Using topic models to identify clients' functioning levels and alliance ruptures in psychotherapy.

Computerized natural language processing techniques can analyze psychotherapy sessions as texts, thus generating information about the therapy process and outcome and supporting the scaling-up of psychotherapy research. We used topic modeling to identify topics discussed in psychotherapy sessions and explored (a) which topics best identified clients' functioning and alliance ruptures and (b) whether changes in these topics were associated with changes in outcome. Transcripts of 873 sessions from 58 clients treated by 52 therapists were analyzed.

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

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.