The Effects of Emotion Suppression During Language Planning and Production Purpose Emotion regulation and language planning occur in parallel during interactive communication, but their processes are often studied separately. It has been suggested that emotion suppression and more complex language production both recruit cognitive resources. However, it is currently less clear how the language planning and production system is impacted ... Research Note
Research Note  |   August 08, 2018
The Effects of Emotion Suppression During Language Planning and Production
 
Author Affiliations & Notes
  • Jennifer M. Roche
    School of Health Sciences, Kent State University, Ohio
  • Hayley S. Arnold
    School of Health Sciences, Kent State University, Ohio
  • Disclosure: The authors have declared that no competing interests existed at the time of publication.
    Disclosure: The authors have declared that no competing interests existed at the time of publication. ×
  • Correspondence to Jennifer M. Roche: jroche3@kent.edu
  • Editor-in-Chief: Sean Redmond
    Editor-in-Chief: Sean Redmond×
  • Editor: Charles Ellis
    Editor: Charles Ellis×
Article Information
Language / Research Note
Research Note   |   August 08, 2018
The Effects of Emotion Suppression During Language Planning and Production
Journal of Speech, Language, and Hearing Research, August 2018, Vol. 61, 2076-2083. doi:10.1044/2018_JSLHR-L-17-0232
History: Received June 15, 2017 , Revised November 20, 2017 , Accepted April 3, 2018
 
Journal of Speech, Language, and Hearing Research, August 2018, Vol. 61, 2076-2083. doi:10.1044/2018_JSLHR-L-17-0232
History: Received June 15, 2017; Revised November 20, 2017; Accepted April 3, 2018

Purpose Emotion regulation and language planning occur in parallel during interactive communication, but their processes are often studied separately. It has been suggested that emotion suppression and more complex language production both recruit cognitive resources. However, it is currently less clear how the language planning and production system is impacted when required to emotionally suppress outward displays of affect (i.e., expressive suppression). The purpose of the current study was to evaluate the interactive effects of emotion regulation and language production processes.

Method Through discourse analysis of a corpus of interactive dialogue, we evaluated the production of interjections (i.e., also termed “filled pauses,” a type of speech disfluency) when participants regulated outward displays of emotion and when language was lexically complex (i.e., via lexical diversity). One participant (the sender) was assigned to either express or suppress affective displays during the interaction. The other person (the receiver) was given no special instructions before the interaction. The interactions were transcribed, and their linguistic content (i.e., lexical diversity, lexical alignment, and interjections) was analyzed.

Results Results indicated that participants actively suppressing outward displays of affect produced more interjections and that participants asked to emotionally regulate, both expressors and suppressors, were more disfluent when producing lexically diverse statements (2 cognitively demanding tasks).

Conclusions The current research provides support that, when suppressing emotion, one might be more disfluent when speaking. However, also when engaged in 2 simultaneous, demanding tasks of having to either upregulate or downregulate emotions and utter lexically diverse statements, the combined cognitive load may impede fluency in language production. More specifically, in the context of language planning and production, emotion suppression may pilfer resources away from the language planning and production system, leading to higher rates of disfluent speech. This finding is of particular importance because understanding the interactive effects of emotion and language production may be impactful to interventions for communication disorders.

Acknowledgments
Special thanks go to Jeremy Jamieson and Brett Peters for sharing their data and Alexandra Paxton for sharing her ggplot code. In addition, special thanks to Mary Juergens, Tracy Zhou, Alexis Werner, Sean Brouty, Anthony Germani, Sierra Cason, and Nikki Craycraft for their help in collecting data and annotating videos.
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