The importance of a language-rich home environment during the early years of life has been well established.¹ Existing evidence indicates positive associations between early language exposure and children’s language development,^2-5 socioemotional development,⁶ IQ,⁷ and brain function.^8-10 As a result, programs aiming to increase the amount of parent-child talk in young children’s homes have become increasingly popular.^11-13 Estimates of the home language environment in Australia and the US have shown large variability among families.^14-16 Talking with children may seem an easy and simple activity; however, in the busy lives of families, it may be anything but simple. It is crucial to investigate potential factors within the home environment that may interrupt parents’ opportunities to talk and interact with their children to help inform interventions aimed at building a language-rich home environment and, in turn, support children’s language development.

Screen time guidelines recommend no screens under two years due to the potential negative impacts on development. While current reports suggest many children exceed this, research relies on parent reports of their children's screen exposure. We objectively assess screen exposure during the first two years and how it differs by maternal education and gender. This Australian prospective cohort study used speech recognition technology to understand young children's screen exposure over an average day. Data collection occurred every six months when children were 6, 12, 18 and, 24 months old (n = 207). The technology provided automated counts of children's exposure to electronic noise. Audio segments were then coded as screen exposure. Prevalence of screen exposure was quantified, and differences between demographics examined. At six months, children were exposed to an average of 1hr, 16 min (SD = 1hr, 36 min) of screens per day, increasing to an average of 2 h, 28 min (SD = 2 h, 4 min) by 24-months. Some children at six months were exposed to more than 3 h of screen time per day. Inequalities in exposure were evident as early as six months. Children from higher educated families were exposed to 1hr,43 min fewer screens per day, 95%CI (-2hr, 13 min, -1hr, 11 min) compared to lower educated households, with this difference remaining consistent as children age. Girls were exposed to an additional 12 min of screens 95%CI (−20 min, 44 min) per day compared to boys at six months, but this difference reduced to only 5 min by 24-months. Using an objective measure of screen exposure, many families exceed screen time guidelines, the extent increasing with child's age. Furthermore, substantial differences between maternal education groups emerge as young as six months old. This highlights the need for education and supports for parents around screen use in the early years, balanced within the realities of modern life.

It is well established that children’s school readiness is associated with their later academic achievement, but less is known about whether school readiness is also associated with other measures of school success, such as students’ social and emotional wellbeing. While some previous research has shown a link between early social and emotional development and student wellbeing, results are mixed and the strength of these relationships vary depending on whether data is based on child, teachers or parents ratings and which specific student wellbeing outcomes are measured. The present study explored the association between teacher-rated school readiness (M_age = 5.6 years) across five developmental domains (physical, social, emotional, language and cognitive, and communication and general knowledge) and four aspects of student wellbeing (life satisfaction, optimism, sadness and worries) in Grade 6 (M_age = 11.9 years) in a sample of 3906 Australian children. After adjustment for background child and family-level factors, children’s early physical, social and emotional development were associated with all four wellbeing outcomes in Grade 6, but early language and cognitive skills and communication and general knowledge skills were only associated with internalising behaviours (sadness and worries). Mechanisms through which these different aspects of development might influence later wellbeing are discussed, as well as ways that schools and governments can support students’ social and emotional wellbeing.

The social media application TikTok allows users to view and upload short-form videos. Recent evidence suggests it has significant potential for both industry and health promoters to influence public health behaviours. This protocol describes a standardised, replicable process for investigations that can be tailored to various areas of research interest, allowing comparison of content and features across public health topics. The first 50 appearing videos in each of five relevant hashtags are sampled for analysis. Utilising a codebook with detailed definitions, engagement metadata and content variables applicable to any content area is captured, including an assessment of the video’s overall sentiment (positive, negative, neutral). Additional specific coding variables can be developed to provide targeted information about videos posted within selected hashtags. A descriptive, cross-sectional content analysis is applied to the generic and specific data collected for a research topic area. This flexible protocol can be replicated for any health-related topic and may have a wider application on other platforms or to assess changes in content and sentiment over time. This protocol was developed by a collaborative team of child health and development researchers for application to a series of topics. Findings will be used to inform health promotion messaging and counter-advertising.

Aim: To describe the implementation and outcomes of a combined individual placement and support (IPS) and vocational peer work program for young people with mental ill‐health.Methods: This uncontrolled pilot study co‐located IPS workers and vocational peer workers within two integrated youth mental health services (provided to clients aged 15–25 years old). Employment outcomes included job placements (working 15 hours or more per week in a paid competitive job in the open employment market) and sustained employment (employed for at least 26 weeks). Participants who required additional assistance also received peer work.Results: Of the 326 young people enrolled, 195 (59.8%) achieved competitive employment, including 157 (48.2%) in funder‐approved placements. Among those in approved placements, 87 (55.4%) achieved sustained employment. For the 116 participants additionally receiving vocational peer work, 54 (46.6%) worked in funder‐approved placements, of whom 27 (50.0%) achieved sustained employment. Among 210 participants who did not receive peer work, 103 (49.0%) worked in funder‐approved placements, of whom 60 (58.3%) achieved sustained employment.Conclusions: The program achieved positive vocational outcomes and good fidelity to the IPS model. Approximately half of young people had employment placements, with a relatively high proportion maintained over time. The similar proportion of placements for those who did and did not receive peer work was encouraging given the IPS team determined that the former group needed additional support.Recommendations include upskilling the workforce, a data linkage system to obtain placement evidence, and using implementation science methodologies to understand how IPS programs are successfully embedded. This demands a coordinated effort between governments and funders, policymakers, services, and professional bodies.

Wellbeing and mental health are fundamental rights of children and adolescents essential for sustainable development. Understanding the epidemiology of child and adolescent wellbeing is essential to informing population health approaches to improving wellbeing and preventing mental illness. The present study estimated the prevalence of wellbeing and how wellbeing indicators were distributed across social and economic groups. This study used data from the 2019 Wellbeing and Engagement Collection; an annual census conducted in South Australian schools that measures self-reported wellbeing in students aged 8–18 years (n = 75,966). We estimated the prevalence (n, %) of low, medium and high wellbeing across five outcomes: life satisfaction, optimism, sadness, worries and happiness, overall and stratified by gender, age, language background, socio-economic position and geographical remoteness. The prevalence of low wellbeing on each indicator was: happiness 13%, optimism 16%, life satisfaction 22%, sadness 16% and worries 25%. The prevalence of low wellbeing increased with age, particularly for females. For example, 22.5% of females aged 8–10 years had high levels of worries compared to 43.6% of 15 to 18-year old females. Socioeconomic inequality in wellbeing was evident on all indicators, with 19.5% of children in the most disadvantaged communities having high levels of sadness compared to 12.5% of children in the most advantaged communities. Many children and adolescents experience low wellbeing on one or more indicators (40.7%). The scale of this problem warrants a population-level preventative health response, in addition to a clinical, individual-level responses to acute mental health needs. Universal school-based programs that support social and emotional wellbeing have a role to play in this response but need to be supported by universal and targeted responses from outside of the education system.