English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Due to its popularity and availability, social media data may present a newway to identify individuals who are experiencing mental illness. By analysingblog content, this study aimed to investigate the associations betweenlinguistic features and symptoms of depression, generalised anxiety, andsuicidal ideation. This study utilised a longitudinal study design. Individualswho blogged were invited to participate in a study in which they completedfortnightly mental health questionnaires including the PHQ9 and GAD7 for aperiod of 36 weeks. Linguistic features were extracted from blog data using theLIWC tool. Bivariate and multivariate analyses were performed to investigatethe correlations between the linguistic features and mental health scoresbetween subjects. We then used the multivariate regression model to predictlongitudinal changes in mood within subjects. A total of 153 participantsconsented to taking part, with 38 participants completing the required numberof questionnaires and blog posts during the study period. Between-subjectanalysis revealed that several linguistic features, including tentativeness andnon-fluencies, were significantly associated with depression and anxietysymptoms, but not suicidal thoughts. Within-subject analysis showed no robustcorrelations between linguistic features and changes in mental health score.This study provides further support for the relationship between linguisticfeatures within social media data and symptoms of depression and anxiety. Thelack of robust within-subject correlations indicate that the relationshipobserved at the group level may not generalise to individual changes over time.

The relationship between linguistic expression and symptoms of depression, anxiety, and suicidal thoughts: A longitudinal study of blog content