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Interpersonal difficulties are often implicated in the onset of depressive disorders, and typically exacerbate depressive symptoms. This is particularly true for young people, given rapid changes in, and the increased importance of, their social relationships. The purpose of this narrative review was to identify empirically supported interventions that aim to prevent or treat depression in young people by facilitating improvements in their social environment. We conducted a search of controlled trials, systematic reviews and meta-analyses of such interventions, published between 1980 and June 2020. Our literature search and interpretation of results was informed by consultations with clinical experts and youth consumers and advocates. A number of promising approaches were identified with respect to prevention and treatment. Preliminary evidence was identified suggesting that school- and Internet-based approaches present a viable means to prevent the worsening of depressive symptoms in young people. Notably, delivering interpersonal psychotherapy—adolescent skills training (IPT-AST) in schools appears to be a promising early intervention strategy for young people at risk of full-threshold depressive disorder. In terms of treating depressive disorders in young people, there is strong evidence for the efficacy of interpersonal psychotherapy for adolescents (IPT-A), and preliminary evidence in favour of attachment-based family therapy (ABFT). Results are discussed with respect to recommendations for future research and practice.

This study aimed to explore current data collection and feedback practice, in the form of monitoring and evaluation, among youth mental health (YMH) services and healthcare commissioners; and to identify barriers and enablers to this practice. Qualitative semi-structured interviews were conducted via Zoom videoconferencing software. Data collection and analysis were informed by the Theoretical Domains Framework (TDF). Data were deductively coded to the 14 domains of the TDF and inductively coded to generate belief statements. Healthcare commissioning organisations and YMH services in Australia. Twenty staff from healthcare commissioning organisations and twenty staff from YMH services. The umbrella behaviour 'monitoring and evaluation' (ME) can be sub-divided into 10 specific sub-behaviours (e.g. planning and preparing, providing technical assistance, reviewing and interpreting data) performed by healthcare commissioners and YMH services. One hundred belief statements relating to individual, social, or environmental barriers and enablers were generated. Both participant groups articulated a desire to improve the use of ME for quality improvement and had particular interest in understanding the experiences of young people and families. Identified enablers included services and commissioners working in partnership, data literacy (including the ability to set appropriate performance indicators), relational skills, and provision of meaningful feedback. Barriers included data that did not adequately depict service performance, problems with data processes and tools, and the significant burden that data collection places on YMH services with the limited resources they have to do it. Importantly, this study illustrated that the use of ME could be improved. YMH services, healthcare commissioners should collaborate on ME plans and meaningfully involve young people and families where possible. Targets, performance indicators, and outcome measures should explicitly link to YMH service quality improvement; and ME plans should include qualitative data. Streamlined data collection processes will reduce unnecessary burden, and YMH services should have the capability to interrogate their own data and generate reports. Healthcare commissioners should also ensure that they provide meaningful feedback to their commissioned services, and local and national organisations collecting youth mental health data should facilitate the sharing of this data. The results of the study should be used to design theory-informed strategies to improve ME use.

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.

Purpose Use of alcohol and other substances is a multifaceted issue impacting young people across multiple life domains. This paper aims to elucidate patterns of substance use and associated demographic and clinical factors among young people seeking treatment for their mental health. Methods Young people (12–25 years old) were recruited from five youth-specific primary mental health (“ headspace ”) services in Australia. Self-reported substance use and harms in the past 3 months were measured using WHO-ASSIST. Network analyses were conducted to evaluate interrelationships between use and harms associated with different substances. Subgroups were then identified based on whether participants reported using high centrality substances, and associated demographic and clinical factors were assessed with multinomial logistic regression. Results 1107 youth participated. 70% reported use of at least one substance in the past 3 months, with around 30% of those reporting related health, social, legal or financial problems. Network analysis highlighted substantial interconnections between use and harm indicators for all substances, with amphetamine-type stimulants (ATS) and cannabis being high central substances. Higher levels of substance use and harms were reported in subgroups with ATS or cannabis use and different risk factors were associated with these subgroups. Conclusions Findings highlight the importance of screening for substance use in youth primary mental healthcare settings, offering a key opportunity for early intervention. Clinicians should be aware of the inner connections of use and harms of different drugs and the role of cannabis and amphetamine use as a marker for more substance use profiles.

The specific and multifaceted service needs of young people have driven the development of youth-specific integrated primary mental healthcare models, such as the internationally pioneering services in Australia. Although these services were designed for early intervention, they often need to cater for young people with severe conditions and complex needs, creating challenges in service planning and resource allocation. There is, however, a lack of understanding and consensus on the definition of complexity in such clinical settings. This retrospective study involved analysis of 's clinical minimum data set from young people accessing services in Australia between 1 July 2018 and 30 June 2019. Based on consultations with experts, complexity factors were mapped from a range of demographic information, symptom severity, diagnoses, illness stage, primary presenting issues and service engagement patterns. Consensus clustering was used to identify complexity subgroups based on identified factors. Multinomial logistic regression was then used to evaluate whether these complexity subgroups were associated with other risk factors. A total of 81,622 episodes of care from 76,021 young people across 113 services were analysed. Around 20% of young people clustered into a 'high complexity' group, presenting with a variety of complexity factors, including severe disorders, a trauma history and psychosocial impairments. Two moderate complexity groups were identified representing 'distress complexity' and 'psychosocial complexity' (about 20% each). Compared with the 'distress complexity' group, young people in the 'psychosocial complexity' group presented with a higher proportion of education, employment and housing issues in addition to psychological distress, and had lower levels of service engagement. The distribution of complexity profiles also varied across different services. The proposed data-driven complexity model offers valuable insights for clinical planning and resource allocation. The identified groups highlight the importance of adopting a holistic and multidisciplinary approach to address the diverse factors contributing to clinical complexity. The large number of young people presenting with moderate-to-high complexity to early intervention services emphasises the need for systemic change in youth mental healthcare to ensure the availability of appropriate and timely support for all young people.

Summary: 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.

As interest in animal-assisted therapy (AAT) and canine-assisted psychotherapy (CAP) grows, there are increasing calls for the management of related health, safety, and welfare concerns for canines, providers, and clients. Existing health and safety guidelines lack empirical support and are, at times, contradictory. Welfare is increasingly prioritized; however, tools to monitor and manage welfare are underutilized and under-reported. The aim of this study was to provide expert consensus on the minimum health, safety, and welfare standards required to develop and deliver a CAP group program to adolescents experiencing common mental health disorders. Diverse AAT experts were recruited globally. Using Delphi methodology, over two rounds, 40 panelists reached a consensus agreement to include 32 items from a possible 49 into the minimum standards. Health and safety measures included risk assessment, veterinary screening, preventative medicine, training in infection control, and first aid. Welfare measures included training in welfare assessment, documentation of welfare, and flexible, individualized responses to promote wellbeing. Intestinal screening for parasites and the prohibition of raw food were not supported. Flexible and individualized assessment and management of canine welfare were supported over fixed and time-limited work schedules. Clinical practice implications are discussed, and recommendations are made.

Background: Loneliness and social isolation are major public health challenges linked to premature mortality and significant healthcare and productivity costs. However, their geographic distribution and socio-demographic determinants remain poorly understood, with few studies applying spatial methods to identify high-need areas and protective factors. Methods: This study aimed to investigate the geographic distribution and determinants of loneliness and social isolation across Australia using a spatial epidemiological approach. Utilising longitudinal data from the Household, Income and Labour Dynamics in Australia (HILDA) survey, along with Australian Bureau of Statistics (ABS) census data, greenness vegetation index and walkability index, we employed Bayesian conditional autoregressive (CAR) models to assess spatial and temporal patterns at the Statistical Area Level 3 (SA3) over a 22-year period and present the relative risks (RR) and credible intervals (CrI). Results: Our analysis revealed spatial variation in the RR of both loneliness and social isolation, with notable hotspots in socioeconomically disadvantaged areas. In multivariable models, area-level socio-economic disadvantage (as measured by the Index of Relative Socio-economic Advantage and Disadvantage, IRSAD) (RR = 0.8, 95% CrI: 0.76–0.85) for the highest quintile (most advantaged) and a higher prevalence of depression and/or anxiety (RR = 4.3, 95% CrI: 3.0–6.1) were associated independently with relative risk of loneliness but not with age structure, remoteness, green space or walkability index. For social isolation, higher average hospital admission rates per region were the strongest factor. Conclusions: The spatial heterogeneity observed in our study underscores the need for place-based public health responses, including community-based interventions and targeted resource allocation, especially in disadvantaged communities.

BackgroundSubjective cognitive difficulties are common in mental illness and have a negative impact on role functioning. Little is understood about subjective cognition and the longitudinal relationship with depression and anxiety symptoms in young people.AimsTo examine the relationship between changes in levels of depression and anxiety and changes in subjective cognitive functioning over 3 months in help-seeking youth.MethodThis was a cohort study of 656 youth aged 12–25 years attending Australian headspace primary mental health services. Subjective changes in cognitive functioning (rated as better, same, worse) reported after 3 months of treatment was assessed using the Neuropsychological Symptom Self-Report. Multivariate multinomial logistic regression analysis was conducted to evaluate the impact of baseline levels of and changes in depression (nine-item Patient Health Questionnaire; PHQ9) and anxiety symptoms (seven-item Generalised Anxiety Disorder scale; GAD7) on changes in subjective cognitive function at follow-up while controlling for covariates.ResultsWith a one-point reduction in PHQ9 at follow-up, there was an estimated 11–18% increase in ratings of better subjective cognitive functioning at follow-up, relative to stable cognitive functioning. A one-point increase in PHQ9 from baseline to follow-up was associated with 7–14% increase in ratings of worse subjective cognitive functioning over 3 months, relative to stable cognitive functioning. A similar attenuated pattern of findings was observed for the GAD7.ConclusionsA clear association exists between subjective cognitive functioning outcomes and changes in self-reported severity of affective symptoms in young people over the first 3 months of treatment. Understanding the timing and mechanisms of these associations is needed to tailor treatment.

Tobacco smoking is more prevalent among people with mental illnesses, including bipolar disorder, than in the general community. Most data are cross-sectional, and there are no prospective trials examining the relationship of smoking to outcome in bipolar disorder. The impact of tobacco smoking on mental health outcomes was investigated in a 24-month, naturalistic, longitudinal study of 240 people with bipolar disorder or schizoaffective disorder. Participants were interviewed and data recorded by trained study clinicians at 9 interviews during the study period. Comparisons were made between participants who smoked daily (n = 122) and the remaining study participants (n = 117). During the 24-month study period, the daily smokers had poorer scores on the Clinical Global Impressions–Depression ( P = .034) and Clinical Global Impressions–Overall Bipolar ( P = .026) scales and had lengthier stays in hospital ( P = .012), compared with nonsmokers. Smoking status was determined by self-report. Nicotine dependence was not measured. These findings suggest that smoking is associated with poorer mental health outcomes in bipolar and schizoaffective disorder.