Smartphone-based emotion recognition skills training for alexithymia - A randomized controlled pilot study

Lukas CA, Trevisi Fuentes H, Berking M (2019)


Publication Type: Journal article

Publication year: 2019

Journal

Book Volume: 17

Article Number: 100250

DOI: 10.1016/j.invent.2019.100250

Abstract

Background: Neurobiological studies suggest that deficits in emotion recognition are common phenomena in alexithymia. Thus, effective treatments for alexithymia often include skills training in the domain of emotion recognition. Given that smartphone-based interventions (SBIs)offering skills training have been shown to be promising adjuncts to psychological treatments, a blended SBI facilitating the training of emotional skills might be effective in reducing alexithymia. Methods: In this pilot trial, N = 29 individuals reporting elevated alexithymia levels were randomly assigned to a blended SBI including a psychoeducation session and 14 days of training with the mindtastic alexithymia app (MT-ALEX)or a psychoeducation-only control condition. Primary outcome was emotion recognition skills as assessed in a computer-based two-choice task paradigm. Results: On average, participating in the SBI was associated with a significant increase in computer-assessed emotion recognition skills compared to the control condition (d = 0.97). Conclusions: Study findings provide preliminary evidence that SBIs can improve emotion recognition skills in alexithymic individuals. Research using larger samples and targeting clinical populations is necessary to further evaluate the potential of MT-ALEX.

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APA:

Lukas, C.A., Trevisi Fuentes, H., & Berking, M. (2019). Smartphone-based emotion recognition skills training for alexithymia - A randomized controlled pilot study. Internet Interventions, 17. https://dx.doi.org/10.1016/j.invent.2019.100250

MLA:

Lukas, Christian Aljoscha, Hugo Trevisi Fuentes, and Matthias Berking. "Smartphone-based emotion recognition skills training for alexithymia - A randomized controlled pilot study." Internet Interventions 17 (2019).

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