An analysis of patient motivation for seeking online treatment for binge eating disorder-A mixed methods study combining systematic text condensation with sentiment analysis

Trine Theresa Holmberg; Maxime Sainte-Marie; Esben Kjems Jensen; Jakob Linnet; Eik Runge; Mia Beck Lichtenstein; Kristine Tarp

doi:10.3389/fpsyt.2022.969115

An analysis of patient motivation for seeking online treatment for binge eating disorder-A mixed methods study combining systematic text condensation with sentiment analysis

Front Psychiatry. 2022 Nov 4:13:969115. doi: 10.3389/fpsyt.2022.969115. eCollection 2022.

Authors

Trine Theresa Holmberg¹, Maxime Sainte-Marie², Esben Kjems Jensen^{1

3}, Jakob Linnet^{1

4}, Eik Runge¹, Mia Beck Lichtenstein^{1

3}, Kristine Tarp^{1

3}

Affiliations

¹ Research Unit for Digital Psychiatry, Center for Digital Psychiatry, Mental Health Services in the Region of Southern Denmark, Odense, Denmark.
² Department of Political Science, Danish Center for Studies in Research and Research Policy, Aarhus University, Aarhus, Denmark.
³ Department of Clinical Research, Faculty of Health Sciences, University of Southern Denmark, Odense, Denmark.
⁴ Clinic on Gambling- and Binge Eating Disorder, Department of Occupational and Environmental Medicine, Odense University Hospital, Odense, Denmark.

Abstract

Objective: Online treatment for binge eating disorder (BED) is an easily available option for treatment compared to most standard treatment procedures. However, little is known about how motivation types characterize this population and how these impact treatment adherence and effect in an online setting. Therefore, we aimed to investigate a sample of written motivation statements from BED patients, to learn more about how treatment and online treatment in particular, presents in this population.

Methods: Using self-determination theory in a mixed methods context, we investigated which types of motivation were prevalent in our sample, how this was connected with patient sentiment, and how these constructs influence treatment and adherence.

Results: Contrary to what most current literature suggests, we found that in our sample (n = 148), motivation type was not connected with treatment outcome. We did find a strong association between sentiment scores and motivation types, indicating the model is apt at detecting effects. We found that when comparing an adult and young adult population, they did not differ in motivation type and the treatment was equally effective in young adults and adults. In the sentiment scores there was a difference between sentiment score and adherence in the young adult group, as the more positive the young adults were, the less likely they were to complete the program.

Discussion: Because motivation type does not influence online treatment to the same degree as it would in face-to-face treatment it indicates that the typical barriers to treatment may be less crucial in an online setting. This should be considered during intake; as less motivated patients may be able to adhere better to online treatment, because the latter imposes fewer barriers of the kind that only strong motivation can overcome. The fact that motivation type and sentiment score of the written texts are strongly associated, indicate a potential for automated models to detect motivation based on sentiment.

Keywords: binge eating disorder (BED); cognitive behavioral therapy (CBT); internet based intervention; mixed method approach; self-determination theory (SDT); sentiment analysis.