The Association of Transformer-based Sentiment Analysis with Symptom Distress and Deterioration in Routine Psychotherapy Care

TL;DR

This study explores how transformer-based sentiment analysis of psychotherapy session transcripts correlates with patient distress and deterioration, showing potential as an adjunctive psychometric tool.

Contribution

It introduces a novel application of transformer-derived sentiment features as indicators of patient distress and deterioration in psychotherapy sessions.

Findings

Sentiment features correlate with emotional valence components of the OQ-45.

Significant differences in sentiment distributions for patients at risk of deterioration.

Sentiment features show promise as adjunctive measures for client distress assessment.

Abstract

Sentiment analysis has been of long-standing interest in psychotherapy research. Recently, the Transformer deep learning architecture has produced text-based sentiment analysis models that are highly accurate and context-aware. These models have been explored as proxies for emotion measurement instruments in psychotherapy, but not investigated as stand-alone psychometric tools. Using proposed utterance-level and session-level sentiment features derived from a fine-grained sentiment model on a large corpus of psychotherapy sessions (N = 751), we investigate the distribution of session aggregated sentiment scores. Further, we characterize the relationship of these features to individual components and the overall score of the OQ-45 instrument and find that this sentiment feature is most strongly correlated to components related to emotional valence in directionally intuitive ways. Finally, we report that there are statistically significant differences between the sentiment distributions for patients flagged as at risk of deterioration or dropping out of care via either the OQ Rational or Empirical outcome models. These correlations to a fully-validated psychometric instrument demonstrate that these proposed sentiment features are, at least, adjunctive measures of client distress and deterioration.