Personalised Mental Health Care for Young People: Using Past Outcomes to Build Future Solutions

Mental health disorders present one of the most serious public health challenges we face in the 21st century. Their prevalence, early age of onset and chronicity contribute to the substantial burden and secondary risks associated with these disorders. They tend to emerge during adolescence and young adulthood, a period characterised by major physical and social change, and so the effects of these disorders can often have long-term consequences on the adult lives of young people. Previously young people have had poor access to health services that address their needs, however the development of youth-focused health services has been a critical step forward to addressing this gap, providing better access to mental health care for adolescents and young adults. The nature of mental health disorders among young people, however, means that there are still major challenges in providing quality mental health care that addresses the broad range of health, social and functional needs of young people. The overall aim of this thesis was to examine the long-term outcomes of young people attending early intervention youth mental health services to inform the development and delivery of personalised mental health care that address the needs of young people. The first two studies are empirical papers that generate new knowledge with regard to the real-world long-term health, social and economic outcomes of help-seeking young people who attend an early intervention mental health service. This outcome data was used to delineate which young people are particularly at risk for worse clinical and functional outcomes and guide the development of new approaches that aim to improve the delivery of youth mental health care. A third empirical paper assessed the role of a technology-enabled clinical protocol to identify and respond to suicidal thoughts and behaviours at service entry. This study has been critical to the development of real-world service provisions that address this specific health care need with further implications for broader use. Finally, a systematic review was conducted which collates the findings from over 130 studies to determine the neurobiological correlates of these broader health, social and economic outcomes to inform future clinical research and the integration of further assessment into the delivery of youth mental health care. The overall findings of this thesis are fourfold. The first is that there is still work to be done to ensure young people are receiving mental health care earlier in the course of these illnesses and prior to the emergence of significant problems. Further research is still needed in this area to determine which strategies are most effective for improving help-seeking behaviours and promoting early intervention. The second is that health service strategies should be in place to identify and respond to individual health and social needs young people present with, particularly those that are associated with poorer long-term outcomes, such as substantial functional impairment and suicidal behaviours. The third is that early identification followed by current standard care provisions do not appear to inevitably result in improved outcomes. Instead, it is clear that the development and evaluation of specific, integrated care packages may be needed to reduce the morbidity and mortality due to early-onset major mental health disorders. Finally, there is a role for new technologies in mental health reform and the delivery of personalised mental health care, and future studies should focus on implementation strategies that facilitate the evaluation of these technologies in real world settings

Using new and innovative technologies to assess clinical stage in early intervention youth mental health services: Evaluation study

Background: Globally there is increasing recognition that new strategies are required to reduce disability due to common mental health problems. As 75% of mental health and substance use disorders emerge during the teenage or early adulthood years, these strategies need to be readily accessible to young people. When considering how to provide such services at scale, new and innovative technologies show promise in augmenting traditional clinic-based services. Objective: The aim of this study was to test new and innovative technologies to assess clinical stage in early intervention youth mental health services using a prototypic online system known as the Mental Health eClinic (MHeC). Methods: The online assessment within the MHeC was compared directly against traditional clinician assessment within 2 Sydney-based youth-specific mental health services (headspace Camperdown and headspace Campbelltown). A total of 204 young people were recruited to the study. Eligible participants completed both face-to-face and online assessments, which were randomly allocated and counterbalanced at a 1-to-3 ratio. These assessments were (1) a traditional 45- to 60-minute headspace face-to-face assessment performed by a Youth Access Clinician and (2) an approximate 60-minute online assessment (including a self-report Web-based survey, immediate dashboard of results, and a video visit with a clinician). All assessments were completed within a 2-week timeframe from initial presentation. Results: Of the 72 participants who completed the study, 71% (51/72) were female and the mean age was 20.4 years (aged 16 to 25 years); 68% (49/72) of participants were recruited from headspace Camperdown and the remaining 32% (23/72) from headspace Campbelltown. Interrater agreement of participants’ stage, as determined after face-to-face assessment or online assessment, demonstrated fair agreement (kappa=.39, P\u3c.001) with concordance in 68% of cases (49/72). Among the discordant cases, those who were allocated to a higher stage by online raters were more likely to report a past history of mental health disorders (P=.001), previous suicide planning (P=.002), and current cannabis misuse (P=.03) compared to those allocated to a lower stage. Conclusions: The MHeC presents a new and innovative method for determining key clinical service parameters. It has the potential to be adapted to varied settings in which young people are connected with traditional clinical services and assist in providing the right care at the right tim

What is the prevalence, and what are the clinical correlates, of insulin resistance in young people presenting for mental health care? A cross-sectional study

Objectives: To report the distribution and predictors of insulin resistance (IR) in young people presenting to primary care-based mental health services. Design: Cross-sectional. Setting: Headspace-linked clinics operated by the Brain and Mind Centre of the University of Sydney. Participants: 768 young people (66% female, mean age 19.7±3.5, range 12–30 years). Main outcome measures: IR was estimated using the updated homeostatic model assessment (HOMA2-IR). Height and weight were collected from direct measurement or self-report for body mass index (BMI). Results: For BMI, 20.6% of the cohort were overweight and 10.2% were obese. However,6.9 mmol/L). By contrast, 9.9% had a HOMA2-IR score \u3e2.0 (suggesting development of IR) and 11.7% (n=90) had a score between 1.5 and 2. Further, there was a positive correlation between BMI and HOMA2-IR (r=0.44, p Conclusions: Emerging IR is evident in a significant subgroup of young people presenting to primary care based mental health services. While the major modifiable risk factor is BMI, a large proportion of the variance is not accounted for by other demographic, clinical or treatment factors. Given the early emergence of IR, secondary prevention interventions may need to commence prior to the development of full-threshold or major mood or psychotic disorders

Reducing youth suicide : systems modelling and simulation to guide targeted investments across the determinants

Background: Reducing suicidal behaviour (SB) is a critical public health issue globally. The complex interplay of social determinants, service system factors, population demographics, and behavioural dynamics makes it extraordinarily difficult for decision makers to determine the nature and balance of investments required to have the greatest impacts on SB. Real-world experimentation to establish the optimal targeting, timing, scale, frequency, and intensity of investments required across the determinants is unfeasible. Therefore, this study harnesses systems modelling and simulation to guide population-level decision making that represent best strategic allocation of limited resources. Methods: Using a participatory approach, and informed by a range of national, state, and local datasets, a system dynamics model was developed, tested, and validated for a regional population catchment. The model incorporated defined pathways from social determinants of mental health to psychological distress, mental health care, and SB. Intervention scenarios were investigated to forecast their impact on SB over a 20-year period. Results: A combination of social connectedness programs, technology-enabled coordinated care, post-attempt assertive aftercare, reductions in childhood adversity, and increasing youth employment projected the greatest impacts on SB, particularly in a youth population, reducing self-harm hospitalisations (suicide attempts) by 28.5% (95% interval 26.3–30.8%) and suicide deaths by 29.3% (95% interval 27.1–31.5%). Introducing additional interventions beyond the best performing suite of interventions produced only marginal improvement in population level impacts, highlighting that ‘more is not necessarily better.’ Conclusion: Results indicate that targeted investments in addressing the social determinants and in mental health services provides the best opportunity to reduce SB and suicide. Systems modelling and simulation offers a robust approach to leveraging best available research, data, and expert knowledge in a way that helps decision makers respond to the unique characteristics and drivers of SB in their catchments and more effectively focus limited health resources

Premature mortality in young people accessing early intervention youth mental healthcare: data-linkage cohort study

Background 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. Aims To establish premature mortality risk in young people accessing early intervention mental health services and identify predictors of mortality. Method 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. Results 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. Conclusion 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

Predictive modelling of deliberate self-harm and suicide attempts in young people accessing primary care: a machine learning analysis of a longitudinal study

Purpose Machine learning (ML) has shown promise in modelling future self-harm but is yet to be applied to key questions facing clinical services. In a cohort of young people accessing primary mental health care, this study aimed to establish (1) the performance of models predicting deliberate self-harm (DSH) compared to suicide attempt (SA), (2) the performance of models predicting new-onset or repeat behaviour, and (3) the relative importance of factors predicting these outcomes. Methods 802 young people aged 12–25 years attending primary mental health services had detailed social and clinical assessments at baseline and 509 completed 12-month follow-up. Four ML algorithms, as well as logistic regression, were applied to build four distinct models. Results The mean performance of models predicting SA (AUC: 0.82) performed better than the models predicting DSH (AUC: 0.72), with mean positive predictive values (PPV) approximately twice that of the prevalence (SA prevalence 14%, PPV: 0.32, DSH prevalence 22%, PPV: 0.40). All ML models outperformed standard logistic regression. The most frequently selected variable in both models was a history of DSH via cutting. Conclusion History of DSH and clinical symptoms of common mental disorders, rather than social and demographic factors, were the most important variables in modelling future behaviour. The performance of models predicting outcomes in key sub-cohorts, those with new-onset or repetition of DSH or SA during follow-up, was poor. These findings may indicate that the performance of models of future DSH or SA may depend on knowledge of the individual’s recent history of either behaviour

Clinical staging and the differential risks for clinical and functional outcomes in young people presenting for youth mental health care

Background: Clinical staging proposes that youth-onset mental disorders develop progressively, and that active treatment of earlier stages should prevent progression to more severe disorders. This retrospective cohort study examined the longitudinal relationships between clinical stages and multiple clinical and functional outcomes within the frst 12 months of care. Methods: Demographic and clinical information of 2901 young people who accessed mental health care at age 12–25 years was collected at predetermined timepoints (baseline, 3 months, 6 months, 12 months). Initial clinical stage was used to defne three fxed groups for analyses (stage 1a: ‘non-specifc anxious or depressive symptoms’, 1b: ‘attenuated mood or psychotic syndromes’, 2+: ‘full-threshold mood or psychotic syndromes’). Logistic regression models, which controlled for age and follow-up time, were used to compare clinical and functional outcomes (role and social function, suicidal ideation, alcohol and substance misuse, physical health comorbidity, circadian disturbances) between staging groups within the initial 12 months of care. Results: Of the entire cohort, 2093 young people aged 12–25 years were followed up at least once over the frst 12 months of care, with 60.4% female and a baseline mean age of 18.16 years. Longitudinally, young people at stage 2+ were more likely to develop circadian disturbances (odds ratio [OR]=2.58; CI 1.60–4.17), compared with individuals at stage 1b. Additionally, stage 1b individuals were more likely to become disengaged from education/employment (OR=2.11, CI 1.36–3.28), develop suicidal ideations (OR=1.92; CI 1.30–2.84) and circadian disturbances (OR=1.94, CI 1.31–2.86), compared to stage 1a. By contrast, we found no relationship between clinical stage and the emergence of alcohol or substance misuse and physical comorbidity. Conclusions: The diferential rates of emergence of poor clinical and functional outcomes between early versus late clinical stages support the clinical staging model’s assumptions about illness trajectories for mood and psychotic syndromes. The greater risk of progression to poor outcomes in those who present with more severe syndromes may be used to guide specifc intervention packages

Transdiagnostic neurocognitive subgroups and functional course in young people with emerging mental disorders: a cohort study.

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