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      Trier social stress test and food-choice: Behavioral, self-report & hormonal data

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          Abstract

          A sample of 144 participants underwent the Trier Social Stress Test (TSST), a psychosocial stress manipulation involving a mock interview and a mental arithmetic task, or a matched control procedure. Physiological stress was estimated via a collection of 7 saliva samples over the course of the experiment analysed for cortisol and alpha-amylase, as well as via the mean heart-rate measured before and during the experimental manipulation. Subjective stress was assessed via the Positive and Negative Affect Scale as well as four Visual Analogue Scales at 6 points over the time course of the experiment. Participants solved an incentive-compatible food-choice task before, immediately after and in the aftermath of the experimental manipulation. In each trial of the food-choice task, participants had to choose one out of a set of two to seven snack bundles. Each snack bundle consisted of specific amounts of a sweet or salty snack and a fruit or vegetable. The snacks for both categories were selected to be similarly attractive according to the previously provided online ratings of the participants. The design of the food-choice task allows for the calculation of revealed preference consistency indices. The dataset further contains several self-report questionnaires administered to the participants before the experimental session, including the Trier Inventory of Chronic Stress.

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          Welcome to the Tidyverse

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            PsychoPy—Psychophysics software in Python

            The vast majority of studies into visual processing are conducted using computer display technology. The current paper describes a new free suite of software tools designed to make this task easier, using the latest advances in hardware and software. PsychoPy is a platform-independent experimental control system written in the Python interpreted language using entirely free libraries. PsychoPy scripts are designed to be extremely easy to read and write, while retaining complete power for the user to customize the stimuli and environment. Tools are provided within the package to allow everything from stimulus presentation and response collection (from a wide range of devices) to simple data analysis such as psychometric function fitting. Most importantly, PsychoPy is highly extensible and the whole system can evolve via user contributions. If a user wants to add support for a particular stimulus, analysis or hardware device they can look at the code for existing examples, modify them and submit the modifications back into the package so that the whole community benefits.
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              GARP for Kids: On the Development of Rational Choice Behavior

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                Author and article information

                Contributors
                @felixjannitsch
                @ManuelaSellitto
                @kalenscher
                Journal
                Data Brief
                Data Brief
                Data in Brief
                Elsevier
                2352-3409
                25 June 2021
                August 2021
                25 June 2021
                : 37
                Affiliations
                Comparative Psychology, Institute for Experimental Psychology, Heinrich-Heine-University Düsseldorf, Germany
                Author notes
                Article
                S2352-3409(21)00529-1 107245
                10.1016/j.dib.2021.107245
                8255170
                34258339
                © 2021 The Author(s). Published by Elsevier Inc.

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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                Data Article

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