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      Nostalgia Counteracts Social Anxiety and Enhances Interpersonal Competence

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          Abstract

          Socially anxious individuals struggle with establishing and maintaining social relationships. We hypothesized that, when socially anxious, people often turn to nostalgia, which alleviates the interpersonal competence deficits that accompany social anxiety. We tested and supported this hypothesis in six studies ( N = 1,858), three preregistered. In cross-sectional Study 1, higher (compared with lower) social anxiety individuals more frequently identified interpersonal incompetence as a trigger of nostalgia. In cross-sectional Study 2, social anxiety was associated negatively with interpersonal competence, but positively with nostalgia, which in turn predicted higher interpersonal competence. In the final four studies, we tested causation. Although social anxiety reduced interpersonal competence, it also triggered nostalgia (Studies 3–3S), and nostalgia increased interpersonal competence (Studies 4–5).

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          G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences

          G*Power (Erdfelder, Faul, & Buchner, 1996) was designed as a general stand-alone power analysis program for statistical tests commonly used in social and behavioral research. G*Power 3 is a major extension of, and improvement over, the previous versions. It runs on widely used computer platforms (i.e., Windows XP, Windows Vista, and Mac OS X 10.4) and covers many different statistical tests of the t, F, and chi2 test families. In addition, it includes power analyses for z tests and some exact tests. G*Power 3 provides improved effect size calculators and graphic options, supports both distribution-based and design-based input modes, and offers all types of power analyses in which users might be interested. Like its predecessors, G*Power 3 is free.
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            Is Open Access

            TurkPrime.com: A versatile crowdsourcing data acquisition platform for the behavioral sciences

            In recent years, Mechanical Turk (MTurk) has revolutionized social science by providing a way to collect behavioral data with unprecedented speed and efficiency. However, MTurk was not intended to be a research tool, and many common research tasks are difficult and time-consuming to implement as a result. TurkPrime was designed as a research platform that integrates with MTurk and supports tasks that are common to the social and behavioral sciences. Like MTurk, TurkPrime is an Internet-based platform that runs on any browser and does not require any downloads or installation. Tasks that can be implemented with TurkPrime include: excluding participants on the basis of previous participation, longitudinal studies, making changes to a study while it is running, automating the approval process, increasing the speed of data collection, sending bulk e-mails and bonuses, enhancing communication with participants, monitoring dropout and engagement rates, providing enhanced sampling options, and many others. This article describes how TurkPrime saves time and resources, improves data quality, and allows researchers to design and implement studies that were previously very difficult or impossible to carry out on MTurk. TurkPrime is designed as a research tool whose aim is to improve the quality of the crowdsourcing data collection process. Various features have been and continue to be implemented on the basis of feedback from the research community. TurkPrime is a free research platform.
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              Determining Power and Sample Size for Simple and Complex Mediation Models

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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                Social Psychological and Personality Science
                Social Psychological and Personality Science
                SAGE Publications
                1948-5506
                1948-5514
                July 20 2023
                Affiliations
                [1 ]Peking University, Beijing, China
                [2 ]University of Southampton, UK
                Article
                10.1177/19485506231187680
                e6c54eac-9483-43db-afc8-05797983897f
                © 2023

                http://journals.sagepub.com/page/policies/text-and-data-mining-license

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