TY  - JOUR
PY  - 2022//
TI  - Prospective associations of text-message-based sentiment with symptoms of depression, generalized anxiety, and social anxiety
JO  - Depression and anxiety
A1  - Stamatis, Caitlin A.
A1  - Meyerhoff, Jonah
A1  - Liu, Tingting
A1  - Sherman, Garrick
A1  - Wang, Harry
A1  - Liu, Tony
A1  - Curtis, Brenda
A1  - Ungar, Lyle H.
A1  - Mohr, David C.
SP  - ePub
EP  - ePub
VL  - ePub
IS  - ePub
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. <br><br>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. <br><br>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). <br><br>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.<p />  <p>Language: en</p>
LA  - en
SN  - 1091-4269
UR  - http://dx.doi.org/10.1002/da.23286
ID  - ref1
ER  -