Psychometric evaluation of the situation test of heterosocial skill

This study examined various psychometric properties of Forms A and B of the Situation Test, developed by Rehm and Marston (Journal of Consulting and Clinical Psychology, 1968, 37, 565–574) for the assessment of heterosocial skill and anxiety. A third test form composed of heterosocially irrelevant items was also examined for comparison purposes. Split-half, alternate-form, and interresponse consistency was determined for measures of skill, anxiety, response latency, and response duration. Differences across test forms on these measures were also investigated. Subsequently, criterion-related validity was examined relative to three criteria of heterosocial skill. Results indicated that two measures, anxiety and response duration, displayed adequate internal consistency, while that of skill and response latency was marginal. Interresponse consistency was moderately low for all three test forms. Comparisons of mean performances across forms revealed significant differences, with heterosocially irrelevant items appearing easier, in general, than the heterosocial items of Forms A and B. Lastly, significant predictions of peer-reported heterosocial behavior were obtained for all three test forms, but two self-report criteria were not found to be related to test behavior. Various implications of these findings are discussed.Portions of this research were completed while the authors were affiliated with the University of Georgia, Athens, Georgia. The advice and consultation provided by the late William K. Boardman is gratefully acknowledged. Appreciation is also extended to Michael Breakwell, Linda Maertzweller, Steven Ray, and Jan Rockley for their assistance with data collection.Copies of assessment material and specific instructions to subjects are available upon request.     

It's lonely at the bottom (too): The effects of experienced powerlessness on social closeness and disengagement

Although “powerlessness” is a pervasive experience for employees, prior social power research has predominantly focused on consequences of “powerfulness.” This has led to contradictory predictions for how experienced powerlessness influences employees’ social perceptions and behaviors. To resolve this theoretical tension, we build on Social Distance Theory (Magee & Smith) to develop a theoretical model suggesting that experienced powerlessness reduces social closeness and subsequently causes social disengagement behaviors both at work (reduced helping and increased interaction avoidance) and at home (increased withdrawal). Our model also elucidates the processes that cause powerlessness to reduce social closeness, demonstrating that employees’ affiliation motive and their expectation of others’ interest in affiliating explain this relationship. We further propose that the effect of powerlessness on social closeness will be stronger for employees high (vs. low) in political skill because these employees are more attuned to workplace power dynamics. We find support for our model in an experience-sampling field experiment and two experimental scenario studies. Our research clarifies the effects of powerlessness on social closeness and organizationally relevant downstream consequences, qualifies dominant assumptions that the powerless always behave in ways opposite those of the powerful, and demonstrates the importance of political skill as a moderator of power's effects.     

Should I Drive Today? Development of a daily driving decisions model for older adults

BackgroundOlder adults in communities make daily decisions about how to meet their transportation needs so they can access services and stay socially connected. With the aging of populations in developed countries, the travel decisions of older adults will have increasing impacts. Research studies have identified different sets of factors that contribute to certain travel decisions, but little research has been directed towards understanding how individuals select information from all available factors, what information they include in their decisions under different circumstances, and the processes they use in making their transportation decisions.MethodsThis exploratory study involved 20 men and 17 women, mean age 78.6 years (range 70–96), who drove weekly. All participants were involved in each phase of the 3-phase study. In Phase 1, a review of the literature and interviews with the participants was used to collect information, and inductive thematic analysis was employed to construct a draft conceptual model of older driver decision-making. In Phase 2, participants completed a stated preference task of written scenarios to demonstrate their decision-making strategies. Results were tabulated and used to refine a final Daily Driving Decisions model. In Phase 3, a card sorting decision task was used to test the model with participants.ResultsThe final dynamic Daily Driving Decisions Model was confirmed to describe decision processes used by the participants in making decisions about how they would meet their transportation needs. The model describes three categories of factors used in decisions, labelled Motivators, Constraint/Enablers and Context, each containing four attribute themes. A significant finding was the variable use of the same item to either constrain or enable the decision to drive depending on the variation of other factors in the scenario. Participants demonstrated use of compensatory and noncompensatory (heuristic, habitual) decision processes that were accommodated by the model.ConclusionThe proposed Daily Driving Decisions Model addresses a gap in our understanding of how older drivers make their decisions about meeting their transportation needs. The model presents a template for classifying the types of information used, ignored or discarded by older adults, and the pathways that they take to arrive at their decisions. The model provides opportunities for further research in testing the influence of other factors such as urban/rural residence, income, health status and culture on driving decisions. Further, the model can be used by practitioners to gain insight into the decision-making behaviours of individuals and to develop interventions to enhance their decision-making skills.     

心理资本对大学生职业决策困难的影响:有调节的中介模型

本研究提出一个有调节的中介模型,揭示了心理资本"怎样"影响大学生职业决策困难及这种影响在不同个体中是否存在差异。采用心理资本量表、职业决策自我效能感量表、社会技能量表和职业决策困难量表对730名大学生进行研究。研究显示：（1）职业决策自我效能感部分中介了心理资本与大学生职业决策困难的关系;（2）社会技能调节了心理资本通过职业决策自我效能感影响大学生职业决策困难的中介过程的前半路径和后半路径。研究结论对促进大学生成功就业具有重要的理论与实证价值。     

The influence of road familiarity on distracted driving activities and driving operation using naturalistic driving study data

This paper analyzed the influence of familiarity on the involvement of secondary tasks and driving operation using naturalistic driving study (NDS) data. Distracted driving activities were extracted from face videos captured in 557 trips, including 501 trips on familiar roads and 56 trips on unfamiliar roads. These trips were completed by 155 drivers using their own vehicles during daytime hours under good weather conditions. The data showed the frequency of distracted driving activities and duration time were higher on familiar roads compared to unfamiliar roads. More types of secondary tasks were found on familiar roads. Focusing on objects was the most common distracted driving activity on familiar roads. The average time drivers used to eat or drink was highest (8.67 s) on familiar roads. The time drivers spent checking their cell phone was high on both familiar roads and unfamiliar roads. Since driving operation is directly related to crash risk, this paper also analyzed the difference of driving operation on familiar roads and unfamiliar roads. The speed profiles were generated on well-known versus unfamiliar roads. It was shown that drivers were more likely to be speeding and select a short distance to deceleration near the intersections. The findings indicated that distracted driving phenomenon was more serious on familiar roads.     

Modelling the human lane-change execution behaviour through Multilayer Perceptrons and Convolutional Neural Networks

Driving is a highly complex task that involves the execution of multiple cognitive tasks belonging to different levels of abstraction. Traffic emerges from the interaction of a big number of agents implementing those behaviours, but until recent years, modelling it by the interaction of these agents in the so called micro-simulators was a nearly impossible task as their number grows. However, with the growing computing power it is possible to model increasingly large quantities of individual vehicles according to their individual behaviours. These models are usually composed of two sub-models for two well-defined tasks: car-following and lane-change. In the case of lane-change the literature proposes many different models, but few of them use Computational Intelligence (CI) techniques, and much less use personalization for reaching individual granularity. This study explores one of the two aspects of the lane-change called lane-change acceptance, where the driver performs or not a lane-change given his intention and the vehicle environment. We demonstrate how the lane-change acceptance of a specific driver can be learned from his lane change intention and surrounding environment in an urban scenario using CI techniques such as feed-forward Artificial Neural Network (ANN). We work with Multilayer Perceptron (MLP) and Convolutional Neural Networks (CNN) architectures. How they perform one against the other and how the different topologies affect both to the generalization of the problem and the learning process are studied.     

Adaptive warning signals adjusted to driver passenger conversation: Impact of system awareness on behavioral adaptations

The study investigated behavioral adaptation caused by warning signals that adaptively support drivers engaged in a passenger conversation. Novel advanced driver assistance systems (ADAS) could monitor the driver state to provide warnings adjusted to the driver’s current need for support. While first research indicates positive effects of dynamically adjusting ADAS, the overall safety potential of such adaptive systems remains unclear as little is known about adverse behavioral effects. Occasional inappropriate support due to an incorrect prediction of the current driver state might lead to critical situations when drivers are aware of the adaptive nature of the system and thus rely on the expected system behavior. To better understand behavioral adaptation to dynamically adjusting warnings, 46 participants driving on a test track reacted to two types of warnings (auditory, vibrotactile-auditory) while engaging in driver-passenger conversation or not. In a compensating warning strategy, vibrotactile-auditory warnings were displayed during conversations and auditory warnings in situations without conversation. This strategy was compared to a non-compensating warning strategy in which these assignments were reversed. The impact of behavioral adaptation was measured by considering reactions to simulated failures of these strategies. The role of system awareness for behavioral adaptation was investigated by manipulating awareness of these warning strategies across groups. We found that vibrotactile-auditory warnings reduced the detrimental effects of conversation on reaction times. Crucially, adverse behavioral adaptation was observed whenever an expected vibrotactile-auditory warning was replaced by an auditory warning but this effect was restricted to drivers in the awareness group. The results show that adaptive warning signals optimize the effectiveness of warnings during driver-passenger conversation but adverse behavioral adaptation develops when drivers are aware of the underlying warning strategy. This implies that future adaptive systems are less likely to be associated with behavioral adaptation if the adaptive nature of the system remains unnoticeable to the driver. Our findings could be used for developing and optimizing user-centered ADAS.     

“What Makes a Cooperative Driver?” Identifying parameters of implicit and explicit forms of communication in a lane change scenario

An automated vehicle needs to learn how human road users communicate with each other in order to avoid misunderstandings and prevent giving a negative outward image during interactions. The aim of the present work is to develop an autonomous driving system which communicates its intentions to change lanes based on implicit and explicit rules used by human drivers. To reach this goal, we aimed at gaining a deeper understanding of which aspects of lane change behaviour makes them cooperative from the perspective of other drivers. Therefore a vehicle used various lane change announcement strategies by varying combinations of driving parameters in a static driving simulator. (First study: Start indicator signal, Waittime, lane change duration; Second study: Longitudinal acceleration). It’s impact on the perception and behaviour of other road users was observed in two studies (N = 25 per study). The results showed that the earlier the merging vehicle was indicating its intentions, the more cooperative it was perceived. When turning on the indicator at a later time participants considered it as more cooperative to merge with a slower or faster lane change duration or to wait longer in the lane before starting to move to the other lane. An early longitudinal acceleration when starting to change lanes is perceived more cooperative. These findings can be used to model a lane change strategy based on human behaviour, which will eventually lead to more acceptable and safer interactions between automated and non-automated road users.     

“三番式”临床技能教学模式的建立及其在临床医学教学中的应用与思考

传统的临床技能教学存在诸多弊端,从而影响了医学生临床技能的培养及合格医学人才的培养。我们在多年的临床教学实践基础上,构建了临床技能学实践教学平台,创建了“三番式”临床技能教学模式,并将其应用于临床实践教学中,对所取得的显著教学效果进行深入剖析。     

Cross-cultural comparison of drivers’ tendency to commit different aberrant driving behaviours

The first aim of the present study was to identify key items which are rated differently by drivers from Finland, Sweden, Greece and Turkey. The second aim was to examine how these key items relate to drivers’ self-reported accident involvement. Similar comparisons have previously been conducted in Europe but these have only included items classified as violations and errors, but not lapses. A sample of Finnish (N = 200), Swedish (N = 200), Greek (N = 200) and Turkish (N = 200) drivers completed the driver behaviour questionnaire (DBQ) and reported their accident involvement during the previous 3 years. The results showed that nine key items (which drivers from different countries rated differently) could be identified. These items included two aggressive violations, four ordinary violations, three lapses, but no errors. Out of these nine items, five items (Become angered by a certain type of driver and indicate your hostility by whatever means you can, Disregard the speed limit on a motorway, Overtake a slow driver on the inside, Pull out of a junction so far that the driver with right of way has to stop and let you out and Get into the wrong lane approaching a roundabout or a junction) could explain differences in drivers’ self-reported yearly accident involvement when all four countries were taken together. At the same time, none of the items could explain differences in self-reported yearly accident involvement in Finland and Sweden while one of the items (Overtake a slow driver on the inside) could explain differences in self-reported yearly accident involvement in Greece and two of the items (Become angered by a certain type of driver and indicate your hostility by whatever means you can and Disregard the speed limit on a residential road) could explain differences in self-reported yearly accident involvement in Turkey. This shows that different countries have different problems with regard to aberrant driving behaviours which need to be taken into account when promoting traffic safety interventions and the driver behaviour questionnaire (DBQ) can be used to diagnose risk areas and to better inform road safety practitioners within and between countries.