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Background: World-wide, health service providers are moving towards innovative models of clinical home-based care services as a key strategy to improve equity of access and quality of care. To optimise existing and new clinical home-based care programs, evidence informed approaches are needed that consider the complexity of the health care system across different contexts. Methods: We present a protocol for working with health services and their partners to perform rapid identification, prioritisation, and co-design of content-appropriate strategies to optimise the delivery of healthcare at home for older people in rural and regional areas. The protocol combines Systems Thinking and Implementation Science using a Consensus Mapping and Co-design (CMC) process delivered over five workshops. Discussion: The protocol will be implemented with rural and regional healthcare providers to identify digital and non-digital solutions that have the potential to inform models of service delivery, improve patient experience, and optimise health outcomes. The combination of system and implementation science is a unique approach for optimising healthcare at home for older populations, especially in the rural context where need is high. This is the first protocol to integrate the use of systems and implementation science into one process and articulating these methods will help with replicating this in future practice. Results of the design phase will translate into practice through standard health service planning methods to enhance implementation and sustainability. The delivery of the protocol will include building capacity of health service workers to embed the design, implementation, and evaluation approach into normal practice. This protocol forms part of the DELIVER (Delivering Enhanced heaLthcare at home through optImising Virtual tools for oldEr people in Rural and regional Australia) Project. Funded by Australia's Medical Research Future Fund, DELIVER involves a collaboration with public health services of Western Victoria, Australia. [ABSTRACT FROM AUTHOR]

Background: Insufficient sleep is potentially an important modifiable risk factor for obesity and poor physical activity and sedentary behaviours among children. However, inconsistencies across studies highlight the need for more objective measures. This paper examines the relationship between sleep duration and objectively measured physical activity, sedentary time and weight status, among a sample of Victorian Primary School children.Methods: A sub-sample of 298 grades four (n = 157) and six (n = 132) Victorian primary school children (aged 9.2-13.2 years) with complete accelerometry and anthropometry data, from 39 schools, were taken from a pilot study of a larger state based cluster randomized control trial in 2013. Data comprised: researcher measured height and weight; accelerometry derived physical activity and sedentary time; and self-reported sleep duration and hypothesised confounding factors (e.g. age, gender and environmental factors).Results: Compared with sufficient sleepers (67 %), those with insufficient sleep (<10 hrs/day) were significantly more likely to be overweight (OR 1.97, 95 % CI:1.11-3.48) or obese (OR 2.43, 95 % CI:1.26-4.71). No association between sleep and objectively measured physical activity levels or sedentary time was found.Conclusion: The strong positive relationship between weight status and sleep deprivation merits further research though PA and sedentary time do not seem to be involved in the relationship. Strategies to improve sleep duration may help obesity prevention initiatives in the future. [ABSTRACT FROM AUTHOR]

Purpose: To explore the cross-sectional relationships between health-related quality of life (HRQoL) and physical activity (PA) behaviours and screen-based media (SBM) use among a sample of Australian adolescents. Methods: Data came from baseline measures collected for the It's Your Move! community-based obesity prevention intervention. Questionnaire data on sociodemographics, PA, SBM and HRQoL were collected from 3,040 students (56% boys) aged 11-18 years in grade levels 7-11 in 12 secondary schools. Anthropometric data were measured. Results: The highest level of PA at recess, lunchtime and after school was associated with higher HRQoL scores (boys, by 5.3, 8.1, 6.3 points; girls, by 4.2, 6.1, 8.2 points) compared with not being active during these periods. Exceeding 2 h of SBM use each day was associated with significantly lower HRQoL scores (boys, by 3.2 points; girls, by 4.0 points). Adolescents who were physically active and low SBM users on school days had higher HRQoL scores (boys, by 6.6 points; girls, by 7.8 points) compared with those who were not physically active every school day and high SBM users on school days. Conclusions: Several of the relationships between low PA and high SBM use and HRQoL were comparable to those previously observed between chronic disease conditions and HRQoL, indicating that these behaviours deserve substantial attention. [ABSTRACT FROM AUTHOR]

Background: Research has highlighted the multitude of factors that are negatively associated with coach mental well-being but has failed to investigate how the determinants of mental well-being can affect the coach both positively and negatively. Accordingly, the aim of this study was to investigate levels of mental well-being among sport coaches and assess whether areas of work life-specifically workload and control-are related to levels of mental well-being. Method: An online survey comprising demographic and coaching experience details, the Areas of Work Life Scale (AWS), and the Warwick-Edinburgh Mental Well-Being Scale was completed by 464 Australian coaches involved in a range of sports. Differences in coach mental well-being according to key demographic and coaching-related subgroups were assessed using separate t-test and ANOVA analyses and the magnitude of effects was determined using Cohen's d and the eta-squared ( ή 2 ) statistics. Multiple linear regression was used to examine relationships between both workload and control and mental well-being after controlling for age, gender, coaching setting and weekly coaching activity. Results: The findings indicate poorer mental well-being among both male and younger coaches and indicate that coach mental well-being is related to the ability to self-manage the workload associated with their role as a coach as well as greater autonomy over coaching-related tasks and activities. Specifically, a one-unit increase in AWS workload and AWS control were associated with ~three- and ~four-unit increases in coach mental well-being, respectively. Conclusion : Greater provision of resources and education is required to assist coaches to manage their own mental well-being, while being supported by the organisation they coach for. Enabling coaches to balance their coaching requirements and to have control over their environment will improve their ability to constantly coach at a high standard.