Increasing daylight exposure might be a simple way to improve mental health. However, little is known about daylight-symptom associations in depressive disorders.

In a subset of the Australian Genetics of Depression Study (N = 13,480; 75% female), we explored associations between self-reported number of hours spent in daylight on a typical workday and free day and seven symptom dimensions: depressive (overall, somatic, psychological); hypo-manic-like; psychotic-like; insomnia; and daytime sleepiness. Polygenic scores for major depressive disorder (MDD); bipolar disorder (BD); and schizophrenia (SCZ) were calculated. Models were adjusted for age, sex, shift work status, employment status, season, and educational attainment. Exploratory analyses examined age-stratified associations (18–24 years; 25–34 years; 35–64 years; 65 and older). Bonferroni-corrected associations (p < 0.004) are discussed.

Adults with depression reported spending a median of one hour in daylight on workdays and three hours on free days. More daylight exposure on workdays and free days was associated with lower depressive (overall, psychological, somatic) and insomnia symptoms (p’s<0.001), but higher hypo-manic-like symptoms (p’s<0.002). Genetic loading for MDD and SCZ were associated with less daylight exposure in unadjusted correlational analyses (effect sizes were not meaningful). Exploratory analyses revealed age-related heterogeneity. Among 18–24-year-olds, no symptom dimensions were associated with daylight. By contrast, for the older age groups, there was a pattern of more daylight exposure and lower insomnia symptoms (p < 0.003) (except for 25–34-year-olds on free days, p = 0.019); and lower depressive symptoms with more daylight on free days, and to some extent workdays (depending on the age-group).

Exploration of the causal status of daylight in depression is warranted.

Functional impairment is a major concern among those presenting to youth mental health services and can have a profound impact on long-term outcomes. Early recognition and prevention for those at risk of functional impairment is essential to guide effective youth mental health care. Yet, identifying those at risk is challenging and impacts the appropriate allocation of indicated prevention and early intervention strategies.

We developed a prognostic model to predict a young person’s social and occupational functional impairment trajectory over 3 months. The sample included 718 young people (12–25 years) engaged in youth mental health care. A Bayesian random effects model was designed using demographic and clinical factors and model performance was evaluated on held-out test data via 5-fold cross-validation.

Eight factors were identified as the optimal set for prediction: employment, education, or training status; self-harm; psychotic-like experiences; physical health comorbidity; childhood-onset syndrome; illness type; clinical stage; and circadian disturbances. The model had an acceptable area under the curve (AUC) of 0.70 (95% CI, 0.56–0.81) overall, indicating its utility for predicting functional impairment over 3 months. For those with good baseline functioning, it showed excellent performance (AUC = 0.80, 0.67–0.79) for identifying individuals at risk of deterioration.

We developed and validated a prognostic model for youth mental health services to predict functional impairment trajectories over a 3-month period. This model serves as a foundation for further tool development and demonstrates its potential to guide indicated prevention and early intervention for enhancing functional outcomes or preventing functional decline.

Primary youth mental health services in Australia have increased access to care for young people, yet the longer-term outcomes and utilisation of other health services among these populations is unclear.

To describe the emergency department presentation patterns of a help-seeking youth mental health cohort.

Data linkage was performed to extract Emergency Department Data Collection registry data (i.e. emergency department presentations, pattern of re-presentations) for a transdiagnostic cohort of 7024 youths (aged 12–30 years) who presented to mental health services. Outcome measures were pattern of presentations and reason for presentations (i.e. mental illness; suicidal behaviours and self-harm; alcohol and substance use; accident and injury; physical illness; and other).

During the follow-up period, 5372 (76.5%) had at least one emergency department presentation. The presentation rate was lower for males (IRR = 0.87, 95% CI 0.86–0.89) and highest among those aged 18 to 24 (IRR = 1.117, 95% CI 1.086–1.148). Almost one-third (31.12%) had an emergency department presentation that was directly associated with mental illness or substance use, and the most common reasons for presentation were for physical illness and accident or injury. Index visits for mental illness or substance use were associated with a higher rate of re-presentation.

Most young people presenting to primary mental health services also utilised emergency services. The preventable and repeated nature of many presentations suggests that reducing the ongoing secondary risks of mental disorders (i.e. substance misuse, suicidality, physical illness) could substantially improve the mental and physical health outcomes of young people.

The needs of young people attending mental healthcare can be complex and often span multiple domains (e.g., social, emotional and physical health factors). These factors often complicate treatment approaches and contribute to poorer outcomes in youth mental health. We aimed to identify how these factors interact over time by modelling the temporal dependencies between these transdiagnostic social, emotional and physical health factors among young people presenting for youth mental healthcare.

Dynamic Bayesian networks were used to examine the relationship between mental health factors across multiple domains (social and occupational function, self-harm and suicidality, alcohol and substance use, physical health and psychiatric syndromes) in a longitudinal cohort of 2663 young people accessing youth mental health services. Two networks were developed: (1) ‘initial network’, that shows the conditional dependencies between factors at first presentation, and a (2) ‘transition network’, how factors are dependent longitudinally.

The ‘initial network’ identified that childhood disorders tend to precede adolescent depression which itself was associated with three distinct pathways or illness trajectories; (1) anxiety disorder; (2) bipolar disorder, manic-like experiences, circadian disturbances and psychosis-like experiences; (3) self-harm and suicidality to alcohol and substance use or functioning. The ‘transition network’ identified that over time social and occupational function had the largest effect on self-harm and suicidality, with direct effects on ideation (relative risk [RR], 1.79; CI, 1.59–1.99) and self-harm (RR, 1.32; CI, 1.22–1.41), and an indirect effect on attempts (RR, 2.10; CI, 1.69–2.50). Suicide ideation had a direct effect on future suicide attempts (RR, 4.37; CI, 3.28–5.43) and self-harm (RR, 2.78; CI, 2.55–3.01). Alcohol and substance use, physical health and psychiatric syndromes (e.g., depression and anxiety, at-risk mental states) were independent domains whereby all direct effects remained within each domain over time.

This study identified probable temporal dependencies between domains, which has causal interpretations, and therefore can provide insight into their differential role over the course of illness. This work identified social, emotional and physical health factors that may be important early intervention and prevention targets. Improving social and occupational function may be a critical target due to its impacts longitudinally on self-harm and suicidality. The conditional independence of alcohol and substance use supports the need for specific interventions to target these comorbidities.

Understanding premature mortality risk from suicide and other causes in youth mental health cohorts is essential for delivering effective clinical interventions and secondary prevention strategies.

To establish premature mortality risk in young people accessing early intervention mental health services and identify predictors of mortality.

State-wide data registers of emergency departments, hospital admissions and mortality were linked to the Brain and Mind Research Register, a longitudinal cohort of 7081 young people accessing early intervention care, between 2008 and 2020. Outcomes were mortality rates and age-standardised mortality ratios (SMR). Cox regression was used to identify predictors of all-cause mortality and deaths due to suicide or accident.

There were 60 deaths (male 63.3%) during the study period, 25 (42%) due to suicide, 19 (32%) from accident or injury and eight (13.3%) where cause was under investigation. All-cause SMR was 2.0 (95% CI 1.6–2.6) but higher for males (5.3, 95% CI 3.8–7.0). The mortality rate from suicide and accidental deaths was 101.56 per 100 000 person-years. Poisoning, whether intentional or accidental, was the single greatest primary cause of death (26.7%). Prior emergency department presentation for poisoning (hazard ratio (HR) 4.40, 95% CI 2.13–9.09) and psychiatric admission (HR 4.01, 95% CI 1.81–8.88) were the strongest predictors of mortality.

Premature mortality in young people accessing early intervention mental health services is greatly increased relative to population. Prior health service use and method of self-harm are useful predictors of future mortality. Enhanced care pathways following emergency department presentations should not be limited to those reporting suicidal ideation or intent.

The schizophrenia polygenic risk score (SCZ-PRS) is an emerging tool in psychiatry.

We aimed to evaluate the utility of SCZ-PRS in a young, transdiagnostic, clinical cohort.

SCZ-PRSs were calculated for young people who presented to early-intervention youth mental health clinics, including 158 patients of European ancestry, 113 of whom had longitudinal outcome data. We examined associations between SCZ-PRS and diagnosis, clinical stage and functioning at initial assessment, and new-onset psychotic disorder, clinical stage transition and functional course over time in contact with services.

Compared with a control group, patients had elevated PRSs for schizophrenia, bipolar disorder and depression, but not for any non-psychiatric phenotype (for example cardiovascular disease). Higher SCZ-PRSs were elevated in participants with psychotic, bipolar, depressive, anxiety and other disorders. At initial assessment, overall SCZ-PRSs were associated with psychotic disorder (odds ratio (OR) per s.d. increase in SCZ-PRS was 1.68, 95% CI 1.08–2.59, P = 0.020), but not assignment as clinical stage 2+ (i.e. discrete, persistent or recurrent disorder) (OR = 0.90, 95% CI 0.64–1.26, P = 0.53) or functioning (R = 0.03, P = 0.76). Longitudinally, overall SCZ-PRSs were not significantly associated with new-onset psychotic disorder (OR = 0.84, 95% CI 0.34–2.03, P = 0.69), clinical stage transition (OR = 1.02, 95% CI 0.70–1.48, P = 0.92) or persistent functional impairment (OR = 0.84, 95% CI 0.52–1.38, P = 0.50).

In this preliminary study, SCZ-PRSs were associated with psychotic disorder at initial assessment in a young, transdiagnostic, clinical cohort accessing early-intervention services. Larger clinical studies are needed to further evaluate the clinical utility of SCZ-PRSs, especially among individuals with high SCZ-PRS burden.

Predictors of new-onset bipolar disorder (BD) or psychotic disorder (PD) have been proposed on the basis of retrospective or prospective studies of ‘at-risk’ cohorts. Few studies have compared concurrently or longitudinally factors associated with the onset of BD or PDs in youth presenting to early intervention services. We aimed to identify clinical predictors of the onset of full-threshold (FT) BD or PD in this population.

Multi-state Markov modelling was used to assess the relationships between baseline characteristics and the likelihood of the onset of FT BD or PD in youth (aged 12–30) presenting to mental health services.

Of 2330 individuals assessed longitudinally, 4.3% (n = 100) met criteria for new-onset FT BD and 2.2% (n = 51) met criteria for a new-onset FT PD. The emergence of FT BD was associated with older age, lower social and occupational functioning, mania-like experiences (MLE), suicide attempts, reduced incidence of physical illness, childhood-onset depression, and childhood-onset anxiety. The emergence of a PD was associated with older age, male sex, psychosis-like experiences (PLE), suicide attempts, stimulant use, and childhood-onset depression.

Identifying risk factors for the onset of either BD or PDs in young people presenting to early intervention services is assisted not only by the increased focus on MLE and PLE, but also by recognising the predictive significance of poorer social function, childhood-onset anxiety and mood disorders, and suicide attempts prior to the time of entry to services. Secondary prevention may be enhanced by greater attention to those risk factors that are modifiable or shared by both illness trajectories.

Neurocognitive impairments robustly predict functional outcome. However, heterogeneity in neurocognition is common within diagnostic groups, and data-driven analyses reveal homogeneous neurocognitive subgroups cutting across diagnostic boundaries.

To determine whether data-driven neurocognitive subgroups of young people with emerging mental disorders are associated with 3-year functional course.

Model-based cluster analysis was applied to neurocognitive test scores across nine domains from 629 young people accessing mental health clinics. Cluster groups were compared on demographic, clinical and substance-use measures. Mixed-effects models explored associations between cluster-group membership and socio-occupational functioning (using the Social and Occupational Functioning Assessment Scale) over 3 years, adjusted for gender, premorbid IQ, level of education, depressive, positive, negative and manic symptoms, and diagnosis of a primary psychotic disorder.

Cluster analysis of neurocognitive test scores derived three subgroups described as ‘normal range’ (n = 243, 38.6%), ‘intermediate impairment’ (n = 252, 40.1%), and ‘global impairment’ (n = 134, 21.3%). The major mental disorder categories (depressive, anxiety, bipolar, psychotic and other) were represented in each neurocognitive subgroup. The global impairment subgroup had lower functioning for 3 years of follow-up; however, neither the global impairment (B = 0.26, 95% CI −0.67 to 1.20; P = 0.581) or intermediate impairment (B = 0.46, 95% CI −0.26 to 1.19; P = 0.211) subgroups differed from the normal range subgroup in their rate of change in functioning over time.

Neurocognitive impairment may follow a continuum of severity across the major syndrome-based mental disorders, with data-driven neurocognitive subgroups predictive of functional course. Of note, the global impairment subgroup had longstanding functional impairment despite continuing engagement with clinical services.