Predicting Early Indicators of Dropout in Online Therapy for Problem Drinkers

LIWC Research Series:

Mental disorders such as Alcohol Use Disorders (AUD), including alcohol abuse and dependence, are highly prevalent in the Netherlands. Problem drinking affects the mental well-being of those suffering from it and often cause other psychological issues, mainly anxiety and depression disorders. Online therapy treatments designed for problem drinkers are effective on average, though do not consider individual differences, and are characterised by high dropout rates. Moreover, premature quitting the intervention often results in worsening or chronic symptoms. It is important to note that there exists a literature gap in predicting dropout in online interventions using linguistic predictors, as non-linguistic predictors for dropout such as gender, age and education have been researched before. Therefore, the purpose of this research was to identify what factors can predict dropout in online therapy, by means of using non-linguistic and linguistic factors.

A number of categories of LIWC were found to predict for completion: 3rd person singular, impersonal pronouns, common adverbs, positive emotion, negative emotion, male references, tentative, biological processes, affiliation, focus past, leisure, and informal words.

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Hazel, T.S. van den (2020) Predicting early indicators of dropout in online therapy for problem drinkers : using LIWC to analyse email contact between client and counsellor.