Previous structural and functional neuroimaging studies have implicated distributed brain regions and networks in depression. However, there are no robust imaging biomarkers that are specific to depression, which may be due to clinical heterogeneity and neurobiological complexity. A dimensional approach and fusion of imaging modalities may yield a more coherent view of the neuronal correlates of depression. We used linked independent component analysis to fuse cortical macrostructure (thickness, area, gray matter density), white matter diffusion properties and resting‐state functional magnetic resonance imaging default mode network amplitude in patients with a history of depression (n = 170) and controls (n = 71). We used univariate and machine learning approaches to assess the relationship between age, sex, case–control status, and symptom loads for depression and anxiety with the resulting brain components. Univariate analyses revealed strong associations between age and sex with mainly global but also regional specific brain components, with varying degrees of multimodal involvement. In contrast, there were no significant associations with case–control status, nor symptom loads for depression and anxiety with the brain components, nor any interaction effects with age and sex. Machine learning revealed low model performance for classifying patients from controls and predicting symptom loads for depression and anxiety, but high age prediction accuracy. Multimodal fusion of brain imaging data alone may not be sufficient for dissecting the clinical and neurobiological heterogeneity of depression. Precise clinical stratification and methods for brain phenotyping at the individual level based on large training samples may be needed to parse the neuroanatomy of depression.

Background: Over-the-counter analgesics (OTCA) such as Paracetamol and Ibuprofen are frequently used by adolescents, and the route of administration and access at home allows unsupervised use. Psychological distress and pain occur simultaneously and are more common among females than among males. There is a dynamic interplay between on-label pain indications and psychological distress, and frequent OTCA use or misuse can exacerbate symptoms. No studies have to date provided an overview of frequent OTCA use in a larger population-based study. The current study used survey data to explore associations between and the relative predictive value of on-label pain indication and measures of psychological distress, together with sex differences for weekly OTCA use.Methods: This study included 349,528 adolescents aged 13–19. The data was collected annually between January 2014 and December 2018 as part of the Norwegian Young Data survey. Performance analysis was conducted to explore the relative roles and associations between on-label pain indication and psychological distress in weekly OTCA use. A mixed-effects logistic regression model was used to explore the unique contributions from four domains of on-label pain indication and psychological distress as measured by a combined measure of anxiety and depression (HSCL-10) and peer-bullying involvement as victims or bullies.Results: Thirty percent of females and 13 % of males use OTCA weekly. Headache is the strongest on-label pain predictor of weekly OTCA use, followed by abdominal pain. Depression and anxiety are the strongest psychological predictor of weekly OTCA use, and higher symptom levels and being female increase the strength of this association. Anxiety and depression also predict weekly OTCA use after controlling for physiological pain.Conclusions: Sex, pain and anxiety and depression are inter-correlated and strong predictors of frequent OTCA use. Frequent OTCA use in the context of psychological distress may be a form of self-medication that can exacerbate symptoms and decrease psychosocial function. Longitudinal studies that explore causal trajectories between frequent on-label OTCA use and psychological distress are required. OTCA use among adolescents, and particularly among females, with anxiety and depression should be administered with caution and closely monitored.

Dysfunctional metacognitive beliefs (‘metacognitions’) and executive control are important factors in mental disorders such as depression and anxiety, but the relationship between these concepts has not been studied systematically. We examined whether there is an association between metacognitions and executive control and hypothesised that decreased executive control statistically predicts increased levels of metacognitions. Two hundred and ninety-nine individuals recruited from the general population and outpatient psychiatric clinics completed the Metacognitions Questionnaire-30 and three subtests from the Cambridge Neuropsychological Test Automated Battery corresponding to the three-component model of executive functions. Controlling for current depression and anxiety symptoms, decreased ability to shift between mental sets was associated with increased negative beliefs about the uncontrollability and danger of worry and beliefs about the need to control thoughts. The results suggest a basic association between metacognitions and executive control. Individual differences in executive control could prove important in the personalisation of metacognitive therapy.