A psychosocial analysis of parent's decisions for limiting their young child's screen time: An examination of attitudes, social norms and roles, and control perceptions

- Objectives Preschool-aged children spend substantial amounts of time engaged in screen-based activities. As parents have considerable control over their child's health behaviours during the younger years, it is important to understand those influences that guide parents' decisions about their child's screen time behaviours. - Design A prospective design with two waves of data collection, 1 week apart, was adopted. - Methods Parents (n = 207) completed a Theory of Planned Behaviour (TPB)-based questionnaire, with the addition of parental role construction (i.e., parents' expectations and beliefs of responsibility for their child's behaviour) and past behaviour. A number of underlying beliefs identified in a prior pilot study were also assessed. - Results The model explained 77% (with past behaviour accounting for 5%) of the variance in intention and 50% (with past behaviour accounting for 3%) of the variance in parental decisions to limit child screen time. Attitude, subjective norms, perceived behavioural control, parental role construction, and past behaviour predicted intentions, and intentions and past behaviour predicted follow-up behaviour. Underlying screen time beliefs (e.g., increased parental distress, pressure from friends, inconvenience) were also identified as guiding parents' decisions. - Conclusion Results support the TPB and highlight the importance of beliefs for understanding parental decisions for children's screen time behaviours, as well as the addition of parental role construction. This formative research provides necessary depth of understanding of sedentary lifestyle behaviours in young children which can be adopted in future interventions to test the efficacy of the TPB mechanisms in changing parental behaviour for their child's health.

Geometry-free stochastic analysis of BDS triple frequency signals

The paper presents a geometry-free approach to assess the variation of covariance matrices of undifferenced triple frequency GNSS measurements and its impact on positioning solutions. Four independent geometryfree/ ionosphere-free (GFIF) models formed from original triple-frequency code and phase signals allow for effective computation of variance-covariance matrices using real data. Variance Component Estimation (VCE) algorithms are implemented to obtain the covariance matrices for three pseudorange and three carrier-phase signals epoch-by-epoch. Covariance results from the triple frequency Beidou System (BDS) and GPS data sets demonstrate that the estimated standard deviation varies in consistence with the amplitude of actual GFIF error time series. The single point positioning (SPP) results from BDS ionosphere-free measurements at four MGEX stations demonstrate an improvement of up to about 50% in Up direction relative to the results based on a mean square statistics. Additionally, a more extensive SPP analysis at 95 global MGEX stations based on GPS ionosphere-free measurements shows an average improvement of about 10% relative to the traditional results. This finding provides a preliminary confirmation that adequate consideration of the variation of covariance leads to the improvement of GNSS state solutions.

Detailed analysis of a conservative difference approximation for the time fractional diffusion equation

Diffusion equations that use time fractional derivatives are attractive because they describe a wealth of problems involving non-Markovian Random walks. The time fractional diffusion equation (TFDE) is obtained from the standard diffusion equation by replacing the first-order time derivative with a fractional derivative of order α ∈ (0, 1). Developing numerical methods for solving fractional partial differential equations is a new research field and the theoretical analysis of the numerical methods associated with them is not fully developed. In this paper an explicit conservative difference approximation (ECDA) for TFDE is proposed. We give a detailed analysis for this ECDA and generate discrete models of random walk suitable for simulating random variables whose spatial probability density evolves in time according to this fractional diffusion equation. The stability and convergence of the ECDA for TFDE in a bounded domain are discussed. Finally, some numerical examples are presented to show the application of the present technique.

Reducing the global burden of depression : population level analysis of intervention cost-effectiveness in 14 world regions

International evidence on the cost and effects of interventions for reducing the global burden of depression remain scarce. Aims: To estimate the population-level cost-effectiveness of evidence-based depression interventions and their contribution towards reducing current burden. Method: Primary-care-based depression interventions were modelled at the level of whole populations in 14 epidemiological subregions of the world. Total population-level costs (in international dollars or I$) and effectiveness (disability adjusted life years (DALYs) averted) were combined to form average and incremental cost-effectiveness ratios. Results: Evaluated interventions have the potential to reduce the current burden of depression by 10–30%. Pharmacotherapy with older antidepressant drugs, with or without proactive collaborative care, are currently more cost-effective strategies than those using newer antidepressants, particularly in lower-income subregions. Conclusions: Even in resource-poor regions, each DALYaverted by efficient depression treatments in primary care costs less than 1 year of average per capita income, making such interventions a cost-effective use of health resources. However, current levels of burden can only be reduced significantlyif there is a substantialincrease substantial increase intreatment coverage.