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      Prosocial Influence and Opportunistic Conformity in Adolescents and Young Adults

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          Abstract

          Adolescence is associated with heightened social influence, especially from peers. This can lead to detrimental decision-making in domains such as risky behavior but may also raise opportunities for prosocial behavior. We used an incentivized charitable-donations task to investigate how people revise decisions after learning about the donations of others and how this is affected by age ( N = 220; age range = 11–35 years). Our results showed that the probability of social influence decreased with age within this age range. In addition, whereas previous research has suggested that adults are more likely to conform to the behavior of selfish others than to the behavior of prosocial others, here we observed no evidence of such an asymmetry in midadolescents. We discuss possible interpretations of these findings in relation to the social context of the task, the perceived value of money, and social decision-making across development.

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          Most cited references40

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          Random effects structure for confirmatory hypothesis testing: Keep it maximal.

          Linear mixed-effects models (LMEMs) have become increasingly prominent in psycholinguistics and related areas. However, many researchers do not seem to appreciate how random effects structures affect the generalizability of an analysis. Here, we argue that researchers using LMEMs for confirmatory hypothesis testing should minimally adhere to the standards that have been in place for many decades. Through theoretical arguments and Monte Carlo simulation, we show that LMEMs generalize best when they include the maximal random effects structure justified by the design. The generalization performance of LMEMs including data-driven random effects structures strongly depends upon modeling criteria and sample size, yielding reasonable results on moderately-sized samples when conservative criteria are used, but with little or no power advantage over maximal models. Finally, random-intercepts-only LMEMs used on within-subjects and/or within-items data from populations where subjects and/or items vary in their sensitivity to experimental manipulations always generalize worse than separate F 1 and F 2 tests, and in many cases, even worse than F 1 alone. Maximal LMEMs should be the 'gold standard' for confirmatory hypothesis testing in psycholinguistics and beyond.
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            Gorilla in our midst: An online behavioral experiment builder

            Behavioral researchers are increasingly conducting their studies online, to gain access to large and diverse samples that would be difficult to get in a laboratory environment. However, there are technical access barriers to building experiments online, and web browsers can present problems for consistent timing—an important issue with reaction-time-sensitive measures. For example, to ensure accuracy and test–retest reliability in presentation and response recording, experimenters need a working knowledge of programming languages such as JavaScript. We review some of the previous and current tools for online behavioral research, as well as how well they address the issues of usability and timing. We then present the Gorilla Experiment Builder (gorilla.sc), a fully tooled experiment authoring and deployment platform, designed to resolve many timing issues and make reliable online experimentation open and accessible to a wider range of technical abilities. To demonstrate the platform’s aptitude for accessible, reliable, and scalable research, we administered a task with a range of participant groups (primary school children and adults), settings (without supervision, at home, and under supervision, in both schools and public engagement events), equipment (participant’s own computer, computer supplied by the researcher), and connection types (personal internet connection, mobile phone 3G/4G). We used a simplified flanker task taken from the attentional network task (Rueda, Posner, & Rothbart, 2004). We replicated the “conflict network” effect in all these populations, demonstrating the platform’s capability to run reaction-time-sensitive experiments. Unresolved limitations of running experiments online are then discussed, along with potential solutions and some future features of the platform. Electronic supplementary material The online version of this article (10.3758/s13428-019-01237-x) contains supplementary material, which is available to authorized users.
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              A Social Neuroscience Perspective on Adolescent Risk-Taking.

              This article proposes a framework for theory and research on risk-taking that is informed by developmental neuroscience. Two fundamental questions motivate this review. First, why does risk-taking increase between childhood and adolescence? Second, why does risk-taking decline between adolescence and adulthood? Risk-taking increases between childhood and adolescence as a result of changes around the time of puberty in the brain's socio-emotional system leading to increased reward-seeking, especially in the presence of peers, fueled mainly by a dramatic remodeling of the brain's dopaminergic system. Risk-taking declines between adolescence and adulthood because of changes in the brain's cognitive control system - changes which improve individuals' capacity for self-regulation. These changes occur across adolescence and young adulthood and are seen in structural and functional changes within the prefrontal cortex and its connections to other brain regions. The differing timetables of these changes make mid-adolescence a time of heightened vulnerability to risky and reckless behavior.
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                Author and article information

                Journal
                Psychol Sci
                Psychol Sci
                PSS
                sppss
                Psychological Science
                SAGE Publications (Sage CA: Los Angeles, CA )
                0956-7976
                1467-9280
                23 November 2020
                December 2020
                23 May 2021
                : 31
                : 12
                : 1585-1601
                Affiliations
                [1 ]Division of Psychology and Language Sciences, Institute of Cognitive Neuroscience, University College London
                [2 ]Department of Psychology, University of Cambridge
                Author notes
                [*]Gabriele Chierchia, University of Cambridge, Department of Psychology E-mail: gsc34@ 123456cam.ac.uk
                Author information
                https://orcid.org/0000-0002-5623-4573
                https://orcid.org/0000-0002-6707-9943
                Article
                10.1177_0956797620957625
                10.1177/0956797620957625
                7734552
                33226891
                a5bf1f8f-a0cb-4d44-aa53-f977e25ad46a
                © The Author(s) 2020

                This article is distributed under the terms of the Creative Commons Attribution 4.0 License ( https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page ( https://us.sagepub.com/en-us/nam/open-access-at-sage).

                History
                : 22 July 2019
                : 12 June 2020
                Funding
                Funded by: Wellcome Trust, FundRef https://doi.org/10.13039/100004440;
                Award ID: 104908/Z/14/Z
                Funded by: Jacobs Foundation, FundRef https://doi.org/Jacobs Foundation;
                Funded by: Nuffield Foundation, FundRef https://doi.org/10.13039/501100000279;
                Funded by: Royal Society, FundRef https://doi.org/10.13039/501100000288;
                Categories
                General Articles
                Research Articles
                Custom metadata
                open-data
                open-materials
                ts1

                Clinical Psychology & Psychiatry
                social influences,conformity,cooperation,adolescent development,prosocial decisions,open data,open materials

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