Right care, first time: a highly personalised and measurement-based care model to manage youth mental health.

IntroductionMental disorders are a leading cause of long-term disability worldwide. Much of the burden of mental ill-health is mediated by early onset, comorbidities with physical health conditions and chronicity of the illnesses. This study aims to track the early period of mental disorders among young people presenting to Australian mental health services to facilitate more streamlined transdiagnostic processes, highly personalised and measurement-based care, secondary prevention and enhanced long-term outcomes.Methods and analysisRecruitment to this large-scale, multisite, prospective, transdiagnostic, longitudinal clinical cohort study (‘Youth Mental Health Tracker’) will be offered to all young people between the ages of 12 and 30 years presenting to participating services with proficiency in English and no history of intellectual disability. Young people will be tracked over 3 years with standardised assessments at baseline and 3, 6, 12, 24 and 36 months. Assessments will include self-report and clinician-administered measures, covering five key domains including: (1) social and occupational function; (2) self-harm, suicidal thoughts and behaviour; (3) alcohol or other substance misuse; (4) physical health; and (5) illness type, clinical stage and trajectory. Data collection will be facilitated by the use of health information technology. The data will be used to: (1) determine prospectively the course of multidimensional functional outcomes, based on the differential impact of demographics, medication, psychological interventions and other key potentially modifiable moderator variables and (2) map pathophysiological mechanisms and clinical illness trajectories to determine transition rates of young people to more severe illness forms.Ethics and disseminationThe study has been reviewed and approved by the Human Research Ethics Committee of the Sydney Local Health District (2019/ETH00469). All data will be non-identifiable, and research findings will be disseminated through peer-reviewed journals and scientific conference presentations.

BackgroundClinical 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 first 12 months of care.MethodsDemographic 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 define three fixed groups for analyses (stage 1a: ‘non-specific 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.ResultsOf the entire cohort, 2093 young people aged 12–25 years were followed up at least once over the first 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.ConclusionsThe differential 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 specific intervention packages.

Problem and Context: Measurement-based care (MBC) involves the systematic administration of standardized measures and the use of results to drive clinical decision-making within a therapeutic relationship framework. It is an integral part of youth-centered care and a core standard of integrated youth mental health services. Despite the wealth of evidence for the benefits of MBC in supporting high quality care, the implementation of MBC into routine mental health care is rarely incorporated. Who is it for? Youth mental health problems are a growing concern in Canada and globally, causing significant distress, impairment, and negative adult outcomes when untreated. Despite evidence-based interventions, only a minority of youth access and receive adequate treatment, with most youth facing barriers to high quality and effective interventions. To address these gaps, integrated youth service (IYS) models are established globally for youth ages 12-25 and emphasize timely access, youth friendliness, and holistic care, integrate mental and physical health, substance use, education, employment, peer support, and navigation into ‘one-stop shops’. Youth Wellness Hubs Ontario (YWHO) is Ontario’s IYS network with 22 integrated service networks in more than 30 communities across the province. MBC is a core component of the YWHO model and is implemented in 22 sites. Who did you involve and engage with? A fundamental contribution of YWHO is the inclusion of meaningful youth and family engagement processes in service design, delivery, and evaluation. YWHO has youth and family advisory councils both at the provincial and local levels who contribute to planning and operations, including service planning, governance, training, evaluation, communications, and funding-related decision-making. What did you do? This presentation will present the strategies, challenges, solutions, and subsequent adaptations we used to implement MBC within integrated youth services. We will describe the lessons we learned as we confronted practical obstacles around implementing MBC into integrated care pathways. What results did you get? MBC lessons learned included: 1. Leadership, service provider, and youth engagement in MBC; selection of measures and when to use measures, integrated data platform and electronic health records, addressing data quality issues early on, preparing for a demanding process of change, establishing support and coaching mechanisms, adapting MBC to a virtual environment, and adapting MBC in non-dominant cultural contexts. What is the learning for the international audience? MBC has been shown to improve the quality of care and clinical outcomes but it also requires substantial commitment, time, resources, and change management that can make it difficult to implement well in integrated care settings. Despite these challenges, we provide some creative solutions and adaptations within our model of youth-centered care that will inform audiences of how to effectively use MBC to personalize care, and how best to use MBC to engage service providers and youth in monitoring and management of symptoms. What are the next steps? Future directions include continuous learning and evaluation of the implementation of MBC in integrated care settings and identifying the factors for successful implementation.

Special Report: Measurement-Based Care—Using Data to Augment Psychotherapy

The role of new technologies in monitoring the evolution ofpsychopathology and providing measurement-based care in youngpeople.

How to Overcome the Limitations of Diagnosis in Psychiatry

AimsThe 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.MethodsDynamic 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.ResultsThe ‘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.ConclusionsThis 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.

Imagine that major auto manufacturers have announced a quality breakthrough. Going forward, they will produce each model of car by using a standard set of parts assembled in the same order. And before selling any vehicle, they will test to be sure it can both start and stop. As auto consumers, we might not celebrate this breakthrough. Instead we might ask, “What has taken you so long?” The learning collaborative program described by Vannoy and colleagues in this issue deserves celebration. Primary care and mental health clinics serving disadvantaged patients can successfully implement integrated care programs for mood disorders, including evidence-based care protocols and systematic outcome assessment. However, evidence-based depression care guidelines have existed for 20 years, and standard depression outcome measures have existed for 40. So consumers might ask, “What has taken you so long?” Unfortunately, spreading evidence-based and measurement-based mental health care is not as straightforward as improving auto manufacturing. Some providers fear that evidence-based care means “cookbook medicine,” precluding personalization for individuals. In addition, organized mental health outcome measurement raises concerns about privacy of sensitive information. Neither of these concerns, however, actually argues against evidence-based or measurement-based care. The supposed conflict between evidence-based mental health care and personalized care is rooted in misunderstanding; the two are completely compatible. If we hope to choose the best treatment for any individual, we require two things. First, we need better evidence regarding how individual characteristics (such as symptom patterns and genetic variation) predict response to specific treatments. Our evidence must extend beyond average effectiveness to consider individual differences. Second, we need accurate measurement of how individuals differ in pre-treatment characteristics and in response to specific treatments. Better evidence and better measurement are therefore essential to personalizing care. Conflict between personalized care and evidence-based care arises only if we are personalizing care to meet the needs of providers. That is, unfortunately, sometimes the case. Privacy concerns regarding measurement-based care are also sometimes misplaced. Consumers’ privacy concerns focus more on sensitive personal details than on standard outcome questionnaires. In contrast, providers’ privacy concerns often reflect a wish to avoid scrutiny regarding quality or safety. Consumers’ privacy deserves protection; unsafe or ineffective care has no right to privacy. None of these comments are intended to dispute the importance of the collaborative efforts that Vannoy and colleagues describe. Instead they are intended as an apologetic answer to the question, “What has taken you so long?” We can celebrate the success of these learning collaboratives and also hope for a day when such success is no longer a newsworthy breakthrough.

BackgroundAustralia’s mental health care system has long been fragmented and under-resourced, with services falling well short of demand. In response, the World Economic Forum has recently called for the rapid deployment of smarter, digitally enhanced health services to facilitate effective care coordination and address issues of demand. The University of Sydney’s Brain and Mind Centre (BMC) has developed an innovative digital health solution that incorporates 2 components: a highly personalized and measurement-based (data-driven) model of youth mental health care and a health information technology (HIT) registered on the Australian Register of Therapeutic Goods. Importantly, research into implementation of such solutions considers education and training of clinicians to be essential to adoption and optimization of use in standard clinical practice. The BMC’s Youth Mental Health and Technology Program has subsequently developed a comprehensive education and training program to accompany implementation of the digital health solution.ObjectiveThis paper describes the protocol for an evaluation study to assess the effectiveness of the education and training program on the adoption and optimization of use of the digital health solution in service delivery. It also describes the proposed tools to assess the impact of training on knowledge and skills of mental health clinicians.MethodsThe evaluation study will use the Kirkpatrick Evaluation Model as a framework with 4 levels of analysis: Reaction (to education and training), Learning (knowledge acquired), Behavior (practice change), and Results (client outcomes). Quantitative and qualitative data will be collected using a variety of tools, including evaluation forms, pre- and postknowledge questionnaires, skill development and behavior change scales, as well as a real-time clinical practice audit.ResultsThis project is funded by philanthropic funding from Future Generation Global. Ethics approval has been granted via Sydney Local Health District’s Human Research Ethics Committee. At the time of this publication, clinicians and their services were being recruited to this study. The first results are expected to be submitted for publication in 2021.ConclusionsThe education and training program teaches clinicians the necessary knowledge and skills to assess, monitor, and manage complex needs; mood and psychotic syndromes; and trajectories of youth mental ill-health using a HIT that facilitates a highly personalized and measurement-based model of care. The digital health solution may therefore guide clinicians to help young people recover low functioning associated with subthreshold diagnostic presentations and prevent progression to more serious mental ill-health.International Registered Report Identifier (IRRID)PRR1-10.2196/24697

ObjectivesMany adolescents and young adults with emerging mood disorders do not achieve substantial improvements in education, employment, or social function after receiving standard youth mental health care. We have developed...

BackgroundTheory and correlational research indicate organizational leadership and climate are important for successful implementation of evidence-based practices (EBPs) in healthcare settings; however, experimental evidence is lacking. We addressed this gap using data from the WISDOM (Working to Implement and Sustain Digital Outcome Measures) hybrid type III effectiveness-implementation trial. Primary outcomes from WISDOM indicated the Leadership and Organizational Change for Implementation (LOCI) strategy improved fidelity to measurement-based care (MBC) in youth mental health services. In this study, we tested LOCI’s hypothesized mechanisms of change, namely: (1) LOCI will improve implementation and transformational leadership, which in turn will (2) mediate LOCI’s effect on implementation climate, which in turn will (3) mediate LOCI’s effect on MBC fidelity.MethodsTwenty-one outpatient mental health clinics serving youth were randomly assigned to LOCI plus MBC training and technical assistance or MBC training and technical assistance only. Clinicians rated their leaders’ implementation leadership, transformational leadership, and clinic implementation climate for MBC at five time points (baseline, 4-, 8-, 12-, and 18-months post-baseline). MBC fidelity was assessed using electronic metadata for youth outpatients who initiated treatment in the 12 months following MBC training. Hypotheses were tested using longitudinal mixed-effects models and multilevel mediation analyses.ResultsLOCI significantly improved implementation leadership and implementation climate from baseline to follow-up at 4-, 8-, 12-, and 18-month post-baseline (all ps < .01), producing large effects (range of ds = 0.76 to 1.34). LOCI’s effects on transformational leadership were small at 4 months (d = 0.31, p = .019) and nonsignificant thereafter (ps > .05). LOCI’s improvement of clinic implementation climate from baseline to 12 months was mediated by improvement in implementation leadership from baseline to 4 months (proportion mediated [pm] = 0.82, p = .004). Transformational leadership did not mediate LOCI’s effect on implementation climate (p = 0.136). Improvement in clinic implementation climate from baseline to 12 months mediated LOCI’s effect on MBC fidelity during the same period (pm = 0.71, p = .045).ConclusionsLOCI improved MBC fidelity in youth mental health services by improving clinic implementation climate, which was itself improved by increased implementation leadership. Fidelity to EBPs in healthcare settings can be improved by developing organizational leaders and strong implementation climates.Trial registrationClinicalTrials.gov identifier: NCT04096274. Registered September 18, 2019.

BackgroundFor youth receiving care in community mental health centers, comorbidities are the rule rather than the exception. Using measurement-based care (MBC), or the routine evaluation of symptoms to inform care decisions, as the foundation of treatment for youth with comorbid problems significantly improves the impact of psychotherapy by focusing care and building engagement and alliance. MBC increases the rate of symptom improvement, detects clients who would otherwise deteriorate, and alerts clinicians to non-responders. Despite its demonstrated utility, MBC is rarely implemented with fidelity; less than 15% of providers report using MBC per recommendations. Previous efforts to support MBC implementation have yielded suboptimal outcomes, in part, due to organizations’ challenges with identifying and prioritizing barriers and selecting and developing strategies to overcome them. New methods are needed for identifying and prioritizing barriers, and matching strategies to barriers to optimize MBC implementation and treatment quality to improve youth mental health outcomes in community settings.MethodsPragmatic implementation methods will be piloted in four diverse community mental health centers. Methods include (a) rapid evidence synthesis; (b) rapid ethnography; (c) design kits (e.g., kits with disposable cameras, journals, maps); (d) barrier prioritization, and (e) causal pathway diagramming. These activities will generate actionable barriers; subsequently, we will use facilitated group processes to prioritize barriers and develop causal pathway diagrams to match strategies to barriers to create implementation plans that optimize MBC fidelity (Aim 1). We will track strategy deployment for 6 months, then compare MBC fidelity for another 6 months post-implementation with data from 2 years of historical controls (Aim 2). Finally, we will co-design a toolkit for design kit methods with youth and the practice and scientific communities (Aim 3).DiscussionOptimizing MBC implementation in community mental health centers could transform youth mental health care by ensuring the most pressing symptoms are targeted early in treatment. The discussion section highlights expected challenges and limits to using the five methods, including recruitment and engagement given the high pressure on community mental health settings.Trial registrationClinicaltrials.gov. NCT05644756. Registered on 18 November 2022. This trial was retrospectively registered.

IntroductionChildren and adolescents often do not receive mental healthcare when they need it. By 2021, the complex impact of the COVID-19 pandemic, structural racism, inequality in access to healthcare, and a growing shortage of mental health providers led to a national emergency in child and adolescent mental health in the United States. The need for effective, accessible treatment is more pressing than ever. Interdisciplinary, team-based pediatric integrated mental healthcare has been shown to be efficacious, accessible, and cost-effective.MethodsIn response to the youth mental health crisis, Rady Children’s Hospital-San Diego’s Transforming Mental Health Initiative aimed to increase early identification of mental illness and improve access to effective treatment for children and adolescents. A stakeholder engagement process was established with affiliated pediatric clinics, community mental health organizations, and existing pediatric integrated care programs, leading to the development of the Primary Care Mental Health Integration program and drawing from established models of integrated care: Primary Care Behavioral Health and Collaborative Care.ResultsAs of 2023, the Primary Care Mental Health Integration program established integrated care teams in 10 primary care clinics across San Diego and Riverside counties in California. Measurement-based care has been implemented and preliminary results indicate that patient response to therapy has resulted in a 44% reduction in anxiety symptoms and a 62% decrease in depression symptoms. The program works toward fiscal sustainability via fee-for-service reimbursement and more comprehensive payor contracts. The impact on patients, primary care provider satisfaction, measurement-based care, funding strategies, as well as challenges faced and changes made will be discussed using the lens of the Reach, Effectiveness, Adoption, Implementation and Maintenance framework.DiscussionPreliminary results suggest that the Primary Care Mental Health Integration is a highly collaborative integrated care model that identifies the needs of children and adolescents and delivers brief, evidence informed treatment. The successful integration of this model into 10 primary care clinics over 3 years has laid the groundwork for future program expansion. This model of care can play a role addressing youth mental health and increasing access to care. Challenges, successes, and lessons learned will be reviewed.

Despite high levels of mental ill-health amongst young people (aged 15-30), this group demonstrates low help-seekingand high drop-out from mental health services (MHS). Whilstshared decision-making can assist people in receiving appropriate and effective health care, young people frequently report that they do not feel involved in treatment decisions. The current study focused on co-design of a clinical education and participant information programme for the Brain and Mind Centre Youth Model of Care. This model, which articulates a youth-focused form of highly personalised and measurement-based care, is designed to promote shared decision-making between young people and clinical service providers. We conducted workshops with 24 young people (16-31; MAge = 21.5) who had accessed mental health services. Participants were asked what advice they would give to young people entering services, before giving advice on existing materials. Workshops were conducted and transcripts were coded using thematic analysisby two lived experience researchers and a clinical researcher. Young people found it empowering to be educated on transdiagnostic models of mental illness, namely clinical staging, which givesthem a better understanding of why certain treatments may be inappropriate and ineffective, and thus reduce self-blame. Similarly, young people had limited knowledge of links between mental health and other life domains and found it helpful to be educated on multidisciplinary treatment options. Measurement-based care was seen as an important method of improving shared decision-making between young people and health professionals;however, to facilitate shared decision-making, young people also wanted better information on their rights in care and more support to share their expertise in their own needs, valuesand treatment preferences. These findings will inform the delivery of the further development and implementation of a youth-specific clinical education and participant information programme for the BMC Youth Model. Workshops were facilitated by researchers with lived expertise in mental ill-health (A.H. and/or C.G.) and a clinical researcher (who has expertise as an academic and a clinical psychologist). A.H. and C.G. were also involved in conceptualisation, analysis, interpretation, review and editing of this paper.

BACKGROUND Digital technologies can substantially improve mental health care by facilitating measurement-based care through routine outcome monitoring. However, their effectiveness is constrained by the extent to which these technologies are used by services, clinicians, and clients. OBJECTIVE This study aims to investigate engagement with the Innowell platform, a measurement-based digital mental health technology (DMHT), to gain insights into the individual and service-level factors influencing engagement. METHODS Participants were 2,682 help-seeking clients from 12 Australian mental health services (11 headspace centers and one private practice, Mind Plasticity) wherein the Innowell platform was implemented. Although the initial implementation was standardized, services varied in their practical and continued use of the platform, as well as in the resources allocated to foster engagement. All participants completed an initial assessment during onboarding. Engagement here was defined as their ensuing completion of the summary questionnaire, designed for routine outcome monitoring. Participants were classified as ‘Initial Assessment Only’, 'Single Use' (one completion of the summary questionnaire), or '2+ Uses' (two or more completions). We analyzed engagement differences across services and associations between engagement and initial assessment scores. RESULTS Of the sample, 75.4% completed the initial assessment only, 11.5% had one completion of the summary questionnaire, and 13.0% had two or more completions. The service center was the strongest predictor of engagement, with Mind Plasticity participants showing over eight times higher engagement than other centers. At the individual level, higher scores in depression (P = .002), mania-like experiences (P = .047), suicide ideation (P = .004), hospitalization history for mental illness (P = .013), and physical activity (P &lt; .001) were associated with increased engagement. Conversely, higher levels of anxiety symptoms (P = .011), substance misuse (P &lt; .001), self-reported mental illness severity (P = .024), and social support (P = .047) predicted lower engagement. Age and several other clinical variables were not significant predictors when controlling for service-level factors. CONCLUSIONS This study reveals that both individual and service-level factors significantly influence DMHT engagement, with the service center being the strongest predictor. This highlights the importance of service-level technology integration and support roles like Digital Navigators in fostering engagement. Significant variation in engagement among user groups indicates the need for a nuanced approach to measurement-based care. While mental illness generally did not impede engagement, self-perceived severity and anxiety symptoms were barriers. These findings underscore the critical importance of systemic factors and service-level integration strategies in driving DMHT engagement. User-centered designs remain important, but effective integration of DMHTs into existing mental health services is paramount for improving engagement across diverse user groups and clinical presentations. This multi-level approach – encompassing individual, service, and system-wide considerations – is essential for realizing DMHTs' full potential in delivering effective measurement-based care.