Understanding the complexity, patterns, and correlates of alcohol and other substance use among young people seeking help for mental ill-health.

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 Neuropsychological Symptoms Self-Report: psychometric properties in an adolescent and young adult mental health cohort.

BACKGROUND: Subjective cognitive symptoms are common in young people receiving mental health treatment and are associated with poorer outcomes. The aim of this study was to determine the psychometric properties of the Neuropsychological Symptoms Self-Report (NSSR), an eight-item measure recently developed to provide a snapshot of young people's perceived change in cognitive functioning in relation to mental health treatment. METHOD: The sample included 633 youth aged 12-25 years (Mage = 18.2, 66.5% female, 88.6% Australian-born) who had sought mental health treatment in primary headspace services. At three-month follow-up, participants completed the NSSR and self-report measures of depression and anxiety. RESULTS: Excellent internal consistency was found: Cronbach's alpha = 0.93. The NSSR had negative correlations with self-reported anxiety (r = -.33, p < .001) and depression (r = -.48, p < .001) symptoms, suggesting a link with affective symptoms, but still independence of constructs. Exploratory and confirmatory factor analyses supported a single-factor model. Item response theory (IRT) analysis suggested good model fit (homogeneity, data integrity, scalability, local independence and monotonicity) for all items. There was some evidence of measurement noninvariance (for item thresholds) by sex and age, but not diagnosis. IRT models also supported briefer six- and three-item versions of the NSSR. CONCLUSION: In busy clinical practice, clinicians need a rapid and reliable method for determining whether cognitive symptoms are of concern and in need of further assessment and treatment. Study findings support the NSSR as a brief, psychometrically sound measure for assessing subjective cognitive functioning in adolescents and young adults receiving mental health treatment.

Factors affecting the implementation of an outcome measurement feedback system in youth mental health settings.

Objective: Measurement feedback systems provide clinicians with regular snapshots of a client's mental health status, which can be used in treatment planning and client feedback. There are numerous barriers to clinicians using outcome measures routinely. This study aimed to investigate factors affecting the use of a measurement feedback system across youth mental health settings. Methods: The participants were 210 clinicians from headspace youth mental health services across Australia. They were surveyed on predictors and use of MyLifeTracker, a routine outcome measure. This was explored through three processes: looking at MyLifeTracker before session, using MyLifeTracker in treatment planning, and providing feedback of MyLifeTracker scores to clients. Results: Clinicians were more likely to look at MyLifeTracker before session, less likely to use it in treatment planning, and least likely to provide MyLifeTracker scores to clients. Each measurement feedback system process had a distinct group of predictors. Perceptions of MyLifeTracker's practicality was the only significant predictor of all three processes. Conclusion: Practically, organisations and supervisors can increase the use of measurement feedback systems through targeted supports.

Young men's access to community-based mental health care: qualitative analysis of barriers and facilitators.

BACKGROUND: Young men experiencing mental ill health report the lowest rates of professional help-seeking of any demographic group across the lifespan. This phase of life (i.e. adolescence and emerging adulthood) also corresponds to a period of disconnection from healthcare services for young men. AIMS: The present exploratory qualitative study aimed to identify barriers and facilitators to mental health care, as identified by a sample of young help-seeking men and staff involved in mental health service provision. METHOD: Interviews and focus groups were undertaken with 25 young males (mean = 18.80 years, SD = 3.56) and four service providers. Participants were recruited from headspace enhanced primary care early intervention centres in Australia. RESULTS: Thematic analysis indicated four overarching barriers and facilitators. The identified barriers were male role expectations, talk therapy as unknown territory, difficulties navigating the system and intake processes. The identified facilitators were positive initial contact, effective cross-sector partnerships, availability of male practitioners and use of targeted messaging. CONCLUSIONS: Given the ongoing low rates of help-seeking, high rates of suicide and other adverse outcomes for young men, priority research and clinical attention is needed for this group. Recommendations are offered for future research, including suggestions for implementation of targeted strategies addressing gender-based health needs.

Integrated (one-stop shop) youth health care: best available evidence and future directions.

Although mental health problems represent the largest burden of disease in young people, access to mental health care has been poor for this group. Integrated youth health care services have been proposed as an innovative solution. Integrated care joins up physical health, mental health and social care services, ideally in one location, so that a young person receives holistic care in a coordinated way. It can be implemented in a range of ways. A review of the available literature identified a range of studies reporting the results of evaluation research into integrated care services. The best available data indicate that many young people who may not otherwise have sought help are accessing these mental health services, and there are promising outcomes for most in terms of symptomatic and functional recovery. Where evaluated, young people report having benefited from and being highly satisfied with these services. Some young people, such as those with more severe presenting symptoms and those who received fewer treatment sessions, have failed to benefit, indicating a need for further integration with more specialist care. Efforts are underway to articulate the standards and core features to which integrated care services should adhere, as well as to further evaluate outcomes. This will guide the ongoing development of best practice models of service delivery.

Facilitators of recovery for step-up and step-down clients of a sub-acute residential mental health service.

BACKGROUND: Sub-acute residential mental health services provide care for people who are not acutely unwell but require more support than generally available when living in the community. Little is known about how these services facilitate recovery and whether these facilitators differ for clients entering from the community (step-up) or from inpatient settings (step-down). AIM: To identify features of a sub-acute residential service that have assisted step-up and step-down clients in their recovery. METHOD: Semi-structured interviews were conducted with 16 step-up and 21 step-down clients. Interview transcripts were examined using an inductive, semantic content analysis approach. RESULTS: Themes identified included the community context, personal support, the formal program offered and assistance in personal recovery processes, with the level of support for these themes differing for step-up and step-down clients. CONCLUSIONS: Step-up and step-down clients have differing needs to be addressed in a sub-acute service. These services can better meet the needs of clients if they are aware of the setting the client has come from and tailor their services accordingly. Step-up clients prefer support in developing social skills and illness management techniques; step-down clients prefer a less structured environment with assistance in living skills and personal processes of recovery.

Changes in psychological distress and psychosocial functioning in young people visiting headspace centres for mental health problems.

OBJECTIVES: To examine changes in psychological distress and psychosocial functioning in young people presenting to headspace centres across Australia for mental health problems. DESIGN: Analysis of routine data collected from headspace clients who had commenced an episode of care between 1 April 2013 and 31 March 2014, and at 90-day follow-up. PARTICIPANTS: A total of 24 034 people aged 12-25 years who had first presented to one of the 55 fully established headspace centres for mental health problems during the data collection period. MAIN OUTCOME MEASURES: Main reason for presentation, types of therapeutic services provided, Kessler Psychological Distress Scale (K10) scores, and Social and Occupational Functioning Assessment Scale (SOFAS) scores. RESULTS: Most headspace mental health clients presented with symptoms of depression and anxiety and were likely to receive cognitive behaviour therapy (CBT). Younger males were more likely than other age- and sex-defined groups to present for anger and behavioural problems, while younger females were more likely to present for deliberate self-harm. From presentation to last assessment, over one-third of clients had significant improvements in psychological distress (K10) and a similar proportion in psychosocial functioning (SOFAS). Sixty per cent of clients showed significant improvement on one or both measures. CONCLUSIONS: Data regarding outcomes for young people using mental health care services similar to headspace centres are scarce, but the current results compare favourably with those reported overseas, and show positive outcomes for young people using headspace centres.

The services provided to young people through the headspace centres across Australia.

OBJECTIVES: To describe the services provided to young people aged 12-25 years who attend headspace centres across Australia, and how these services are being delivered. DESIGN: A census of headspace clients commencing an episode of care between 1 April 2013 and 31 March 2014. PARTICIPANTS: All young people first attending one of the 55 fully established headspace centres during the data collection period (33,038 young people). MAIN OUTCOME MEASURES: Main reason for presentation, wait time, service type, service provider type, funding stream. RESULTS: Most young people presented for mental health problems and situational problems (such as bullying or relationship problems); most of those who presented for other problems also received mental health care services as needed. Wait time for the first appointment was 2 weeks or less for 80.1% of clients; only 5.3% waited for more than 4 weeks. The main services provided were a mixture of intake and assessment and mental health care, provided mainly by psychologists, intake workers and allied mental health workers. These were generally funded by the headspace grant and the Medicare Benefits Schedule. CONCLUSIONS: headspace centres are providing direct and indirect access to mental health care for young people.

A systematic review of mental health outcome measures for young people aged 12 to 25 years.

BACKGROUND: Mental health outcome measures are used to monitor the quality and effectiveness of mental health services. There is also a growing expectation for implementation of routine measurement and measures being used by clinicians as a feedback monitoring system to improve client outcomes. The recent focus in Australia and elsewhere targeting mental health services to young people aged 12-25 years has meant that outcome measures relevant to this age range are now needed. This is a shift from the traditional divide of child and adolescent services versus adult services with a transitioning age at 18 years. This systematic review is the first to examine mental health outcome measures that are appropriate for the 12 to 25 year age range. METHODS: MEDLINE and PsychINFO databases were systematically searched to identify studies using mental health outcome measures with young people aged 12 to 25 years. The search strategy complied with the relevant sections of the PRISMA statement. RESULTS: A total of 184 published articles were identified, covering 29 different outcome measures. The measures were organised into domains that consisted of eight measures of cognition and emotion, nine functioning measures, six quality of life measures, and six multidimensional mental health measures. No measures were designed specifically for young people aged 12 to 25 years and only two had been used by clinicians as a feedback monitoring system. Five measures had been used across the whole 12 to 25 year age range, in a range of mental health settings and were deemed most appropriate for this age group. CONCLUSIONS: With changes to mental health service systems that increasingly focus on early intervention in adolescence and young adulthood, there is a need for outcome measures designed specifically for those aged 12 to 25 years. In particular, multidimensional measures that are clinically meaningful need to be developed to ensure quality and effectiveness in youth mental health. Additionally, outcome measures can be clinically useful when designed to be used within routine feedback monitoring systems.

Social influences on seeking help from mental health services, in-person and online, during adolescence and young adulthood.

BACKGROUND: This study provides the first comprehensive empirical evidence of developmental changes in the social influences on seeking mental health care, both in-person and online, during the critical lifestages for mental health of adolescence and young adulthood. METHODS: Main source of help-seeking influence was determined via self-report for all young people accessing youth-targeted mental health services in Australia for a first episode of care over a 12 month period during 2013. This comprised 30,839 young people who accessed in-person services and 7,155 clients of the online service. RESULTS: Results show a major developmental shift in help-seeking influence across the age range, which varied for males and females, and a striking difference between the online and in-person service modalities. The dominant influence online, regardless of age, was the young person themself. In contrast, for in-person services, the dominant influence during adolescence was family, but this changed markedly in late adolescence to favour self-influence, with a lessor, but still substantial effect of family. The influence of friends was surprisingly low. CONCLUSIONS: To support young people with mental health problems to access mental health care, the personal connection of parents and family needs to be engaged to encourage in-person service use through better mental health literacy, particularly for adolescents. In the online environment, ways to ensure that young people themselves are guided to appropriate services are required.

headspace - Australia's innovation in youth mental health: who are the clients and why are they presenting?

OBJECTIVES: To provide the first national profile of the characteristics of young people (aged 12-25 years) accessing headspace centre services - the Australian Government's innovation in youth mental health service delivery - and investigate whether headspace is providing early service access for adolescents and young adults with emerging mental health problems. DESIGN AND PARTICIPANTS: Census of all young people accessing a headspace centre across the national network of 55 centres comprising a total of 21 274 headspace clients between 1 January and 30 June 2013. MAIN OUTCOME MEASURES: Reason for presentation, Kessler Psychological Distress Scale, stage of illness, diagnosis, functioning. RESULTS: Young people were most likely to present with mood and anxiety symptoms and disorders, self-reporting their reason for attendance as problems with how they felt. Client demographic characteristics tended to reflect population-level distributions, although clients from regional areas and of Aboriginal and Torres Strait Islander background were particularly well represented, whereas those who were born outside Australia were underrepresented. CONCLUSION: headspace centres are providing a point of service access for young Australians with high levels of psychological distress and need for care in the early stages of the development of mental disorder.

Capturing the clinical complexity in young people presenting to primary mental health services: a data-driven approach.

AIMS: 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 headspace 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. METHODS: This retrospective study involved analysis of headspace'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. RESULTS: 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 headspace services. CONCLUSIONS: 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 headspace 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.

The effect of survey administration mode on youth mental health measures: Social desirability bias and sensitive questions.

Aim: Research on trends in youth mental health is used to inform government policy and service funding decisions. It often uses interviewer-administered surveys, which may be affected by mode effects related to social desirability bias. This study sought to determine the impact of survey administration mode on mental health measures, comparing mode effects for sensitive mental health measures (psychological distress and wellbeing) and non-sensitive (physical activity) measures. Methods: Data were from two large national community samples of young Australians aged 12-25 years conducted in 2020 (N = 6238) and 2022 (N = 4122), which used both interviewer-administered and self-report modes of data collection. Results: Results showed participants reported lower psychological distress and higher wellbeing in the interviewer-assisted compared with the self-report mode. No mode effects were found for the non-sensitive physical activity measures. No interaction between mode and gender was found, but an age group by mode interaction revealed that those in the 18-21 and 22-25-year age groups were more strongly affected than younger adolescents. Conclusions: These findings suggest underestimates of mental health issues from interview survey formats, particularly for young adults. The results show how even a weak mode effect can have a large impact on mental health prevalence indicators. Researchers and policy makers need to be aware of the impact social desirability bias can have on mental health measures and consider taking steps to mitigate this effect.

Development and Validation of a Routine Session-by-Session Experience Measure for Youth Mental Health Services: My Youth Mental Health Session Experience (MySE).

Purpose: The 'My youth mental health Session Experience' (MySE) measure was developed by headspace, Australia's National Youth Mental Health Foundation, in collaboration with young people, for use as a routine session experience measure across its national centre service network. The measure fills a gap in measures needed to implement measurement-informed care in youth mental health care. Participants and Methods: Routinely collected data from 37,201 young people aged 12 to 25 years who commenced an episode of care at one of the 150 headspace centres between 1 July 2021 and 30 June 2022 were used to validate the five-item measure. Results: MySE demonstrated high internal consistency invariant over age and gender groups. There was one latent factor of session experience that all MySE items relate to, although this factor does not adequately capture all the information present in the individual items. A significant age effect showed that young adults reported more positive session experiences than adolescents. Conclusion: MySE demonstrated strong psychometric properties and is suitable for use in youth mental health care as a routine session-by-session experience measure. Such measures are needed to routinely inform clinicians of how young people are experiencing their treatment sessions, thereby contributing to better retention, engagement, and client outcomes through measurement-informed care.

Structured data vs. unstructured data in machine learning prediction models for suicidal behaviors: A systematic review and meta-analysis.

Suicide remains a leading cause of preventable death worldwide, despite advances in research and decreases in mental health stigma through government health campaigns. Machine learning (ML), a type of artificial intelligence (AI), is the use of algorithms to simulate and imitate human cognition. Given the lack of improvement in clinician-based suicide prediction over time, advancements in technology have allowed for novel approaches to predicting suicide risk. This systematic review and meta-analysis aimed to synthesize current research regarding data sources in ML prediction of suicide risk, incorporating and comparing outcomes between structured data (human interpretable such as psychometric instruments) and unstructured data (only machine interpretable such as electronic health records). Online databases and gray literature were searched for studies relating to ML and suicide risk prediction. There were 31 eligible studies. The outcome for all studies combined was AUC = 0.860, structured data showed AUC = 0.873, and unstructured data was calculated at AUC = 0.866. There was substantial heterogeneity between the studies, the sources of which were unable to be defined. The studies showed good accuracy levels in the prediction of suicide risk behavior overall. Structured data and unstructured data also showed similar outcome accuracy according to meta-analysis, despite different volumes and types of input data.

Strengthening assessment and response to mental health needs for Aboriginal and Torres Strait Islander children and adolescents in primary care settings: study protocol for the Ngalaiya Boorai Gabara Budbut implementation project.

INTRODUCTION: Opportunities for improved mental health and wellbeing of Aboriginal and Torres Strait Islander children and young people lie in improving the capability of primary healthcare services to identify mental healthcare needs and respond in timely and appropriate ways. The development of culturally appropriate mental health assessment tools and clinical pathways have been identified as opportunities for strengthening workforce capacity in this area. The Ngalaiya Boorai Gabara Budbut implementation project seeks to pursue these opportunities by developing and validating a psychosocial assessment tool, understanding what services need to better care for your people and developing resources that address those needs. METHODS AND ANALYSIS: The project will be governed by a research governance group comprising Aboriginal service providers, young people, and researchers. It will be implemented in an urban health service in Canberra, and regional services in Moree, Wollongong, and the Illawarra regions of New South Wales Australia. The validation study will follow an argument-based approach, assessing cultural appropriateness and ease of use; test-retest validity; internal consistency, construct validity and the quality of decisions made based on the assessment. Following piloting with a small group of young people and their caregivers (n=10), participants (n=200) will be young people and/or their caregivers, attending one of the partner services. The needs assessment will involve an in-depth exploration of service via an online survey (n=60) and in-depth interviews with service providers (n=16) and young people (n=16). These activities will run concurrently. Service providers, researchers and the governance group will codesign resources that respond to the needs identified and pilot them through the participating services. ETHICS AND DISSEMINATION: The Aboriginal Health and Medical Research Council of NSW Human Research Ethics committee (#1769/21) has approved this project. Informed consent will be obtained from all participants and/or their caregivers (with assent from those aged <16 years) prior to participating in all aspects of the study. Research dissemination will occur through participating health services, academic journal articles and conference presentations.

Consumer Perspectives on the Use of Artificial Intelligence Technology and Automation in Crisis Support Services: Mixed Methods Study.

BACKGROUND: Emerging technologies, such as artificial intelligence (AI), have the potential to enhance service responsiveness and quality, improve reach to underserved groups, and help address the lack of workforce capacity in health and mental health care. However, little research has been conducted on the acceptability of AI, particularly in mental health and crisis support, and how this may inform the development of responsible and responsive innovation in the area. OBJECTIVE: This study aims to explore the level of support for the use of technology and automation, such as AI, in Lifeline's crisis support services in Australia; the likelihood of service use if technology and automation were implemented; the impact of demographic characteristics on the level of support and likelihood of service use; and reasons for not using Lifeline's crisis support services if technology and automation were implemented in the future. METHODS: A mixed methods study involving a computer-assisted telephone interview and a web-based survey was undertaken from 2019 to 2020 to explore expectations and anticipated outcomes of Lifeline's crisis support services in a nationally representative community sample (n=1300) and a Lifeline help-seeker sample (n=553). Participants were aged between 18 and 93 years. Quantitative descriptive analysis, binary logistic regression models, and qualitative thematic analysis were conducted to address the research objectives. RESULTS: One-third of the community and help-seeker participants did not support the collection of information about service users through technology and automation (ie, via AI), and approximately half of the participants reported that they would be less likely to use the service if automation was introduced. Significant demographic differences were observed between the community and help-seeker samples. Of the demographics, only older age predicted being less likely to endorse technology and automation to tailor Lifeline's crisis support service and use such services (odds ratio 1.48-1.66, 99% CI 1.03-2.38; P<.001 to P=.005). The most common reason for reluctance, reported by both samples, was that respondents wanted to speak to a real person, assuming that human counselors would be replaced by automated robots or machine services. CONCLUSIONS: Although Lifeline plans to always have a real person providing crisis support, help-seekers automatically fear this will not be the case if new technology and automation such as AI are introduced. Consequently, incorporating innovative use of technology to improve help-seeker outcomes in such services will require careful messaging and assurance that the human connection will continue.

Community expectations and anticipated outcomes for crisis support services-Lifeline Australia.

Crisis lines provide a critical first line of mental wellbeing support for community members in distress. Given the increasing referral to such services, there is a need to understand what the expectations of the community are around the role of such services in our public health responses. A computer assisted telephone interview was undertaken between 28th October and 30th November 2019. The aim was to explore expectations and anticipated outcomes of Lifeline Australia's crisis support services from a nationally representative community sample (N = 1,300). Analysis was undertaken to determine if demographic variables (age, gender, indigenous status, country of birth, culturally and linguistically diverse (CALD) status, sexual orientation, household composition, region and State/territory) and past service use affected community expectations. Results showed that a majority of respondents expected Lifeline to listen and provide support, recommend other services, and provide information. Help-seekers were expected to feel heard and listened to, receive safety advice or support to stay safe, and feel more hopeful. Lifeline was expected to prioritise people feeling suicidal, in immediate personal crisis, and experiencing domestic violence. Findings reveal that community members hold expectations for Lifeline Australia to serve as a suicide prevention and general crisis support service, which are congruent with the service's aims. There was little variation in community expectations of crisis support services based on demographic factors and past service use. The results show that the community has extensive and diverse expectations for this national crisis service to meet both short and longer-term needs for all vulnerable members of the community-entailing a very substantial public health service responsibility.