A Prototype Software Framework for Transferable Computational Health Economic Models and Its Early Application in Youth Mental Health.

We are developing an economic model to explore multiple topics in Australian youth mental health policy. To help make that model more readily transferable to other jurisdictions, we developed a software framework for authoring modular computational health economic models (CHEMs) (the software files that implement health economic models). We specified framework user requirements for: a simple programming syntax; a template CHEM module; tools for authoring new CHEM modules; search tools for finding existing CHEM modules; tools for supplying CHEM modules with data; reproducible analysis and reporting tools; and tools to help maintain a CHEM project website. We implemented the framework as six development version code libraries in the programming language R that integrate with online services for software development and research data archiving. We used the framework to author five development version R libraries of CHEM modules focussed on utility mapping in youth mental health. These modules provide tools for variable validation, dataset description, multi-attribute instrument scoring, construction of mapping models, reporting of mapping studies and making out of sample predictions. We assessed these CHEM module libraries as mostly meeting transparency, reusability and updatability criteria that we have previously developed, but requiring more detailed documentation and unit testing of individual modules. Our software framework has potential value as a prototype for future tools to support the development of transferable CHEMs.Code: Visit https://www.ready4-dev.com for more information about how to find, install and apply the prototype software framework.

Inequalities in Access to Mental Health Treatment by Australian Youths During the COVID-19 Pandemic.

OBJECTIVE: The authors aimed to evaluate changes in use of government-subsidized primary mental health services, through the Medicare Benefits Schedule (MBS), by young people during the first year of the COVID-19 pandemic in Australia and whether changes were associated with age, sex, socioeconomic status, and residence in particular geographical areas. METHODS: Interrupted time-series analyses were conducted by using quarterly mental health MBS service data (all young people ages 12-25 years, 2015-2020) for individual Statistical Area Level 3 areas across Australia. The data captured >22.4 million service records. Meta-analysis and meta-regression models estimated the pandemic interruption effect at the national level and delineated factors influencing these estimates. RESULTS: Compared with expected prepandemic trends, a 6.2% (95% CI=5.3%-7.2%) increase was noted for all young people in use of MBS mental health services in 2020. Substantial differences were found between age and sex subgroups, with a higher increase among females and young people ages 18-25. A decreasing trend was observed for males ages 18-25 (3.5% reduction, 95% CI=2.5%-4.5%). The interruption effect was strongly associated with socioeconomic status. Service uptake increased in areas of high socioeconomic status, with smaller or limited uptake in areas of low socioeconomic status. CONCLUSIONS: During 2020, young people's use of primary mental health services increased overall. However, increases were inequitably distributed and relatively low, compared with increases in population-level mental health burden. Policy makers should address barriers to primary care access for young people, particularly for young males and those from socioeconomically disadvantaged backgrounds.

A systematic review comparing caregiver burden and psychological functioning in caregivers of individuals with schizophrenia spectrum disorders and bipolar disorders.

BACKGROUND: Informal primary caregivers provide crucial supports to loved ones experiencing serious mental illnesses with profound outcomes for the caregivers themselves. A comprehensive understanding of how different serious mental illnesses change the caregiving experience may provide important insight into the ways in which caregivers can be better supported in their role. The aim of this review was to synthesize the comparative literature examining caregiver burden and psychological functioning (anxiety, depression, distress, and psychological wellbeing) between caregivers of people with schizophrenia spectrum disorders and bipolar disorder. METHODS: Studies were included if they compared caregivers across both diagnostic groups and used measures assessing either caregiver burden or psychological functioning of caregivers. Databases searched up until 11th of January 2022 included: Medline COMPLETE, Embase, PsycINFO and CINAHL. Reference list scans and grey literature searches across government, organisational and dissertation databases were also conducted. RESULTS: Twenty-eight studies comprising 6166 caregivers were included. Fourteen studies suggested that caregiving burden was comparable across both groups. The effects of caring on caregiver mental health and stress were comparable across both groups. However, methodological limitations were noted, including a reliance on cross-sectional studies, multiple and sometimes competing definitions of caregiving burden, variable sample sizes, and variation in measures used. CONCLUSION AND IMPLICATIONS: The experience of providing care is multidimensional and complex. Symptoms and functional difficulties experienced by people being cared for may affect caregivers more so than diagnosis. Caregivers play a vital role in helping people with serious mental illness. Supporting caregivers by reducing their burden and improving their psychological functioning may help them to continue to provide support, and cope with, the challenges of providing care.

The EMPOWER blended digital intervention for relapse prevention in schizophrenia: a feasibility cluster randomised controlled trial in Scotland and Australia.

BACKGROUND: Early warning signs monitoring by service users with schizophrenia has shown promise in preventing relapse but the quality of evidence is low. We aimed to establish the feasibility of undertaking a definitive randomised controlled trial to determine the effectiveness of a blended digital intervention for relapse prevention in schizophrenia. METHODS: This multicentre, feasibility, cluster randomised controlled trial aimed to compare Early signs Monitoring to Prevent relapse in psychosis and prOmote Well-being, Engagement, and Recovery (EMPOWER) with treatment as usual in community mental health services (CMHS) in Glasgow and Melbourne. CMHS were the unit of randomisation, selected on the basis of those that probably had five or more care coordinators willing to participate. Participants were eligible if they were older than 16 years, had a schizophrenia or related diagnosis confirmed via case records, were able to provide informed consent, had contact with CMHS, and had had a relapse within the previous 2 years. Participants were randomised within stratified clusters to EMPOWER or to continue their usual approach to care. EMPOWER blended a smartphone for active monitoring of early warning signs with peer support to promote self-management and clinical triage to promote access to relapse prevention. Main outcomes were feasibility, acceptability, usability, and safety, which was assessed through face-to-face interviews. App usage was assessed via the smartphone and self-report. Primary end point was 12 months. Participants, research assistants and other team members involved in delivering the intervention were not masked to treatment conditions. Assessment of relapse was done by an independent adjudication panel masked to randomisation group. The study is registered at ISRCTN (99559262). FINDINGS: We identified and randomised eight CMHS (six in Glasgow and two in Melbourne) comprising 47 care coordinators. We recruited 86 service users between Jan 19 and Aug 8, 2018; 73 were randomised (42 [58%] to EMPOWER and 31 [42%] to treatment as usual). There were 37 (51%) men and 36 (49%) women. At 12 months, main outcomes were collected for 32 (76%) of service users in the EMPOWER group and 30 (97%) of service users in the treatment as usual group. Of those randomised to EMPOWER, 30 (71%) met our a priori criterion of more than 33% adherence to daily monitoring that assumed feasibility. Median time to discontinuation of these participants was 31·5 weeks (SD 14·5). There were 29 adverse events in the EMPOWER group and 25 adverse events in the treatment as usual group. There were 13 app-related adverse events, affecting 11 people, one of which was serious. Fear of relapse was lower in the EMPOWER group than in the treatment as usual group at 12 months (mean difference -7·53 (95% CI -14·45 to 0·60; Cohen's d -0·53). INTERPRETATION: A trial of digital technology to monitor early warning signs blended with peer support and clinical triage to detect and prevent relapse appears to be feasible, safe, and acceptable. A further main trial is merited. FUNDING: UK National Institute for Health Research Health Technology Assessment programme and the Australian National Health and Medical Research Council.