2025
preprint
The Psychological Science Accelerator: Advancing Psychology through a Distributed Collaborative Network
Erica D. Musser, Martin Voracek, John Paul Wilson, Christian K. Tamnes, Jessica Kay Flake, Monica Koehn, Hans IJzerman, Glenn Patrick Williams, Jeremy K. Miller, Janis Zickfeld, Patrick S. Forscher, Aycan Kapucu, Mark Verschoor, Pratibha Kujur, Vilius Dranseika, Carmel Levitan, Pavol Kačmár, Oscar Oviedo-Trespalacios, Stefan Stieger, Jan Antfolk, Zoltan Kekecs, Gerit Pfuhl, Cameron Brick, Michelangelo Vianello, Bastian Jaeger, Melissa Kline Struhl, Lorne Campbell, Daniel Storage, Crystal N. Steltenpohl, Balazs Aczel, Priyanka Chandel, Barnaby Dixson, Nicholas Rule, Michael Mensink, William J. Chopik, Miguel A. Vadillo, wolf vanpaemel, Dana Awlia, Ivan Ropovik, Justin Keene, Cynthia H.Y. Fu, Diego A. Forero, Arti Parganiha, Jerome Olsen, S. Mason Garrison, Armand Chatard, Heather L. Urry, Vidar Schei, Christopher R. Chartier, Martha Lucia, Philipp Kanske, Margaret Messiah Singh, Anna Szabelska, Sara Álvarez Solas, Babita Pande, Evie Vergauwe, Ceylan Okan, Blair Saunders, Hannah Moshontz, Gwendolyn Gardiner, Charles R. Ebersole, Gavin Brent Sullivan, Noorshama Parveen, Susann Fiedler, Katherine S. Corker, Yarrow Dunham, Ernest Baskin, Thomas Rhys Evans, Miroslav Sirota, John Protzko, Steve M. J. Janssen, Sraddha Pradhan, Christopher M. Castille, Amanda C Hahn, Jon Grahe, Daniel Ansari, Asil Ozdogru, Ana Maria Fernandez, Randy J. McCarthy, Kathleen Schmidt, Nicholas Fox [SCORE], David Clarance, Carlota Batres, Tripat Gill, Kaminski Gwenaël
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Le résumé fourni par la source
Concerns have been growing about the veracity of psychological findings. Many findings in psychological science are based on studies with insufficient statistical power and non-representative samples, or may otherwise be limited to specific, ungeneralizable settings or populations. Large-scale collaboration, in which one or more research projects are conducted across multiple lab sites, offers a pragmatic solution to these and other current methodological challenges. The Psychological Science Accelerator (PSA) is a distributed network of laboratories designed to enable and support crowdsourced research projects. The PSA’s mission is to accelerate the accumulation of reliable and generalizable evidence in psychological science. Here, we describe the background, structure, principles, procedures, benefits, and challenges of the PSA. In contrast to other crowdsourced research networks, the PSA is ongoing (as opposed to time-limited), efficient (in terms of re-using structures and principles for different projects), decentralized, diverse (in terms of participants and researchers), and inclusive (of proposals, contributions, and other relevant input from anyone inside or outside of the network). The PSA and other approaches to crowdsourced psychological science will advance our understanding of mental processes and behaviors by enabling rigorous research and systematically examining its generalizability.
Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.
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Les sujets associés
Mental Health Research TopicsDigital Mental Health InterventionsMobile Crowdsensing and Crowdsourcing