Using computerized text analysis to examine associations between linguistic features and clients’ distress during psychotherapy.

Abstract

Raw linguistic data within psychotherapy sessions may provide important information about clients' progress and well-being. In the current study, computerized text analytic techniques were applied to examine whether linguistic features were associated with clients' experiences of distress within and between clients and whether changes in linguistic features were associated with changes in treatment outcome. Transcripts of 729 psychotherapy sessions from 58 clients treated by 52 therapists were analyzed. Prior to each session, clients reported their distress level. Linguistic features were extracted automatically by using natural language parser for first-person singular identification and using positive and negative emotion words lexicon. The association between linguistic features and levels of distress was examined using multilevel models. At the within-client level, fewer first-person singular words, fewer negative emotional words and more positive emotional words were associated with lower distress in the same session; and fewer negative emotion words were associated with lower next session distress (rather small f 2 effect sizes ϭ 0.011 Ͻ f 2 Ͻ 0.022). At the between-client level, only first session use of positive emotion words was associated with first session distress ( p 2 effect size ϭ 0.08). A drop in the use of first-person singular words was associated with improved outcome from pre-to posttreatment (small p 2 effect size ϭ 0.05). The findings provide preliminary support for the association between clients' linguistic features and their fluctuating experience of distress. They point to the potential value of computerized linguistic measures to track therapeutic outcomes. Public Significance StatementThe current study explored whether utterances within sessions contain information about a client's progress. We used automated text analytic techniques to examine whether clients' linguistic features were associated with their experience of distress both relative to themselves and relative to others, and whether changes in these linguistic features were associated with treatment outcomes. The results indicated that when clients experienced less of distress in the days prior to a session they tended to use fewer first-person singular words, more positive emotion words and fewer negative emotion words in that session. In addition, when clients used fewer negative emotion words in a session, their distress in the days prior to the next session tended to be lower. Lastly, lesser use of first-person singular words in the later versus earlier stages of therapy was associated with improved treatment outcomes. These findings provide preliminary support for the potential use of raw linguistic data within psychotherapy session as a complement to standard monitoring systems to evaluate clients' progress.

How Do Emotions during Goal Pursuit in Weight Change over Time? Retrospective Computational Text Analysis of Goal Setting and Striving Conversations with a Coach during a Mobile Weight Loss Program

“…Regardless, our findings suggest that individuals may need increasing support over time for their increasing negative emotion expression over time. Using more negative emotion words can increase feelings of distress immediately afterwards [ 86 , 87 , 88 ]. This could be especially problematic for weight management programs since negative emotion predicts emotional eating and reduced physical activity [ 20 , 65 , 76 ].…”

Intrapersonal and interpersonal vocal affect dynamics during psychotherapy.

“…By contrast this study examined psychodynamic psychotherapy sessions in which speech is typically unbalanced, where clients usually speak more than therapists. For example, analyzing psychodynamic sessions, Shapira et al (2020) found that 78% of all session utterances were made by the clients and 22% by the therapists.…”

“…By contrast this study examined psychodynamic psychotherapy sessions in which speech is typically unbalanced, where clients usually speak more than therapists. For example, analyzing psychodynamic sessions, Shapira et al (2020) found that 78% of all session utterances were made by the clients and 22% by the therapists. Hence, we opted to use the speech analysis method based on speech-turn switches proposed by Levitan and Hirschberg (2011) who found that vocal features surrounding turn-switches carry more information about the emotional interaction between speakers than do average vocal scores from entire speech turns.…”

Hebrew Psychological Lexicons

“…Usage In one study conducted in our lab, we found correlations between a client's and therapist's positive/negative emotion words and client's and therapist's positive/negative emotions as reported in the POMS questionnaire. In another study, that uses our positive-negative emotion lexicons, Shapira et al (2020) examined the relationship between the number of emotion words spoken in a session and the client's self-reported questionnaire regarding her well-being. The findings are consistent with the literature and in line with theoretical views highlighting the role of positive emotions and negative emotions and the association to well-being (e.g., Blatt (1995); Shahar et al (2020); Morales et al (2017)).…”