Work

Methods for a fully online automated cognitive training study on Prolific

Year: 2025

Type: article

Abstract: Intervention studies are the current gold standard when investigating the causal link between an intervention (e.g., physical activity, cognitive training, meditation, action video games) and its impact on cognitive functions. Such studies are resource intensive, especially when conducted to the latest standards in the field. Recently, it has been noted that the development of online tools to conduct such studies may significantly reduce resource demands, and thus allow more of these acutely necessary studies to be carried out. Here we present a series of tools to conduct intervention studies in a fully online fashion such that participants may go through the entire experimental pipeline without any contact with the experimenters. In particular this included Prolific for participant recruitment and management, the implementation of a pseudo-randomized group assignment procedure such that groups are matched at pre-test, and the development of various dashboards for experimenters and participants to follow their progression throughout the pipeline. These tools were implemented in a 12-h mechanistic cognitive training study where participants completed the training and pre- and post-test assessments remotely over multiple weeks. This new digital pipeline allowed us to limit the resource demands, implement strong masking practices, recruit a sample more diverse than the usual WEIRD in-laboratory samples, and complete the study in less time than usually needed. • We need more RCTs to establish the effect of various activities on cognition. • State of the art RCTs are costly in human, time, financial resources. • A fully-automated online pipeline decreased man-hour demands by 90 %. • Adherence rate is similar to supervised online data collection. • Our sample was more diverse (country of origin and SES) than convenience samples.

Source: Acta Psychologica

DOI: 10.1016/j.actpsy.2025.105704

Authors: Freya Joessel, Sylvie Denkinger, Paul-Emile Joessel, C. Shawn Green, Daphne Bavelier

Institutions: University of Geneva, University of Wisconsin–Madison

Language: English

Topic: Mobile Crowdsensing and Crowdsourcing

Subfield: Computer Science Applications

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $2,670