TY - JOUR
T1 - Prospective associations of text-message-based sentiment with symptoms of depression, generalized anxiety, and social anxiety
AU - Stamatis, Caitlin A.
AU - Meyerhoff, Jonah
AU - Liu, Tingting
AU - Sherman, Garrick
AU - Wang, Harry
AU - Liu, Tony
AU - Curtis, Brenda
AU - Ungar, Lyle H.
AU - Mohr, David C.
N1 - Funding Information:
This study was funded by the National Institute of Mental Health (NIMH) R01 MH111610, R34 MH124960, and T32 MH115882 grants, and by the Intramural Research Program of the National Institutes of Health (NIH), National Institute on Drug Abuse (NIDA).
Publisher Copyright:
© 2022 The Authors. Depression and Anxiety published by Wiley Periodicals LLC.
PY - 2022/12
Y1 - 2022/12
N2 - Objective: Language patterns may elucidate mechanisms of mental health conditions. To inform underlying theory and risk models, we evaluated prospective associations between in vivo text messaging language and differential symptoms of depression, generalized anxiety, and social anxiety. Methods: Over 16 weeks, we collected outgoing text messages from 335 adults. Using Linguistic Inquiry and Word Count (LIWC), NRC Emotion Lexicon, and previously established depression and stress dictionaries, we evaluated the degree to which language features predict symptoms of depression, generalized anxiety, or social anxiety the following week using hierarchical linear models. To isolate the specificity of language effects, we also controlled for the effects of the two other symptom types. Results: We found significant relationships of language features, including personal pronouns, negative emotion, cognitive and biological processes, and informal language, with common mental health conditions, including depression, generalized anxiety, and social anxiety (ps <.05). There was substantial overlap between language features and the three mental health outcomes. However, after controlling for other symptoms in the models, depressive symptoms were uniquely negatively associated with language about anticipation, trust, social processes, and affiliation (βs: −.10 to −.09, ps <.05), whereas generalized anxiety symptoms were positively linked with these same language features (βs:.12–.13, ps <.001). Social anxiety symptoms were uniquely associated with anger, sexual language, and swearing (βs:.12–.13, ps <.05). Conclusion: Language that confers both common (e.g., personal pronouns and negative emotion) and specific (e.g., affiliation, anticipation, trust, and anger) risk for affective disorders is perceptible in prior week text messages, holding promise for understanding cognitive-behavioral mechanisms and tailoring digital interventions.
AB - Objective: Language patterns may elucidate mechanisms of mental health conditions. To inform underlying theory and risk models, we evaluated prospective associations between in vivo text messaging language and differential symptoms of depression, generalized anxiety, and social anxiety. Methods: Over 16 weeks, we collected outgoing text messages from 335 adults. Using Linguistic Inquiry and Word Count (LIWC), NRC Emotion Lexicon, and previously established depression and stress dictionaries, we evaluated the degree to which language features predict symptoms of depression, generalized anxiety, or social anxiety the following week using hierarchical linear models. To isolate the specificity of language effects, we also controlled for the effects of the two other symptom types. Results: We found significant relationships of language features, including personal pronouns, negative emotion, cognitive and biological processes, and informal language, with common mental health conditions, including depression, generalized anxiety, and social anxiety (ps <.05). There was substantial overlap between language features and the three mental health outcomes. However, after controlling for other symptoms in the models, depressive symptoms were uniquely negatively associated with language about anticipation, trust, social processes, and affiliation (βs: −.10 to −.09, ps <.05), whereas generalized anxiety symptoms were positively linked with these same language features (βs:.12–.13, ps <.001). Social anxiety symptoms were uniquely associated with anger, sexual language, and swearing (βs:.12–.13, ps <.05). Conclusion: Language that confers both common (e.g., personal pronouns and negative emotion) and specific (e.g., affiliation, anticipation, trust, and anger) risk for affective disorders is perceptible in prior week text messages, holding promise for understanding cognitive-behavioral mechanisms and tailoring digital interventions.
KW - anxiety
KW - depression
KW - digital phenotyping
KW - personal sensing
KW - sentiment analysis
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U2 - 10.1002/da.23286
DO - 10.1002/da.23286
M3 - Article
C2 - 36281621
AN - SCOPUS:85140373902
SN - 1091-4269
VL - 39
SP - 794
EP - 804
JO - Depression and anxiety
JF - Depression and anxiety
IS - 12
ER -
