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Children who have 'early contact' with youth justice (YJ) are a group of significant policy interest. Understanding circumstances which precede or co-occur with YJ contact can support the development of preventive investments and inform debates about systemic reform, such as 'raise the age'. Using whole-of-population administrative data from the SA Better Evidence Better Outcomes Linked Data (BEBOLD) platform, we examine differences between children who have early (i.e. between the ages of 10 and 13 years) versus late (i.e. at age 14 or older) YJ contact, relative to the general population. Children born 1991–2022 were followed from birth to age 18 (N = 249,995). Compared to the late-contact group, children with early contact experienced more serious YJ contact (91% versus 59% experienced custody); were more disadvantaged at birth (e.g. 66% versus 45% born into jobless families); had more serious child protection contact by age 10 (26% versus 12% experienced out-of-home care); and experienced mental health-related hospitalisations from ages 12–18 (43% versus 34%). Relative to the general population, both groups were characterised by significant social and economic disadvantage, child protection contact and mental health challenges. The need for investment in early prevention to divert children from the justice system is clear. [ABSTRACT FROM AUTHOR]

It is well-established that social determinants of health contribute to health and well-being. Among the social determinants of health, health-related social needs (HRSNs) are unmet needs that can be identified by the health care system and addressed through referral to community services. Despite the importance of identifying patients with HRSNs, none of the few screening tools for HRSNs available internationally have received a comprehensive psychometric validation. This study aims to conduct a qualitative validation of the Social Determinants of Health Screening Tool (SDoHST). This study took place at Lyell McEwin Hospital, a major tertiary hospital located in Adelaide, South Australia. Patient (n = 5) and stakeholder (n = 9) focus groups were conducted face to face, audio recorded, and transcribed verbatim. Inductive content analysis of focus group transcripts was performed to inform tool modifications (e.g. item rewording). The patient focus group recommended the addition of an explanatory paragraph to improve face validity, and highlighted the importance of reliable transport and internet access. The stakeholder focus group recommended using language that carries less stigma to this particular community and incorporating questions surrounding cultural, linguistic, and spiritual needs. The final version of the SDoHST included 12 items (four original items were removed and seven new items were added during the validation process). The SDoHST is the first validated tool to measure social determinants of health (and specifically HRSNs) in Australia, receiving a comprehensive qualitative validation. The instrument is readily available and future studies will further investigate its psychometric properties with quantitative methods. A brief guide to screening tools for social determinants of health and their validation The importance of social context in contributing to overall health is well-established. Social determinants of health (SDoH) are social and environmental factors such as employment, housing security, financial stability, social isolation, and personal safety, which contribute up to 60% of overall health. In recent years, there has been a paradigm shift in how healthcare systems view health and wellbeing. There is a growing call to intervene in adverse SDoH from within the healthcare system. One such intervention involves screening patients for unmet needs, such as housing or food insecurity, and providing appropriate connections to organizations in the community to assist with their needs. The screening tools implemented in this context are multiple and diverse. Some target only one or two factors while others assess multiple SDoH. However, little is reported about the development of these tools. If a screening tool is not thoroughly developed and validated, it is impossible to know whether the data collected with the tool are appropriate or relevant. This study details the development and validation of a screening tool for unmet social needs by community members and healthcare providers at a major metropolitan hospital in South Australia. [ABSTRACT FROM AUTHOR]

In Australia, the Strengths and Difficulties Questionnaire (SDQ) has been implemented in several national studies, including the Longitudinal Study of Australian Children (LSAC). However, three previous state-level validations indicated problems with instrument dimensionality, warranting further research. To address this gap, the current study employed exploratory graph analysis to investigate dimensionality of the caregiver-completed SDQ version 4 to 10 years in a nationally representative sample of Australian children. Data were from a dual cohort cross-sequential study (LSAC) that included more than 20,000 responses. Gaussian graphical models were estimated in each study wave and exploratory graph analysis applied. Structural consistency, item stability and network loadings were evaluated. The findings provided mixed support for the original SDQ five-factor structure. The Peer Problem scale displayed low structural consistency since items clustered with the Emotional Symptoms and Prosocial behavior, generating four-dimensional structures. Implications for future use of the SDQ version 4 to 10 years in Australia are provided. [ABSTRACT FROM AUTHOR]

The aim of this systematic review and meta-analysis was to document the disparity in dental caries experiences among indigenous and nonindigenous populations globally by measuring dental caries prevalence and severity. An electronic database (MEDLINE) was initially searched using relevant keywords. This was followed by use of the search string in the following electronic databases: Scopus, EBSCOhost, Cochrane, and Open Grey. Two independent reviewers conducted the study search and screening, quality assessment, and data extraction, which was facilitated using JBI SUMARI software. The primary outcome was the decayed missing filled teeth (DMFT) score and dental caries prevalence. Subgroup analysis was done by country of publication to identify causes of heterogeneity. Forest plots were used with the standardized mean difference (SMD) and publication bias was assessed using the Egger test with funnel plot construction. For the final review, 43 articles were selected and 34 were meta-analyzed. The pooled mean DMFT for both the permanent dentition (SMD = 0.26; 95% CI 0.13-0.39) and deciduous dentition (SMD = 0.67; 95% CI 0.47-0.87) was higher for the Indigenous population than for the general population. Indigenous populations experienced more decayed teeth (SMD = 0.44; 95% CI 0.25-0.62), a slightly higher number of missing teeth (SMD = 0.11< 95% CI -0.05 to 0.26), and lesser filled teeth (SMD = -0.04; 95% CI -0.20 to 0.13) than their nonindigenous counterparts. The prevalence of dental caries (SMD = 0.27; 95% CI 0.13-0.41) was higher among indigenous people. Globally, indigenous populations have a higher caries prevalence and severity than nonindigenous populations. The factors which have led to such inequities need to be examined. [ABSTRACT FROM AUTHOR]

Objectives: Network analysis is an innovative, analytic approach that enables visual representation of variables as nodes and their corresponding statistical associations as edges. It also provides a new way of framing oral health‐related questions as complex systems of variables. We aimed to generate networks of oral health variables using epidemiological data of Indigenous children, and to compare network structures of oral health variables among participants who received immediate or delayed delivery of an oral health intervention. Methods: Epidemiological data from 448 mother‐child dyads enrolled in a randomized controlled trial of dental caries prevention in South Australia, Australia, were obtained. Networks were estimated with nodes representing study variables and edges representing partial correlation coefficients between variables. Data included dental caries, impact on quality of life, self‐rated general health, self‐rated oral health, dental service utilization, knowledge of oral health, fatalism and self‐efficacy in three time points. Communities of nodes, centrality, clustering coefficient and network stability were estimated. Results: The oral health intervention interacted with the network through self‐rated general health and knowledge of oral health. Networks depicting groups shortly after receiving the intervention presented higher clustering coefficients and a similar arrangement of nodes. Networks tended to return to a preintervention state. Conclusion: The intervention resulted in increased connectivity and changes in the structure of communities of variables in both intervention groups. Our findings contribute to elucidating dynamics between variables depicting oral health networks over time. [ABSTRACT FROM AUTHOR]

Adolescence is a period in which peer problems and emotional symptoms markedly increase in prevalence. However, the causal mechanisms regarding how peer problems cause emotional symptoms at a behavioral level and vice versa remain unknown. To address this gap, the present study investigated the longitudinal network of peer problems and emotional symptoms among Australian adolescents aged 12-14 years. Data were from the Longitudinal Study of Australian Children. The complete case samples included adolescents who participated in the Longitudinal Study of Australian Children B ( n = 2,694) or K ( n = 3,144) Cohorts at two study follow-ups (ages 12 and 14). Peer problems and emotional symptoms were measured with the self-report Strengths and Difficulties Questionnaire. The analytical steps were (a) in Study 1, a causal discovery algorithm, Bayesian structure learning of directed acyclic graphs (DAGs), was used to identify the longitudinal network in the K Cohort; (b) the DAG discovered was evaluated with Bayesian structural equation modeling in an independent sample (the B Cohort) and compared against a DAG established through expert knowledge; and (c) in Study 2, the longitudinal network was again evaluated but considered contemporaneous effects. The empirically discovered DAG provided a better explanation of independent data than the expert DAG. Based on the discovered DAG, several plausible causal effects were identified such as that being bullied at age 12 negatively affected popularity at age 14. This study provides new insights into potential causal effects established between peer problems and emotional symptoms among Australian adolescents aged 12-14 years. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Background: Given the significant investment of governments and families into the provision of child dental care services in Australia, continued population oral health surveillance through national oral health surveys is imperative., Objective: The aims of this study are to conduct a second National Child Oral Health Survey (NCOHS-2) to (1) describe the prevalence, extent, and impact of oral diseases in contemporary Australian children; (2) evaluate changes in the prevalence and extent of oral diseases in the Australian child population and socioeconomic subgroups since the first National Child Oral Health Study (NCOHS-1) in 2012-2013; and (3) use economic modeling to evaluate the burden of child oral disease from the NCOHS-1 and NCOHS-2 and to estimate the cost-effectiveness of targeted programs for high-risk child groups., Methods: The NCOHS-2 will closely mimic the NCOHS-1 in being a cross-sectional survey of a representative sample of Australian children aged 5-14 years. The survey will comprise oral epidemiological examinations and questionnaires to elucidate associations between dental disease in a range of outcomes, including social and emotional well-being. The information will be analyzed within the context of dental service organization and delivery at national and jurisdictional levels. Information from the NCOHS-1 and NCOHS-2 will be used to simulate oral disease and its economic burden using both health system and household costs of childhood oral health disease., Results: Participant recruitment for the NCOHS-2 will commence in February 2024. The first results are expected to be submitted for publication 6 months after NCOHS-2 data collection has been completed. Thematic workshops with key partners and stakeholders will also occur at this time., Conclusions: Regular surveillance of child oral health at an Australian level facilitates timely policy and planning of each state and territory's dental public health sector. This is imperative to enable the most equitable distribution of scarce public monies, especially for socially disadvantaged children who bear the greatest dental disease burden. The last NCOHS was conducted in 2012-2014, meaning that these data need to be updated to better inform effective dental health policy and planning. The NCOHS-2 will enable more up-to-date estimates of dental disease prevalence and severity among Australian children, with cost-effective analysis being useful to determine the economic burden of poor child dental health on social and emotional well-being and other health indicators., International Registered Report Identifier (irrid): PRR1-10.2196/52233., (©Lisa Jamieson, Liana Luzzi, Sergio Chrisopoulos, Rachel Roberts, Peter Arrow, Sanjeewa Kularatna, Murthy Mittinty, Dandara Haag, Pedro Henrique Ribeiro Santiago, Gloria Mejia. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 14.11.2023.)