Open Science lessons for accelerating EMA/ESM research from a NIDA-funded study on alcohol and marijuana use

The past decade taught us that the scientific literature in psychology is severely biased. Biased research not only wastes limited resources (time, effort, money) but ultimately can impede progress and lead to the application of interventions that are ineffective or potentially even harmful. The extent to which ESM research is biased is unknown, partially due to extensive replication work being unfeasible. I argue that this makes it even more important that we engage in best practices in our ESM work to ensure that our studies are highly credible. For example, as ESM researchers focusing on addiction, we have a responsibility towards patients to improve the prevention and treatment of substance use disorders over time. In this talk I will focus on my experiences with a NIDA-funded study of alcohol and marijuana use to outline how we as ESM researchers can use tools and principles from Open Science (preregistration; sharing of data, code, and materials; large-scale Team Science collaboration) to increase the credibility and trustworthiness of our ESM studies. I will present an ESM Open Science research workflow that we have developed in our lab over the last years. I will discuss concrete challenges I have encountered developing this workflow, how I solved some of them successfully, and what failures taught me for my work moving forward. I hope to convince you in this talk that incorporating Open Science into your ESM workflow is feasible and worthwhile.

May 25, 2023