People with substance use problems differ in the mechanisms triggering and maintaining substance use, therefore it is necessary to understand personalized mechanisms to discuss these during treatment and choose appropriate strategies to change the substance use behavior. In this project, we aim to use personalized ecological momentary assessment (EMA) and derived statistical models to help psychologists and their clients to understand how substance use works in the daily life of each client. Specifically, clients can answer personalized questions on their smartphone multiple times per day for multiple days, then the psychologists in collaboration with the researcher can use these data to generate personalized descriptive statistics (e.g., trends of mood and substance use over time), and inferential statistics (personalized networks). Personalized networks allow to visualize how different factors in the daily life of a client influence each other in one moment or over time, making them particularly promising to understand personalized mechanisms of substance use. The generated personalized networks and other statistics can then be used within psychologist-client sessions to discuss personalized triggers and consequences of substance use and protective factors. We expect this tool to improve psychologist-client communication and intervention outcomes.
As part of this project, we first ran simulation studies to test the feasibility to reliably estimate personalized networks with the data of one client. In a second stage, we developed a personalized EMA module and an application to estimate personalized statistics, and we conducted a case proof-of-principle study where we used this with one participant with cannabis use problems and one psychologist. We are now testing our tool in a preclinical population of young adults who want help to quit or diminish their cannabis use, and who receive a short intervention by trained psychology interns. We are focused on (1) investigating the feasibility of our tool throught semi-structured interviews based on the extended technology acceptance model, (2) investigating preliminary effects of our tool on participant-psychology intern communication, and (3) investigating preliminary effects of our tool on substance use and mental health outcomes. We plan future studies in a clinical setting with patients diagnosed with substance use disorders. This project is conducted in collaboration with the Department of Psychology.
Research team:
- Alessandra Chiara Mansueto (PhD student)
- Dr. Barbara Schouten (Co-promotor)
- Dr. Sacha Epskamp (Co-promotor)
- Prof. Dr. Julia C. M. van Weert (Promotor)
- Prof. Dr. Reinout W. H. J. Wiers (Promotor)
Status: Ongoing since 01/02/2020
Funding: Center for Urban Mental Health, which is part of the University of Amsterdam