Ecological Momentary Assessment and Machine Learning for Predicting Suicidal Ideation
This is a virtual seminar. For a Zoom link, please see "Venue details". Please consider subscribing to mailing list: web.maillist.ox.ac.uk/ox/subscribe/ai4mch
This study aims to understand what extent does the analysis of daily data encompassing mood fluctuations and contextual stressful events effectively predict short- and long-term suicidal ideation in sexual and gender minority individuals. 103 individuals aged 18 to 29 years found that using 25-day ecological momentary assessment yielded acceptable prediction performance on 1-, 3-, and 8-month suicidal ideation. The prediction effect of feelings faded over time, while the prediction effect of contextual events remained strong. The findings suggest a promising future for detecting suicide ideation over time through the analysis of data on specific types of mood fluctuations and contextual events.
Date:
21 November 2023, 15:00 (Tuesday, 7th week, Michaelmas 2023)
Venue:
https://zoom.us/j/91910322449?pwd=eXRTM01Bb1gyYjRBaWpQQmZEV3VqQT09
Speaker:
Dr Runsen Chen (Tsinghua University)
Organising department:
Department of Psychiatry
Organiser:
Dr Andrey Kormilitzin (University of Oxford)
Organiser contact email address:
andrey.kormilitzin@psych.ox.ac.uk
Host:
Dr Andrey Kormilitzin (University of Oxford)
Part of:
Artificial Intelligence for Mental Health Seminar Series
Booking required?:
Not required
Booking url:
https://web.maillist.ox.ac.uk/ox/info/ai4mch
Booking email:
andrey.kormilitzin@psych.ox.ac.uk
Audience:
Public
Editor:
Andrey Kormilitzin
