The use of cannabis in adolescence and early adulthood, critical phases for brain development, is linked to psychotic-like experiences (PLEs). The underlying mechanisms, however, remain unclear. This research examined the relationship between recreational cannabis use and PLEs, emphasizing the connectivity of the salience network (SN), which plays a role in salience processing and psychosis. To determine whether this relationship reflects shared genetic or environmental contributions, twin modeling was used.

We included 232 healthy adolescent Turkish twins who underwent diffusion MRI and psychometric assessment. SN connectivity was quantified using graph theory metrics. Linear mixed models were used to examine the associations among cannabis use, SN factors, and PLEs. Mediation analyses assessed whether SN parameters explained the cannabis–PLEs association. Twin models disentangle genetic and environmental contributions to these traits and their covariation.

Cannabis use was significantly associated with higher overall PLE frequency. A specific SN factor predicted both total and positive PLEs. However, SN connectivity did not mediate the cannabis–PLEs relationship. Twin modeling showed that cannabis use and PLEs were mainly influenced by unique environmental factors. No significant phenotypic covariations were found among cannabis use, PLEs, and SN parameters.

Recreational cannabis use during adolescence and young adulthood is associated with heightened PLEs, although this association is not mediated by SN connectivity. The environment plays an important role during adolescence in shaping these traits independently. The findings underscore the need for longitudinal and genetically informed studies to clarify the mental health effects of adolescent cannabis use.

Individuals with a family history of bipolar disorder are at increased risk of developing affective psychopathology. Longitudinal imaging studies in young people with familial risk have been limited, and cortical developmental trajectories in the progression towards illness remain obscure.

To establish high-resolution longitudinal differences in cortical structure that are associated with risk of bipolar disorder.

Using structural magnetic resonance imaging data from 217 unrelated ‘Bipolar Kids and Sibs study’ participants (baseline n = 217, follow-up n = 152), we examined changes over a 2-year period in cortical area, thickness and volume, measured at each vertex across the cortical surface. Groups comprised 105 ‘high-risk’ participants with a first-degree relative with bipolar disorder (female n = 64; age in years: M (mean) = 20.9, s.d. = 5.5) and 112 controls with no familial psychiatric history (females n = 60; age in years: M = 22.4, s.d. = 3.7).

Accelerated thickness and volume reductions over time were observed in ‘high-risk’ individuals across multiple cortical regions, relative to controls, including right lateral orbitofrontal thickness (β = 0.033, P < 0.001) and inferior frontal volume (β = 0.021, P < 0.001). These differences were observed after controlling for age, sex, ancestry, current medication status, lifetime psychiatric diagnoses and measures of gross brain morphology.

Longitudinal group differences suggest the presence of thicker cortex in familial ‘high-risk’ individuals at earlier developmental stages, followed by accelerated thinning towards the typical age of bipolar disorder onset. Future examination of genetic and environmental components of familial risk and the mechanistic nature (pathological or protective) of cortical-trajectory differences over time may facilitate the identification of prodromal biomarkers and opportunities for early clinical intervention.

Depression runs in families, with both genetic and environmental mechanisms contributing to intergenerational continuity, though these mechanisms have often been studied separately. This study examined the interplay between genetic and environmental influences in the intergenerational continuity of depressive symptoms from parents to offspring.

Using data from the Dutch TRAILS cohort (n = 2201), a prospective, genetically informed, multiple-generation study, we examined the association between parents’ self-reported depressive symptoms (reported at mean age of 41 years) and offspring depressive symptoms, self-reported nearly two decades later, in adulthood (mean age: 29 years). We assessed the role of genetic (polygenic scores for depressive symptoms in parents and offspring) and environmental mechanisms (parental warmth during adolescence) in explaining intergenerational continuity of depressive symptoms in separate and combined models.

Parents’ depressive symptoms, offspring genetic predisposition, and parental warmth were associated with an increased risk of depressive symptoms in offspring. In the combined model, parents’ genetic predisposition was linked to their own depressive symptoms, which were linked to lower parental warmth, which, in turn, was linked to higher depressive symptoms in offspring, after accounting for offspring genetic predisposition, sex, age, and socioeconomic status.

Both genetic and environmental mechanisms contribute to the intergenerational continuity of depressive symptoms independently and in interplay. Despite a significant effect, the influence of parental warmth was modest, suggesting limited covariation between this particular parenting measure and depressive symptoms, at least when assessed with large temporal distance.

Previous studies investigating the association between pubertal timing and depression in girls primarily use self-reported age at menarche (AAM). This study examines a range of pubertal timing indicators, including anthropometric and self-reported measures.

Compare associations of multiple indicators of pubertal timing with depressive symptoms and depression in girls and explore whether these associations persist into early adulthood.

The sample comprised 4607 girls from UK-based Avon Longitudinal Study of Parents and Children. Seven measures of pubertal timing were assessed between ages 7 and 17 (age at: peak height velocity (aPHV); peak weight velocity; peak bone mineral content velocity; Tanner pubic hair and breast development stage 3; axillary hair; and AAM). Depressive symptoms were measured at 14, 17, 18 and 24 years using the Short Mood and Feelings Questionnaire. Depression was assessed at 15, 18 and 24 years using the Development and Well-Being Assessment and Clinical Interview Schedule-Revised. Multivariable logistic regression models were adjusted for socioeconomic status and pre-pubertal body mass index.

Later pubertal timing was associated with lower odds of depressive symptoms at age 14 across six measures, including aPHV (adjusted odds ratio (AOR): 0.82; 95% CI 0.72, 0.95) and AAM (AOR: 0.84; 95% CI 0.76, 0.92). Later AAM and Tanner breast stage 3 were associated with lower odds of depression at age 18 (AOR: 0.85; 95% CI 0.75, 0.97 and AOR: 0.83; 95% CI 0.72, 0.95, respectively). Associations attenuated by age 24.

Later pubertal timing was associated with reduced odds of depressive symptoms during mid-adolescence, with associations attenuating by adulthood.

Understanding the effect(s) of the COVID-19 pandemic is key for planning for future pandemics.

This study examines change in self-reported mental health difficulties during three months of the pandemic among adolescent (10- to 15-year-olds) participants from the UK Household Longitudinal Study (waves 7, 9 and 11 of the main survey and waves 4, 5 and 8 of the COVID-19 surveys).

We focused on mental health difficulties using the Strengths and Difficulties Questionnaire (SDQ), using repeated cross-sectional and longitudinal analyses to examine data among 6471 adolescents who responded to at least one survey since 2015, and 2,300 who responded to at least one COVID-19 survey during July 2020, November 2020 or March 2021.

Repeated cross-sectional data showed similar mean total SDQ across surveys before and during the pandemic (range during pandemic 11.4 to 11.9; range pre-pandemic 11.1 to 11.8). Longitudinal analyses provided no evidence of mental health change compared with pre-pandemic trends (estimated change mean SDQ (β) = 0.05, 95% CI −0.42 to 0.51; p = 0.85), or differential sociodemographic effects, except greater effects in rural households (β = 0.67, 95% CI −0.08 to 1.41) than urban environments (β = −0.18, 95% CI −0.69 to 0.33). Though subscales generally saw higher scores during the pandemic than before, these were consistent with pre-pandemic trends, excepting a slight improvement in conduct problems (β = −0.26, 95% CI 0.12 to 0.40).

The study offers evidence among a representative sample that mental health difficulties did not, on average, deteriorate for adolescents during three months of the pandemic.

Mental ill-health has a major impact on young people, with pain often co-occurring. We estimated the prevalence and impact of pain in young people with mental ill-health.

Longitudinal data (baseline and three-month follow-up) of 1,107 Australian young people (aged 12–25 years) attending one of five youth mental health services. Multi-level linear mixed models estimated associations between pain characteristics (frequency, intensity, and limitations) and outcomes with false discovery rate (FDR) adjustment. Pain characteristics were baseline-centered to estimate if the baseline score (between-participant effect) and/or change from baseline (within-participant effect) was associated with outcomes.

At baseline, 16% reported serious pain more than 3 days, 51% reported at least moderate pain, and 25% reported pain-related activity limitations in the last week. Between participants, higher serious pain frequency was associated with greater anxiety symptoms (β[95%CI]: 0.90 [0.45, 1.35], FDR-p=0.001), higher pain intensity was associated with greater symptoms of depression (1.50 [0.71, 2.28], FDR-p=0.001), anxiety (1.22 [0.56, 1.89], FDR-p=0.002), and suicidal ideation (3.47 [0.98, 5.96], FDR-p=0.020), and higher pain limitations were associated with greater depressive symptoms (1.13 [0.63, 1.63], FDR-p<0.001). Within participants, increases in pain intensity were associated with increases in tobacco use risk (1.09 [0.48, 1.70], FDR-p=0.002), and increases in pain limitations were associated with increases in depressive symptoms (0.99 [0.54, 1.43], FDR-p<0.001) and decreases in social and occupational functioning (−1.08 [−1.78, −0.38], FDR-p=0.009).

One-in-two young people seeking support for mental ill-health report pain. Youth mental health services should consider integrating pain management.

Ultra-processed food (UPF) consumption varies with socio-economic status (SES) in adults, and evidence suggests that similar patterns exist in adolescents. However, the relationship remains understudied in this critical developmental group. This study aimed to further characterise adolescent UPF consumption and its relationship with SES by exploring dietary patterns within UPF consumption.

Using food-diary data, adolescents’ UPF intake was quantified and categorised. Principal component and clustering analysis were used to identify dietary patterns. Associations of these dietary patterns with socio-demographic characteristics were then analysed.

Pooled data from the rolling, cross-sectional National Diet and Nutrition Survey, waves 1-to-11 (2008–2019).

UK adolescents (11- to18-year-olds) (n 3199).

Three UPF dietary patterns were identified: (i) the ‘Restrictive’ pattern, which included the lowest total consumption of UPF (95 % CI: 33·1, 34·9 % g/d), but elevated consumption of UPF often perceived as healthy, was associated with adolescents of a higher SES; (ii) the ‘Permissive’ pattern included 61·6 % g/d (95 % CI: 60·3, 63·0 % g/d) total UPF, dominated by ‘ready-to-eat,’ low nutrient-density UPF, and was associated with adolescents of a lower SES and (iii) the ‘Traditional’ pattern had moderate consumption of total UPF (95 % CI: 47·6, 50·9 % g/d) with higher intake of UPF used in home-cooking and had less distinct associations with SES.

Results suggest that SES impacts both the amount and type of UPF consumed by adolescents in the UK, underscoring the importance of this factor when designing interventions. Distinct dietary patterns within adolescents’ high UPF diets have potential behavioural, nutritional and health implications.

Executive functioning (EF) impairments are widely known to represent transdiagnostic risk factors of psychopathology. However, a recent alternative account has been proposed, according to which EF impairments emerge as consequences of psychopathology.

Using a longitudinal cross-lagged panel network analysis approach, we tested these competing theoretical accounts at different stages during adolescence. We used data from the Brazilian High-Risk Cohort Study for the Development of Childhood Psychiatric Disorders, in which 61% of individuals at wave 1 were selected due to their high risk for psychopathology. Participants were assessed across three assessment waves during early (wave 1: n = 1,992, mean age = 10.20 years) and middle adolescence (wave 2: n = 1,633, mean age = 13.48 years; wave 3: n = 1,439, mean age = 18.20 years). We examined associations between working memory, inhibitory control, and broad-band measures of psychopathology.

During early adolescence, lower inhibitory control was a risk factor for externalizing problems that, in turn, predicted lower working memory capacity. During middle adolescence, bidirectional associations became more prominent: inhibitory control and working memory functioned as both risk factors and consequences. Externalizing problems both predicted and were predicted by poor inhibitory control. Internalizing and externalizing symptoms showed bidirectional associations over time. Externalizing problems predicted more internalizing symptoms, whereas internalizing symptoms predicted fewer externalizing problems during middle adolescence.

Our results corroborate dynamic theories that describe executive dysfunctions as precursors and consequences of psychopathology in middle adolescence.