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Design and Implementation of an fMRI Study Examining Thought Suppression in Young Women with, and At-risk, for Depression
Published on: May 19, 2015
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Individuals with depression express more distorted thinking on social media
Krishna C Bathina1, Marijn Ten Thij1, Lorenzo Lorenzo-Luaces2
1Luddy School of Informatics, Computing, and Engineering, Indiana University Bloomington, Bloomington, IN, USA.
Nature Human Behaviour
|February 12, 2021
Summary
Individuals with depression show more distorted thinking in their social media language. This finding highlights online language patterns indicative of cognitive distortions associated with depression.
Area of Science:
- Psychology
- Computational Linguistics
- Digital Mental Health
Background:
- Depression is a major global disability, frequently underdiagnosed and undertreated.
- Cognitive behavioral therapy links depression to cognitive distortions affecting emotions and motivation.
Purpose of the Study:
- To investigate if language patterns on social media reflect distorted thinking in individuals with depression.
- To identify specific linguistic markers of cognitive distortions in depression.
Main Methods:
- Analysis of social media language from individuals with self-reported depression against a random sample.
- Linguistic analysis focusing on cognitive distortions, controlling for topic, sentiment, and pronoun usage.
Main Results:
- Social media language of individuals with depression exhibited significantly higher levels of distorted thinking.
- This effect was specific to distorted thinking and not explained by other linguistic factors.
Conclusions:
- Online language patterns can indicate depression-related distorted thinking.
- Future applications require careful consideration of ethical and data privacy concerns.
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