644 research outputs found

    Utilizing Mixed Graphical Network Models to Explore Parent Psychological Symptoms and Their Centrality to Parent Mental Health in Households with High Child Screen Usage

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    Especially among adolescents, screens are being used more than ever. In conjunction with this trend, mental illness is increasingly prevalent among both adults and children, and parental psychological problems are shown to be associated with children\u27s TV watching, video watching, and gaming (Pulkki-Råback et al., 2022). This study aims to approach parent mental illness symptom by symptom to explore which specific symptoms are most central to parent psychological problems in households where children show high screen time behaviors. We draw from the Adolescent Brain Cognitive Development Study (ABCD Study®), a nationwide sample of 11,875 children aged 10-13 collected by the National Institute of Mental Health. We utilize Mixed Graphical Models (MGMs) on both polychoric and dichotomized data, using the Extended Bayesian Information Criterion to choose the best models. Within our polychoric data, we pinpoint “I feel worthless and inferior” as a symptom with both high bridge betweenness and strength between symptom communities within high screen time household networks. Within binary high child screen time networks, we find “I have trouble making decisions” as a parent symptom with high bridge strength and betweenness that is central to the overall structure of the network. Finally, we believe our approach could be more successfully applied to other psychological datasets with more nonzero responses to parent psychological symptoms to further illuminate parent symptoms that are important in households with high child screen time. Our analyses do not establish causality because our data is cross-sectional

    Chronostratigraphy of Miocene Strata in the Berkeley Hills (California Coast Ranges, USA) and the Arrival of the San Andreas Transform Boundary

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    Miocene strata of the Claremont, Orinda, and Moraga formations of the Berkeley Hills (California Coast Ranges, USA) record sedimentation and volcanism during the passage of the Mendocino triple junction and early evolution of the San Andreas fault system. Detrital zircon laser ablation–inductively coupled plasma–mass spectrometry (LA-ICP-MS) age spectra indicate a change in sedimentary provenance between the marine Claremont formation (Monterey Group) and the terrestrial Orinda and Moraga Formations associated with uplift of Franciscan Complex lithologies. A sandstone from the Claremont formation produced a detrital zircon chemical abrasion–isotope dilution–thermal ionization mass spectrometry (CA-ID-TIMS) maximum depositional age of 13.298 ± 0.046 Ma, indicating younger Claremont deposition than previously interpreted. A trachydacite tuff clast within the uppermost Orinda Formation yielded a CA-ID-TIMS U-Pb zircon date of 10.094 ± 0.018 Ma, and a dacitic tuff within the Moraga Formation produced a CA-ID-TIMS U-Pb zircon date of 9.974 ± 0.014 Ma. These results indicate rapid progression from subsidence in which deep-water siliceous sediments of the Claremont formation were deposited to uplift that was followed by subsidence during deposition of terrestrial sediments of the Orinda Formation and subsequent eruption of the Moraga Formation volcanics. We associate the Orinda tuff clast and Moraga volcanics with slab-gap volcanism that followed the passage of the Mendocino triple junction. Given the necessary time lag between triple junction passage and the removal of the slab that led to this volcanism, subsidence associated with ca. 13 Ma Claremont sedimentation and subsequent Orinda to Moraga deposition can be attributed to basin formation along the newly arrived transform boundary

    Changes in beverage purchases following the announcement and implementation of South Africa's Health Promotion Levy: an observational study

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    BACKGROUND: In 2016, South Africa announced an intention to levy a tax on sugar-sweetened beverages (SSBs). In 2018, the country implemented an SSB tax of approximately 10%, known as the Health Promotion Levy (HPL). We aimed to assess changes in the purchases of beverages before and after the HPL announcement and implementation. METHODS: We used Kantar Europanel data on monthly household purchases between January, 2014, and March, 2019, among a sample of South African households (n=113 653 household-month observations) from all nine provinces to obtain per-capita sugar, calories, and volume from taxable and non-taxable beverages purchased before and after the HPL announcement and implementation. We describe survey-weighted means for each period, and regression-controlled predictions of outcomes and counterfactuals based on pre-HPL announcement trends, with bootstrapped 95% CIs, and stratify results by socioeconomic status. FINDINGS: Mean sugar from taxable beverage purchases fell from 16·25 g/capita per day (95% CI 15·80-16·70) to 14·26 (13·85-14·67) from the pre-HPL announcement to post-announcement period, and then to 10·63 g/capita per day (10·22-11·04) in the year after implementation. Mean volumes of taxable beverage purchases fell from 518·99 mL/capita per day (506·90-531·08) to 492·16 (481·28-503·04) from pre-announcement to post announcement, and then to 443·39 mL/capita per day (430·10-456·56) after implementation. Across these time periods, there was a small increase in the purchases of non-taxable beverages, from 283·45 mL/capita per day (273·34-293·56) pre-announcement to 312·94 (296·29-329·29) post implementation. When compared with pre-announcement counterfactual trends, reductions in taxable beverage purchase outcomes were significantly larger than the unadjusted survey-weighted observed reductions. Households with lower socioeconomic status purchased larger amounts of taxable beverages in the pre-announcement period than did households with higher socioeconomic status, but demonstrated bigger reductions after the tax was implemented. INTERPRETATION: The announcement and introduction of South Africa's HPL were followed by reductions in the sugar, calories, and volume of beverage purchases. FUNDING: Bloomberg Philanthropies, International Development Research Centre, South African Medical Research Council, and the US National Institutes of Health

    Moving towards social inclusion: engaging rural voices in priority setting for health

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    Background Achieving universal health coverage (UHC) in the context of limited resources will require prioritising the most vulnerable and ensuring health policies and services are responsive to their needs. One way of addressing this is through the engagement of marginalised voices in the priority setting process. Public engagement approaches that enable group level deliberation as well as individual level preference capturing might be valuable in this regard, but there are limited examples of their practical application, and gaps in understanding their outcomes, especially with rural populations. Objective To address this gap, we implemented a modified priority setting tool (Choosing All Together—CHAT) that enables individuals and groups to make trade-offs to demonstrate the type of health services packages that may be acceptable to a rural population. The paper presents the findings from the individual choices as compared to the group choices, as well as the differences among the individual choices using this tool. Methods Participants worked in groups and as individuals to allocate stickers representing the available budget to different health topics and interventions using the CHAT tool. The allocations were recorded at each stage of the study. We calculated the median and interquartile range across study participants for the topic totals. To examine differences in individual choices, we performed Wilcoxon rank sum tests. Results The results show that individual interests were mostly aligned with societal ones, and there were no statistically significant differences between the individual and group choices. However, there were some statistically significant differences between individual priorities based on demographic characteristics like age. Discussion The study demonstrates that giving individuals greater control and agency in designing health services packages can increase their participation in the priority setting process, align individual and community priorities, and potentially enhance the legitimacy and acceptability of priority setting. Methods that enable group level deliberation and individual level priority setting may be necessary to reconcile plurality. The paper also highlights the importance of capturing the details of public engagement processes and transparently reporting on these details to ensure valuable outcomes. Public Contribution The facilitator of the CHAT groups was a member from the community and underwent training from the research team. The fieldworkers were also from the community and were trained and paid to capture the data. The participants were all members of the rural community- the study represents their priorities

    Use of information entropy measures of sitting postural sway to quantify developmental delay in infants

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    Background: By quantifying the information entropy of postural sway data, the complexity of the postural movement of different populations can be assessed, giving insight into pathologic motor control functioning. Methods: In this study, developmental delay of motor control function in infants was assessed by analysis of sitting postural sway data acquired from force plate center of pressure measurements. Two types of entropy measures were used: symbolic entropy, including a new asymmetric symbolic entropy measure, and approximate entropy, a more widely used entropy measure. For each method of analysis, parameters were adjusted to optimize the separation of the results from the infants with delayed development from infants with typical development. Results: The method that gave the widest separation between the populations was the asymmetric symbolic entropy method, which we developed by modification of the symbolic entropy algorithm. The approximate entropy algorithm also performed well, using parameters optimized for the infant sitting data. The infants with delayed development were found to have less complex patterns of postural sway in the medial-lateral direction, and were found to have different left-right symmetry in their postural sway, as compared to typically developing infants. Conclusion: The results of this study indicate that optimization of the entropy algorithm for infant sitting postural sway data can greatly improve the ability to separate the infants with developmental delay from typically developing infants
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