Story Lab

What works when for whom? Advancing therapy change process research by mining for therapy-related textual features in effective e-mental health interventions

This is an exemplary project of the <Technology for Narrative Methodology> research line.

Mental illnesses, like depression and anxiety, are among the leading causes of the global burden of disease. E-mental health (EMH) interventions, i.e., web-based psychotherapy treatments, are increasingly used to improve access to psychotherapy for a wider audience. Whereas different EMH interventions tend to be equally effective, the responsiveness to a specific treatment shows large individual differences. Therefore, the personalization of treatments is seen as the major road for improvement. Because most EMH interventions use language for communication between counselors and clients, assessing language use provides an important avenue for opening the black box of what happens within therapy. Moreover, EMH makes data of the linguistic interactions between client and counselor available on an unprecedented large scale. The objective of the study is to use e-science methods and tools, in particular natural language processing, visualization and multivariate analysis methods, to analyze patterns in therapy-related textual features in e-mail correspondence between counselor and client. By connecting these patterns to therapy outcome, the question What Works When for Whom? can be answered, which will greatly improve the effectiveness of EMH. The core of the project concerns the development of open source software for the Dutch language, using data from six EMH-interventions with a total of 10.000 e-mails. These data are sufficiently large and varied to allow for computer-based modelling, and testing of use cases with varying complexity. At the end of the project, the step toward English language software will be made to increase the impact of the project.

Funding Agency: Netherlands escience center in collaboration with NWO

Partner: Department of Research Methodology, Measurement and Data Analysis, IGS Datalab

Years: 2016-2020

Contact: Anneke Sools