The Psychological Science Accelerator: Advancing Psychology Through a Distributed Collaborative Network. Issue 4 (December 2018)
- Record Type:
- Journal Article
- Title:
- The Psychological Science Accelerator: Advancing Psychology Through a Distributed Collaborative Network. Issue 4 (December 2018)
- Main Title:
- The Psychological Science Accelerator: Advancing Psychology Through a Distributed Collaborative Network
- Authors:
- Moshontz, Hannah
Campbell, Lorne
Ebersole, Charles R.
IJzerman, Hans
Urry, Heather L.
Forscher, Patrick S.
Grahe, Jon E.
McCarthy, Randy J.
Musser, Erica D.
Antfolk, Jan
Castille, Christopher M.
Evans, Thomas Rhys
Fiedler, Susann
Flake, Jessica Kay
Forero, Diego A.
Janssen, Steve M. J.
Keene, Justin Robert
Protzko, John
Aczel, Balazs
Álvarez Solas, Sara
Ansari, Daniel
Awlia, Dana
Baskin, Ernest
Batres, Carlota
Borras-Guevara, Martha Lucia
Brick, Cameron
Chandel, Priyanka
Chatard, Armand
Chopik, William J.
Clarance, David
Coles, Nicholas A.
Corker, Katherine S.
Dixson, Barnaby James Wyld
Dranseika, Vilius
Dunham, Yarrow
Fox, Nicholas W.
Gardiner, Gwendolyn
Garrison, S. Mason
Gill, Tripat
Hahn, Amanda C.
Jaeger, Bastian
Kačmár, Pavol
Kaminski, Gwenaël
Kanske, Philipp
Kekecs, Zoltan
Kline, Melissa
Koehn, Monica A.
Kujur, Pratibha
Levitan, Carmel A.
Miller, Jeremy K.
Okan, Ceylan
Olsen, Jerome
Oviedo-Trespalacios, Oscar
Özdoğru, Asil Ali
Pande, Babita
Parganiha, Arti
Parveen, Noorshama
Pfuhl, Gerit
Pradhan, Sraddha
Ropovik, Ivan
Rule, Nicholas O.
Saunders, Blair
Schei, Vidar
Schmidt, Kathleen
Singh, Margaret Messiah
Sirota, Miroslav
Steltenpohl, Crystal N.
Stieger, Stefan
Storage, Daniel
Sullivan, Gavin Brent
Szabelska, Anna
Tamnes, Christian K.
Vadillo, Miguel A.
Valentova, Jaroslava V.
Vanpaemel, Wolf
Varella, Marco A. C.
Vergauwe, Evie
Verschoor, Mark
Vianello, Michelangelo
Voracek, Martin
Williams, Glenn P.
Wilson, John Paul
Zickfeld, Janis H.
Arnal, Jack D.
Aydin, Burak
Chen, Sau-Chin
DeBruine, Lisa M.
Fernandez, Ana Maria
Horstmann, Kai T.
Isager, Peder M.
Jones, Benedict
Kapucu, Aycan
Lin, Hause
Mensink, Michael C.
Navarrete, Gorka
Silan, Miguel A.
Chartier, Christopher R.
… (more) - Abstract:
- 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 andConcerns 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. … (more)
- Is Part Of:
- Advances in methods and practices in psychological science. Volume 1:Issue 4(2018)
- Journal:
- Advances in methods and practices in psychological science
- Issue:
- Volume 1:Issue 4(2018)
- Issue Display:
- Volume 1, Issue 4 (2018)
- Year:
- 2018
- Volume:
- 1
- Issue:
- 4
- Issue Sort Value:
- 2018-0001-0004-0000
- Page Start:
- 501
- Page End:
- 515
- Publication Date:
- 2018-12
- Subjects:
- Psychological Science Accelerator -- crowdsourcing -- generalizability -- theory development -- large-scale collaboration
Psychology -- Periodicals
Psychology -- Research -- Periodicals
150 - Journal URLs:
- http://journals.sagepub.com/loi/ampa ↗
http://www.sagepublications.com/ ↗ - DOI:
- 10.1177/2515245918797607 ↗
- Languages:
- English
- ISSNs:
- 2515-2459
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 9305.xml