A systematic review of effective local, community or peer-delivered interventions to improve well-being and employment in regional, rural and remote areas of Australia.

OBJECTIVE: To systematically review evaluated local, community or peer-delivered well-being and employment interventions delivered within regional, rural and remote Australia. DESIGN: Searches within nine databases retrieved peer-reviewed and grey literature from an initial pool of 3186 papers published between 2012 and 2022. PRISMA guidelines were adhered to, and the Mixed Methods Appraisal Tool (MMAT) was used to assess the quality of the well-being or employment (or both) articles. FINDINGS: A total of 19 items met the inclusion criteria, which included two quantitative, 12 qualitative and five mixed-methods evaluations. Intervention cohorts included Indigenous Australians, youth, older people, workers and the general community. The average methodological rating was 83%. The overall level of evidence for the interventions was low due to mostly descriptive studies. DISCUSSION: Interventions that appeared effective in improving well-being tended to focus on addressing social connectedness and self-determination. Unexpected employment outcomes were evident across many of the studies, which highlighted the reciprocity between well-being and employment. CONCLUSION: This review highlights promising interventions for improving well-being by focusing on social connectedness and self-determination. Further empirical evidence is encouraged to explore the reciprocal relationship between well-being and employment, emphasising the significance of social connectedness and self-determination in this context.

FLP: Factor lattice pattern-based automated detection of Parkinson's disease and specific language impairment using recorded speech.

BACKGROUND: Timely detection of neurodevelopmental and neurological conditions is crucial for early intervention. Specific Language Impairment (SLI) in children and Parkinson's disease (PD) manifests in speech disturbances that may be exploited for diagnostic screening using recorded speech signals. We were motivated to develop an accurate yet computationally lightweight model for speech-based detection of SLI and PD, employing novel feature engineering techniques to mimic the adaptable dynamic weight assignment network capability of deep learning architectures. MATERIALS AND METHODS: In this research, we have introduced an advanced feature engineering model incorporating a novel feature extraction function, the Factor Lattice Pattern (FLP), which is a quantum-inspired method and uses a superposition-like mechanism, making it dynamic in nature. The FLP encompasses eight distinct patterns, from which the most appropriate pattern was discerned based on the data structure. Through the implementation of the FLP, we automatically extracted signal-specific textural features. Additionally, we developed a new feature engineering model to assess the efficacy of the FLP. This model is self-organizing, producing nine potential results and subsequently choosing the optimal one. Our speech classification framework consists of (1) feature extraction using the proposed FLP and a statistical feature extractor; (2) feature selection employing iterative neighborhood component analysis and an intersection-based feature selector; (3) classification via support vector machine and k-nearest neighbors; and (4) outcome determination using combinational majority voting to select the most favorable results. RESULTS: To validate the classification capabilities of our proposed feature engineering model, designed to automatically detect PD and SLI, we employed three speech datasets of PD and SLI patients. Our presented FLP-centric model achieved classification accuracy of more than 95% and 99.79% for all PD and SLI datasets, respectively. CONCLUSIONS: Our results indicate that the proposed model is an accurate alternative to deep learning models in classifying neurological conditions using speech signals.

Automated anxiety detection using probabilistic binary pattern with ECG signals.

BACKGROUND AND AIM: Anxiety disorder is common; early diagnosis is crucial for management. Anxiety can induce physiological changes in the brain and heart. We aimed to develop an efficient and accurate handcrafted feature engineering model for automated anxiety detection using ECG signals. MATERIALS AND METHODS: We studied open-access electrocardiography (ECG) data of 19 subjects collected via wearable sensors while they were shown videos that might induce anxiety. Using the Hamilton Anxiety Rating Scale, subjects are categorized into normal, light anxiety, moderate anxiety, and severe anxiety groups. ECGs were divided into non-overlapping 4- (Case 1), 5- (Case 2), and 6-second (Case 3) segments for analysis. We proposed a self-organized dynamic pattern-based feature extraction function-probabilistic binary pattern (PBP)-in which patterns within the function were determined by the probabilities of the input signal-dependent values. This was combined with tunable q-factor wavelet transform to facilitate multileveled generation of feature vectors in both spatial and frequency domains. Neighborhood component analysis and Chi2 functions were used to select features and reduce data dimensionality. Shallow k-nearest neighbors and support vector machine classifiers were used to calculate four (=2 × 2) classifier-wise results per input signal. From the latter, novel self-organized combinational majority voting was applied to calculate an additional five voted results. The optimal final model outcome was chosen from among the nine (classifier-wise and voted) results using a greedy algorithm. RESULTS: Our model achieved classification accuracies of over 98.5 % for all three cases. Ablation studies confirmed the incremental accuracy of PBP-based feature engineering over traditional local binary pattern feature extraction. CONCLUSIONS: The results demonstrated the feasibility and accuracy of our PBP-based feature engineering model for anxiety classification using ECG signals.

Co-designing a digital mental health platform, "Momentum", with young people aged 7-17: A qualitative study.

Introduction: Digital mental health interventions (DMHIs) offer a promising alternative or adjunct treatment method to face-to-face treatment, overcoming barriers associated with stigma, access, and cost. This project is embedded in user experience and co-design to enhance the potential acceptability, usability and integration of digital platforms into youth mental health services. Objective: To co-design a digital mental health platform that provides self-directed, tailored, and modularised treatment for young people aged 7-17 years experiencing anxiety, depression and other related problems. Methods: Sixty-eight participants, aged 7-17 years, engaged in one of 20 co-design workshops. Eight workshops involved children (n = 26, m = 9.42 years, sd = 1.27) and 12 involved adolescents (n = 42, m = 14.57 years, sd = 1.89). Participants engaged in a variety of co-design activities (e.g., designing a website home page and rating self-report assessment features). Workshop transcripts and artefacts (e.g., participants' drawings) were thematically analysed using Gale et al.'s Framework Method in NVivo. Results: Six themes were identified: Interactive; Relatable; Customisable; Intuitive; Inclusive; and Personalised, transparent and trustworthy content. The analysis revealed differences between children's and adolescents' designs and ideas, supporting the need for two different versions of the platform, with age-appropriate activities, features, terminology, and content. Conclusions: This research showcased co-design as a powerful tool to facilitate collaboration with young people in designing DMHIs. Two sets of recommendations were produced: 1) recommendations for the design, functionality, and content of youth DMHIs, supported by child- and adolescent-designed strategies; and 2) recommendations for clinicians and researchers planning to conduct co-design and intervention development research with children and adolescents.

Stepped-care versus therapist-guided, internet-based cognitive behaviour therapy for childhood and adolescent anxiety: A non-inferiority trial.

Objective: This preregistered randomized trial examined whether a stepped-care approach to internet-delivered cognitive behaviour therapy (ICBT-SC) is non-inferior to therapist-guided ICBT (ICBT-TG) for child and adolescent anxiety. Method: Participants were 137 Australians, aged 8-17 years (56 male), with a primary anxiety disorder. This randomized, non-inferiority trial compared ICBT-SC to an evidence-based, ICBT-TG program with assessments conducted at baseline, 12 weeks and 9-months after treatment commencement. All ICBT-SC participants completed the first 5 online sessions without therapist guidance. If they responded to treatment in the first 5 sessions (defined as reductions of anxiety symptoms into non-clinical range), they continued without therapist guidance for the final 5 sessions. If they did not respond to treatment in the first 5 sessions, the final five sessions were supplemented with therapist-guidance (through email). All ICBT-TG participants received therapist guidance (email) after each session, for all 10 sessions. Measures included clinical diagnostic interview (severity rating as primary outcome), as well as parent and child reported anxiety and anxiety-related interference (secondary outcomes). Results: ICBT-SC was found to be non-inferior to ICBT-TG on primary and secondary outcomes, according to clinician, parent and young person report at 12-weeks and 9-months. Treatment satisfaction was moderate to high for both conditions. Significant clinical benefits were evident for participants in both treatments. Of participants who remained in the study, 77 % (50.7 % ITT) of ICBT-SC and 77 % (57.1 % ITT) of ICBT-TG were free of their primary anxiety diagnosis by 9-month follow-up, with no differences between conditions. Conclusion: A stepped-care ICBT approach for clinically anxious children and adolescents may offer an acceptable treatment model that can increase access to evidence-based treatment.

Deep neural network technique for automated detection of ADHD and CD using ECG signal.

BACKGROUND AND OBJECTIVE: Attention Deficit Hyperactivity problem (ADHD) is a common neurodevelopment problem in children and adolescents that can lead to long-term challenges in life outcomes if left untreated. Also, ADHD is frequently associated with Conduct Disorder (CD), and multiple research have found similarities in clinical signs and behavioral symptoms between both diseases, making differentiation between ADHD, ADHD comorbid with CD (ADHD+CD), and CD a subjective diagnosis. Therefore, the goal of this pilot study is to create the first explainable deep learning (DL) model for objective ECG-based ADHD/CD diagnosis as having an objective biomarker may improve diagnostic accuracy. METHODS: The dataset used in this study consist of ECG data collected from 45 ADHD, 62 ADHD+CD, and 16 CD patients at the Child Guidance Clinic in Singapore. The ECG data were segmented into 2 s epochs and directly used to train our 1-dimensional (1D) convolutional neural network (CNN) model. RESULTS: The proposed model yielded 96.04% classification accuracy, 96.26% precision, 95.99% sensitivity, and 96.11% F1-score. The Gradient-weighted class activation mapping (Grad-CAM) function was also used to highlight the important ECG characteristics at specific time points that most impact the classification score. CONCLUSION: In addition to achieving model performance results with our suggested DL method, Grad-CAM's implementation also offers vital temporal data that clinicians and other mental healthcare professionals can use to make wise medical judgments. We hope that by conducting this pilot study, we will be able to encourage larger-scale research with a larger biosignal dataset. Hence allowing biosignal-based computer-aided diagnostic (CAD) tools to be implemented in healthcare and ambulatory settings, as ECG can be easily obtained via wearable devices such as smartwatches.

An exploration of trolling behaviours in Australian adolescents: An online survey.

To understand why people "troll" (i.e., engage in disruptive online behaviour intended to provoke and distress for one's own amusement), researchers have explored a range of individual differences. These studies have primarily been conducted in adult samples, despite adolescents being a particularly vulnerable group with regards to both being trolled and trolling others. In this study we aimed to (1) explore Australian adolescents' experiences of trolling, and (2) replicate adult research that has constructed a psychological profile of the Internet troll by examining the utility of personality traits (psychopathy and sadism), self-esteem, empathy (cognitive and affective), and social rewards (negative social potency) to predict adolescents' trolling behaviours. A sample of 157 Australian adolescents (40.8% male, 58% female, 0.6% non-binary) aged 13-18 years (M = 15.58, SD = 1.71) completed the Global Assessment of Internet Trolling-Revised, Adolescent Measure of Empathy and Sympathy, Rosenberg Self-Esteem Scale, Youth Psychopathy Traits Inventory-Short Version, Social Rewards Questionnaire, Short Sadistic Impulse Scale, and a series of questions related to the experience of trolling. Results showed in the past year, 24.2% of Australian adolescents reported being trolled and 13.4% reported having trolled others. Gender, psychopathy, sadism, self-esteem, cognitive empathy, affective empathy, and "negative social potency" (i.e., enjoyment of antisocial rewards) combined, explained 30.7% of variance in adolescents' trolling behaviours (p < .001). When accounting for shared variance, gender (male), high psychopathy, and high negative social potency were significant predictors of trolling, aligning with findings of adult samples. Contrary to adult samples, sadism was not a unique predictor of adolescents' trolling. For adolescents, the variance in trolling explained by sadism was nonsignificant when controlling for negative social potency. These similarities, and differences, in predictors of trolling across adult and adolescent samples may play a critical role in the development of targeted interventions to prevent or manage trolling.

Short Research Article: Changes in life functioning in a self-help, online program for child and adolescent anxiety.

BACKGROUND: Anxiety-related functional impairment, as reflected by life interference, is a lesser explored but highly relevant treatment outcome, and it is crucial that it be included and examined in the evaluation of treatment outcomes of internet-delivered Cognitive Behavioural Therapy (iCBT). METHODS: This single group, pre-post study examined changes in life interference and anxiety symptoms in a sample of children (n = 1198; mean age 9.66 years) and adolescents (n = 721; mean age 13.66 years) participating in the BRAVE Self-Help program in Australia. RESULTS: Results demonstrated that both children and adolescents showed improvements in anxiety symptoms, with effect sizes ranging from ηp 2  = .194-.318. Reductions in life interference were evident for children (ηp 2  = .008-.044), particularly later in the programme, but adolescents did not show such effects. Adolescents in the low completer group (completing 3-5 sessions) showed increases in at-home interference (ηp 2  = .038). CONCLUSIONS: Adolescents in particular may require more sessions before entrenched life interference, such as that resulting from avoidance behaviours, can be overcome.

Mental health symptoms in children and adolescents during COVID-19 in Australia.

OBJECTIVE: COVID-19 has led to disruptions to the lives of Australian families through social distancing, school closures, a temporary move to home-based online learning, and effective lockdown. Understanding the effects on child and adolescent mental health is important to inform policies to support communities as they continue to face the pandemic and future crises. This paper sought to report on mental health symptoms in Australian children and adolescents during the initial stages of the pandemic (May to November 2020) and to examine their association with child/family characteristics and exposure to the broad COVID-19 environment. METHODS: An online baseline survey was completed by 1327 parents and carers of Australian children aged 4 to 17 years. Parents/carers reported on their child's mental health using five measures, including emotional symptoms, conduct problems, hyperactivity/inattention, anxiety symptoms and depressive symptoms. Child/family characteristics and COVID-related variables were measured. RESULTS: Overall, 30.5%, 26.3% and 9.5% of our sample scored in the high to very high range for emotional symptoms, conduct problems and hyperactivity/inattention, respectively. Similarly, 20.2% and 20.4% of our sample scored in the clinical range for anxiety symptoms and depressive symptoms, respectively. A child's pre-existing mental health diagnosis, neurodevelopmental condition and chronic illness significantly predicted parent-reported child and adolescent mental health symptoms. Parental mental health symptoms, having a close contact with COVID-19 and applying for government financial assistance during COVID-19, were significantly associated with child and adolescent mental health symptoms. CONCLUSION: Our findings show that Australian children and adolescents experienced considerable levels of mental health symptoms during the initial phase of COVID-19. This highlights the need for targeted and effective support for affected youth, particularly for those with pre-existing vulnerabilities.

Psychometric Evaluation of a New Digitally Animated Child Self-Report Assessment Instrument: The Interactive Child Distress Screener.

The present study aimed to provide the first psychometric evaluation of the newly developed, digitally animated assessment instrument: the Interactive Child Distress Screener (ICDS). The latent factor structure of the novel ICDS was first established using exploratory factor analysis (EFA) on 15 pairs of animated items using a community sample (N = 266) of child-parent dyads. EFA results support a two-factor structure representing two broad domains of internalizing and externalizing difficulties (r = .52) and comprised 12 items. The reliability of the factors was strong with ordinal alpha and omega coefficients above .84 and .87, respectively, for each of the subscales. Convergent validity for the overall sample was supported with established child and parent-reported measures of internalizing and externalizing problems; however, the ICDS factors demonstrated convergence greater in magnitude with other child-reported measures such as the Me and My School Survey. Satisfaction and utility ratings by children indicated that the digital format was highly acceptable.

Survivorship care plans and information for rural cancer survivors.

PURPOSE: The purpose of the study was to investigate the amount and type of survivorship care information received by cancer survivors living in rural Australia and whether this varies according to demographic factors or cancer type. METHODS: Self-reported receipt of a survivorship care plan (SCP) and information on various aspects of survivorship care (e.g., managing side effects, healthy lifestyles, psychosocial advice and monitoring for recurrence) were collected from 215 cancer survivors who had returned home to a rural area in Queensland Australia after receiving cancer treatment in a major city within the previous 5 years (72% in the previous 12 months). Logistic regression was used to assess for differences across demographic factors and cancer type. RESULTS: Only 35% of participants reported receiving a SCP and proportions of those reporting the receipt of specific information varied from 74% for information on short-term side effects to less than 30% for information on finances, chemoprevention and monitoring for signs of recurrence. No significant differences were found in the receipt of survivorship care information across demographic factors or cancer type. CONCLUSIONS: Findings suggest that cancer survivors living in rural areas are not consistently provided with adequate survivorship care information, particularly that pertaining to long-term health and recovery. IMPLICATIONS FOR CANCER SURVIVORS: Without improved systems for delivering survivorship care information to patients returning home to rural communities after treatment, these cancer survivors risk missing out on necessary information and advice to maintain their health, wellbeing and long-term recovery.

Inequity in psychiatric healthcare use in Australia.

BACKGROUND: Despite recent substantial mental healthcare reforms to increase the supply of healthcare, mental health inequality in Australia is rising. Understanding of the level of inequity (unmet need gap) in psychiatric service use in Australia's mixed public-private health care system is lacking. OBJECTIVE: To present a novel method to measure inequity in the delivery of psychiatric care. METHODS: Data came from wave 9 (year 2009, n = 11,563) and wave 17 (year 2017, n = 16,194) of the Household, Income and Labour Dynamics in Australia (HILDA) survey. Multiple logistic regression was employed to estimate the psychiatric care utilisation compared to its need and the Gini index was used to estimate the standardised distribution of utilisation to measure the extent of inequity. RESULTS: The results show the inequity indices (need-standardised Gini) in psychiatric care utilisation were significant and found to be 0.066 and 0.096 in 2009 and 2017, respectively, for all individuals. In 2009, the inequity indices were found to be 0.051 and 0.078 for males and females, respectively, and 0.045 and 0.068 for rural and urban residents, respectively. In 2017, the indices were calculated to be 0.081 and 0.109 for males and females, respectively, and 0.086 and 0.097 for rural and urban residents, respectively. CONCLUSIONS: This study showed a marked increase in unmet needs in psychiatric care utilisation since 2009. There is a greater need to develop policies to improve equity in psychiatric care utilisation in Australia.

A thematic analysis of the personal factors influencing mental health help-seeking in farmers.

PURPOSE: It is crucial to understand the micro-level personal factors that impact farmer mental health help-seeking, given that farmers are at increased risk of suicide yet show reduced mental health help-seeking behaviors. METHODS: Ten farmers, 10 farmers' partners, and 8 general practitioners (ie, family physicians) from Australia completed qualitative semi-structured interviews. Braun and Clarke's method of thematic analysis was used to analyze the data. FINDINGS: The analysis resulted in 4 themes: "mental health literacy," "stigma of mental illness and help-seeking," "support, the partners' role in help-seeking," and "the intersectionality between being a farmer, age, and gender." Farmers' knowledge and understanding of mental health and treatments was varied. Stigma was reported to be reducing, but still present toward both mental illness and mental health help-seeking. Support from a partner was reported to facilitate help-seeking if delivered tactfully. Lastly, being older and male were reported to negatively impact farmer mental health help-seeking. CONCLUSION: The findings contribute to understanding farmer mental health help-seeking and could inform quantitative research and the development and implementation of interventions to promote mental health help-seeking in this group.

Support-seeking by cancer caregivers living in rural Australia.

OBJECTIVE: Rural cancer caregivers report poor wellbeing and high unmet needs for support. This study investigates sources of support sought by cancer caregivers living in rural Australia, and factors associated with support-seeking. METHODS: Informal caregivers of people with cancer completed a questionnaire assessing sociodemographic characteristics, caregiver factors and support-seeking. Descriptive statistics, bivariate analyses and logistic regression were used to identify common sources of support and factors associated with support-seeking. Alluvial and radar plots were used to identify and describe support-seeking profiles. FINDINGS: Of 244 rural caregivers, 64% reported seeking support for themselves, 72% for the cancer patient, and 22% did not seek any support. The most common sources of support were general practitioners and online. Higher caregiver burden, higher income, caring for someone with anxiety/depression or caring for someone who has difficulty completing their usual activities were associated with seeking support from a greater number of sources. The 'No support-seekers' profile had the highest proportions of caregivers who were male, caring for someone <12 months post-diagnosis and lower income earners. CONCLUSIONS: Many rural caregivers seek support for themselves and the cancer patient, commonly from medical and online sources. IMPLICATIONS FOR PUBLIC HEALTH: Further work may be needed to reduce caregiver burden and support caregivers who are male, caring for someone recently diagnosed, and those with lower incomes.

Understanding parent perspectives on engagement with online youth-focused mental health programs.

OBJECTIVE: Online youth-focused health programs often include parent modules-that equip parents with skills to assist their child in improving their health-alongside youth-specific content. BRAVE Self-Help, an evidence-based program designed for children and teenagers with early signs of anxiety, is a popular Australian program that includes six parent modules. Despite its popularity and proven efficacy, BRAVE Self-Help shares the same challenge as many online self-help programs-that of low participant engagement. Using parents registered in BRAVE Self-Help as 'information rich' participants, we explored (a) factors that influenced parent engagement in online health programs, and (b) their recommendations for enhancing parent engagement. DESIGN AND OUTCOME MEASURE: We conducted semi-structured interviews with 14 parents registered in BRAVE Self-Help. Data were analysed through reflexive thematic analysis. RESULTS: Social-, family- and program-related factors drove parents' program engagement and recommendations. Social sub-themes related to the benefits of professional and community support in promoting more engagement. Family sub-themes included difficulties with program engagement due to competing priorities, perceptions that condition severity influenced engagement, and feelings that previously-acquired health knowledge reduced motivation to engage. Program sub-themes included perceived usefulness and ease-of-use. CONCLUSION: Program designers could target support systems, include flexible delivery options, and use iterative design processes to enhance parent engagement.

Transition approaches for autistic young adults: A case series study.

The aim of this study was to evaluate the experience of autistic young adults aged 18 to 25 years old over a 12-month transition period from 2016 to 2017. Data was collected through a longitudinal repeated measures case series design with assessments conducted at 2 time points, at baseline then 12 months later. Assessments included self-report evaluations of transition planning and intervention received at high school, engagement in post-secondary education and access to employment, living circumstances, and social support. Examination of 9 cases showed family and social support was an important facilitator of successful transition whilst low independence was a risk factor associated with unsuccessful transition. In-depth analysis of cases showed a lack of engagement in post-secondary education and unemployment were associated with poor quality of life whilst skills development, work experience placements, and support from service providers were associated with improved quality of life. Implications of the findings highlight the need for educational and socially inclusive interventions to support the heterogeneity in individual, social, communication, and behavioural challenges in autistic young adults.

Do family and maternal background matter? A multilevel approach to modelling mental health status of Australian youth using longitudinal data.

PURPOSE: Most previous research place great importance on the influence of family and maternal background on child and adolescents' mental health. However, age of onset studies indicates that the majority of the mental health disease prevalence occurs during the youth years. This study investigates the relationship of family and maternal background, as well as individual circumstance on youth mental health status. METHOD: Data from 975 participants and 4632 observations of aged cohort 15 to 19 years in the Household, Income and Labour Dynamics in Australia (HILDA) longitudinal study were followed for 10 years (2007-2017). Multilevel logistic regression models were used to analyse the impact of youth circumstances on mental health status. RESULTS: The findings suggests that not all dimensions of family and maternal background (especially maternal education) have impacts on youth mental health. We found low household income (AOR: 1.572, 95% CI: 1.017-2.43) and adverse living arrangement (AOR: 1.586, 95% CI: 1.097-2.294) significantly increases mental disorder odds whereas maternal education or occupation fixed effects were not significant. Individual level circumstances have much stronger impact on youth mental health. We found financial shock (AOR: 1.412, 95% CI: 1.277-1.561), life event shock (AOR: 1.157, 95% CI: 1.01-1.326), long term health conditions (AOR: 2.855, 95% CI: 2.042-3.99), smoking (AOR: 1.676, 95% CI: 1.162-2.416), drinking (AOR: 1.649, 95% CI: 1.286-2.114) and being female (AOR: 2.021, 95% CI: 1.431-2.851) have significant deteriorating effects on youth mental health. CONCLUSIONS: Our finding is in contrast to the majority of studies in the literature which give a preeminent role to maternal characteristics in child and youth mental health status. Mental health interventions should consider heterogeneity of adverse youth circumstances and health-related behaviours.

Cost-effectiveness analysis of paediatric mental health interventions: a systematic review of model-based economic evaluations.

Mental health disorders among children and youth are causing significant burden on health care systems. Hence, identifying cost-effective interventions is important for effective mental health care allocation. Although model-based economic evaluations are an essential component of assessing cost-effectiveness, evidence are limited in the context of child and youth mental health care. The objective was to systematically review the model-based economic evaluations of mental health interventions for children and youth.MethodsFour databases (MEDLINE, EMBASE, PsycINFO and Web of Science) were searched using appropriate search terms to retrieve model-based economic evaluations of mental health interventions for children and youth. The reporting quality of the included studies were appraised using the Consolidated health economic evaluation reporting standards (CHEERS) checklist.ResultsThe database search yielded 1921 records. Of the 12 selected for review, 66% were published after year 2015. Most of the studies were related to anxiety and post-traumatic stress disorder. There were eight cost-utility studies, three cost-effectiveness studies, and one study using both forms of analysis. Six studies used Markov models, three used decision trees, and three studies used both types of models. However, the model structure, health states, time horizon, and economic perspective showed wide variation. The reporting quality of the included studies varied from 91 to 96%.ConclusionModel based mental health economic evaluations among children and youth are increasingly being reported in recent research. The included studies used Markov models and decision trees, either alone or in combination, and the majority of the articles were of good reporting quality.

The quality of life of regional and remote cancer caregivers in Australia.

OBJECTIVE: This study compares the well-being of rural caregivers with that of the general population and explores the potential drivers of poorer outcomes. METHOD: Patient-caregiver dyads (n = 241) residing in regional or remote Queensland, Australia, reported on QoL, chronic illness, caregiver burden, depression, anxiety and stress. Caregiver outcomes were compared with population norms and patient outcomes. Multiple regressions were conducted to identify factors associated with poorer caregiver outcomes. RESULTS: Caregivers reported lower mental health-related QoL (M = 0.436, 95% CI = 0.410-0.462) in comparison with age-matched population norms (M = 0.556, 95% CI = 0.532-0.580). No differences existed between caregiver and population norms for anxiety, stress and depression. Caregiver chronic illness and higher burden were associated with poorer mental and physical QoL, depression, anxiety and stress (η2 s ranging from 0.03 to 0.30). These associations were slightly stronger for male caregivers when compared with female caregivers (η2 s ranging from 0.03 to 0.08). CONCLUSION: It is vital that efforts are made to improve rural caregivers' mental and emotional well-being. Interventions that support caregivers with chronic conditions reduce caregiver burden and take into consideration the unique experience of male caregivers will go some way to addressing this. Future research is needed to identify other drivers of health outcomes in this group.

A health action process approach for developing invitee endorsed interventions to increase mail-out bowel cancer screening.

Theory-based, user-informed interventions are needed to increase the low participation rates of population-based faecal occult blood test (FOBT) bowel cancer screening. This study investigated the theoretical fit of the health action process approach (HAPA) for home FOBT screening and measured screening invitees' attitudes towards different intervention strategies. A cross-sectional sample (n = 377), aged 50-74 years, participated in this study. Two scales were created for this study. The process approach to mail-out screening (PAMS) scale measured HAPA constructs, and the user ratings of mail-out screening interventions (UR-MSI) scale measured attitudes towards different intervention strategies. Structural equation modelling was used to assess the fit of PAMS scale responses to the HAPA model, and descriptive statistics were calculated for UR-MSI responses. PAMS results showed acceptable model fit, CFI = .968, RMSEA = .050 and explained 49.9% of the variation in FOBT screening participation. Positive ratings of interventions ranged from 20.47%, an intervention prompting planning to complete the FOBT kit, to 72.25%, an intervention promoting the positive health outcome associated with FOBT screening. Intervention strategies should be combined such that they target all factors specified within the HAPA model. User-informed intervention design should be used to effectively facilitate FOBT uptake in the community.