The Psychological Science Accelerator: Advancing psychology through a distributed collaborative network


Hannah Moshontz

Lorne Campbell

Charles R. Ebersole

Hans IJzerman

Heather L. Urry

Patrick S. Forscher

Jon E. Grahe

Randy J. McCarthy

Erica D. Musser

Jan Antfolk

Christopher M. Castille

Thomas Rhys Evans

Susann Fiedler

Jessica Kay Flake

Diego A. Forero

Steve M. J. Janssen

Justin Robert Keene

John Protzko

Balazs Aczel

Sara Álvarez Solas

Daniel Ansari

Dana Awlia

Ernest Baskin

Carlota Batres

Martha Lucia Borras-Guevara

Cameron Brick

Priyanka Chandel

Armand Chatard

William J. Chopik

David Clarance

Nicholas A. Coles

Katherine S. Corker

Barnaby James Wyld Dixson

Vilius Dranseika

Yarrow Dunham

Nicholas W. Fox

Gwendolyn Gardiner

S. Mason Garrison

Tripat Gill

Amanda C. Hahn

Bastian Jaeger

Pavol Kačmár

Gwenaël Kaminski

Philipp Kanske

Zoltan Kekecs

Melissa Kline

Monica A. Koehn

Pratibha Kujur

Carmel A. Levitan

Jeremy K. Miller

Ceylan Okan

Jerome Olsen

Oscar Oviedo-Trespalacios

Asil Ali Özdoğru

Babita Pande

Arti Parganiha

Noorshama Parveen

Gerit Pfuhl

Sraddha Pradhan

Ivan Ropovik

Nicholas O. Rule

Blair Saunders

Vidar Schei

Kathleen Schmidt

Margaret Messiah Singh

Miroslav Sirota

Crystal N. Steltenpohl

Stefan Stieger

Daniel Storage

Gavin Brent Sullivan

Anna Szabelska

Christian K. Tamnes

Miguel A. Vadillo

Jaroslava V. Valentova

Wolf Vanpaemel

Marco A. C. Varella

Evie Vergauwe

Mark Verschoor

Michelangelo Vianello

Martin Voracek

Glenn P. Williams

John Paul Wilson

Janis H. Zickfeld

Jack D. Arnal

Burak Aydin

Sau-Chin Chen

Lisa M. DeBruine

Ana Maria Fernandez

Kai T. Horstmann

Peder M. Isager

Benedict Jones

Aycan Kapucu

Hause Lin

Michael C. Mensink

Gorka Navarrete

Miguel A. Silan

Christopher R. Chartier


Concerns about the veracity of psychological research have been growing. Many findings in psychological science are based on studies with insufficient statistical power and nonrepresentative samples, or may otherwise be limited to specific, ungeneralizable settings or populations. Crowdsourced research, a type of 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. These projects can focus on novel research questions or replicate prior research in large, diverse samples. 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 that structures and principles are reused for different projects), decentralized, diverse (in both subjects and researchers), and inclusive (of proposals, contributions, and other relevant input from anyone inside or outside the network). The PSA and other approaches to crowdsourced psychological science will advance understanding of mental processes and behaviors by enabling rigorous research and systematic examination of its generalizability.