Association of adolescent symptoms of depression and anxiety with daily smoking and nicotine dependence in young adulthood: findings from a 10-year longitudinal study

Background. The aim of this paper was to examine the association between major depression and cigarette smoking among young adults in a birth cohort before and after adjusting for confounding factors.Method. Data were gathered over the course of the Christchurch Health and Development Study (CHDS). The CHDS is a longitudinal study of a birth cohort of 1265 New Zealand children studied to age 21. Data were gathered by interview on: (a) major depression over the period 16–21 years; (b) daily smoking and nicotine dependence over the period from 16–21 years. In addition, the study included extensive information on social, family, and behavioural factors in childhood and adolescence.Results. Young people meeting DSM-IV criteria for major depression had elevated rates of daily smoking and nicotine dependence. These associations were reduced substantially by control for potential confounding child and adolescent factors. Nonetheless, even after such control, major depression was associated with increased rates of daily smoking (IRR=1·19; 95% CI=1·03, 1·39) and elevated rates of nicotine dependence (OR=1·75; 95% CI=1·13, 2·70).Conclusions. The results suggest that much of the association between smoking and depression reflects common confounding factors that are associated with both outcomes. Nonetheless, even after control for these factors there is evidence of a possible causal linkage between smoking and depression. The direction of causality between smoking and depression remains unknown.

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

PLoS ONE ◽

10.1371/journal.pone.0251787 ◽

2021 ◽

Vol 16 (5) ◽

pp. e0251787

Author(s):

Bridianne O’Dea ◽

Tjeerd W. Boonstra ◽

Mark E. Larsen ◽

Thin Nguyen ◽

Svetha Venkatesh ◽

...

Keyword(s):

Social Media ◽

Longitudinal Study ◽

Depression And Anxiety ◽

Linguistic Features ◽

Suicidal Thoughts ◽

Subject Analysis ◽

Symptoms Of Depression ◽

Final Sample ◽

Social Media Platforms ◽

Within Subjects

Data generated within social media platforms may present a new way to identify individuals who are experiencing mental illness. This study aimed to investigate the associations between linguistic features in individuals’ blog data and their symptoms of depression, generalised anxiety, and suicidal ideation. Individuals who blogged were invited to participate in a longitudinal study in which they completed fortnightly symptom scales for depression and anxiety (PHQ-9, GAD-7) for a period of 36 weeks. Blog data published in the same period was also collected, and linguistic features were analysed using the LIWC tool. Bivariate and multivariate analyses were performed to investigate the correlations between the linguistic features and symptoms between subjects. Multivariate regression models were used to predict longitudinal changes in symptoms within subjects. A total of 153 participants consented to the study. The final sample consisted of the 38 participants who completed the required number of symptom scales and generated blog data during the study period. Between-subject analysis revealed that the linguistic features “tentativeness” and “non-fluencies” were significantly correlated with symptoms of depression and anxiety, but not suicidal thoughts. Within-subject analysis showed no robust correlations between linguistic features and changes in symptoms. The findings may provide evidence of a relationship between some linguistic features in social media data and mental health; however, the study was limited by missing data and other important considerations. The findings also suggest that linguistic features observed at the group level may not generalise to, or be useful for, detecting individual symptom change over time.

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