891 resultados para Behavioral tasks


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This paper is an elaboration of one of the chapters in our Rethinking Wetland Archaeology (Van de Noort & O'Sullivan 2006), and concerns the archaeological study of wetland landscapes. In this book, we argue that many approaches to the archaeology of wetlands have failed to influence our peers and colleagues in the broader field of landscape archaeology and, indeed, archaeology itself, and thus the great promise of wetland archaeology remains unfulfilled (Coles 2001).

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We study the behavior and emotional arousal of the participants in an experimental auction, leading to an asymmetric social dilemma involving an auctioneer and two bidders. An antisocial transfer (bribe) which is beneficial for the auctioneer (official) is paid, if promised, by the winner of the auction. Some pro-social behavior on both the auctioneers' and the bidders' sides is observed even in the absence of any punishment mechanism (Baseline, Treatment 0). However, pro-social behavior is adopted by the vast majority of subjects when the loser of the auction can inspect the transaction between the winner and the auctioneer (Inspection, Treatment 1). The inspection and punishment mechanism is such that, if a bribe is (not) revealed, both corrupt agents (the denouncing bidder) lose(s) this period's payoffs. This renders the inspection option unprofitable for the loser and is rarely used, especially towards the end of the session, when pro-social behavior becomes pervasive. Subjects' emotional arousal was obtained through skin conductance responses. Generally speaking, our findings suggest that stronger emotions are associated with decisions deviating from pure monetary reward maximization, rather than with (un)ethical behavior per se. In fact, using response times as a measure of the subject's reflection during the decision-making process, we can associate emotional arousal with the conflict between primary or instinctive and secondary or contemplative motivations and, more specifically, with deviations from the subject's pure monetary interest.

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The courtship behavior of the navel orangeworm, Amyelois transitella, was examined in a wind tunnel. Sixty nine courtship sequences were analyzed and successful sequences divided into two categories: rapid courtship sequences, which involved few breaks in contact, short or no periods of male/female chasing and lasted <10 s between initial contact and mating; and prolonged courtship sequences, which involved many breaks in contact, extended periods of male/female chasing and lasted >10 s. Fifty six (81%) courtships were successful (50.7% rapid courtship and 30.4% prolonged courtship); the remaining 13 (18.8%) sequences were failed courtships. Of failed courtships, 9 (13.0%) were due to males losing contact with females during courtship chases and 4 (5.8%) due to females flying away immediately after male contact. Of all courtship sequences involving a break in contact during a chase, 38.5% resulted in an unsuccessful mating attempt. These findings contrast with previous studies of the courtship behavior of the navel orangeworm, potentially indicating that the type of bioassay used to study courtship may have a large effect on the behavioral sequences displayed. We evaluate several diagnostic techniques for the analysis of sequences of behavioral transitions.

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Traditionally, biosensors have been defined as consisting of two parts; a biological part, which is used to detect chemical or physical changes in the environment, and a corresponding electronic component, which tranduces the signal into an electronically readable format. Biosensors are used for detection of volatile compounds often at a level of sensitivity unattainable by traditional analytical techniques. Classical biosensors and traditional analytical techniques do not allow an ecological context to be imparted to the volatile compound/s under investigation. Therefore, we propose the use of behavioral biosensors, in which a whole organism is utilized for the analysis of chemical stimuli. In this case, the organism detects a chemical or physical change and demonstrates this detection through modifications of its behavior; it is the organism's behavior itself that defines the biosensor. In this review, we evaluate the use and future prospects of behavioral biosensors, with a particular focus on parasitic wasps.

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Abstract. In two linked studies we examined children’s performance on tasks required for participation in cognitive therapy. In Study 1 we piloted some new tasks with children aged 5 to 11 years. In study 2 the effects of IQ, age and educational experience were examined in children aged 5 to 7 years. In study 1, 14 children aged 5 to 11 completed three tasks related to cognitive therapy; generating post-event attributions, naming emotions, and linking thoughts and feelings. Study 2 used a between-subjects design in which 72 children aged 5, 6, or 7 years from two primary schools completed the three tasks and the Block Design and Vocabulary sub-tests from the WISC III or WPPSI-R. Children were tested individually during the school day. All measures were administered on the same occasion. In study 2 administration order of the cognitive therapy task and the WISC III/WPPSI-R were randomized. The majority of children demonstrated some ability on each of the three tasks. In study 2, performance was associated with school and with IQ but not with age. There were no gender differences. Children attending a school with an integrated thinking skills programme and those with a higher 1Q were more successful on the cognitive therapy tasks. These results suggest that many young children could engage in cognitive therapy given age-appropriate materials. The effects of training in relevant meta-cognitive skills on children’s ability to use concepts in CBT may warrant further research. Keywords: Cognitive behaviour therapy, young children, cognitive development

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Farmers are necessary agents in global efforts to conserve the environment now that croplands and pastures together constitute the largest terrestrial system on Earth – covering some 48% of ice-free land surface. Whereas standard economic models predict that farmers will participate in conservation programs so long as they are profitable, empirical findings from behavioral economics point to a number of normally unobservable preferences that may influence the decision-making process. This study tests, for the first time, whether heterogeneity in behavioral preferences correlates with decisions to participate in Payments for Environmental Services (PES) programs. We elicit individual trust and time preferences using economic experiments and link resulting measures to household survey data and participation decisions in a Ugandan PES program. We find that farmers who exhibit a preference for proximate gains – present-biased preferences – are 47.7% more likely to participate in the program than those who show time-consistent or future-biased preferences. This result has implications for ongoing and planned PES programs involving farmers, particularly in Africa, by highlighting a potential relationship between payment timing and participation, and further validates the use of behavioral experiments in explaining real-world decisions.

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The use of economic incentives for biodiversity (mostly Compensation and Reward for Environmental Services including Payment for ES) has been widely supported in the past decades and became the main innovative policy tools for biodiversity conservation worldwide. These policy tools are often based on the insight that rational actors perfectly weigh the costs and benefits of adopting certain behaviors and well-crafted economic incentives and disincentives will lead to socially desirable development scenarios. This rationalist mode of thought has provided interesting insights and results, but it also misestimates the context by which ‘real individuals’ come to decisions, and the multitude of factors influencing development sequences. In this study, our goal is to examine how these policies can take advantage of some unintended behavioral reactions that might in return impact, either positively or negatively, general policy performances. We test the effect of income's origin (‘Low effort’ based money vs. ‘High effort’ based money) on spending decisions (Necessity vs. Superior goods) and subsequent pro social preferences (Future pro-environmental behavior) within Madagascar rural areas, using a natural field experiment. Our results show that money obtained under low effort leads to different consumption patterns than money obtained under high efforts: superior goods are more salient in the case of low effort money. In parallel, money obtained under low effort leads to subsequent higher pro social behavior. Compensation and rewards policies for ecosystem services may mobilize knowledge on behavioral biases to improve their design and foster positive spillovers on their development goals.

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Clustering methods are increasingly being applied to residential smart meter data, providing a number of important opportunities for distribution network operators (DNOs) to manage and plan the low voltage networks. Clustering has a number of potential advantages for DNOs including, identifying suitable candidates for demand response and improving energy profile modelling. However, due to the high stochasticity and irregularity of household level demand, detailed analytics are required to define appropriate attributes to cluster. In this paper we present in-depth analysis of customer smart meter data to better understand peak demand and major sources of variability in their behaviour. We find four key time periods in which the data should be analysed and use this to form relevant attributes for our clustering. We present a finite mixture model based clustering where we discover 10 distinct behaviour groups describing customers based on their demand and their variability. Finally, using an existing bootstrapping technique we show that the clustering is reliable. To the authors knowledge this is the first time in the power systems literature that the sample robustness of the clustering has been tested.

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Understanding how wildlife responds to road and traffic is essential for effective conservation. Yet, not many studies have evaluated how roads influence wildlife in protected areas, particularly within the large iconic African National Parks where tourism is mainly based on sightings from motorized vehicles with the consequent development and intense use of roads. To reduce this knowledge gap, we studied the behavioral response and local spatial distribution of impala Aepyceros melampus along the heterogeneous (with variation in road surface type and traffic intensity) road-network of Kruger National Park (KNP, South Africa). We surveyed different types of roads (paved and unpaved) recording the occurrence of flight responses among sighted impala and describing their local spatial distribution (in relation to the roads). We observed relatively few flight responses (19.5% of 118 observations), suggesting impalas could be partly habituated to vehicles in KNP. In addition, impala local distribution is apparently unaffected by unpaved roads, yet animals seem to avoid the close proximity of paved roads. Overall, our results suggest a negative, albeit small, effect of traffic intensity, and of presence of pavement on roads on the behavior of impala at KNP. Future studies would be necessary to understand how roads influence other species, but our results show that even within a protected area that has been well-visited for a long time, wildlife can still be affected by roads and traffic. This result has ecological (e.g., changes in spatial distribution of fauna) and management implications (e.g., challenges of facilitating wildlife sightings while minimizing disturbance) for protected areas where touristic activities are largely based on driving.

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Population ecology is a discipline that studies changes in the number and composition (age, sex) of the individuals that form a population. Many of the mechanisms that generate these changes are associated with individual behavior, for example how individuals defend their territories, find mates or disperse. Therefore, it is important to model population dynamics considering the potential influence of behavior on the modeled dynamics. This study illustrates the diversity of behaviors that influence population dynamics describing several methods that allow integrating behavior into population models and range from simpler models that only consider the number of individuals to complex individual-based models that capture great levels of detail. A series of examples shows the importance of explicitly considering behavior in population modeling to avoid reaching erroneous conclusions. This integration is particularly relevant for conservation, as incorrect predictions regarding the dynamics of populations of conservation interest can lead to inadequate assessment and management. Improved predictions can favor effective protection of species and better use of the limited financial and human conservation resources.

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Aims Training has been shown to improve the ability of people with intellectual disabilities (IDs) to perform some cognitive behavioural therapy (CBT) tasks. This study used a computerised training paradigm with the aim of improving the ability of people with IDs to: a) discriminate between behaviours, thoughts and feelings, and b) link situations, thoughts and feelings. Methods Fifty-five people with mild-to-moderate IDs were randomly assigned to a training or attention-control condition in a single-blind mixed experimental design. Computerised tasks assessed the participants’ skills in: (a) discriminating between behaviours, thoughts and feelings (separately and pooled together), and (b) cognitive mediation by selecting appropriate emotions as consequences to given thoughts, and appropriate thoughts as mediators of given emotions. Results Training significantly improved ability to discriminate between behaviours, thoughts and feelings pooled together, compared to the attention-control condition, even when controlling for baseline scores and IQ. Large within-group improvements in the ability to identify behaviours and feelings were observed for the training condition, but not the attention-control group. There were no significant between-group differences in ability to identify thoughts, or on cognitive mediation skills. Conclusions A single session of computerised training can improve the ability of people with IDs to understand and practise CBT tasks relating to behaviours and feelings. There is potential for computerised training to be used as a “primer” for CBT with people with IDs to improve engagement and outcomes, but further development on a specific computerised cognitive mediation task is needed.

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Background: Health care literature supports the development of accessible interventions that integrate behavioral economics, wearable devices, principles of evidence-based behavior change, and community support. However, there are limited real-world examples of large scale, population-based, member-driven reward platforms. Subsequently, a paucity of outcome data exists and health economic effects remain largely theoretical. To complicate matters, an emerging area of research is defining the role of Superusers, the small percentage of unusually engaged digital health participants who may influence other members. Objective: The objective of this preliminary study is to analyze descriptive data from GOODcoins, a self-guided, free-to-consumer engagement and rewards platform incentivizing walking, running and cycling. Registered members accessed the GOODcoins platform through PCs, tablets or mobile devices, and had the opportunity to sync wearables to track activity. Following registration, members were encouraged to join gamified group challenges and compare their progress with that of others. As members met challenge targets, they were rewarded with GOODcoins, which could be redeemed for planet- or people-friendly products. Methods: Outcome data were obtained from the GOODcoins custom SQL database. The reporting period was December 1, 2014 to May 1, 2015. Descriptive self-report data were analyzed using MySQL and MS Excel. Results: The study period includes data from 1298 users who were connected to an exercise tracking device. Females consisted of 52.6% (n=683) of the study population, 33.7% (n=438) were between the ages of 20-29, and 24.8% (n=322) were between the ages of 30-39. 77.5% (n=1006) of connected and active members met daily-recommended physical activity guidelines of 30 minutes, with a total daily average activity of 107 minutes (95% CI 90, 124). Of all connected and active users, 96.1% (n=1248) listed walking as their primary activity. For members who exchanged GOODcoins, the mean balance was 4,000 (95% CI 3850, 4150) at time of redemption, and 50.4% (n=61) of exchanges were for fitness or outdoor products, while 4.1% (n=5) were for food-related items. Participants were most likely to complete challenges when rewards were between 201-300 GOODcoins. Conclusions: The purpose of this study is to form a baseline for future research. Overall, results indicate that challenges and incentives may be effective for connected and active members, and may play a role in achieving daily-recommended activity guidelines. Registrants were typically younger, walking was the primary activity, and rewards were mainly exchanged for fitness or outdoor products. Remaining to be determined is whether members were already physically active at time of registration and are representative of healthy adherers, or were previously inactive and were incentivized to change their behavior. As challenges are gamified, there is an opportunity to investigate the role of superusers and healthy adherers, impacts on behavioral norms, and how cooperative games and incentives can be leveraged across stratified populations. Study limitations and future research agendas are discussed.