The Psychological Science Accelerator: Advancing Psychology through a Distributed Collaborative Network

Abstract

Concerns have been growing about the veracity of psychological research. 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 attempt to 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 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.

Future Directions in Single-Session Youth Mental Health Interventions

“…We encourage others to make their materials available as well to optimize the rate of discovery with respect to SSIs-most critically, identifying when and for whom they do and do not help. In the long-term, SSI investigators could follow the model of Psychological Science Accelerator (Moshontz et al, 2018) and collaborate on large-scale interventions with harmonized measures across many sites. This model, along with pre-registration of analysis plans to avoid over-fitting, could help identify specific, robust contextual factors that may impact intervention response beyond individual-level characteristics.…”

Advancing Transparency and Openness in Child Development Research: Opportunities

“…In line with SRCD’s objectives and goals on inclusivity, data sharing creates opportunities to connect and collaborate with researchers across the world. Several emerging national and international efforts, such as the Many Labs studies (e.g., Klein et al, ), the Many Babies project (Frank et al, ), the Psychological Science Accelerator (Moshontz et al, ), and the Play and Learning Across a Year Project (https://www.play-project.org), aim to crowdsource psychological science. Such initiatives will result in larger and more diverse datasets than any researcher could collect alone.…”

And one more for the road: Commentary on the Special Issue on alcohol and eyewitness memory

“…They are expensive to conduct, researchers only have limited time available for data collection, and the exclusion and drop‐out rates are high. Nonetheless, a solution might be large‐scale collaborations across multiple laboratories, similar to the Many Labs (Klein et al, ) or the Psychological Science Accelerator (Moshontz et al, ) projects, in which researchers from different laboratories conducted the same experiment and then collated the data from their experiments. Ideally, such large‐scalecollaboration—a Many Drinks project, if you will—would be submitted as a registered report, limiting possible bias.…”