to show that this is a dangerous practice. When level-specific effects of level-1 variables differ, failing to disaggregate them can severely bias estimation of level-2 predictor slopes. We show mathematically why this is the case and highlight factors that can exacerbate such bias. We corroborate these findings with simulations and present an empirical example, showing how such distortions can severely alter substantive conclusions. We ultimately recommend that simply including the cluster mean of the level-1 variable as a control will alleviate the problem.