Resolving the fine-scale velocity structure of continental hyperextension at the Deep Galicia Margin using full-waveform inversion

Continental hyperextension during magma-poor rifting at the Deep Galicia Margin is characterised by a complex pattern of faulting, thin continental fault blocks, and the serpentinisation, with local exhumation, of mantle peridotites along the S-reflector, interpreted as a detachment surface. In order to understand fully the evolution of these features, it is important to image seismically the structure and to model the velocity structure to the greatest resolution possible. Travel-time tomography models have revealed the long-wavelength velocity structure of this hyperextended domain, but are often insufficient to match accurately the short-wavelength structure observed in reflection seismic imaging. Here we demonstrate the application of two-dimensional (2D) time-domain acoustic full-waveform inversion to deep water seismic data collected at the Deep Galicia Margin, in order to attain a high resolution velocity model of continental hyperextension. We have used several quality assurance procedures to assess the velocity model, including comparison of the observed and modelled waveforms, checkerboard tests, testing of parameter and inversion strategy, and comparison with the migrated reflection image. Our final model exhibits an increase in the resolution of subsurface velocities, with particular improvement observed in the westernmost continental fault blocks, with a clear rotation of the velocity field to match steeply dipping reflectors. Across the S-reflector there is a sharpening in the velocity contrast, with lower velocities beneath S indicative of preferential mantle serpentinisation. This study supports the hypothesis that normal faulting acts to hydrate the upper mantle peridotite, observed as a systematic decrease in seismic velocities, consistent with increased serpentinisation. Our results confirm the feasibility of applying the full-waveform inversion method to sparse, deep water crustal datasets

Relationships between brain and body temperature, clinical and imaging outcomes after ischemic stroke

Pyrexia soon after stroke is associated with severe stroke and poor functional outcome. Few studies have assessed brain temperature after stroke in patients, so little is known of its associations with body temperature, stroke severity, or outcome. We measured temperatures in ischemic and normal-appearing brain using (1)H-magnetic resonance spectroscopy and its correlations with body (tympanic) temperature measured four-hourly, infarct growth by 5 days, early neurologic (National Institute of Health Stroke Scale, NIHSS) and late functional outcome (death or dependency). Among 40 patients (mean age 73 years, median NIHSS 7, imaged at median 17 hours), temperature in ischemic brain was higher than in normal-appearing brain on admission (38.6°C-core, 37.9°C-contralateral hemisphere, P=0.03) but both were equally elevated by 5 days; both were higher than tympanic temperature. Ischemic lesion temperature was not associated with NIHSS or 3-month functional outcome; in contrast, higher contralateral normal-appearing brain temperature was associated with worse NIHSS, infarct expansion and poor functional outcome, similar to associations for tympanic temperature. We conclude that brain temperature is higher than body temperature; that elevated temperature in ischemic brain reflects a local tissue response to ischemia, whereas pyrexia reflects the systemic response to stroke, occurs later, and is associated with adverse outcomes

Whatever happened to the Child Trust Fund? The abandonment of universal savings for UK children

Child development accounts (CDAs) provide subsidised savings accounts for children to help meet life course needs. While now largely forgotten, the Child Trust Fund was an innovative savings scheme for UK children that sought to generate a capital sum when they turned 18. The first children to receive these funds reached this point in late 2020 so it is timely to review the impact of this national scheme, which by 2022 had £10 bn saved in it. We consider how far the Child Trust Fund led to higher levels of savings for those children who were eligible for it and whether there is any evidence it created a savings habit in young people and their parents. We use six waves of longitudinal ONS Wealth and Assets Survey data. While we find a small effect on savings, with children from better‐off families benefiting the most, there is little evidence of a meaningful effect on savings habits. Nonetheless, the policy's impact on generating even small amounts of savings could be important, especially as most children in the UK have no savings. The study offers policy recommendations to support children's savings in the UK, based on the significant example of asset‐based welfare policy that the CTF provides

A mixed methods study to explore the effects of program design elements and participant characteristics on parents' engagement with an mHealth program to promote healthy infant feeding: The growing healthy program

Copyright © 2019 Taki, Russell, Lymer, Laws, Campbell, Appleton, Ong and Denney-Wilson. Purpose: Mobile health (mHealth) interventions have great potential to promote health. To increase consumer engagement in mHealth interventions it is necessary to address factors that influence the target demographic. The Growing healthy (GH) program is the first obesity prevention program delivered via a smartphone app and website offering evidence-based information on infant feeding from birth until 9 months of age. This sub-study aimed to explore how the design features, quality of the app and participant characteristics influenced parents' engagement with the GH app. Methods: A sequential mixed methods design was used. The GH app participants (225/301) were considered for this sub-study. Participant app engagement was measured through a purpose-built Engagement Index (EI) using app metrics. Participants were categorized as low, moderately or highly engaged based on their EI score upon completing the 9 months program and were then invited to participate in semi-structured telephone interviews. Participants who used the app program, given an EI score and expressed interest to participate in these interviews were eligible. The interviews explored factors that influenced app engagement including delivery features and quality. Thematic analysis networks was used for analysis. Results: 108/225 expressed interest and 18 interviews were conducted from low (n = 3), moderately (n = 7), or highly (n = 8) engaged participants based on purposeful sampling. Participants defined as highly engaged were likely to be a first-time parent, felt the app content to be trustworthy and the app design facilitated easy navigation and regularly opened the push notifications. Participants defined as having low or moderate engagement were likely to have experience from previous children, felt they had sufficient knowledge on infant feeding and the app did not provide further information, or experienced technological issues including app dysfunction due to system upgrades. Conclusions/Implications: This study demonstrated a novel approach to comprehensively analyse engagement in an mHealth intervention through quantitative (Engagement Index) and qualitative (interviews) methods. It provides an insight on maximizing data collected from these programs for measuring effectiveness and to understand users of various engagement levels interaction with program features. Measuring this can determine efficacy and refine programs to meet user requirements

Assessing User Engagement of an mHealth Intervention: Development and Implementation of the Growing Healthy App Engagement Index.

BACKGROUND: Childhood obesity is an ongoing problem in developed countries that needs targeted prevention in the youngest age groups. Children in socioeconomically disadvantaged families are most at risk. Mobile health (mHealth) interventions offer a potential route to target these families because of its relatively low cost and high reach. The Growing healthy program was developed to provide evidence-based information on infant feeding from birth to 9 months via app or website. Understanding user engagement with these media is vital to developing successful interventions. Engagement is a complex, multifactorial concept that needs to move beyond simple metrics. OBJECTIVE: The aim of our study was to describe the development of an engagement index (EI) to monitor participant interaction with the Growing healthy app. The index included a number of subindices and cut-points to categorize engagement. METHODS: The Growing program was a feasibility study in which 300 mother-infant dyads were provided with an app which included 3 push notifications that was sent each week. Growing healthy participants completed surveys at 3 time points: baseline (T1) (infant age ≤3 months), infant aged 6 months (T2), and infant aged 9 months (T3). In addition, app usage data were captured from the app. The EI was adapted from the Web Analytics Demystified visitor EI. Our EI included 5 subindices: (1) click depth, (2) loyalty, (3) interaction, (4) recency, and (5) feedback. The overall EI summarized the subindices from date of registration through to 39 weeks (9 months) from the infant's date of birth. Basic descriptive data analysis was performed on the metrics and components of the EI as well as the final EI score. Group comparisons used t tests, analysis of variance (ANOVA), Mann-Whitney, Kruskal-Wallis, and Spearman correlation tests as appropriate. Consideration of independent variables associated with the EI score were modeled using linear regression models. RESULTS: The overall EI mean score was 30.0% (SD 11.5%) with a range of 1.8% - 57.6%. The cut-points used for high engagement were scores greater than 37.1% and for poor engagement were scores less than 21.1%. Significant explanatory variables of the EI score included: parity (P=.005), system type including "app only" users or "both" app and email users (P<.001), recruitment method (P=.02), and baby age at recruitment (P=.005). CONCLUSIONS: The EI provided a comprehensive understanding of participant behavior with the app over the 9-month period of the Growing healthy program. The use of the EI in this study demonstrates that rich and useful data can be collected and used to inform assessments of the strengths and weaknesses of the app and in turn inform future interventions

Improving Tax Literacy and Tax Morale in Young People

This research considers socio-demographic influences and the impact enhancements to financial and tax literacy may have on young adults’ tax morale. It also considers the subjects’ perceptions of tax compliance and tax administration. The results show that gender, tax tuition, and employment experience influence tax morale. Most of the 377 students surveyed thought the UK tax system is fair, but complex with personal tax rates that are too high. The majority also believe that a significant number of taxpayers cheat by paying less than they legally owe. The research shows the positive impact of focused tax tuition on university students in raising financial and tax literacy as well as an appreciation for public finance. While the researchers were unable to conclude enhanced literacy resulted in enhanced tax morale in this study, the results nevertheless demonstrated marginal improvements in this regard, thus warranting further research into causation. The researchers make several recommendations for further initiatives and enhancements to existing programmes in taxpayer education focused on young people before they leave school and enter the job market

A randomised controlled trial of clinician supported vs self-help delivery of online cognitive behaviour therapy for Bulimia Nervosa.

High dropout rates and poor adherence associated with digital interventions have prompted research into modifications of these treatments to improve engagement and completion rates. This trial aimed to investigate the added benefit of clinician support when paired alongside a ten-session, online cognitive behaviour therapy (CBT) self-help intervention for bulimia nervosa (BN). As part of a three-arm, phase II randomised controlled trial, 114 participants (16 years or over) with full or subthreshold BN were randomly assigned to complete the intervention in a self-help mode (with administrative researcher contact; n = 38), with adjunct clinician support (weekly 30-minute videoconferencing sessions; n = 37), or a no-treatment waitlist control (WLC; n = 39). Baseline to post-treatment (12-weeks) decreases in objective binge episode frequency were significantly greater for clinician-supported participants as compared to WLC, but not for self-help when compared to WLC. However, due to continued improvements for self-help across follow-up (24-weeks), both arms outperformed WLC when analysed as an overall rate of change across three timepoints. Clinician-supported participants outperformed self-help in regards to laxative use and dietary restraint. Our results demonstrate that good clinical outcomes can be achieved with a relatively brief online CBT-based program even in the absence of structured clinical support, indicating a possible overreliance upon clinician support as a primary adherence-facilitating mechanism

Impact of the growing healthy mhealth program on maternal feeding practices, infant food preferences, and satiety responsiveness: Quasi-experimental study

© Catherine Georgina Russell, Elizabeth Denney-Wilson, Rachel A Laws, Gavin Abbott, Miaobing Zheng, Sharyn J Lymer, Sarah Taki, Eloise-Kate V Litterbach, Kok-Leong Ong, Karen J Campbell. Background: Infancy is an important life stage for obesity prevention efforts. Parents’ infant feeding practices influence the development of infants’ food preferences and eating behaviors and subsequently diet and weight. Mobile health (mHealth) may provide a feasible medium through which to deliver programs to promote healthy infant feeding as it allows low cost and easy access to tailored content. Objective: The objective of this study was to describe the effects of an mHealth intervention on parental feeding practices, infant food preferences, and infant satiety responsiveness. Methods: A quasi-experimental study was conducted with an mHealth intervention group (Growing Healthy) and a nonrandomized comparison group (“Baby's First Food"). The intervention group received access to a free app with age-appropriate push notifications, a website, and an online forum that provided them with evidence-based advice on infant feeding for healthy growth from birth until 9 months of age. Behavior change techniques were selected using the Behaviour Change Wheel framework. Participants in both groups completed three Web-based surveys, first when their infants were less than 3 months old (baseline, T1), then at 6 months (time 2, T2), and 9 months of age (time 3, T3). Surveys included questions on infant feeding practices and beliefs (Infant Feeding Questionnaire, IFQ), satiety responsiveness (Baby Eating Behaviour Questionnaire), and infant’s food exposure and liking. Multivariate linear regression models, estimated using maximum likelihood with bootstrapped standard errors, were fitted to compare continuous outcomes between the intervention groups, with adjustment for relevant covariates. Multivariate logistic regression adjusting for the same covariates was performed for categorical outcomes. Results: A total of 645 parents (Growing Healthy: n=301, Baby's First Food: n=344) met the eligibility criteria and were included in the study, reducing to a sample size of 546 (Growing Healthy: n=234, Baby's First Food: n=312) at T2 and a sample size of 518 (Growing Healthy: n=225, Baby's First Food: n=293) at T3. There were approximately equal numbers of boy and girl infants, and infants were aged less than 3 months at baseline (Growing Healthy: mean 7.0, SD 3.7 weeks; Baby's First Food: mean 7.9, SD 3.8 weeks), with Growing Healthy infants being slightly younger than Baby's First Food infants (P=.001). All but one (IFQ subscale “concerns about infant overeating or becoming overweight” at T2) of the measured outcomes did not differ between Growing Healthy and Baby's First Food. Conclusions: Although mHealth can be effective in promoting some health behaviors and offers many advantages in health promotion, the results of this study suggest that design and delivery characteristics needed to maximize the impact of mHealth interventions on infant feeding are uncertain. The sensitivity of available measurement tools and differences in baseline characteristics of participants may have also affected the results

Key Lessons and Impact of the Growing Healthy mHealth Program on Milk Feeding, Timing of Introduction of Solids, and Infant Growth: Quasi-Experimental Study.

BACKGROUND: The first year of life is an important window to initiate healthy infant feeding practices to promote healthy growth. Interventions delivered by mobile phone (mHealth) provide a novel approach for reaching parents; however, little is known about the effectiveness of mHealth for child obesity prevention. OBJECTIVE: The objective of this study was to determine the feasibility and effectiveness of an mHealth obesity prevention intervention in terms of reach, acceptability, and impact on key infant feeding outcomes. METHODS: A quasi-experimental study was conducted with an mHealth intervention group (Growing healthy) and a nonrandomized comparison group (Baby's First Food). The intervention group received access to a free app and website containing information on infant feeding, sleep and settling, and general support for parents with infants aged 0 to 9 months. App-generated notifications directed parents to age-and feeding-specific content within the app. Both groups completed Web-based surveys when infants were less than 3 months old (T1), at 6 months of age (T2), and 9 months of age (T3). Survival analysis was used to examine the duration of any breastfeeding and formula introduction, and cox proportional hazard regression was performed to examine the hazard ratio for ceasing breast feeding between the two groups. Multivariate logistic regression with adjustment for a range of child and parental factors was used to compare the exclusive breastfeeding, formula feeding behaviors, and timing of solid introduction between the 2 groups. Mixed effect polynomial regression models were performed to examine the group differences in growth trajectory from birth to T3. RESULTS: A total of 909 parents initiated the enrollment process, and a final sample of 645 parents (Growing healthy=301, Baby's First Food=344) met the eligibility criteria. Most mothers were Australian born and just under half had completed a university education. Retention of participants was high (80.3%, 518/645) in both groups. Most parents (226/260, 86.9%) downloaded and used the app; however, usage declined over time. There was a high level of satisfaction with the program, with 86.1% (143/166) reporting that they trusted the information in the app and 84.6% (170/201) claiming that they would recommend it to a friend. However, some technical problems were encountered with just over a quarter of parents reporting that the app failed to work at times. There were no significant differences between groups in any of the target behaviors. Growth trajectories also did not differ between the 2 groups. CONCLUSIONS: An mHealth intervention using a smartphone app to promote healthy infant feeding behaviors is a feasible and acceptable mode for delivering obesity prevention intervention to parents; however, app usage declined over time. Learnings from this study will be used to further enhance the program so as to improve its potential for changing infant feeding behaviors

Joint developmental trajectories of internalizing and externalizing problems from mid-childhood to late adolescence and childhood risk factors: Findings from a prospective pre-birth cohort.

There is limited evidence on heterogenous co-developmental trajectories of internalizing (INT) and externalizing (EXT) problems from childhood to adolescence and predictors of these joint trajectories. We utilized longitudinal data from Raine Study participants (n = 2393) to identify these joint trajectories from 5 to 17 years using parallel-process latent class growth analysis and analyze childhood individual and family risk factors predicting these joint trajectories using multinomial logistic regression. Five trajectory classes were identified: Low-problems (Low-INT/Low-EXT, 29%), Moderate Externalizing (Moderate-EXT/Low-INT, 26.5%), Primary Internalizing (Moderate High-INT/Low-EXT, 17.5%), Co-occurring (High-INT/High-EXT, 17%), High Co-occurring (Very High-EXT/High-INT, 10%). Children classified in Co-occurring and High Co-occurring trajectories (27% of the sample) exhibited clinically meaningful co-occurring problem behaviors and experienced more adverse childhood risk-factors than other three trajectories. Compared with Low-problems: parental marital problems, low family income, and absent father predicted Co-occurring and High Co-occurring trajectories; maternal mental health problems commonly predicted Primary Internalizing, Co-occurring, and High Co-occurring trajectories; male sex and parental tobacco-smoking uniquely predicted High Co-occurring membership; other substance smoking uniquely predicted Co-occurring membership; speech difficulty uniquely predicted Primary Internalizing membership; child's temper-tantrums predicted all four trajectories, with increased odds ratios for High Co-occurring (OR = 8.95) and Co-occurring (OR = 6.07). Finding two co-occurring trajectories emphasizes the importance of early childhood interventions addressing comorbidity