Natural language sentiment as an indicator of depression and anxiety symptoms: a longitudinal mixed methods study1

0585799 - PSÚ 2025 eng J - Journal Article
Kaźmierczak, I. - Jakubowska, A. - Pietraszkiewicz, A. - Zajenkowska, A. - Lacko, David - Wawer, A. - Sarzyńska-Wawer, J.
Natural language sentiment as an indicator of depression and anxiety symptoms: a longitudinal mixed methods study1.
Cognition & Emotion. (2024). ISSN 0269-9931. E-ISSN 1464-0600
Institutional support: RVO:68081740
Keywords : depression * anxiety * language * valence * word sentiment
OECD category: Psychology (including human - machine relations)
Impact factor: 2.6, year: 2022
Method of publishing: Limited access
https://www.tandfonline.com/doi/full/10.1080/02699931.2024.2351952

The study tested how the use of positive- (e.g. beautiful) and negative-valenced (e.g. horrible) words in natural language and its change in time affects the severity of depression and anxiety symptoms among depressed and non-depressed individuals. This longitudinal mixed methods study (N = 40 participants, n = 1440 narratives) with three measurements within a year showed that at the between-person level the use of negative-valenced words was strongly associated with the increase in anxiety and depression symptoms over time while the use of positive-valenced words was slightly associated with the decrease in anxiety and depression symptom. These effects were not supported for within-person level (i.e. changes in word usage). No significant differences were observed in the effects between depressed and non-depressed groups. Summing up, the overall use of positive- and negative-valenced words (particularly negative-valenced words) had a stronger effect on the severity of psychopathological symptoms than their change over time. The results were discussed in the context of natural language processing and its application in diagnosing depression and anxiety symptoms.
Permanent Link: https://hdl.handle.net/11104/0353478