Digital Traces of Subjective Well-Being: Leveraging Smartphone Data and Machine Learning for Well-Being Research
Type
conference contribution
Date Issued
2024
Author(s)
;
;
Ramona Schoedel
;
Markus Buehner
;
Gabriella Harari
;
Samuel Gosling
;
Mirjam Stieger
;
Mathias Allemand
;
Abstract
Subjective well-being (SWB) is one of the most valued psychological resources by people, predicting life outcomes in various domains (e.g., work, health, social). In the pursuit of improving people’s SWB, previous research has consistently associated everyday behaviors with the level and deliberate change of SWB. However, as these insights are mainly based on self-reports the relationship between SWB and actual everyday behavior remains unclear. The present study leverages a machine learning approach and large-scale smartphone data, to study the relationship between SWB and real-life behavior. Framed as a prediction task, we investigate how people’s SWB can be predicted from smartphone-based digital records of behavior and which behavioral traces are most important in this regard. The results shed light on how signals of SWB can manifest in people’s everyday behavior. This can inform behavioral theories on SWB as well as the development of scalable tools to estimate and improve people’s SWB.
Refereed
Yes
Event Title
European Conference on Personality 2024
Event Location
Berlin, Germany
Subject(s)
Division(s)