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Background: Preterm infants are a group at high risk of having experienced placental insufficiency. It is unclear which growth charts perform best in identifying infants at increased risk of stillbirth and other adverse perinatal outcomes. We compared 2 birthweight charts (population centiles and INTERGROWTH-21st birthweight centiles) and 3 fetal growth charts (INTERGROWTH-21st fetal growth charts, World Health Organization fetal growth charts, and Gestation Related Optimal Weight [GROW] customised growth charts) to identify which chart performed best in identifying infants at increased risk of adverse perinatal outcome in a preterm population.Methods and Findings: We conducted a retrospective cohort study of all preterm infants born at 24.0 to 36.9 weeks gestation in Victoria, Australia, from 2005 to 2015 (28,968 records available for analysis). All above growth charts were applied to the population. Proportions classified as <5th centile and <10th centile by each chart were compared, as were proportions of stillborn infants considered small for gestational age (SGA, <10th centile) by each chart. We then compared the relative performance of non-overlapping SGA cohorts by each chart to our low-risk reference population (infants born appropriate size for gestational age [>10th and <90th centile] by all intrauterine charts [AGAall]) for the following perinatal outcomes: stillbirth, perinatal mortality (stillbirth or neonatal death), Apgar <4 or <7 at 5 minutes, neonatal intensive care unit admissions, suspicion of poor fetal growth leading to expedited delivery, and cesarean section. All intrauterine charts classified a greater proportion of infants as <5th or <10th centile than birthweight charts. The magnitude of the difference between birthweight and fetal charts was greater at more preterm gestations. Of the fetal charts, GROW customised charts classified the greatest number of infants as SGA (22.3%) and the greatest number of stillborn infants as SGA (57%). INTERGROWTH classified almost no additional infants as SGA that were not already considered SGA on GROW or WHO charts; however, those infants classified as SGA by INTERGROWTH had the greatest risk of both stillbirth and total perinatal mortality. GROW customised charts classified a larger proportion of infants as SGA, and these infants were still at increased risk of mortality and adverse perinatal outcomes compared to the AGAall population. Consistent with similar studies in this field, our study was limited in comparing growth charts by the degree of overlap, with many infants classified as SGA by multiple charts. We attempted to overcome this by examining and comparing sub-populations classified as SGA by only 1 growth chart.Conclusions: In this study, fetal charts classified greater proportions of preterm and stillborn infants as SGA, which more accurately reflected true fetal growth restriction. Of the intrauterine charts, INTERGROWTH classified the smallest number of preterm infants as SGA, although it identified a particularly high-risk cohort, and GROW customised charts classified the greatest number at increased risk of perinatal mortality. [ABSTRACT FROM AUTHOR]

Given school enrollments but in the absence of a student residence census, we present a gravity-like model to infer the residential distribution of enrolled students across various administrative units. Multi-scale analysis of the effects of aggregation across different administrative levels allows for the identification of administrative units with sub-optimally located schools and highlights the challenges in allocating resources. Using this method, we verify that the current scheme of free cross-enrollment across administrative boundaries is needed in achieving universal education in the Philippines. [ABSTRACT FROM AUTHOR]

Internet and social media participation open doors to a plethora of positive opportunities for the general public. However, in addition to these positive aspects, digital technology also provides an effective medium for spreading hateful content in the form of cyberbullying, bigotry, hateful ideologies, and harassment of individuals and groups. This research aims to investigate the growing body of online hate research (OHR) by mapping general research indices, prevalent themes of research, research hotspots, and influential stakeholders such as organizations and contributing regions. For this, we use scientometric techniques and collect research papers from the Web of Science core database published through March 2019. We apply a predefined search strategy to retrieve peer-reviewed OHR and analyze the data using CiteSpace software by identifying influential papers, themes of research, and collaborating institutions. Our results show that higher-income countries contribute most to OHR, with Western countries accounting for most of the publications, funded by North American and European funding agencies. We also observed increased research activity post-2005, starting from more than 50 publications to more than 550 in 2018. This applies to a number of publications as well as citations. The hotbeds of OHR focus on cyberbullying, social media platforms, co-morbid mental disorders, and profiling of aggressors and victims. Moreover, we identified four main clusters of OHR: (1) Cyberbullying, (2) Sexual solicitation and intimate partner violence, (3) Deep learning and automation, and (4) Extremist and online hate groups, which highlight the cross-disciplinary and multifaceted nature of OHR as a field of research. The research has implications for researchers and policymakers engaged in OHR and its associated problems for individuals and society. [ABSTRACT FROM AUTHOR]

Microcephaly and Zika Virus infection (ZIKV) were declared Public Health Emergencies of International Concern by the World Health Organization in 2016. Brazil was considered the epicenter of the outbreak. However, the occurrence of both ZIKV and microcephaly in Brazil was not evenly distributed across the country. To better understand this phenomenon, we investigate regional characteristics at the municipal level that can be associated with the incidence of microcephaly, our response variable, and its relationship with ZIKV and other predictors. All epidemiological data in this study was provided by the Ministry of Health official database (DATASUS). Microcephaly was only confirmed after birth and the diagnostic was made regardless of the mother’s ZIKV status. Using exploratory spatial data analysis and spatial autoregressive Tobit models, our results show that microcephaly incidence is significantly, at 95% confidence level, related not only to ZIKV, but also to access to primary care, population size, gross national product, mobility and environmental attributes of the municipalities. There is also a significant spatial autocorrelation of the dependent variable. The results indicate that municipalities that show a high incidence of microcephaly tend to be clustered in space and that incidence of microcephaly varies considerably across regions when correlated only with ZIKV, i.e. that ZIKV alone cannot explain the differences in microcephaly across regions and their correlation is mediated by regional attributes. [ABSTRACT FROM AUTHOR]

Objective: The Centers for Disease Control and Prevention (CDC) coordinates a labor-intensive process to measure the prevalence of autism spectrum disorder (ASD) among children in the United States. Random forests methods have shown promise in speeding up this process, but they lag behind human classification accuracy by about 5%. We explore whether more recently available document classification algorithms can close this gap. Materials and methods: Using data gathered from a single surveillance site, we applied 8 supervised learning algorithms to predict whether children meet the case definition for ASD based solely on the words in their evaluations. We compared the algorithms’ performance across 10 random train-test splits of the data, using classification accuracy, F1 score, and number of positive calls to evaluate their potential use for surveillance. Results: Across the 10 train-test cycles, the random forest and support vector machine with Naive Bayes features (NB-SVM) each achieved slightly more than 87% mean accuracy. The NB-SVM produced significantly more false negatives than false positives (P = 0.027), but the random forest did not, making its prevalence estimates very close to the true prevalence in the data. The best-performing neural network performed similarly to the random forest on both measures. Discussion: The random forest performed as well as more recently available models like the NB-SVM and the neural network, and it also produced good prevalence estimates. NB-SVM may not be a good candidate for use in a fully-automated surveillance workflow due to increased false negatives. More sophisticated algorithms, like hierarchical convolutional neural networks, may not be feasible to train due to characteristics of the data. Current algorithms might perform better if the data are abstracted and processed differently and if they take into account information about the children in addition to their evaluations. Conclusion: Deep learning models performed similarly to traditional machine learning methods at predicting the clinician-assigned case status for CDC’s autism surveillance system. While deep learning methods had limited benefit in this task, they may have applications in other surveillance systems. [ABSTRACT FROM AUTHOR]

Social stress and inflammatory processes are strong regulators of one another. Considerable evidence shows that social threats trigger inflammatory responses that increase infection susceptibility in both humans and animals, while infectious disease triggers inflammation that in turn regulates social behaviours. However, no previous study has examined whether young children’s popularity and their rate of infectious disease are associated. We investigated the longitudinal bidirectional links between children’s popularity status as perceived by peers, and parent reports of a variety of infectious diseases that are common in early childhood (i.e. common cold as well as eye, ear, throat, lung and gastric infections). We used data from the ‘Matter of the First Friendship Study’ (MOFF), a longitudinal prospective multi-informant study, following 579 Norwegian pre-schoolers (292 girls, median age at baseline = six years) with annual assessments over a period of three years. Social network analysis was used to estimate each child’s level of popularity. Cross-lagged autoregressive analyses revealed negative dose–response relations between children’s popularity scores and subsequent infection (b = –0.18, CI = –0.29, –0.06, and b = –0.13, CI = –0.23, –0.03). In conclusion, the results suggest that children who are unpopular in early childhood are at increased risk of contracting infection the following year. [ABSTRACT FROM AUTHOR]

Background: Social media has become increasingly important for communication among young people. It is also often used to communicate suicidal ideation. Aims: To investigate the link between acute suicidality and language use as well as activity on Instagram. Method: A total of 52 participants, aged on average around 16 years, who had posted pictures of non-suicidal self-injury on Instagram, and reported a lifetime history of suicidal ideation, were interviewed using Instagram messenger. Of those participants, 45.5% reported suicidal ideation on the day of the interview (acute suicidal ideation). Qualitative text analysis (software ATLAS.ti 7) was used to investigate experiences with expressions of active suicidal thoughts on Instagram. Quantitative text analysis of language use in the interviews and directly on Instagram (in picture captions) was performed using the Linguistic Inquiry and Word Count software. Language markers in the interviews and in picture captions, as well as activity on Instagram were added to regression analyses, in order to investigate predictors for current suicidal ideation. Results: Most participants (80%) had come across expressions of active suicidal thoughts on Instagram and 25% had expressed active suicidal thoughts themselves. Participants with acute suicidal ideation used significantly more negative emotion words (Cohen’s d = 0.66, 95% CI: 0.088–1.232) and words expressing overall affect (Cohen’s d = 0.57, 95% CI: 0.001–1.138) in interviews. However, activity and language use on Instagram did not predict acute suicidality. Conclusions: While participants differed with regard to their use of language in interviews, differences in activity and language use on Instagram were not associated with acute suicidality. Other mechanisms of machine learning, like identifying picture content, might be more valuable. [ABSTRACT FROM AUTHOR]

Introduction: Childhood morbidities are common in Ghana. The present study sought to geospatially analyze morbidities among children (0–23 months of age) using five different survey datasets (1993–2014) from the Ghana Demographic and Health Survey. Methods: Logistic regression was used to examine childhood morbidity within a place of residence. Then three spatial statistical tools were applied to analyze morbidities among children (0–23 months of age). These tools were: spatial autocorrelation (Global Moran’s I)—used to examine clustering or dispersion patterns; cluster and outlier analysis (Anselin’s local Moran’s I)—to ascertain geographic composition of childhood morbidity clusters and outliers; and hot spot analysis (Getis-Ord G)—to identify clusters of high values (hot spots) and low values (cold spots). Results: Children in rural areas were much burdened with the occurrence of childhood morbidity. The study revealed positive spatial autocorrelation for childhood morbidity in Ghana. Childhood morbidity (diarrhoea, ARI, anaemia, and fever) clusters were identified within districts in the country. Children in rural areas were more likely to be morbid with diarrhoea, anaemia, and fever compared to those in urban areas. Hot spot districts for diarrhoea, anaemia and fever were mainly situated in semi-arid areas and those with ARI were located both at the semi-arid areas and coastal portions of Ghana. Conclusion: Rural children are much exposed to have higher burden of a childhood morbidity compared to their urban counterparts. Most semi-arid districts in Ghana are burdened with diarrhoea, ARI, anaemia, and fever. To minimize the occurrence of childhood morbidity in Ghana, designing of more context-based interventions to target hot spots districts of these morbidities are required in order to use scarce resources judiciously. [ABSTRACT FROM AUTHOR]

The prevalence of electronic cigarette (e-cigarette) use has rapidly increased among young people, while conventional cigarette use has decreased in this age group. However, some evidence suggests that e-cigarette use is likely to induce conventional cigarette smoking. The present study explored the social influence of the prevalence of e-cigarette use in the peer network and in the general population as a potential mechanism by which e-cigarette use affects adolescents’ overall smoking behaviours. For this purpose, we developed an agent-based model in which young agents repeatedly choose to smoke conventional cigarettes and/or e-cigarettes, or to remain non-smokers. The choice is based on the agent’s evaluation of the utility derived from smoking and attitude towards smoking (‘openness’), which is influenced by smoking prevalence in the agent’s peer network and in the broader society. We also assumed a ‘crossover’ effect between the different types of smoking. The model was calibrated with United States National Youth Tobacco Survey data to reflect real-world numbers. We further simulated the prevalence of different types of smoking under counterfactual scenarios with different levels of openness and crossover effects. The models developed successfully reproduced actual prevalence trends in different types of smoking from 2011 to 2014. Openness to smoking is associated with a dramatic increase in e-cigarette smoking and especially in dual smoking, which cancels out the decline in sole conventional smoking. Larger crossover effects are associated with a higher prevalence of conventional smoking. The simulation results indicate that the social influence of the prevalence of e-cigarette use may influence young people to initiate or continue conventional cigarette smoking. Assessing the impact of e-cigarettes in the general population as a ‘healthier’ alternative to conventional smoking may require carefully monitoring trends in young people’s smoking behaviours. [ABSTRACT FROM AUTHOR]

The present study reports on the first evaluation of a parenting intervention utilizing a smartphone app, BabyMind. The intervention aimed to facilitate mothers’ mind-mindedness—attunement to their infants’ internal states. Mothers in the intervention group (n = 90) used the BabyMind app from their infants’ births and were followed up at age 6 months (n = 66). Mothers in the control group (n = 151) were recruited when their infants were age 6 months and had never used the BabyMind app. Mind-mindedness when interacting with their infants was significantly higher in intervention group mothers than in control group mothers. The intervention was equally effective in facilitating mind-mindedness in young and older mothers. These findings are discussed in terms of the potential for interventions utilizing smartphone apps to improve parenting and children’s developmental outcome in vulnerable and hard-to-reach groups. [ABSTRACT FROM AUTHOR]

Background: Alcohol use and abuse constitute a major public health problem and identifying their determinants is a priority. Social network analysis can indicate how characteristics of social networks are related to individual health behaviors. A growing number of studies have used social network analysis to examine how social network characteristics influence adult alcohol consumption, but this literature has never been systematically reviewed and summarized. The current paper systematically reviews empirical studies that used social network analysis to assess the influence of social network characteristics on drinking behaviors in adults. Methods: A literature search of PubMed/MEDLINE, EMBASE, PsycINFO and Web of Science databases and a review of the reference lists of retrieved articles was conducted in March 2019. Two reviewers independently screened 5,510 non-duplicate records, and further screened the full text of 150 articles to determine their eligibility for inclusion. Seventeen articles were judged eligible and included. Results: Most studies were conducted among young adults (mean age<30), in university settings or follow up visits with adolescent networks moving into adulthood. The objectives and methods of the included studies were heterogeneous. All included studies reported a statistically significant association between a social network characteristic and an alcohol consumption-related outcome. Social network members drinking behaviors were associated with participants’ drinking behaviors in multiple ways. Discussion: In young adults, among whom the majority of identified studies were conducted, with whom they socialize and how they socialize appears to be associated with alcohol consumption; this was observed across methodologies and settings. We still know very little about the relationship of social networks to drinking in older age groups, and in populations most impacted by alcohol. As social networks appear to play a role in the consumption of alcohol in young adulthood, interventions that utilize social networks to help reduce harmful alcohol consumption should be considered. [ABSTRACT FROM AUTHOR]

Background: Heart rate variability (HRV) has been emerging in neonatal medicine. It may help for the early diagnosis of pathology and estimation of autonomous maturation. There is a lack of standardization and automation in the selection of the sequences to analyze and some features have not been explored in this specific population. The main objective of this study was to analyze the impact of the time length of the sequences on the estimation of linear and non-linear HRV features, including horizontal visibility graphs (HVG). Methods: HRV features were repeatedly measured with linear and non-linear methods on 2-, 5-, 10-minute sequences selected from the longest 15-min sequence and recorded on a weekly basis in 39 infants less than 31 weeks at birth. The associations between HRV measurements were analyzed through principal component analysis and k-means clustering. The effects of the time lengths on HRV measurements and post-menstrual age (PMA) were analyzed by linear mixed effect model for repeated measures. Results: The domains of analysis were concordant for their descriptive parameters of short (rMSSD, SD1 and HF) and long-term (SD, SD2 and LF) variability. α1 was correlated with the LF/HF and SD2/SD1. DC and AC were correlated with short-term variability estimates and significantly increased with GA and PMA. Shortening the windows of analysis increased the random measurement error for all the features and increased the bias for all but short term features and HVGs. Conclusion: The linear and non-linear measurements of HRV are correlated each other. Shortening the windows of analysis increased the random error for all the features and increased the bias for all but short term features and HVGs. Short-term HRV can be an index for evaluating the maturation in whatever sequence length. [ABSTRACT FROM AUTHOR]

Introduction: Depressive emotions can lead to subsequent unhealthy behaviors such as Internet addiction, especially in female adolescents; therefore, studies that examine the relationships among depression, health‑related behaviors, and Internet addiction in female adolescents are warranted. Purpose: To examine (1) the relationship between depression and health-related behaviors and (2) the relationship between depression and Internet addiction. Method: A cross-sectional study design was adopted using a structured questionnaire to measure depression, health-related behaviors, and Internet addiction in female adolescents. The data were collected from students of a junior college in southern Taiwan using convenience sampling to select the participants. The questionnaire was divided into four sections: demographics, the Center for Epidemiologic Studies Depression Scale (CES-D), the Health Promoting Lifestyle Profile (HPLP), and the Internet Addiction Test (IAT). Results: The final sample comprised 503 female junior college students, with the participants mainly aged between 15 to 22 years (mean age = 17.30 years, SD = 1.34). Regarding the HPLP scores, the overall score, nutrition subscale score, and self-actualization subscale score were significantly and negatively associated with the CES-D depression score (p < 0.05–0.01). In other words, depression level was lower in students who exhibited more healthy behaviors, put more emphasis on dietary health, and had higher levels of self-admiration and confidence toward life. Regarding the IAT scores, the overall score and six domain scores were all positively associated (p < 0.01) to the CES-D depression score. In other words, the higher an individual’s Internet addiction score was, the higher her depression level was. Conclusions: The results confirmed the relationship between depression, health-related behaviors, and Internet addiction. The cultivation of health-related behaviors may help in lowering depressive symptoms. Teenagers with depression have higher risks of developing Internet addiction, and such addiction is likely to affect their daily functioning. [ABSTRACT FROM AUTHOR]

Exploiting nation-wide data from the Danish National Birth Cohort, we show that children’s emotional and behavioral problems measured by the Strengths and Difficulties Questionnaire (SDQ) are closely related to their performance in standardized academic tests for reading and mathematics in sixth grade. The relationship is remarkably linear across the entire distribution for both the total difficulties score and subscale scores of the SDQ; higher scores on the SDQ (more problems) are related to worse performance in academic tests. We assess the similarity across respondent type; parent (child age 7 and 11), teacher (child age 11) and self-reported scores (child age 11), and find that teacher and parent reported scores have very similar slopes in the SDQ–test score relationship, while the child reported SDQ in relation to the academic test performance has a flatter slope. [ABSTRACT FROM AUTHOR]

Introduction: La Maison Bleue is a community-based perinatal health and social centre in Montreal that provides services during pregnancy up to age five to families living in vulnerable contexts. The study aimed to describe: 1) the challenges and protective factors that affect the well-being of migrant families receiving care at La Maison Bleue; and 2) how La Maison Bleue strengthens resilience among these families. Methods: We conducted a focused ethnography. Immigrants, refugees, asylum seekers and undocumented migrants were invited to participate. We collected data from November to December 2017 via semi-structured interviews and participant observation during group activities at La Maison Bleue. Data were thematically analysed. Results: Twenty-four mothers participated (9 interviewed, 17 observed). Challenges to well-being included family separation, isolation, loss of support, the immigration process, an unfamiliar culture and environment, and language barriers. Key protective factors were women’s intrinsic drive to overcome difficulties, their positive outlook and ability to find meaning in their adversity, their faith, culture and traditions, and supportive relationships, both locally and transnationally. La Maison Bleue strengthened resilience by providing a safe space, offering holistic care that responded to both medical and psychosocial needs, and empowering women to achieve their full potential towards better health for themselves and their families. Conclusion: Migrant mothers have many strengths and centres like La Maison Bleue can offer a safe space and be an empowering community resource to assist mothers in overcoming the multiple challenges that they face while resettling and raising their young children in a new country. [ABSTRACT FROM AUTHOR]

Parenthood, marital status and social networks have been shown to relate to the well-being and mental health of older people. Using a large sample of respondents aged 50 and older from 16 European countries, we identify the associations of well-being and mental health with family status. Making use of detailed social network data of the respondents, we also identify how different social support networks correlate with the well-being and health indicators. We observe positive associations for all network types, over and beyond any direct associations of family status with well-being. Results suggest that non-residential children are important providers of social support for their parents at older age. [ABSTRACT FROM AUTHOR]

People are connected by various social networks, resulting in the interdependence of consumer choice. Therefore, it is very important and realistic to assume choice interdependence in private car ownership modeling. In this paper, we investigate the interdependence of private car ownership choice using a spatial autoregressive binary probit model estimated by the Bayesian Markov chain Monte Carlo (MCMC) method. Constructing the autoregressive matrix demographically shows that the private car ownership choice of a household is dependent on other household choices. Compared with the pure binary probit model estimated by the MCMC method, the spatial autoregressive model achieves a significant improvement both in loglikelihood value and log marginal density value, which are calculated using the importance sampling method of Newton and Raftery, from approximately -202 to approximately -63 and from -208 to -145, respectively. Moreover, the results indicated by the spatial autoregressive probit model suggest that the number of children, the ownership of an apartment or the availability of a parking lot are positively and significantly associated with the private car ownership level. To test the out-of-sample performance of the model, we estimate the model using 600 data points and test it using another 148 data points. The results indicate that the predictive power is greatly improved. Finally, we analyze the augmented parameter and discover that it is associated with the parking variable in addition to the license variable. [ABSTRACT FROM AUTHOR]

Given the highly dynamic and complex nature of the human gut microbial community, the ability to identify and predict time-dependent compositional patterns of microbes is crucial to our understanding of the structure and functions of this ecosystem. One factor that could affect such time-dependent patterns is microbial interactions, wherein community composition at a given time point affects the microbial composition at a later time point. However, the field has not yet settled on the degree of this effect. Specifically, it has been recently suggested that only a minority of taxa depend on the microbial composition in earlier times. To address the issue of identifying and predicting temporal microbial patterns we developed a new model, MTV-LMM (Microbial Temporal Variability Linear Mixed Model), a linear mixed model for the prediction of microbial community temporal dynamics. MTV-LMM can identify time-dependent microbes (i.e., microbes whose abundance can be predicted based on the previous microbial composition) in longitudinal studies, which can then be used to analyze the trajectory of the microbiome over time. We evaluated the performance of MTV-LMM on real and synthetic time series datasets, and found that MTV-LMM outperforms commonly used methods for microbiome time series modeling. Particularly, we demonstrate that the effect of the microbial composition in previous time points on the abundance of taxa at later time points is underestimated by a factor of at least 10 when applying previous approaches. Using MTV-LMM, we demonstrate that a considerable portion of the human gut microbiome, both in infants and adults, has a significant time-dependent component that can be predicted based on microbiome composition in earlier time points. This suggests that microbiome composition at a given time point is a major factor in defining future microbiome composition and that this phenomenon is considerably more common than previously reported for the human gut microbiome. [ABSTRACT FROM AUTHOR]

Neuroimaging studies of subjects with ADHD typically show altered functional connectivity in prefrontal, striatal, and several temporal brain regions. While the majority of studies have focused on connectivity that is averaged over time, we investigated the temporal dynamics of brain network changes in resting-state fMRI. Using the ADHD-200 consortium, we characterized the time course of latent state changes using Hidden Markov Modeling, and compared state changes between boys and girls with ADHD along with typically developing controls. Sex differences were found in latent state switching, with boys dwelling longer in a given state than girls, and concurrently having fewer overall state transitions. These sex differences were found in children with ADHD and in typically developing controls. Children with ADHD were also found to be more variable in terms of state transitions than controls. These findings add to the growing literature on neural sex differences and may be related to the sex difference in focal versus diffuse attention. [ABSTRACT FROM AUTHOR]

Objectives: In August 2016, new prescription guidelines were introduced in Hungary to reduce the co-payments for antibiotics among children aged 0-4. This study aims at analysing the implementation of this policy and its effect on the use of antibiotics. Methods: The analysis is based on administrative prescription records between January 2010—February 2018, covering the entire population of Hungary aged 0-7. Spatial autocorrelation indices are calculated and settlement level regression models are estimated to analyse the spatial variation in the application of the new guidelines. The effect of reduced co-payments on antibiotic use is estimated with a difference-in-differences type model: the treatment and control groups are children aged 0-4 and 5-7, respectively; the treatment and control periods are August 2016—February 2018 and January 2010—July 2016, respectively. Results: The new prescription guidelines are more widely applied in settlements with higher per capita income and lower unemployment rate. Adherence to the new guidelines is spatially clustered. A 10–15% decrease in the out-of-pocket costs of antibiotics is estimated to increase the consumption of antibiotics by about 5% (95% CI: 2.63%–7.55%). Conclusions: In the absence of clear enforcement mechanisms, the adoption of the new prescription guidelines is selective, contradicting the aims of the policy of making antibiotics affordable for the poor children. The results point to the possible role of physicians’ information networks in the application of prescription guidelines. The use of antibiotics among children aged 0-4 is responsive to the price subsidy of antibiotics. [ABSTRACT FROM AUTHOR]

Background: In previous pilot work we demonstrated that a novel automated signal analysis tool could accurately identify successful ablation sites during Wolff-Parkinson-White (WPW) ablation at a single center. Objective: We sought to validate and refine this signal analysis tool in a larger multi-center cohort of children with WPW. Methods: A retrospective review was performed of signal data from children with WPW who underwent ablation at two pediatric arrhythmia centers from 2008–2015. All patients with WPW ≤ 21 years who underwent invasive electrophysiology study and ablation with ablation signals available for review were included. Signals were excluded if temperature or power delivery was inadequate or lesion time was < 5 seconds. Ablation lesions were reviewed for each patient. Signals were classified as successful if there was loss of antegrade and retrograde accessory pathway (AP) conduction or unsuccessful if ablation did not eliminate AP conduction. Custom signal analysis software analyzed intracardiac electrograms for amplitudes, high and low frequency components, integrated area, and signal timing components to create a signal score. We validated the previously published signal score threshold 3.1 in this larger, more diverse cohort and explored additional scoring options. Logistic regression with lasso regularization using Youden’s index criterion and a cost-benefit criterion to identify thresholds was considered as a refinement to this score. Results: 347 signals (141 successful, 206 unsuccessful) in 144 pts were analyzed [mean age 13.2 ± 3.9 years, 96 (67%) male, 66 (45%) left sided APs]. The software correctly identified the signals as successful or unsuccessful in 276/347 (80%) at a threshold of 3.1. The performance of other thresholds did not significantly improve the predictive ability. A signal score threshold of 3.1 provided the following diagnostic accuracy for distinguishing a successful from unsuccessful signal: sensitivity 83%, specificity 77%, PPV 71%, NPV 87%. Conclusions: An automated signal analysis software tool reliably distinguished successful versus unsuccessful ablation electrograms in children with WPW when validated in a large, diverse cohort. Refining the tools using an alternative threshold and statistical method did not improve the original signal score at a threshold of 3.1. This software was effective across two centers and multiple operators and may be an effective tool for ablation of WPW. [ABSTRACT FROM AUTHOR]

The 5Rights Youth Juries are an educational intervention to promote digital literacy by engaging participants (i.e. jurors) in a deliberative discussion around their digital rights. The main objective of these jury-styled focus groups is to encourage children and young people to identify online concerns and solutions with a view to developing recommendations for government policy-makers and industry chiefs. The methodology included a series of dramatized scenarios that encourage jurors to deliberate about their digital rights. This paper compares two formats for these scenarios: live actors and professionally recorded and edited videos of the same actors. Results failed to show any major differences between formats indicating the cost-effectiveness of the video-recorded format and the possibility for others to run the 5Rights Youth Juries with the support of an online open educational resource. [ABSTRACT FROM AUTHOR]

Objective: Adaptation to social life changes after migration may be beneficial or detrimental to migrants’ oral health outcomes and related behaviors. This systematic review aims to synthesize the scientific literature on the impact of social support on immigrants’ and ethnic minorities’ oral health status and/or behaviors. Methods: A comprehensive electronic search, up to November 2018, was conducted using five electronic databases. We included cross-sectional and longitudinal quantitative studies that examine associations between social support and oral health outcomes among immigrants and ethnic minorities. Study selection, data extraction, and risk of bias assessment were completed in duplicate and the Newcastle-Ottawa checklist was used to appraise the methodological quality of the quantitative studies. Results: A total of 26 studies met the eligibility criteria. Included studies examined multiple oral health outcomes such as dental care utilization, oral health behaviors, oral health problems, self-rated oral health, oral health knowledge, and oral health-related quality of life among immigrants and ethnic minorities. The social support level is assessed either by social support indicators or by adapting certain scales. Overall, social support was found to be positively associated with dental care utilization, number of carious teeth, periodontal disease, oral health behaviors, oral health knowledge, oral health-related quality of life, and self-rated oral health. Conclusion: Although immigrants and ethnic minorities encounter several challenges after migration to a new country that could affect their oral health, social support from their surrounding environment in the form of structural or functional support plays an important role in improving their oral health outcomes. [ABSTRACT FROM AUTHOR]

American Indian and Alaska Native (AI/AN) youth are more likely to ever have had sex, and to have engaged in sexual activity prior to age 13 compared to all other race groups. It is essential to understand the development of skills to refuse sexual experience in early adolescence in order to reduce disparities associated with early sexual debut among AI/AN youth. Familial, social, and individual factors can act as protective influences on adolescent sexual experience; however, in other settings, research has shown that frequent residential mobility disrupts these protective influences and may increase the likelihood of adolescent sexual activity. AI/AN youth are highly mobile, and, as a result, may be especially vulnerable to increased sexual risk. To date, no prior study has considered the impact of residential mobility on AI/AN youth sexual experience, nor the influence on precursors that reduce initiation of sex. We used data from a longitudinal study of AI/AN youth attending all middle schools from a Northern Plains reservation from 2006–2009 to estimate a structural equation model based on a cultural and age adapted theoretical framework. The tested model included frequent residential mobility as the independent variable and sex refusal self-efficacy as the dependent variable. Mediating variables included factors related to individual risks, psychological well-being, and social supports. Results indicate a direct association between residential mobility and sex refusal self-efficacy (-.29, p = 0.05) and an indirect association mediated by deviant peers (-.08, p = .05). Other mediating variables did not provide insight on the mechanism by which residential mobility influences skills to refuse sexual intercourse among AI/AN youth in early adolescence. Findings provide evidence for an association between residential mobility and precursors to sexual experience suggesting augmenting sexual health interventions for highly mobile youth. [ABSTRACT FROM AUTHOR]

Objective: Suicide in adolescents is a major problem worldwide and previous history of suicide ideation and attempt represents the strongest predictors of future suicidal behavior. The aim of this study was to develop prediction model to identify Korean adolescents of high risk suicide (= who have history of suicide ideation/attempt in previous year) using machine learning techniques. Methods: A nationally representative dataset of Korea Youth Risk Behavior Web-based Survey (KYRBWS) was used (n = 59,984 of middle and high school students in 2017). The classification process was performed using machine learning techniques such as logistic regression (LR), random forest (RF), support vector machine (SVM), artificial neural network (ANN), and extreme gradient boosting (XGB). Results: A total of 7,443 adolescents (12.4%) had a previous history of suicidal ideation/attempt. In the multivariable analysis, sadness (odds ratio [OR], 6.41; 95% confidence interval [95% CI], 6.08–6.87), violence (OR, 2.32; 95% CI, 2.01–2.67), substance use (OR, 1.93; 95% CI, 1.52–2.45), and stress (OR, 1.63; 95% CI, 1.40–1.86) were associated factors. Taking into account 26 variables as predictors, the accuracy of models of machine learning techniques to predict the high-risk suicidal was comparable with that of LR; the accuracy was best in XGB (79.0%), followed by SVM (78.7%), LR (77.9%), RF (77.8%), and ANN (77.5%). Conclusions: The machine leaning techniques showed comparable performance with LR to classify adolescents who have previous history of suicidal ideation/attempt. This model will hopefully serve as a foundation for decreasing future suicides as it enables early identification of adolescents at risk of suicide and modification of risk factors. [ABSTRACT FROM AUTHOR]

Adolescence is a developmental phase in which feelings of loneliness often increase. It is also a time period during which computer-mediated communication (CMC) is frequently used by youth to communicate with their peers. Strong family relationships protect youth from experiencing a wide range of adversities and mental health problems, including loneliness, and yet use of CMC to contact peers may leave adolescents feeling disconnected and lonely while also limiting the amount of time they spend with their family. This study examines the association between CMC and feelings of loneliness among Canadian youth, with family communication explored as an effect modifier. The study base was the Canadian 2013–2014 Health Behaviour in School-aged Children study used in a cross-sectional analysis (N = 30117; grades 6–10). Random-effects multilevel Poisson regression methods were used to quantify risks for adolescent loneliness among daily vs. non-daily users of verbal CMC (e.g., Skype, phone calls), text/instant messaging and social media CMC with friends. Effect modification was tested via the inclusion of modelled interaction terms. Family communication quality moderated the relationship between daily CMC use and loneliness among Canadian youth. Among youth experiencing high relative quality of family communication, daily use of verbal and social media CMC to contact friends was positively associated with reports of loneliness, compared to non-daily users. Findings suggest that family communication must remain central in societal discussions of youth loneliness, mental health and use of CMC. [ABSTRACT FROM AUTHOR]

Background: In recent years, researchers have begun to explore the implications of shyness for the psychosocial wellbeing of children and adolescents, exploring its association with internalizing problems. Research in an Italian context is hindered by the lack of a validated self-report measure of shyness. We report two studies aimed to assess the psychometric properties of an Italian translation of the Children’s Shyness Questionnaire (CSQ-it) and investigate its correlations with convergent and divergent constructs. The first study aimed to examine associations between CSQ-it and self-report measures of anxiety and somatic symptoms and attachment with parents and peers. The second study aimed to investigate its relations to internet addiction. Methods: The self-report measures were completed by 550 participants in the first study and 131 participants in the second study. Parents provided information on their child’s problems. Psychometric properties were assessed by Cronbach’s alpha in both studies and by exploratory and confirmatory factor analysis in Study 1. The relations between shyness and measures of internalizing problems and attachments were analyzed by correlational methods. In Study 2 a moderated mediation model tested the hypothesis that the relationship between shyness and internet addiction is mediated by somatic symptoms and that shyness moderates the relationship between somatic symptoms and internet addiction. Results: The reliability and validity of the Italian Version of the Children’s Shyness Questionnaire were satisfactory. Results from confirmatory factor analyses confirmed the single-factor model of the questionnaire previously identified in North American and Chinese studies. There were significant correlations between shyness, anxious and somatic symptomatology, impaired psychosocial functioning and specific components of attachment relationships. In Study 2 the indirect effect of shyness on internet addiction through somatic symptoms was significant as well as significantly moderated for high shyness scores but not for low levels of shyness. Conclusion: To our knowledge this is the first study that explored the psychometric proprieties of the Children’s Shyness Questionnaire in the Italian context. Findings demonstrated that this self-reported measure of shyness has sound psychometric properties and can be used as a sensitive and appropriate instrument for the assessment of shyness in children and adolescents. [ABSTRACT FROM AUTHOR]

Following the March 2011 accident at Fukushima Daiichi Nuclear Power Plant, many residents of Fukushima have faced anxieties about the health impacts of radiation exposure. Considering that source of information may influence resident anxiety, this study aimed to elucidate the correlation between the two. In addition, a health literacy query was included to examine a possible relationship between anxiety and health literacy skills. A mail survey was conducted in August 2016 among 2000 residents of Fukushima Prefecture aged 20 to 79 years. Survey items included questions about current health anxieties caused by radiation, trusted sources of information about radiation, and media used to obtain information on radiation. The survey valid response rate was 43.4%. Results of multiple linear regression analysis revealed that anxiety was significantly higher for the groups indicating “trust in citizen groups” and “use of internet sites.” Anxiety was significantly lower for the groups indicating “trust in government ministries,” “trust in local government,” and “use of local broadcast television.” Also anxiety was significantly lower for groups with higher health literacy. It was found that the significant relationship to anxiety varies depending on the sources of trust and media used. There is a possibility that this was caused by the difference between the contents of each information and media reports. In preparation for any future nuclear accident, government may consider action to improve the media literacy of residents. In addition, improving health literacy of both the recipient and the sender of information can improve access to information and thereby safeguard the health and well-being of the public. [ABSTRACT FROM AUTHOR]

Background: Children living in disadvantaged socio-economic circumstances (SEC) are more commonly victims of bullying, but pathways leading to social inequalities in being bullied are unclear. We assess how early life risk factors might mediate the increased risk of being bullied at age seven for children living in disadvantaged circumstances. Material and methods: Using data from 5,857 children in the UK Millennium Cohort Study (MCS) we calculate risk ratios (RR) for being bullied at age seven (child-reported), by household income quintile. Socially patterned risk factors for being bullied relating to social networks, family relationships and child characteristics from birth to age five were adjusted for to assess if they mediated any association between SEC and being bullied. Results: 48.6% of children reported having been bullied. Children living in the lowest income households were at 20% greater risk of being bullied compared to those from the highest (RR1.20, 95%CI 1.06,1.36). Controlling for social networks, family relationships and child characteristics attenuated the increased risk for children in low income households to aRR 1.19 (95%CI 1.05, 1.35), aRR 1.16 (95%CI 1.02,1.32) and aRR 1.13 (95%CI 1.00,1.28) respectively. Our final model adjusted for risk factors across all domains attenuated the RR by 45% (aRR 1.11,95%CI 0.97,1.26). Conclusions: About half of children reported being bullied by age seven with a clear social gradient. The excess risk in children growing up in disadvantaged circumstances was partially explained by differences in their early years relating to their social network, family relationships and the child’s own abilities and behaviours. Policies to reduce inequalities in these risk factors may also reduce inequalities in the risk of being bullied in childhood. [ABSTRACT FROM AUTHOR]

The Demographic and Health Surveys (DHS) are a major source for many demographic and health indicators in developing countries. Although these indicators are well defined in the literature, using survey data to calculate some of these indicators has never been an easy task for data users. This paper presents the software, a user-friendly R package developed to calculate fertility indicators, such as the total fertility rate, general fertility rate, and age-specific fertility rates, and childhood mortality indicators, such as the neonatal mortality rate, post-neonatal mortality rate, infant mortality rate, child mortality rate, and under-5 mortality rate, from the DHS data. The package allows for national and subnational indicators. In addition, the package calculates sampling error indicators such as standard error, design effect, relative standard error, and confidence interval for each demographic indicator. The package can also be used to calculate the same indicators from other population surveys such as the Multiple Indicator Cluster Survey (MICS). [ABSTRACT FROM AUTHOR]

Understanding which tobacco products adolescents use first can lead to insights for tobacco prevention interventions and policies. We used cross-sectional data from high school students who reported ever using a tobacco product from the 2017 North Carolina Youth Tobacco Survey (n = 1,053). In multivariable regressions, we examined how demographic and psychosocial factors were associated with adolescents’ first product tried and how first product tried was associated with current tobacco use (i.e., no use, use of a single product, use of multiple products) and frequency of tobacco use. Cigarettes (34.8%) and e-cigarettes (33.7%) were the most frequently reported first products tried, followed by cigars (15.6%), smokeless tobacco (10.7%), waterpipe (4.0%), and other tobacco products (i.e., pipe tobacco or some other tobacco product) (1.2%). Demographic differences in adolescents’ first product tried existed, with Black adolescents having higher odds of initiating tobacco use via cigars (aOR: 6.17, 95% CI: 3.75, 10.14). Adolescents who initiated tobacco use via cigars (aOR: 2.33, 95% CI: 1.31, 4.13) or smokeless tobacco (aOR: 2.45, 95% CI: 1.18, 5.04) had higher odds of being a multiple current tobacco product user, whereas adolescents who initiated tobacco use via e-cigarettes (aOR: 0.57, 95% CI: 0.34, 0.93) had lower odds of being a multiple current tobacco product user. Additionally, adolescents who initiated tobacco use via smokeless tobacco had higher odds of currently using at least one tobacco product frequently (aOR: 1.90, 95% CI: 1.04, 3.48), while adolescents who initiated tobacco use via e-cigarettes had lower odds of currently using at least one tobacco product frequently (aOR: 0.40, 95% CI: 0.23, 0.70). These findings suggest that most adolescents reported initiating tobacco use via cigarettes or e-cigarettes and that trying certain products first (e.g., cigars, smokeless tobacco) was associated with higher odds of multiple current tobacco product use. [ABSTRACT FROM AUTHOR]

Background: Spouses have a key position in the treatment of patients with acute leukemia (AL) who are increasingly managed in an outpatient setting. Patients live at home but appear at the hospital every second day for follow-up visits. Patients must adhere to specific precautions due to an impaired immune system, which challenges and influence the life of the whole family. This qualitative study, based on individual and group interviews with spouses to AL patients in curative intended treatment, elucidates how the intense and substantial caregiver role affects the everyday lives of spouses to AL patients in curative intended treatment. Methods: Qualitative semi-structured group interviews (n = 6) and individual interviews (n = 5) with spouses to AL patients were conducted at different time points during the whole course of treatment. Theories of everyday life served as the theoretical framework. Results: The spouses described their life as a constant state of vigilance and attention as a consequence of the responsibility they felt arising from the treatment in the outpatient setting. These made them experience their role as a burden. The social life of the spouses and the families suffered substantially due to the precautions that were instated in the home. However, many experienced that relations in the family were developed positively. Conclusions: Close relatives experience additional psychosocial burdens instigated by the outpatient management regimens. This is important knowledge for the health care system to include in future development of AL outpatient settings, to prioritize and support offers to the relatives that recognize their sense of burden. This could apply not only to relatives of AL patients but to the relatives of other severely ill patients as well. [ABSTRACT FROM AUTHOR]

Background: BMI is a feasible and recommended measure for overweight and obesity screening in children and adolescents. The study aimed to determine how often physicians correctly identified obesity/ overweight status in children and adolescents by using BMI percentile charts. Methods: This retrospective cross-sectional study reviewed the paper medical records of children and adolescents (6–14 years) who visited family medicine and pediatric outpatient clinics (Jan-June 2012) in a medical city in Riyadh. Investigators calculated BMI percentiles (using height, weight, age and gender data retrieved from the records) in order to identify patient weight status. Physician documentation of obesity/overweight diagnoses in patient problem lists were cross checked against their BMI percentile to assess the accuracy of physicians’ identification of weight status. The recommended management plan for identified patients was also recorded. Results: A total of 481 charts were reviewed, 213 (44%) children were seen by family medicine physicians and 268 (56%) by pediatricians. The sample was equally distributed by gender. Height was undocumented for 13% (71) of visiting patients. Eighteen percent of patients (86) were classified as overweight (35)/obese (51) according to age and sex adjusted BMI percentile. Physicians’ correctly identified and documented weight status in 20% of overweight/obese patients: 17 out of 86 subjects. Weight status identification was higher among pediatricians—25% as compared to family medicine physicians—10% [p = 0.08]. Dietary referral was the most common management plan for the identified children. Physicians were more likely to identify obese children {≥95th} compared to overweight {≥85th - 95th} children. Subjects whose BMI for age classified them into the highest BMI percentile category {≥95th} were more likely to be correctly identified (29%) compared to those classified within {≥85th - 95th} category—6% [p = 0.007]. Conclusion: Physician identification of obesity/ overweight status for children and adolescents was low, irrespective of their specialty, and despite the condition being prevalent in the sample. Future research that concentrates on interventions that may improve documentation of obesity/overweight diagnoses and parameters needed for BMI indices would be beneficial. [ABSTRACT FROM AUTHOR]

Introduction: Grief among bereaved parents is known to cause psychological distress and physical illness, but knowledge concerning factors that can contribute to health promotion after bereavement is scarce. Childhood cancer remains the most common non-accidental cause of death among children in Norway. The aim of the present study was to explore if resilience factors among cancer-bereaved parents could predict whether they will be able to come to terms with their grief 2–8 years following the loss. Methods: A Norwegian cross-sectional national survey was conducted among 161 cancer-bereaved parents using a study-specific questionnaire. Logistic regression was used to explore whether resilience factors predicted parents' grief outcome 2–8 years after their loss. Results: On the Resilience Scale for Adults (RSA), three of the resilience factors contributed significantly in predicting whether the parents in the present study would come to terms with their grief 2–8 years after the loss their child: "Perception of self "(OR 2.08, p = .048), "Social resources" (OR 2.83, p = .008) and "Family cohesion" (OR .41, p = .025). The results showed a negative relationship between time since loss (2–6 years) and whether the parents answered that they had come to terms with their grief (p = < .05). The loss of a parent (OR .30, p = .030) combined with the loss of their child had a negative and significant effect on whether they indicated that they had processed their grief. Conclusion: The total score of RSA and three of the six resilient factors contributed significantly in predicting whether cancer-bereaved parents in the present study indicated that they had come to terms with their grief to a great extent. The present study supports hypotheses that regard resilience as an important contribution in predicting healthy outcomes in people exposed to adverse life events. [ABSTRACT FROM AUTHOR]

Background: Male circumcision devices have the potential to accelerate adolescent voluntary medical male circumcision roll-out. Here, we present findings on safety, acceptability and satisfaction from active surveillance of PrePex implementation among 618 adolescent males (13–17 years) circumcised in Zimbabwe. Methods: The first 618 adolescents consecutively circumcised from October 2015 to October 2016 using PrePex during routine service delivery were actively followed up. Outcome measures included PrePex uptake, attendance for post-circumcision visits and adverse events (AEs). A survey was conducted amongst 500 consecutive active surveillance clients to assess acceptability and satisfaction with PrePex. Results: A total of 1,811 adolescent males were circumcised across the three PrePex active surveillance sites. Of these, 870 (48%) opted for PrePex but only 618/870 (71%) were eligible. Among the 618, two (0.3%) self-removals requiring surgery (severe AEs), were observed. Four (0.6%) removals by providers (moderate AEs) did not require surgery. Another 6 (1%) mild AEs were due to: bleeding (n = 2), swelling (n = 2), and infection (n = 2). All AEs resolved without sequelae. Adherence to follow-up appointments was high (97.7% attended 7 day visit). A high proportion (71.6%) of survey respondents said they heard about PrePex from a mobilizer; 49.8% said they chose PrePex because they wanted to avoid the pain associated with the surgical procedure/surgery on their penis. Acceptability and satisfaction with PrePex was high; 95.4% indicated willingness to recommend PrePex to peers. A majority (92%) reported experiencing pain when PrePex was being removed. Conclusions: Active surveillance of the first 618 adolescent males circumcised using PrePex suggests that the device is both safe and acceptable when used in routine service delivery among 13–17 year-olds. There is need to intensify specific demand generation activities for PrePex male circumcision among this group of males. [ABSTRACT FROM AUTHOR]

This paper demonstrates how Geographic Information Systems (GIS) can be utilized to study the effects of spatial phenomena. Since experimental designs such as Randomized Controlled Trials are generally not feasible for spatial problems, researchers need to rely on quasi-experimental approaches using observational data. We provide a regression-based framework of the key procedures for GIS-based empirical research design using georeferenced point data for both spatial events of interest and subjects exposed to the events. We illustrate its utility and implementation through a case study on the impacts of the Cambodian genocide under the Pol Pot regime on post-conflict education. [ABSTRACT FROM AUTHOR]

Background: Rapid antibiotic administration is known to improve sepsis outcomes, however early diagnosis remains challenging due to complex presentation. Our objective was to develop a model using readily available electronic health record (EHR) data capable of recognizing infant sepsis at least 4 hours prior to clinical recognition. Methods and findings: We performed a retrospective case control study of infants hospitalized ≥48 hours in the Neonatal Intensive Care Unit (NICU) at the Children’s Hospital of Philadelphia between September 2014 and November 2017 who received at least one sepsis evaluation before 12 months of age. We considered two evaluation outcomes as cases: culture positive–positive blood culture for a known pathogen (110 evaluations); and clinically positive–negative cultures but antibiotics administered for ≥120 hours (265 evaluations). Case data was taken from the 44-hour window ending 4 hours prior to evaluation. We randomly sampled 1,100 44-hour windows of control data from all times ≥10 days removed from any evaluation. Model inputs consisted of up to 36 features derived from routine EHR data. Using 10-fold nested cross-validation, 8 machine learning models were trained to classify inputs as sepsis positive or negative. When tasked with discriminating culture positive cases from controls, 6 models achieved a mean area under the receiver operating characteristic (AUC) between 0.80–0.82 with no significant differences between them. Including both culture and clinically positive cases, the same 6 models achieved an AUC between 0.85–0.87, again with no significant differences. Conclusions: Machine learning models can identify infants with sepsis in the NICU hours prior to clinical recognition. Learning curves indicate model improvement may be achieved with additional training examples. Additional input features may also improve performance. Further research is warranted to assess potential performance improvements and clinical efficacy in a prospective trial. [ABSTRACT FROM AUTHOR]

Background: In an intensive care units, experts in mechanical ventilation are not continuously at patient’s bedside to adjust ventilation settings and to analyze the impact of these adjustments on gas exchange. The development of clinical decision support systems analyzing patients’ data in real time offers an opportunity to fill this gap. Objective: The objective of this study was to determine whether a machine learning predictive model could be trained on a set of clinical data and used to predict transcutaneous hemoglobin oxygen saturation 5 min (5min SpO2) after a ventilator setting change. Data sources: Data of mechanically ventilated children admitted between May 2015 and April 2017 were included and extracted from a high-resolution research database. More than 776,727 data rows were obtained from 610 patients, discretized into 3 class labels (< 84%, 85% to 91% and c92% to 100%). Performance metrics of predictive models: Due to data imbalance, four different data balancing processes were applied. Then, two machine learning models (artificial neural network and Bootstrap aggregation of complex decision trees) were trained and tested on these four different balanced datasets. The best model predicted SpO2 with area under the curves < 0.75. Conclusion: This single center pilot study using machine learning predictive model resulted in an algorithm with poor accuracy. The comparison of machine learning models showed that bagged complex trees was a promising approach. However, there is a need to improve these models before incorporating them into a clinical decision support systems. One potentially solution for improving predictive model, would be to increase the amount of data available to limit over-fitting that is potentially one of the cause for poor classification performances for 2 of the three class labels. [ABSTRACT FROM AUTHOR]

Youth gambling is an increasing concern. As a response, the “Don’t Gamble Away our Future (DGAOF)” program has been implemented among children in central Illinois. We aim to assess the long-term effectiveness of this school-based youth gambling prevention program in Illinois using the data from 2005 to 2009. The intervention included interactive PowerPoint presentations and prevention materials in parent packets. Students aged 8 to 18 years were eligible to participate in the intervention and the questionnaire pre-post knowledge tests (total score 0–9). Students in 5th grade and above also received a gambling behavior screen test using the Modified South Oaks Gambling Screening for Teens (MSOGST) for identifying probable gamblers. Multivariable generalized mixed models were conducted to detect the effects of a 5-year youth gambling prevention program as controlling potential confounders. A total of 16,262 and 16,421 students completed pre-post tests and MSOGST tests, respectively. Of 16,262, half were female, the majority (76.1%) were from senior high school, and 21.3% received the intervention at least twice. The median gap between interventions was 368 days. Students receiving multiple interventions had higher scores on the pre-test as compared to those receiving a single intervention (P<0.001 for all comparisons among groups), and they demonstrated an increasing trend of awareness about gambling over time (P<0.001 for multiple interventions; P = 0.538 for single intervention). The prevalence of problem gambling had decreased among students receiving the intervention twice as compared to receiving the intervention once (7.9% versus 9.4%; OR = 0.89, 95% CL: 0.82–0.97). However, this effect was not confirmed among students receiving the intervention three or more times. In conclusion, the DGAOF program has demonstrated a positive long-term impact on increasing gambling knowledge and partially reducing pathological gamblers through direct training. It suggests that multiple repeated interventions are important for youth gambling prevention. [ABSTRACT FROM AUTHOR]

Background: The aim of this study is to review patient characteristics, injury patterns, and outcomes of trauma cases admitted to pediatric intensive care in Children’s Health Queensland, Brisbane, Queensland, Australia. Methods: Routinely recorded data collected prospectively from the Children’s Health Queensland Trauma Service registry from November 2008 to October 2015 were reviewed. Demographic and clinical characteristics of trauma cases in children under 16 years of age are described, and their association with age and mortality analyzed. Results: There were 542 cases of pediatric trauma identified and 66.4% were male. The overall mortality since January 2012 was 11.1%. The median injury severity score (ISS) was 11 (IQR = 9–22), 48.2% (n = 261) had an ISS > 12 and 41.7% (n = 226) patients had an ISS > 15. The most common injury patterns were isolated head injury (29.7%; n = 161) and multiple trauma (31.2%; n = 169). In 28.4% of cases (n = 154) surgery was required. The home was reported to be the most common place of injury (37.6%; n = 204). Children aged 0–4 years were least likely to survive their injury (15.3% mortality) compared with the 5–9 (5.6% mortality) and 10–15 (9.0% mortality) age groups. Higher mortality was associated with more severe injuries, abdomen/spine/thorax injuries, inflicted injuries, drowning and hanging. Conclusion: This description of major pediatric trauma cases admitted to pediatric intensive care in Children’s Health Queensland, Australia, will inform future pediatric major trauma service requirements as it identifies injury patterns and profiles, injury severity, management and mortality across different age groups. [ABSTRACT FROM AUTHOR]

We present an equivalence between stochastic and deterministic variable approaches to represent ranked data and find the expressions obtained to be suggestive of statistical-mechanical meanings. We first reproduce size-rank distributions N(k) from real data sets by straightforward considerations based on the assumed knowledge of the background probability distribution P(N) that generates samples of random variable values similar to real data. The choice of different functional expressions for P(N): power law, exponential, Gaussian, etc., leads to different classes of distributions N(k) for which we find examples in nature. Then we show that all of these types of functions can be alternatively obtained from deterministic dynamical systems. These correspond to one-dimensional nonlinear iterated maps near a tangent bifurcation whose trajectories are proved to be precise analogues of the N(k). We provide explicit expressions for the maps and their trajectories and find they operate under conditions of vanishing or small Lyapunov exponent, therefore at or near a transition to or out of chaos. We give explicit examples ranging from exponential to logarithmic behavior, including Zipf’s law. Adoption of the nonlinear map as the formalism central character is a useful viewpoint, as variation of its few parameters, that modify its tangency property, translate into the different classes for N(k). [ABSTRACT FROM AUTHOR]

Background: The onset age of physiological puberty is greatly variable. This variability has been attributed to environmental factors and to genetic factors although a very little is explained by genome-wide associations studies. Previously, we reported the existence of an association between the onset age of puberty and final height. It is known that final height is associated with parental height (specifically, with the "target height"). We hypothesized that the variability of the onset age of puberty contributes to the attainment of a final height which is similar to the target height. We hypothesized that whenever a child's height-percentile differs from the target height percentile (we called this difference the "height gap"), the onset of puberty is advanced or delayed so that they are closer or even equal at the end of pubertal growth. The association between height gap and onset age of puberty was investigated in the reported study. Methods: The study is an observational retrospective study on growth during puberty in 170 Israeli (60 girls) and 335 Polish children (162 girls). Anthropometric measurements were analyzed by multivariable linear regression with the onset age of the pubertal growth spurt (PGS) as the dependent variable, and two independent variables "height gap" and body mass index (BMI)—both standardized. Results: The adjusted coefficient of determination (adj R2) between the onset age of the PGS and the two independent variables was 0.69 (Israeli girls), 0.50 (Israeli boys, BMI excluded), 0.25 (Polish girls) and 0.13 (Polish boys). A prediction model for the onset age of puberty is presented. Conclusions: The association between the "height gap" and the onset age of puberty suggests that the variability of this age is part of the targeted process of statural growth. The proposed model may explain idiopathic cases of precocious and delayed puberty. [ABSTRACT FROM AUTHOR]

In interpreting attention-deficit/hyperactivity disorder (ADHD) symptoms, categorical and dimensional approaches are commonly used. Both employ binary symptom counts which give equal weighting, with little attention to the combinations and relative contributions of individual symptoms. Alternatively, symptoms can be viewed as an interacting network, revealing the complex relationship between symptoms. Using a novel network modelling approach, this study explores the relationships between the 18 symptoms in the Diagnostic Statistical Manual (DSM-5) criteria and whether network measures are useful in predicting outcomes. Participants were from a community cohort, the Children’s Attention Project. DSM ADHD symptoms were recorded in a face-to-face structured parent interview for 146 medication naïve children with ADHD and 209 controls (aged 6–8 years). Analyses indicated that not all symptoms are equal. Frequencies of endorsement and configurations of symptoms varied, with certain symptoms playing a more important role within the ADHD symptom network. In total, 116,220 combinations of symptoms within a diagnosis of ADHD were identified, with 92% demonstrating a unique symptom configuration. Symptom association networks highlighted the relative importance of hyperactive/impulsive symptoms in the symptom network. In particular, the ‘motoric’-type symptoms as well as interrupts as a marker of impulsivity in the hyperactive domain, as well as loses things and does not follow instructions in the inattentive domain, had high measures of centrality. Centrality-measure weighted symptom counts showed significant association with clinical but not cognitive outcomes, however the relationships were not significantly stronger than symptom count alone. The finding may help to explain heterogeneity in the ADHD phenotype. [ABSTRACT FROM AUTHOR]

There is a critical need for fast, inexpensive, objective, and accurate screening tools for childhood psychopathology. Perhaps most compelling is in the case of internalizing disorders, like anxiety and depression, where unobservable symptoms cause children to go unassessed–suffering in silence because they never exhibiting the disruptive behaviors that would lead to a referral for diagnostic assessment. If left untreated these disorders are associated with long-term negative outcomes including substance abuse and increased risk for suicide. This paper presents a new approach for identifying children with internalizing disorders using an instrumented 90-second mood induction task. Participant motion during the task is monitored using a commercially available wearable sensor. We show that machine learning can be used to differentiate children with an internalizing diagnosis from controls with 81% accuracy (67% sensitivity, 88% specificity). We provide a detailed description of the modeling methodology used to arrive at these results and explore further the predictive ability of each temporal phase of the mood induction task. Kinematical measures most discriminative of internalizing diagnosis are analyzed in detail, showing affected children exhibit significantly more avoidance of ambiguous threat. Performance of the proposed approach is compared to clinical thresholds on parent-reported child symptoms which differentiate children with an internalizing diagnosis from controls with slightly lower accuracy (.68-.75 vs. .81), slightly higher specificity (.88–1.00 vs. .88), and lower sensitivity (.00-.42 vs. .67) than the proposed, instrumented method. These results point toward the future use of this approach for screening children for internalizing disorders so that interventions can be deployed when they have the highest chance for long-term success. [ABSTRACT FROM AUTHOR]

Altered reward processing is a transdiagnostic factor implicated in a wide range of psychiatric disorders. While prior animal and adult research has shown that stress contributes to reward dysfunction, less is known about how stress impacts reward processing in youth. Towards addressing this gap, the present study probed neural activation associated with reward processing following an acute stressor. Healthy adolescents (n = 40) completed a clinical assessment, and fMRI data were acquired while participants completed a monetary guessing task under a no-stress condition and then under a stress condition. Based on prior literature, analyses focused on a priori defined regions-of-interest, specifically the striatum (win trials) and dorsal anterior cingulate cortex [dACC] and insula (loss trials). Two main findings emerged. First, reward-related neural activation (i.e., striatum) was blunted in the stress relative to the no-stress condition. Second, the stress condition also contributed to blunted neural response following reward in loss-related regions (i.e., dACC, anterior insula); however, there were no changes in loss sensitivity. These results highlight the importance of conceptualizing neural vulnerability within the presence of stress, as this may clarify risk for mental disorders during a critical period of development. [ABSTRACT FROM AUTHOR]

Background: Expressing anthropometric parameters (height, weight, BMI) as z-score is a key principle in the clinical assessment of children and adolescents. The Centre for Disease Control and Prevention (CDC) growth charts and the CDC-LMS method for z-score calculation are widely used to assess growth and nutritional status, though they can be imprecise in some percentiles. Objective: To improve the accuracy of z-score calculation by revising the statistical method using the original data used to develop current z-score calculators. Design: A Gaussian Process Regressions (GPR) was designed and internally validated. Z-scores for weight-for-age (WFA), height-for-age (HFA) and BMI-for-age (BMIFA) were compared with WHO and CDC-LMS methods in 1) standard z-score cut-off points, 2) simulated population of 3000 children and 3) real observations 212 children aged 2 to 18 yo. Results: GPR yielded more accurate calculation of z-scores for standard cut-off points (p<<0.001) with respect to CDC-LMS and WHO approaches. WFA, HFA and BMIFA z-score calculations based on the 3 different methods using simulated and real patients, showed a large variation irrespective of gender and age. Z-scores around 0 +/- 1 showed larger variation than the values above and below +/- 2. Conclusion: The revised z-score calculation method was more accurate than CDC-LMS and WHO methods for standard cut-off points. On simulated and real data, GPR based calculation provides more accurate z-score determinations, and thus, a better classification of patients below and above cut-off points. Statisticians and clinicians should consider the potential benefits of updating their calculation method for an accurate z-score determination. [ABSTRACT FROM AUTHOR]

This study examined how classroom peer relations can be described in terms of the network of help relations among students, and the positions students take up in this help network, and whether the structure of adolescent classroom help networks and individual network positions were associated with academic achievement. Help networks were based on the peer nomination question "Who helps you with problems?" Building on previous studies on classroom climate and individual network position, higher academic achievement was expected in classrooms with: a dense help network; no or a few network isolates (referring to students that did not give or receive help at all); less segmentation in help relations; equally distributed help nominations. In addition, higher achievement was expected for individuals with more helpers and a more central position in the help network. Using the Dutch SNARE data (54 classrooms; 1,144 students), the multilevel models suggested that lower achievement was related to an unequal distribution of help relations in a classroom. Moreover, the centrality of individuals in the help network was linked to higher achievement. Classrooms varied strongly on network dimensions, and networks that would theoretically be expected to be most beneficial for achievement (with high density, a few isolates, low segmentation, and high equality) turned out to be highly uncommon. The findings demonstrated that subtle network processes were relevant for academic success, and that classroom network characteristics are associated with classroom-level variation in academic achievement. Descriptive results underlined the complexity of the social context of classrooms, and the absence of 'beneficial' classrooms suggests that researchers should adjust their notion of what is a beneficial or detrimental classroom environment for adolescents. [ABSTRACT FROM AUTHOR]

Background: Unintentional exposure to medications is a noted problem in pediatric populations despite the prevalent use of child-resistant (CR) packaging and educational campaigns informing consumers about appropriate storage. Objective: Conduct a proof-of concept study that evaluates how package designs that engage the attention of children in meaningless ways affect opening time and number of openings. Study design: Non-CR vials with or without distracters were provided to 108 children (24–51 months) in pairs. Each participant was handed a vial and instructed to “do whatever you want to with it.” Successful opening and time to opening were recorded. Data were analyzed using generalized linear mixed models. Results: Older children were approximately four times more likely than younger children to successfully open a vial with a visual distracter (P = 0.049); when distracters were not present, no evidence for differences was apparent between age groups (P = 0.64). For successful openings of either age group, distracter presence significantly prolonged time to opening (P = 0.0375); vials containing distracters took nearly three times longer to open than those without. Conclusions: Existing CR designs almost exclusively rely on late stages of information processing (e.g. difficult to understand or open). Our results suggest that packaging designs that target early stage processing (i.e. perception) represent a potential paradigm for creating effective CR designs. It should be acknowledged that visual distracters, by their very nature, have the potential to act as "attractive nuisances" (i.e. if it were to be so effective that it drew children to the hazard). Further studies designed to specifically investigate this possibility are advised. [ABSTRACT FROM AUTHOR]

The Tathmini GBV study was a cluster randomized trial to assess the impact of a comprehensive health facility- and community-based program delivered through the HIV/AIDS program platform on reduction in gender-based violence and improved care for survivors. Twelve health facilities and surrounding communities in the Mbeya Region of Tanzania were randomly assigned to intervention or control arms. Population-level effects were measured through two cross-sectional household surveys of women ages 15–49, at baseline (n = 1,299) and at 28 months following program scale-out (n = 1,250). Delivery of gender-based violence services was assessed through routine recording in health facility registers. Generalized linear mixed effects models and analysis of variance were used to test intervention effects on population and facility outcomes, respectively. At baseline, 52 percent of women reported experience of recent intimate partner violence. The odds of reporting experience of this violence decreased by 29 percent from baseline to follow-up in the absence of the intervention (time effect OR = 0.71, 95% CI: 0.57–0.89). While the intervention contributed an additional 15 percent reduction, the effect was not statistically significant. The program, however, was found to contribute to positive, community-wide changes including less tolerance for certain forms of violence, more gender equitable norms, better knowledge about gender-based violence, and increased community actions to address violence. The program also led to increased utilization of gender-based violence services at health facilities. Nearly three times as many client visits for gender-based violence were recorded at intervention (N = 1,427) compared to control (N = 489) facilities over a 16-month period. These visits were more likely to include provision of an HIV test (55.3% vs. 19.6%, p = .002). The study demonstrated the feasibility and impact of integrating gender-based violence and HIV programming to combat both of these major public health problems. Further opportunities to scale out GBV prevention and response strategies within HIV/AIDS service delivery platforms should be pursued. Trial Registration: Pan African Clinical Trials Registry No. . [ABSTRACT FROM AUTHOR]

Background: The standard approaches to diagnosing autism spectrum disorder (ASD) evaluate between 20 and 100 behaviors and take several hours to complete. This has in part contributed to long wait times for a diagnosis and subsequent delays in access to therapy. We hypothesize that the use of machine learning analysis on home video can speed the diagnosis without compromising accuracy. We have analyzed item-level records from 2 standard diagnostic instruments to construct machine learning classifiers optimized for sparsity, interpretability, and accuracy. In the present study, we prospectively test whether the features from these optimized models can be extracted by blinded nonexpert raters from 3-minute home videos of children with and without ASD to arrive at a rapid and accurate machine learning autism classification.Methods and Findings: We created a mobile web portal for video raters to assess 30 behavioral features (e.g., eye contact, social smile) that are used by 8 independent machine learning models for identifying ASD, each with >94% accuracy in cross-validation testing and subsequent independent validation from previous work. We then collected 116 short home videos of children with autism (mean age = 4 years 10 months, SD = 2 years 3 months) and 46 videos of typically developing children (mean age = 2 years 11 months, SD = 1 year 2 months). Three raters blind to the diagnosis independently measured each of the 30 features from the 8 models, with a median time to completion of 4 minutes. Although several models (consisting of alternating decision trees, support vector machine [SVM], logistic regression (LR), radial kernel, and linear SVM) performed well, a sparse 5-feature LR classifier (LR5) yielded the highest accuracy (area under the curve [AUC]: 92% [95% CI 88%-97%]) across all ages tested. We used a prospectively collected independent validation set of 66 videos (33 ASD and 33 non-ASD) and 3 independent rater measurements to validate the outcome, achieving lower but comparable accuracy (AUC: 89% [95% CI 81%-95%]). Finally, we applied LR to the 162-video-feature matrix to construct an 8-feature model, which achieved 0.93 AUC (95% CI 0.90-0.97) on the held-out test set and 0.86 on the validation set of 66 videos. Validation on children with an existing diagnosis limited the ability to generalize the performance to undiagnosed populations.Conclusions: These results support the hypothesis that feature tagging of home videos for machine learning classification of autism can yield accurate outcomes in short time frames, using mobile devices. Further work will be needed to confirm that this approach can accelerate autism diagnosis at scale. [ABSTRACT FROM AUTHOR]