Analysis of the Emails From the Dutch Web-Based Intervention "Alcohol de Baas": Assessment of Early Indications of Drop-Out in an Online Alcohol Abuse Intervention.

Wouter A C Smink,Auke Elfrink,Anneke M Sools,Marloes G Postel,Gerben J Westerhof,Bernard P Veldkamp,Lukas B Libbertz-Mohr,Erik Tjong Kim Sang

doi:10.3389/fpsyt.2021.575931

Wouter A C Smink, Auke Elfrink + Show 6 more

Open Access

https://doi.org/10.3389/fpsyt.2021.575931

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Abstract

Nowadays, traditional forms of psychotherapy are increasingly complemented by online interactions between client and counselor. In (some) web-based psychotherapeutic interventions, meetings are exclusively online through asynchronous messages. As the active ingredients of therapy are included in the exchange of several emails, this verbal exchange contains a wealth of information about the psychotherapeutic change process. Unfortunately, drop-out-related issues are exacerbated online. We employed several machine learning models to find (early) signs of drop-out in the email data from the “Alcohol de Baas” intervention by Tactus. Our analyses indicate that the email texts contain information about drop-out, but as drop-out is a multidimensional construct, it remains a complex task to accurately predict who will drop out. Nevertheless, by taking this approach, we present insight into the possibilities of working with email data and present some preliminary findings (which stress the importance of a good working alliance between client and counselor, distinguish between formal and informal language, and highlight the importance of Tactus' internet forum).

Highlights

Addictive behaviors and substance dependencies have a global impact, with alcohol use disorder as the prevailing substance abuse disorder [1]
Web-based psychotherapy is an established alternative to classic face-to-face therapy, with the large drawback that almost all online interventions are plagued by a high rate of drop-out
We found a drop-out rate of nearly half, which was high, but similar to past studies [9]

Summary

Introduction

Addictive behaviors and substance dependencies have a global impact, with alcohol use disorder as the prevailing substance abuse disorder [1]. Around the world, 283 million individuals suffer from alcohol use disorder, representing ∼5.1% of all adults [2]. As these numbers are predicted to increase globally [3], the need for accessible treatment becomes more apparent than ever. Webbased psychotherapeutic interventions have been established as effective interventions for alcohol use disorder [7, 8], they are plagued by high rates of drop-out [9, 10], thereby adding to the already well-known problems of high drop-out in alcohol treatment [11]. The aim of this study is to analyze whether emails that were written by clients early in the treatment process can predict drop-out of the online treatment

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