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Background: Depression and anxiety are associated with increased risk of sickness absence (SA), yet the developmental patterns of SA remain unclear. We aimed to identify trajectories of SA in young adults with depression and/or anxiety, accounting for sociodemographic and occupational factors. Methods: Longitudinal study of 1445 twin individuals with elevated depressive/anxiety symptoms in late adolescence or young adulthood (age range: 19-30), assessed in Swedish surveys completed in 2005. Through linkage to nationwide registries, individuals were prospectively followed from 2006 to 2018. The outcome included consecutive annual days of SA, which were analyzed using group-based trajectory modeling. Multinomial logistic regression estimating odds ratios (OR) with 95 % confidence intervals (CI) was used to examine associations of age, sex, and educational level with the resulting SA trajectories. Results: Four distinct SA trajectories were identified in the total sample: 'high-increasing' (6 %), 'low-increasing' (12 %), 'high-decreasing' (13 %), and 'low-constant' (69 %). Increasing age was associated with higher odds of belonging to the low-increasing trajectory (OR = 1.07, 95 % CI = 1.02-1.12). Women had higher odds of belonging to the low-increasing trajectory (OR = 1.67, 95 % CI = 1.10-2.53), compared with men. Higher education was associated with lower odds of belonging to high-increasing (OR = 0.34, 95 % CI = 0.22-0.54) and high-decreasing (OR = 0.59, 95 % CI = 0.43-0.81) trajectories, compared with lower education. Few differences were observed in analyses stratified by occupational sector. Limitations: Information on potential confounders (e.g., psychiatric comorbidity, work-environment factors) was not available. Conclusions: Among young adults with prior depression/anxiety, close to every fifth showed rising SA trajectories over time. This calls for targeted strategies to improve public mental health already at young ages.

Objective: Depression is common, impairing, and the leading cause of disease burden in youths. This study aimed to identify the effects of childhood/adolescent depression on a broad range of longer-term outcomes. Method: The analysis is based on the prospective, representative Great Smoky Mountains Study of 1,420 participants. Participants were assessed with the structured Child and Adolescent Psychiatric Assessment interview up to 8 times in childhood (age 9 similar to 16 years; 6,674 observations; 1993-2000) for DSM-based depressive disorders, associated psychiatric comorbidities, and childhood adversities. Participants were followed up 4 times in adulthood (ages 19, 21, 25, and 30 years; 4,556 observations of 1,336 participants; 1999-2015) with the structured Young Adult Psychiatric Assessment Interview for psychiatric outcomes and functional outcomes. Results: In all, 7.7% of participants met criteria for a depressive disorder in childhood/adolescence. Any childhood/adolescent depression was associated with higher levels of adult anxiety and illicit drug disorders and also with worse health, criminal, and social functioning; these associations persisted when childhood psychiatric comorbidities and adversities were accounted for. No sex-specific patterns were identified. However, timing of depression mattered: individuals with adolescent-onset depression had worse outcomes than those with child-onset. Average depressive symptoms throughout childhood and adolescence were associated with more adverse outcomes. Finally, specialty mental health service use was protective against adult diagnostic outcomes. Conclusion: Early depression and especially persistent childhood/adolescent depressive symptoms have robust, lasting associations with adult functioning. Some of these effects may be attenuated by service use.

Background: Correct prediction of treatment response is a central goal of precision psychiatry. Here, we tested the predictive accuracy of a variety of pre-treatment patient characteristics, including clinical, demographic, molecular genetic, and neuroimaging markers, for treatment response in patients with social anxiety disorder (SAD). Methods: Forty-seven SAD patients (mean +/- SD age 33.9 +/- 9.4 years, 24 women) were randomized and commenced 9 weeks' Internet-delivered cognitive behavior therapy (CBT) combined either with the selective serotonin reuptake inhibitor (SSRI) escitalopram (20 mg daily [10 mg first week], SSRI+CBT, n= 24) or placebo (placebo+CBT, n= 23). Treatment responders were defined from the Clinical Global Impression-Improvement scale (CGI- I <= 2). Before treatment, patients underwent functional magnetic resonance imaging and the Multi-Source Interference Task taxing cognitive interference. Support vector machines (SVMs) were trained to separate responders from nonresponders based on pre-treatment neural reactivity in the dorsal anterior cingulate cortex (dACC), amygdala, and occipital cortex, as well as molecular genetic, demographic, and clinical data. SVM models were tested using leave-one-subject-out cross-validation. Results: The best model separated treatment responders (n= 24) from nonresponders based on pre-treatment dACC reactivity (83% accuracy, P= 0.001). Responders had greater pre-treatment dACC reactivity than nonresponders especially in the SSRI+CBT group. No other variable was associated with clinical response or added predictive accuracy to the dACC SVM model. Limitations: Small sample size, especially for genetic analyses. No replication or validation samples were available. Conclusions: The findings demonstrate that treatment outcome predictions based on neural cingulate activity, at the individual level, outperform genetic, demographic, and clinical variables for medication-assisted Internet-delivered CBT, supporting the