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Short abstract:

In this paper, I investigate how the vagueness and plurality of definitions related to who is categorized as a problem drinker is managed in and influenced by mHealth technology, e.g., apps for reducing harmful alcohol use.

Long abstract:

Given widespread mortality, morbidity and suffering related to alcohol consumption, research-based measures to intervene on problematic alcohol use are needed. What complicates the development of interventions is that in research, policymaking, as well as in lay parlance, there is no consensus about how to understand and identify problematic alcohol use (Saunders et al. 2018). What behaviors or which drinkers are labelled as problematic is influenced by societal norms related to, for instance, gender and class (Room 2006; John 2018). Moreover, it is noteworthy that the current diagnostic systems DSM and ICD have different categorizations, and a person might be diagnosed as suffering from an alcohol problem in one system and not in another (Saunders et al. 2018). In this paper, I investigate how this vagueness and plurality related to who is categorized as a problem drinker is managed in mHealth technology. I aim, first, to analyze the assumptions considering problematic alcohol use that underlie studies assessing the effectiveness of different mHealth technology interventions (e.g., Smaart app) to harmful use of alcohol, alcohol dependence, and alcohol use disorder. How do socially-laden norms related to ‘normal’ alcohol use influence how effectiveness in understood? Second, I ask how such apps mediate (Verbeek 2015) the relationship between a user and their experience of consuming alcohol. In particular, does mHealth have the potential to shape how ‘normal’ alcohol use is perceived?