Linguistic analysis of Latinx patients’ responses to a text messaging adjunct during cognitive behavioral therapy for depression

Journal Article (2022)
Authors

Rosa Hernandez-Ramos (University of California)

Edgar Altszyler (Universidad de Buenos Aires)

Caroline A. Figueroa (University of California)

Patricia Avila-Garcia (University of California)

Adrian Aguilera (University of California, University of San Francisco)

Affiliation
External organisation
To reference this document use:
https://doi.org/10.1016/j.brat.2021.104027
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Publication Year
2022
Language
English
Affiliation
External organisation
Volume number
150
DOI:
https://doi.org/10.1016/j.brat.2021.104027

Abstract

Cognitive behavioral therapy (CBT) is efficacious to treat depression, however more research is needed to understand its functions among Latinxs. This study analyzed qualitative responses that were paired with a mood rating (1–9 scale) from daily ecological momentary assessments via text-messaging of 52 low-income, Spanish-speaking patients to assess the relationship between word use and changes in mood during group CBT. Based on previous research, we chose 11 linguistic dimensions from the Linguistic Inquiry and Word Count text analysis software that conceptually related to core CBT treatment elements and sociocultural factors of depression in Latinxs. Results showed that the use of words from the categories of Friends, Religion, Positive Emotions, and Leisure (proxy for behavioral activation) were significantly associated with a significant increase in mood. The use of Negative Emotions and Health words were significantly associated with a significant decrease in mood. Post-hoc analysis revealed that Certainty (proxy for cognitive inflexibility) words were related to a significant decrease in mood when Negative Emotional words were present. Findings contribute to our understanding of the role of sociocultural factors and core CBT elements in changes in mood among Latinxs. Lastly, this paper demonstrates the potential for analyzing language content during a digital health intervention to better understand user experiences.

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