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In summary, our results suggest a right-shifted weighting function in this non-industrialized small society. The deviation might be caused by the particular living situation of the DuLong people, their sensitivity to monetary payoffs, and the elicitation procedure.With age might come a decline in crucial driving skills. The effect of a collision warning system (CWS) on older drivers' head movements behavior at intersections was examined. Methods Twenty-six old-adults, between 55 and 64 years of age, and 16 Older drivers between 65 and 83 years of age, participated in the study. A CWS (Mobileye Inc.) and a front-back in-vehicle camera (IVC) were installed in each of the participants' own vehicles for 6 months. The CWS was utilized to identify unsafe events during naturalistic driving situations, and the IVC was used to capture head direction at intersections. The experimental design was conducted in three phases (baseline, intervention, and carryover), 2 months each. Unsafe events were recorded by the CWS during all phases of the study. In the second phase, the CWS feedback was activated to examine its effect on drivers' head movement' behavior at intersections. Results Older drivers (65+) drove significantly more hours in total during the intervention phase (M = 79.1 hn the light of this complex picture, using the technological feedback with older drivers should be followed with an additional mediation or follow-up to ensure safety.The use of automation in cars is increasing. In future vehicles, drivers will no longer be in charge of the main driving task and may be allowed to perform a secondary task. However, they might be requested to regain control of the car if a hazardous situation occurs (i.e., conditionally automated driving). Performing a secondary task might increase drivers' mental workload and consequently decrease the takeover performance if the workload level exceeds a certain threshold. Knowledge about the driver's mental state might hence be useful for increasing safety in conditionally automated vehicles. Measuring drivers' workload continuously is essential to support the driver and hence limit the number of accidents in takeover situations. This goal can be achieved using machine learning techniques to evaluate and classify the drivers' workload in real-time. To evaluate the usefulness of physiological data as an indicator for workload in conditionally automated driving, three physiological signals from 90 subjects were collected during 25 min of automated driving in a fixed-base simulator. Half of the participants performed a verbal cognitive task to induce mental workload while the other half only had to monitor the environment of the car. Three classifiers, sensor fusion and levels of data segmentation were compared. Results show that the best model was able to successfully classify the condition of the driver with an accuracy of 95%. In some cases, the model benefited from sensors' fusion. Increasing the segmentation level (e.g., size of the time window to compute physiological indicators) increased the performance of the model for windows smaller than 4 min, but decreased for windows larger than 4 min. In conclusion, the study showed that a high level of drivers' mental workload can be accurately detected while driving in conditional automation based on 4-min recordings of respiration and skin conductance.Organic agriculture promotes the transformation toward sustainability because of positive effects for the environment. The organic label on food products enables consumers to make more sustainable purchasing decisions. Although the global market for organic food has grown rapidly in recent years, only a part of the organic product range benefits from this positive trend. To develop the organic market further, it is important to understand the food-related values and attitudes that drive the purchase of organic food. [https://www.selleckchem.com/products/ms177.html MS177 price] Previous research on this topic has suffered from two main weaknesses. Firstly, most studies have been based on surveys and rely on stated behavior instead of actual purchase behavior. Secondly, the focus of most extant studies is predominantly on organic food in general or on food products with a relatively high organic market share, such as milk and eggs. To address this knowledge gap, the present study analyzes the value-attitude-behavior relationship by means of structural equation modeling using household purchase panel data from GfK. The paper provides evidence for the existence of an attitude-behavior gap in the organic market, with this gap found to be much stronger in the case of meat, frozen food, cheese, and sweets than for organic purchases in total. Analysis in different product categories reveals that while purchase behavior is driven by the same food-related values, their relative importance differs.In response to the coronavirus disease 2019 (COVID-19) schools around the world have been closed to protect against the spread of coronavirus. In several countries, homeschooling has been introduced to replace classroom schooling. With a focus on individual differences, the present study examined 138 schoolers (age range = 6 to 21 years) regarding their self-control and boredom proneness. The results showed that both traits were important in predicting adherence to homeschooling. Schoolers with higher levels of self-control perceived homeschooling as less difficult, which in turn increased homeschooling adherence. In contrast, schoolers with higher levels of boredom proneness perceived homeschooling as more difficult, which in turn reduced homeschooling adherence. These results partially hold when it comes to studying in the classroom. However, boredom threatened adherence only in the homeschooling context. Our results indicate that boredom proneness is a critical construct to consider when educational systems switch to homeschooling during a pandemic.With the advent of COVID-19, a sudden, unexpected, and forced shift has been produced in the field of psychotherapy. Worldwide, many therapists closed their offices and started to deliver psychotherapy online through a screen. Although different media started to be incorporated, videoconferencing is undoubtedly the most common way in which therapists are doing therapy these days. This is catalyzing a rapid change in the practice of psychotherapy with probable lasting effects and deserves to be carefully reflected upon. Therefore, in this paper our aim is to outline the main challenges for a medium that may have arrived to stay. In that sense, we review the literature to describe the state-of-the-art regarding the main aspects of videoconferencing psychotherapy as well as to suggest possible avenues for future research and practice.