In this Papers Podcast, Isaac Ahuvia discusses his JCPP paper ‘Evaluating a treatment selection approach for online single-session interventions for adolescent depression’ (https://doi.org/10.1111/jcpp.13822). Isaac is the lead author of the paper.
There is an overview of the paper, methodology, key findings, and implications for practice.
Discussion points include:
- Definition of single-session interventions.
- How the treatment selection algorithms were created and tested.
- Implications for future research and front-line clinicians.
- Will these types of machine-learning algorithms be refined to be usable for the future?
In this series, we speak to authors of papers published in one of ACAMH’s three journals. These are The Journal of Child Psychology and Psychiatry (JCPP); The Child and Adolescent Mental Health (CAMH) journal; and JCPP Advances.
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Isaac Ahuvia (he/him) is a Ph.D. candidate in the Clinical Psychology program at Stony Brook University. His research focuses on the ways that adolescents understand depression, and how their beliefs about depression shape their experiences and clinical outcomes. As a member of the Lab for Scalable Mental Health, he has conducted research on treatment matching for single-session interventions, depression belief change through single-session interventions, and has co-designed a single-session intervention targeting body dissatisfaction.
The post What Works for Whom: Treatment Selection Approach for Single-Session Interventions for Depression appeared first on ACAMH.
