In two studies, we examine the relationship between self-reported everyday activities and SWB, while allowing individuals to express their activities freely by allowing open-ended responses that were then analyzed with state-of-the-art (transformers-based) Natural Language Processing.
We show that using a recent break-through in artificial intelligence –transformers–, psychological assessments from text-responses can approach theoretical upper limits in accuracy, converging with standard psychological rating scales..
The study provides preliminary evidence for the MBFP’s cross-cultural validity, and strengthens previous claims for its efficacy as a new, accessible alternative for enhancing wellbeing.
We suggest that the use of computerized methods to quantify and analyze text can be an important tool to move the affective profiles model into the era of big text data