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Objective The purpose of this study was to develop self-report and parent-proxy measures of children’s physical activity for clinical research and practice and to demonstrate a valid and reliable instrument of children’s lived experience of physical activity as reported by the children themselves or their parent proxies. Methods This study involved qualitative development of item pools followed by 2 cross-sectional validity and reliability studies. The National Institutes of Health Patient Reported Outcome Measurement Information System (PROMIS) instrument development standards were applied to create child self-report and parent-proxy physical activity instruments from previously developed, content-valid pools of physical activity items. Each item used a 7-day recall period and had 5 response options. Item bank calibration was based on national samples totaling 3033 children aged 8 to 17 years and 2336 parents of children aged 5 to 17 years. Quantitative analyses included reliability assessments, factor analyses, item response theory calibration, differential item functioning, and construct validation. Results The final item banks comprised 10 items each. The items were selected based on content and psychometric properties. The item banks appeared to be unidimensional and free from differential item functioning. They showed excellent reliability and a high degree of precision across the range of the latent variable. Child-report and parent-proxy 4- and 8-item fixed-length instruments were specified. The instruments showed moderate correlation with existing self-report measures of physical activity. Conclusion The PROMIS Pediatric Physical Activity instruments provide precise and valid measurement of children’s lived experiences of physical activity. Impact The availability of the PROMIS Pediatric Physical Activity instruments will support advances in clinical practice and research that require measurement of pediatric physical activity by self- and parent-proxy report.

Prior studies of early antibiotic use and growth have shown mixed results, primarily on cross-sectional outcomes. This study examined the effect of oral antibiotics before age 24 months on growth trajectory at age 2-5 years.We captured oral antibiotic prescriptions and anthropometrics from electronic health records through PCORnet, for children with ≥1 height and weight at 0-12 months of age, ≥1 at 12-30 months, and ≥2 between 25 and 72 months. Prescriptions were grouped into episodes by time and by antimicrobial spectrum. Longitudinal rate regression was used to assess differences in growth rate from 25 to 72 months of age. Models were adjusted for sex, race/ethnicity, steroid use, diagnosed asthma, complex chronic conditions, and infections.430,376 children from 29 health U.S. systems were included, with 58% receiving antibiotics before 24 months. Exposure to any antibiotic was associated with an average 0.7% (95% CI 0.5, 0.9, p 0.0001) greater rate of weight gain, corresponding to 0.05 kg additional weight. The estimated effect was slightly greater for narrow-spectrum (0.8% [0.6, 1.1]) than broad-spectrum (0.6% [0.3, 0.8], p 0.0001) drugs. There was a small dose response relationship between the number of antibiotic episodes and weight gain.Oral antibiotic use prior to 24 months of age was associated with very small changes in average growth rate at ages 2-5 years. The small effect size is unlikely to affect individual prescribing decisions, though it may reflect a biologic effect that can combine with others.

BACKGROUND: Most children with atopic dermatitis(AD) suffer from sleep disturbance, but reliable and valid assessment tools are lacking. OBJECTIVES: To test PROMIS (Patient Reported Outcomes Measurement Information System) sleep measures in pediatric AD and to develop an algorithm to screen, assess and intervene to reduce sleep disturbance. METHODS: A cross-sectional study was conducted with AD children ages 5–17 years and one parent(n=61), who completed sleep, itch, and AD-specific questionnaires; clinicians assessed disease severity. All children wore actigraphy watches for 1-week-objective sleep assessment. RESULTS: PROMIS sleep disturbance parent-proxy-reliability was high (Cronbach’s α=0.90) and differentiated among Patient Oriented Eczema Measure (POEM)-determined disease severity groups (mean±SD in mild vs. moderate vs. severe was 55.7±7.5 vs. 59.8±10.8 vs. 67.1±9.5, p

Background PROMIS Pediatric patient-reported outcome measures were developed with children from the general population, and their content validity has not been established in children with chronic disease. This study was done to evaluate the content validity of the PROMIS Pediatric Pain Interference and Fatigue measures in children 8–17 years-old with Crohn’s disease and the PROMIS Pediatric Fatigue, Sleep Disturbance, and Sleep-related Impairment measures for children 8–17 years-old with chronic kidney disease. Methods We conducted semi-structured interviews with individuals affected by Crohn’s disease and chronic kidney disease. The interviews were done to elicit children’s lived experiences of the PROMIS outcomes of interest. We used deductive content analysis to contrast the participants’ reports of their symptoms and impacts on daily life with existing conceptual frameworks for the PROMIS measures, each of which was developed with input from children in the general population. Results On average, we elicited an average of 7 pain interference and 7 fatigue concepts from Crohn’s disease participants (n = 37), while chronic kidney disease participants (n = 26) provided 9 concepts for fatigue, 4 for sleep disturbance, and 7 for sleep-related impairment. Concept saturation was achieved after 16–19 interviews across the four PROMIS measures. Children with these two chronic health conditions reported the same breadth and types of lived experiences as children from the development samples drawn from the general population. Conclusion The study supports the content validity of several PROMIS Pediatric measures for children with Crohn’s disease and chronic kidney disease. These findings provide evidence that PROMIS Pediatric measures, developed as universally relevant patient-reported outcomes, may be more broadly applicable to children with chronic disease.

OBJECTIVE: To develop and evaluate the validity of a self-report measure of sleep practices for youth 8–17 years. METHODS: Following recommended guidelines for the development of patient reported outcomes (PROs), sleep practice concepts were identified through expert (n=8) and child (n=28) concept elicitation interviews and a systematic literature review. Items were developed based on these concepts and tested in cognitive interviews with children (n=32). Psychometric analyses were applied to item response data collected from a diverse sample of youth 8–17 years (n=307). Construct validity was evaluated through tests of associations between sleep practices and sleep disturbance and sleep-related impairment. Finally, clinical validity of the tool was assessed by comparing scores of youth with and without a parent-identified sleep problem. RESULTS: The final Pediatric Sleep Practices Questionnaire (PSPQ) included 15 items that were used to identify 5 sleep practices: sleep timing, sleep routines and consistency, technology use before bedtime, sleep environment, and the need for parental presence to fall asleep. A confirmatory factor analysis supported the hypothesized structure (all factor loadings ≥ 0.72) and PSPQ indices were significantly associated with self-reported sleep disturbances and sleep-related impairment. Finally, children with parent-reported sleep problems had shorter sleep opportunity, later bedtimes, greater need for parental presence, poorer bedtime routines, and more technology use than children without parent-reported sleep problems. CONCLUSIONS: The PSPQ was developed using best-practice PRO development methodology. The PSPQ can be used in clinical settings and for research assessment to capture modifiable sleep practices that may promote or interfere with healthy sleep.

PURPOSE: To identify and evaluate methods for assessing pediatric patient-reported outcome (PRO) data quality at the individual level. METHODS: We conducted a systematic literature review to identify methods for detecting invalid responses to PRO measures. Eight data quality indicators were applied to child-report data collected from 1780 children ages 8–11 years. We grouped children with similar data quality patterns and tested for between-group differences in factors hypothesized to influence self-report capacity. RESULTS: We identified 126 articles that described 494 instances in which special measures or statistical techniques were applied to evaluate data quality at the individual level. We identified 22 data quality indicator subtypes: 9 direct methods (require administration of special items) and 13 archival techniques (statistical procedures applied to PRO data post hoc). Application of archival techniques to child-report PRO data revealed 3 distinct patterns (or classes) of the data quality indicators. Compared to class 1 (56%), classes 2 (36%) and 3 (8%) had greater variation in their PRO item responses. Three archival indicators were especially useful for differentiating plausible item response variation (class 2) from statistically unlikely response patterns (class 3). Neurodevelopmental conditions, which are associated with a range of cognitive processing challenges, were more common among children in class 3. CONCLUSION: A multi-indicator approach is needed to identify invalid PRO responses. Once identified, assessment environments and measurement tools should be adapted to best support these individuals’ self-report capacity. Individual-level data quality indicators can be used to gauge the effectiveness of these accommodations.

BACKGROUND: We aimed to evaluate validity of natural language processing (NLP) and machine learning (ML) algorithms in identifying features of unstructured patient-reported outcomes (PROs) for child/adolescent cancer survivors vs. expert judgment as the gold standard. METHODS: A cross-section study to collect unstructured PROs from 52 survivors aged 8-17.9 years and 35 caregivers who visited a Comprehensive Cancer Center in 2016. PROs including pain interference and fatigue symptoms were reported through in-depth interviews. After verbatim transcription, analyzable sentences (i.e., meaning units) were semantically labeled by 2 content experts based on problems with physical, cognitive, or social attributes. Two NLP/ML methods were used to extract and validate the semantic features: 1) Bidirectional Encoder Representations from Transformers (BERT) and 2) Word2vec plus one of the ML methods, the Support Vector Machine (SVM) and Extreme Gradient Boosting (XGBoost). Receiver operating characteristic (ROC) and precision-recall (PR) curves evaluated the accuracy and validity of NLP/ML methods, respectively. FINDINGS: In total, 391 meaning units in pain interference and 423 in fatigue domains were labeled and analyzed. Compared to Word2vec/SVM and Word2vec/XGBoost, BERT demonstrated higher accuracy on both symptom domains, including 0.931 (95%CI=0.905, 0.957) and 0.916 (95% CI=0.887, 0.941) for problems with cognitive and social attributes on pain interference, and 0.929 (95% CI=0.903, 0.953) and 0.917 (95% CI=0.891, 0.943) for problems with cognitive and social attributes on fatigue. In addition, BERT yielded superior areas under the ROC curve for cognitive attribute on pain interference and fatigue domains (0.923 [95% CI=0.879, 0.997]; 0.948 [95% CI=0.922, 0.979]), and superior areas under the PR curve for cognitive attribute on pain interference and fatigue domains (0.818 [95% CI=0.735, 0.917]; 0.855 [95% CI=0.791, 0.930). INTERPRETATIONS: As an alternative to standard PRO surveys, collecting unstructured PROs via interviews or conversations during clinical encounters and applying NLP/ML methods can facilitate PRO assessment in cancer survivors. FUNDING STATEMENT: The research reported in this manuscript was supported by the National Cancer Institute under award numbers U01CA195547 and P30CA021765-33, and the National Institute of Arthritis and Musculoskeletal and Skin Diseases of the National Institutes of Health under award number U19AR069525. The content is solely the responsibility of the authors and does not necessarily represent the official views of the funding agencies. DECLARATION OF INTERESTS: All co-authors declare no conflict of interest. ETHICS APPROVAL STATEMENT: The research protocol was approved by St. Jude’s Institutional Review Board. Assent from survivors and consent from caregivers were obtained.

To understand how parents and physicians make decisions regarding antibiotics and whether a potential associated risk of obesity would alter decisions, we conducted a qualitative study of parents and physicians who care for children. Parent focus groups and physician interviews used a guide focused on experience with antibiotics and perceptions of risks and benefits, including obesity. Content analysis was used to understand how a risk of obesity would influence antibiotic decisions. Most parents (n = 59) and physicians (n = 22) reported limited discussion about any risks at the time of antibiotic prescriptions. With an acute illness, most parents prioritized symptomatic improvement and chose to start antibiotics. Physicians’ treatment preferences were varied. An obesity risk did not change most parents’ or physicians’ preferences. Given that parent-physician discussion at the time of acute illness is unlikely to change preferences, public health messaging may be a more successful approach to counter obesity and antibiotics overuse.

International audience; BACKGROUND: There is a widely recognized need for more pragmatic trials that evaluate interventions in real-world settings to inform decision-making by patients, providers, and health system leaders. Increasing availability of electronic health records, centralized research ethics review, and novel trial designs, combined with support and resources from governments worldwide for patient-centered research, have created an unprecedented opportunity to advance the conduct of pragmatic trials, which can ultimately improve patient health and health system outcomes. Such trials raise ethical issues that have not yet been fully addressed, with existing literature concentrating on regulations in specific jurisdictions rather than arguments grounded in ethical principles. Proposed solutions (e.g. using different regulations in "learning healthcare systems") are speculative with no guarantee of improvement over existing oversight procedures. Most importantly, the literature does not reflect a broad vision of protecting the core liberty and welfare interests of research participants. Novel ethical guidance is required. We have assembled a team of ethicists, trialists, methodologists, social scientists, knowledge users, and community members with the goal of developing guidance for the ethical design and conduct of pragmatic trials. METHODS: Our project will combine empirical and conceptual work and a consensus development process. Empirical work will: (1) identify a comprehensive list of ethical issues through interviews with a small group of key informants (e.g. trialists, ethicists, chairs of research ethics committees); (2) document current practices by reviewing a random sample of pragmatic trials and surveying authors; (3) elicit views of chairs of research ethics committees through surveys in Canada, UK, USA, France, and Australia; and (4) elicit views and experiences of community members and health system leaders through focus groups and surveys. Conceptual work will consist of an ethical analysis of identified issues and the development of new ethical solutions, outlining principles, policy options, and rationales. The consensus development process will involve an independent expert panel to develop a final guidance document. DISCUSSION: Planned output includes manuscripts, educational materials, and tailored guidance documents to inform and support researchers, research ethics committees, journal editors, regulators, and funders in the ethical design and conduct of pragmatic trials.

Obesity, as an independent risk factor for increased morbidity and mortality throughout the lifecycle, is a major health issue in the United States. Pediatric obesity is a strong risk factor for adult obesity, as it tends to be stable and tracks into adulthood. Therefore, prevention of childhood obesity is urgently required for reduction in obesity prevalence and obesity related comorbidities. In this paper, the general pediatric obesity development pattern and the onset time period of early childhood obesity was identified via analysis of approximately 11 million pediatric clinical encounters of 860,510 unique individuals. XGBoost model was developed to predict at age 2 years if individuals would develop obesity in early childhood. The model is generalized to both males and females, and achieved an AUC of 81% (± 0.1%). Obesity associated risk factors were further analyzed via interpretation of the XGBoost model predictions. Besides known predictive factors such as weight, height, race, and ethnicity, new factors such as body temperature and respiratory rate were also identified. As body temperature and respiratory rate are related to human metabolism, novel physiologic mechanisms that cause these associations might be discovered in future research. We decomposed model recall to different age ranges when obesity incidence occurred. The model recall for individuals with obesity incidence between 24–36 months was 97.63%, while recall for obesity incidence between 72–84 months was 48.96%, suggesting obesity is less predictable further in the future. Since obesity is largely affected by evolving factors such as life style, diet, and living environment, it is possible that obesity prevention may be achieved via changes in adjustable factors.

Purpose We conducted a systematic review of literature published on January 2000–May 2017 that spatially linked electronic health record (EHR) data with environmental information for population health research. Methods We abstracted information on the environmental and health outcome variables and the methods and data sources used. Results The automated search yielded 669 articles; 128 articles are included in the full review. The number of articles increased by publication year; the majority (80%) were from the United States, and the mean sample size was approximately 160,000. Most articles used cross-sectional (44%) or longitudinal (40%) designs. Common outcomes were health care utilization (32%), cardiometabolic conditions/obesity (23%), and asthma/respiratory conditions (10%). Common environmental variables were sociodemographic measures (42%), proximity to medical facilities (15%), and built environment and land use (13%). The most common spatial identifiers were administrative units (59%), such as census tracts. Residential addresses were also commonly used to assign point locations, or to calculate distances or buffer areas. Conclusions Future research should include more detailed descriptions of methods used to geocode addresses, focus on a broader array of health outcomes, and describe linkage methods. Studies should also explore using longitudinal residential address histories to evaluate associations between time-varying environmental variables and health outcomes.

OBJECTIVES: The National Patient-Centered Clinical Research Network (PCORnet) supports observational and clinical research using healthcare data. The PCORnet Antibiotics and Childhood Growth Study is one of PCORnet’s inaugural observational studies. The objectives of this manuscript are to describe (1) the processes used to integrate and analyze data from children across 36 participating institutions and (2) the cohort characteristics and prevalence of antibiotic use. METHODS: We included children in the cohort if they had at least one same-day height and weight measured in each of three age periods: 1) before 12 months, 2) 12 to 30 months, and 3) after 24 months. We distributed statistical queries that each institution ran on its local version of the PCORnet Common Data Model, with aggregate data returned for analysis. We defined overweight or obesity as age-sex-specific body mass index ≥ 85(th), obesity ≥95(th) percentile, and severe obesity ≥120% of the 95(th) percentile. RESULTS: 681,739 children met the cohort inclusion criteria and were racially/ethnically diverse (24.9% black, 17.5% Hispanic). Before 24 months, 55.2% of children received at least one antibiotic prescription; 21.3% received a single antibiotic prescription, 14.3% received four or more, and 33.3% received a broad spectrum antibiotic. Overweight and obesity prevalence was 27.6% at 4 to

Mark J Pletcher,1,2 Christopher B Forrest,3 Thomas W Carton4 1Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, 2Division of General Internal Medicine, Department of Medicine, University of California, San Francisco, CA, 3Applied Clinical Research Center, Children’s Hospital of Philadelphia, Philadelphia, PA, 4Division of Health Services Research, Louisiana Public Health Institute, New Orleans, LA, USA Abstract: The Patient-Centered Outcomes Research Institute (PCORI) launched a multi-institutional “network of networks” in 2013 – Patient-Centered Clinical Research Network (PCORnet) – that is designed to conduct clinical research that is faster, less expensive, and more responsive to the information needs of patients and clinicians. To enhance cross-network and cross-institutional collaboration and catalyze the use of PCORnet, PCORI has supported formation of 11 Collaborative Research Groups focusing on specific disease types (e.g., ­cardiovascular health and cancer) or particular patient populations (e.g., pediatrics and health disparities). PCORnet’s Collaborative Research Groups are establishing research priorities within these focus areas, establishing relationships with potential funders, and supporting development of specific research projects that will use PCORnet resources. PCORnet remains a complex, multilevel, and heterogeneous network that is still maturing and building a diverse portfolio of observational and interventional people-centered research; engaging with PCORnet can be daunting, particularly for outside investigators. We believe the Collaborative Research Groups are stimulating interest and helping investigators navigate the complexity, but only time will tell if these efforts will bear fruit in terms of funded multicenter PCORnet projects. Keywords: PCORI, PCORnet, network, collaboration, infrastructure

Background Assessing patient-reported outcomes (PROs) through interviews or conversations during clinical encounters provides insightful information about survivorship. Objective This study aims to test the validity of natural language processing (NLP) and machine learning (ML) algorithms in identifying different attributes of pain interference and fatigue symptoms experienced by child and adolescent survivors of cancer versus the judgment by PRO content experts as the gold standard to validate NLP/ML algorithms. Methods This cross-sectional study focused on child and adolescent survivors of cancer, aged 8 to 17 years, and caregivers, from whom 391 meaning units in the pain interference domain and 423 in the fatigue domain were generated for analyses. Data were collected from the After Completion of Therapy Clinic at St. Jude Children’s Research Hospital. Experienced pain interference and fatigue symptoms were reported through in-depth interviews. After verbatim transcription, analyzable sentences (ie, meaning units) were semantically labeled by 2 content experts for each attribute (physical, cognitive, social, or unclassified). Two NLP/ML methods were used to extract and validate the semantic features: bidirectional encoder representations from transformers (BERT) and Word2vec plus one of the ML methods, the support vector machine or extreme gradient boosting. Receiver operating characteristic and precision-recall curves were used to evaluate the accuracy and validity of the NLP/ML methods. Results Compared with Word2vec/support vector machine and Word2vec/extreme gradient boosting, BERT demonstrated higher accuracy in both symptom domains, with 0.931 (95% CI 0.905-0.957) and 0.916 (95% CI 0.887-0.941) for problems with cognitive and social attributes on pain interference, respectively, and 0.929 (95% CI 0.903-0.953) and 0.917 (95% CI 0.891-0.943) for problems with cognitive and social attributes on fatigue, respectively. In addition, BERT yielded superior areas under the receiver operating characteristic curve for cognitive attributes on pain interference and fatigue domains (0.923, 95% CI 0.879-0.997; 0.948, 95% CI 0.922-0.979) and superior areas under the precision-recall curve for cognitive attributes on pain interference and fatigue domains (0.818, 95% CI 0.735-0.917; 0.855, 95% CI 0.791-0.930). Conclusions The BERT method performed better than the other methods. As an alternative to using standard PRO surveys, collecting unstructured PROs via interviews or conversations during clinical encounters and applying NLP/ML methods can facilitate PRO assessment in child and adolescent cancer survivors.

Background The SARS CoV-2 virus has caused one of the deadliest pandemics in recent history, resulting in over 170 million deaths and global economic disruption. There remains an urgent need for clinical trials to test therapies for treatment and prevention. Design An online research platform was created to support a registry community of healthcare workers (HCWs) to understand their experiences and conduct clinical studies to address their concerns. The first study, HERO-HCQ, was a double-blind, multicenter, randomized, pragmatic trial to evaluate the superiority of hydroxychloroquine (HCQ) vs placebo for pre-exposure prophylaxis (PrEP) of COVID-19 clinical infection in HCWs. Secondary objectives were to assess the efficacy of HCQ in preventing viral shedding of COVID-19 among HCWs and to assess the safety and tolerability of HCQ. Methods HCWs joined the Registry and were pre-screened for trial interest and eligibility. Trial participants were randomized 1:1 to receive HCQ or placebo. On-site baseline assessment included a COVID-19 nasopharyngeal PCR and blood serology test. Weekly follow-up was done via an online portal and included screening for symptoms of COVID-19, self-reported testing, adverse events, and quality of life assessments. The on-site visit was repeated at Day 30. Discussion The HERO research platform offers an approach to rapidly engage, screen, invite and enroll into clinical studies using a novel participant-facing online portal interface and remote data collection, enabling limited onsite procedures for conduct of a pragmatic clinical trial. This platform may be an example for future clinical trials of common conditions to enable more rapid evidence generation.

Introduction It has been posited that policies to promote child health and prevent obesity should target neighborhood environments but evidence on the impact of neighborhoods on child weight is conflicting and longitudinal studies (which have benefits for causal inference) are scarce. Methods We used electronic health records (2007–2016) from an urban, pediatric integrated delivery system and linked children (N = 51,873, ages 6–19 years, 77% African American) to neighborhood-level data to investigate how changes in neighborhood environments relate to changes in body mass index (BMI). Measures of neighborhood environment were resources for healthy foods and physical activity (‘resources’), greenness, violent crime rate, perceived safety and social cohesion. Fixed effects models estimated associations between changes in neighborhood environment exposures and changes in BMI z-score and whether effects differed by sex, baseline age, neighborhood socioeconomic status and population density. Results Approximately 22% of the cohort was obese (BMI z-score ≥ 95th percentile). In adjusted models, increases in neighborhood greenness and perceived safety were associated with decreases in BMI z-score (mean change in BMI z-score for 1-SD increase for both: -0.012; 95% CI= (−0.018, −0.007)). Increases in neighborhood safety had a stronger effect in children ages 6–10 years than in older children. Increases in social cohesion were associated with increases in BMI z-score (mean change: 0.005 95% CI = (0.003, 0.008)) especially in boys. Increases in food and physical activity resources were not associated with changes in BMI. Conclusions This study suggests that increasing neighborhood greenness and safety are potential approaches to reduce children's BMI.

Key Points Question Is early antibiotic exposure associated with altered body mass index (BMI) trajectory milestone patterns in childhood? Findings This cohort study of 183 444 children identified small associations with age and magnitude of BMI at peak in infancy and rebound in early childhood after antibiotic exposure before 48 months of age. Meaning The findings of this study suggest these small associations with BMI trajectory milestones after early-life antibiotic exposure should not affect the individual decision to prescribe antibiotics., Importance Past studies have showed associations between antibiotic exposure and child weight outcomes. Few, however, have documented alterations to body mass index (BMI) (calculated as weight in kilograms divided by height in meters squared) trajectory milestone patterns during childhood after early-life antibiotic exposure. Objective To examine the association of antibiotic use during the first 48 months of life with BMI trajectory milestones during childhood in a large cohort of children. Design, Setting, and Participants This retrospective cohort study used electronic health record data from 26 institutions participating in the National Patient-Centered Clinical Research Network from January 1, 2009, to December 31, 2016. Participant inclusion required at least 1 valid set of same-day height and weight measurements at each of the following age periods: 0 to 5, 6 to 11, 12 to 23, 24 to 59, and 60 to 131 months (183 444 children). Data were analyzed from June 1, 2019, to June 30, 2020. Exposures Antibiotic use at 0 to 5, 6 to 11, 12 to 23, 24 to 35, and 36 to 47 months of age. Main Outcomes and Measures Age and magnitude of BMI peak and BMI rebound. Results Of 183 444 children in the study (mean age, 3.3 years [range, 0-10.9 years]; 95 228 [51.9%] were boys; 80 043 [43.6%] were White individuals), 78.1% received any antibiotic, 51.0% had at least 1 episode of broad-spectrum antibiotic exposure, and 65.0% had at least 1 episode of narrow-spectrum antibiotic exposure at any time before 48 months of age. Exposure to any antibiotics at 0 to 5 months of age (vs no exposure) was associated with later age (β coefficient, 0.05 months [95% CI, 0.02-0.08 months]) and higher BMI (β coefficient, 0.09 [95% CI, 0.07-0.11]) at peak. Exposure to any antibiotics at 0 to 47 months of age (vs no exposure) was associated with an earlier age (−0.60 months [95% CI, −0.81 to −0.39 months]) and higher BMI at rebound (β coefficient, 0.02 [95% CI, 0.01-0.03]). These associations were strongest for children with at least 4 episodes of antibiotic exposure. Effect estimates for associations with age at BMI rebound were larger for those exposed to antibiotics at 24 to 35 months of age (β coefficient, −0.63 [95% CI, −0.83 to −0.43] months) or 36 to 47 (β coefficient, −0.52 [95% CI, −0.72 to −0.31] months) than for those exposed at 0 to 5 months of age (β coefficient, 0.26 [95% CI, 0.01-0.51] months) or 6 to 11 (β coefficient, 0.00 [95% CI, −0.20 to 0.20] months). Conclusions and Relevance In this cohort study, antibiotic exposure was associated with statistically significant, but small, differences in BMI trajectory milestones in infancy and early childhood. The small risk of an altered BMI trajectory milestone pattern associated with early-life antibiotic exposure is unlikely to be a key factor during prescription decisions for children., This cohort study uses data from the National Patient-Centered Clinical Research Network (PCORnet) Antibiotics Childhood Growth Study to examine the association of antibiotic use during the first 4 years of life and body mass index trajectory milestones during childhood in a large cohort of children.

Objective This study compares seven machine learning models developed to predict childhood obesity from age > 2 to ≤ 7 years using Electronic Healthcare Record (EHR) data up to age 2 years. Materials and methods EHR data from of 860,510 patients with 11,194,579 healthcare encounters were obtained from the Children’s Hospital of Philadelphia. After applying stringent quality control to remove implausible growth values and including only individuals with all recommended wellness visits by age 7 years, 27,203 (50.78 % male) patients remained for model development. Seven machine learning models were developed to predict obesity incidence as defined by the Centers for Disease Control and Prevention (age/sex adjusted BMI>95th percentile). Model performance was evaluated by multiple standard classifier metrics and the differences among seven models were compared using the Cochran's Q test and post-hoc pairwise testing. Results XGBoost yielded 0.81 (0.001) AUC, which outperformed all other models. It also achieved statistically significant better performance than all other models on standard classifier metrics (sensitivity fixed at 80 %): precision 30.90 % (0.22 %), F1-socre 44.60 % (0.26 %), accuracy 66.14 % (0.41 %), and specificity 63.27 % (0.41 %). Discussion and conclusion Early childhood obesity prediction models were developed from the largest cohort reported to date. Relative to prior research, our models generalize to include males and females in a single model and extend the time frame for obesity incidence prediction to 7 years of age. The presented machine learning model development workflow can be adapted to various EHR-based studies and may be valuable for developing other clinical prediction models.

To describe the development of pediatric family relationships measures, with versions for child self-report (8–17 years) and parent-report for children 5–17 years old. Measures were created for integration into the Patient Reported Outcomes Measurement Information System (PROMIS®). Semi-structured interviews with 10 experts, 24 children, and 8 parents were conducted to elicit and clarify essential elements of family relationships. A systematic literature review was conducted to identify item concepts representative of each element. The concepts were transformed into items that were iteratively revised based on cognitive interviews (n = 43 children) and item translatability review. Psychometric studies involving 2846 children and 2262 parents were conducted to further refine and validate the instruments. Qualitative procedures supported the development of content valid Family Relationships item banks. Final child- and parent-report item banks each contain 47 items. Unidimensional item banks were calibrated using IRT-modeling to estimate item parameters representative of the US population and to enable computerized adaptive test administration. Four- and eight-item short forms were constructed for standard fixed format administration. All instruments have strong internal consistency, retest-reliability, and provide precise estimates of various levels of family relationship quality. Preliminary evidence of the instruments’ validity was provided by known-group comparisons and convergence with legacy measures. The PROMIS pediatric Family Relationships measures can be applied in research focused on determinants, outcomes, and the protective effects of children’s subjective family relationship experiences.

Introduction Clinicians require tools to rapidly identify individuals with significant childhood adversity as part of routine primary care. The goal of this study was to shorten the 11-item Behavioral Risk Factor Surveillance System Adverse Childhood Experiences (ACEs) measure and evaluate the feasibility and validity of this shortened measure as a screener to identify adults who have experienced significant childhood adversity. Methods Statistical analysis was conducted in 2015. ACE item responses obtained from 2011–2012 Behavioral Risk Factor Surveillance System data were combined to form a sample of 71,413 adults aged ≥18 years. The 11-item Behavioral Risk Factor Surveillance System ACE measure was subsequently reduced to a two-item screener by maintaining the two dimensions of abuse and household stressors and selecting the most prevalent item within each dimension. Results The screener included household alcohol and childhood emotional abuse items. Overall, 42% of respondents and at least 75% of the individuals with four or more ACEs endorsed one or both of these experiences. Using the 11-item ACE measure as the standard, a cut off of one or more ACEs yielded a sensitivity of 99%, but specificity was low (66%). Specificity improved to 94% when using a cut off of two ACEs, but sensitivity diminished (70%). There was no substantive difference between the 11-and two-item ACE measures in their strength of association with an array of health outcomes. Conclusions A two-item ACE screener appropriate for rapid identification of adults who have experienced significant childhood adversity was developed.

The purpose of this study is to describe the psychometric evaluation and item response theory (IRT) calibration of the PROMIS Pediatric Positive Affect item bank, child-report and parent-proxy editions. The initial item pool comprising 53 items, previously developed using qualitative methods, was administered to 1874 children 8–17 years old and 909 parents of children 5–17 years old. Analyses included descriptive statistics, reliability, factor analysis, differential item functioning, and construct validity. A total of 14 items were deleted, because of poor psychometric performance, and an 8-item short form constructed from the remaining 39 items was administered to a national sample of 1004 children 8–17 years old, and 1306 parents of children 5–17 years old. The combined sample was used in IRT calibration analyses. The final item bank appeared unidimensional, the items appeared locally independent, and the items were free from differential item functioning. The scales showed excellent reliability and convergent and discriminant validity. Positive affect decreased with children’s age and was lower for those with a special health care need. After IRT calibration, we found that 4 and 8 item short forms had a high degree of precision (reliability) across a wide range of the latent trait (>4 SD units). The PROMIS Pediatric Positive Affect item bank and its short forms provide an efficient, precise, and valid assessment of positive affect in children and youth.

Introduction Sleep disturbances are common during pediatric cancer treatment and recent evidence suggests a correlation between sleep and symptom burden. Improving nighttime sleep may impact patients’ ability to cope with symptoms. The current study tests the interaction between sleep hygiene and sleep disturbances in predicting cancer-related symptoms to determine if the relationship between sleep and symptoms is different for patients with better sleep hygiene. Methods 102 caregivers of children with cancer (ages 5-17, M=10.12, SD=4.02; 58% female) completed parent-proxy Pediatric Sleep Practices Questionnaire (yielding routine consistency and sleep opportunity scores) and measures of cancer-related symptoms (PROMIS Sleep Disturbance, Fatigue, and Pain Interference; PedsQL—Cancer Module-Nausea subscale). The interaction between sleep disturbances and sleep hygiene (consistency, opportunity) on each symptom (pain, nausea, fatigue) were tested using PROCESS moderation. Results 81% of caregivers report that their child receives sufficient sleep but only 12% reported regular consistent sleep patterns/routines. Sleep opportunity was not related to sleep disturbances or cancer-related symptoms, but more routine consistency was related to fewer sleep disturbances (r=.30, p=.003). The interaction between sleep disturbances and routine consistency significantly predicted pain interference [R2=.16, F(3, 98)=6.37, p Conclusion The sleep/pain and sleep/nausea relationships are stronger in patients with more consistent sleep routines and the sleep/nausea relationship is also stronger in patients with sufficient/well-timed sleep opportunities. Sleep and fatigue were moderately related across all levels of both sleep hygiene components. Clinical interventions that target sleep hygiene together with sleep disturbances such as nighttime awakenings and poor sleep quality may be more effective in addressing cancer-related symptoms such as pain and nausea. Support This work was supported in part by funding from the Patient-Centered Outcomes Research Institute (PCORI-D-17-00187; PI Christopher Forrest).

Objective To examine the clinical validity of the Patient Reported Outcome Measurement Information System (PROMIS) Pediatric Sleep Disturbance (SD) and Sleep-Related Impairment (SRI) short forms. Methods Youth (8–17 years) from clinical populations with known SDs (sleep clinic n = 126, autism n = 276, asthma n = 82, asthma + eczema n = 68) and the general population (n = 902) completed the PROMIS Pediatric SD and SRI 8-item short forms, along with established measures of sleep (Children’s Report of Sleep Patterns, Sleep Habits Survey), PROMIS Pediatric Fatigue, and parent-reported clinical indicators (does child have sleep problem, use melatonin, use prescription sleep medication). Results Confirmatory factor analyses demonstrated factorial invariance for all clinical groups. Significant differences between the general population and clinical groups were found for SD and SRI (medium to large effect sizes). Convergent validity was demonstrated through separate hierarchical regression models that showed significant associations between parent-reported clinical indicators and SD and SRI, above and beyond clinical group, as well as moderate to strong correlations between the PROMIS sleep measures and both established measures of sleep and fatigue. Conclusions The PROMIS Pediatric SD and SRI short forms provide clinicians and researchers a brief, accurate, and valid way to measure patient-reported sleep outcomes in pediatric populations.

Background: Pancreatic ductal adenocarcinoma (PDAC) is associated with high symptom burden. However, treatment decisions currently depend heavily on physician interpretation of clinical parameters and may not consider patients’ health preferences. The NIH Patient-Reported Outcomes Measurement Information System (PROMIS) initiative standardized a set of patient-reported outcomes for use in chronic diseases. This study identifies preference rankings among patients with PDAC and physicians for PROMIS domains and compares the priorities of patients and their providers. Methods: We condensed the 96 NIH PROMIS adult domains into 31 domains and created a Maximum Difference Scaling questionnaire. Domain preference scores were generated from the responses of patients with PDAC and physicians, which were compared using Maximum Difference Scaling software across demographic and clinical variables. Results: Participants included 135 patients with PDAC (53% male; median age, 68 years) and 54 physicians (76% male; median years of experience, 10). Patients selected physical functioning (PF) as their top priority, whereas physicians identified pain as most important. PF, ability to perform activities of daily living, and symptom management were within the top 5 domains for both patients and physicians, and varied only slightly across age, sex, and ethnicity. However, several domains were ranked significantly higher by patients than by physicians, including but not limited to PF; ability to do things for yourself, family, and friends; ability to interact with others to obtain help; and sleep quality. Physicians ranked pain, anxiety, and depression higher than patients did. Conclusions: Our findings suggest that patients with PDAC value PF and engaging in daily and social activities the most, whereas physicians prioritize symptoms such as pain. Patient-reported outcomes need to become more integrated into PDAC care and research to better identify unmet patient needs, inform treatment decisions, and develop therapies that address outcomes valued by patients.

Background Widespread implementation of electronic health records (EHR) has created new opportunities for pediatric oncology observational research. Little attention has been given to using EHR data to identify patients with pediatric hematologic malignancies. Methods This study used EHR-derived data in a pediatric clinical data research network, PEDSnet, to develop and evaluate a computable phenotype algorithm to identify pediatric patients with leukemia and lymphoma who received treatment with chemotherapy. To guide early development, multiple computable phenotype-defined cohorts were compared to one institution's tumor registry. The most promising algorithm was chosen for formal evaluation and consisted of at least two leukemia/lymphoma diagnoses (Systematized Nomenclature of Medicine codes) within a 90-day period, two chemotherapy exposures, and three hematology-oncology provider encounters. During evaluation, the computable phenotype was executed against EHR data from 2011 to 2016 at three large institutions. Classification accuracy was assessed by masked medical record review with phenotype-identified patients compared to a control group with at least three hematology-oncology encounters. Results The computable phenotype had sensitivity of 100% (confidence interval [CI] 99%, 100%), specificity of 99% (CI 99%, 100%), positive predictive value (PPV) and negative predictive value (NPV) of 100%, and C-statistic of 1 at the development institution. The computable phenotype performance was similar at the two test institutions with sensitivity of 100% (CI 99%, 100%), specificity of 99% (CI 99%, 100%), PPV of 96%, NPV of 100%, and C-statistic of 0.99. Conclusion The EHR-based computable phenotype is an accurate cohort identification tool for pediatric patients with leukemia and lymphoma who have been treated with chemotherapy and is ready for use in clinical studies.

OBJECTIVES:To investigate children’s general health and life satisfaction in the context of chronic illness.METHODS:Caregivers (n = 1113) from 3 concurrent cohort studies completed the Patient-Reported Outcomes Measurement Information System Parent-Proxy Global Health measure, which is used to assess a child’s overall physical, mental, and social health, as well as the Patient-Reported Outcomes Measurement Information System Parent-Proxy Life Satisfaction measure between March 2017 and December 2017 for 1253 children aged 5 to 9 years. We harmonized demographic factors and family environmental stressors (single parent, maternal mental health, and income) to common metrics across the cohorts. To examine associations between chronic illness and children’s general health and life satisfaction, we fit linear regression models with cohort fixed effects and accounted for the multilevel data structure of multiple children nested within the same family (ie, twins and other siblings) with generalized estimating equations.RESULTS:Children with chronic illness had worse general health than those without illness (adjusted β = −1.20; 95% confidence interval: −2.49 to 0.09). By contrast, children with chronic illness had similar levels of life satisfaction (adjusted β = −.19; 95% confidence interval: −1.25 to 0.87). Additionally, children’s psychological stress had the strongest negative association with both outcomes, even after adjusting for demographics and family environmental stressors.CONCLUSIONS:Although children with chronic illness have lower parent-reported general health, their life satisfaction appears comparable with that of peers without chronic illness. With this study, we provide evidence that chronic illnesses do not preclude children from leading happy and satisfying lives.

Background Pediatric primary care visits are a foundational element in the health maintenance of children. Differential access may be a driver of racial inequities in health. We hypothesized that pediatric primary care accessibility would be lowest in neighborhoods with higher proportion of non-Hispanic Black residents. Methods Annual ratios (2008–2016) of providers to pediatric population were calculated by census tract in Philadelphia, Pennsylvania. Marginal logistic regression was used to estimate the independent association between neighborhood racial composition and access to pediatric primary care controlling for confounders. Results In general, low access to care was associated with greater neighborhood disadvantage (e.g., SES, % poverty, % public insurance). After controlling for neighborhood indicators of disadvantage, risk of being in the lowest quintile of access significantly increased as the percent of non-Hispanic Black residents increased. Conclusion A new measure of pediatric primary care accessibility demonstrates a persistent disparity in primary care access for predominantly non-Hispanic Black neighborhoods.

BACKGROUND: Developing a research agenda that is focused on the priorities of key stakeholders may expedite implementation and dissemination. Our objective was to identify the highest-priority patient-safety research topics among pediatric clinicians, health care leaders, and families. METHODS: The Children’s Hospitals Solutions for Patient Safety Network is a network of >100 children’s hospitals working together to eliminate harm due to health care. Parents and site leaders responded to an open-ended, anonymous e-mail survey used to elicit research topics. A key stakeholder panel winnowed related topics and prioritized topics using Likert scale ratings. Site leaders and parents responded to a second anonymous e-mail survey and rated the importance of each topic. Health system executive interviews were used to elicit their opinions regarding top priorities for patient-safety research. RESULTS: The elicitation survey had 107 respondents who produced 49 unique research topics. The key stakeholder panel developed a final list of 24 topics. The prioritization survey had 74 respondents. Top-priority research topics concerned high reliability, safety culture, open communication, and early detection of patient deterioration and sepsis. During 7 qualitative interviews, health system executives highlighted diagnostic error, medication safety, deterioration, and ambulatory patient safety as priority areas. CONCLUSIONS: With this study, we take a first step toward a stakeholder-driven research agenda on the basis of the assumption that stakeholders are best positioned to determine what research will be used to address the problems of most concern to them.

BackgroundThe Johns Hopkins ACG System is widely used to predict patient healthcare service use and costs. Most applications have focused on adult populations. In this study, we evaluated the use of the ACG software to predict pediatric unplanned hospital admission in a given month, based on the past year's clinical information captured by electronic health records (EHRs).Methods and findingsEHR data from a multi-state pediatric integrated delivery system were obtained for 920,051 patients with at least one physician visit during January 2009 to December 2016. Over this interval an average of 0.36% of patients each month had an unplanned hospitalization. In a 70% training sample, we used the generalized linear mixed model (GLMM) to generate regression coefficients for demographic, clinical predictors derived from the ACG system, and prior year hospitalizations. Applying these coefficients to a 30% test sample to generate risk scores, we found that the area under the receiver operator characteristic curve (AUC) was 0.82. Omitting prior hospitalizations decreased the AUC from 0.82 to 0.80, and increased under-estimation of hospitalizations at the greater risk levels. Patients in the top 5% of risk scores accounted for 43% and the top 1% of risk scores accounted for 20% of all unplanned hospitalizations.ConclusionsA predictive model based on 12-months of demographic and clinical data using the ACG system has excellent predictive performance for 30-day pediatric unplanned hospitalization. This model may be useful in population health and care management applications targeting patients likely to be hospitalized. External validation at other institutions should be done to confirm our results.

OBJECTIVES: Adult obesity is linked to asthma cases and is estimated to lead to 250 000 new cases yearly. Similar incidence and attributable risk (AR) estimates have not been developed for children. We sought to describe the relationship between overweight and obesity and incident asthma in childhood and quantify AR statistics in the United States for overweight and obesity on pediatric asthma. METHODS: The PEDSnet clinical data research network was used to conduct a retrospective cohort study (January 2009–December 2015) to compare asthma incidence among overweight and/or obese versus healthy weight 2- to 17-year-old children. Asthma incidence was defined as ≥2 encounters with a diagnosis of asthma and ≥1 asthma controller prescription. Stricter diagnostic criteria involved confirmation by spirometry. We used multivariable Poisson regression analyses to estimate incident asthma rates and risk ratios and accepted formulas for ARs. RESULTS: Data from 507 496 children and 19 581 972 encounters were included. The mean participant observation period was 4 years. The adjusted risk for incident asthma was increased among children who were overweight (relative risk [RR]: 1.17; 95% confidence interval [CI]: 1.10–1.25) and obese (RR: 1.26; 95% CI: 1.18–1.34). The adjusted risk for spirometry-confirmed asthma was increased among children with obesity (RR: 1.29; 95% CI: 1.16–1.42). An estimated 23% to 27% of new asthma cases in children with obesity is directly attributable to obesity. In the absence of overweight and obesity, 10% of all cases of asthma would be avoided. CONCLUSIONS: Obesity is a major preventable risk factor for pediatric asthma.

Importance There is limited information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing and infection among pediatric patients across the United States. Objective To describe testing for SARS-CoV-2 and the epidemiology of infected patients. Design, Setting, and Participants A retrospective cohort study was conducted using electronic health record data from 135 794 patients younger than 25 years who were tested for SARS-CoV-2 from January 1 through September 8, 2020. Data were from PEDSnet, a network of 7 US pediatric health systems, comprising 6.5 million patients primarily from 11 states. Data analysis was performed from September 8 to 24, 2020. Exposure Testing for SARS-CoV-2. Main Outcomes and Measures SARS-CoV-2 infection and coronavirus disease 2019 (COVID-19) illness. Results A total of 135 794 pediatric patients (53% male; mean [SD] age, 8.8 [6.7] years; 3% Asian patients, 15% Black patients, 11% Hispanic patients, and 59% White patients; 290 per 10 000 population [range, 155-395 per 10 000 population across health systems]) were tested for SARS-CoV-2, and 5374 (4%) were infected with the virus (12 per 10 000 population [range, 7-16 per 10 000 population]). Compared with White patients, those of Black, Hispanic, and Asian race/ethnicity had lower rates of testing (Black: odds ratio [OR], 0.70 [95% CI, 0.68-0.72]; Hispanic: OR, 0.65 [95% CI, 0.63-0.67]; Asian: OR, 0.60 [95% CI, 0.57-0.63]); however, they were significantly more likely to have positive test results (Black: OR, 2.66 [95% CI, 2.43-2.90]; Hispanic: OR, 3.75 [95% CI, 3.39-4.15]; Asian: OR, 2.04 [95% CI, 1.69-2.48]). Older age (5-11 years: OR, 1.25 [95% CI, 1.13-1.38]; 12-17 years: OR, 1.92 [95% CI, 1.73-2.12]; 18-24 years: OR, 3.51 [95% CI, 3.11-3.97]), public payer (OR, 1.43 [95% CI, 1.31-1.57]), outpatient testing (OR, 2.13 [1.86-2.44]), and emergency department testing (OR, 3.16 [95% CI, 2.72-3.67]) were also associated with increased risk of infection. In univariate analyses, nonmalignant chronic disease was associated with lower likelihood of testing, and preexisting respiratory conditions were associated with lower risk of positive test results (standardized ratio [SR], 0.78 [95% CI, 0.73-0.84]). However, several other diagnosis groups were associated with a higher risk of positive test results: malignant disorders (SR, 1.54 [95% CI, 1.19-1.93]), cardiac disorders (SR, 1.18 [95% CI, 1.05-1.32]), endocrinologic disorders (SR, 1.52 [95% CI, 1.31-1.75]), gastrointestinal disorders (SR, 2.00 [95% CI, 1.04-1.38]), genetic disorders (SR, 1.19 [95% CI, 1.00-1.40]), hematologic disorders (SR, 1.26 [95% CI, 1.06-1.47]), musculoskeletal disorders (SR, 1.18 [95% CI, 1.07-1.30]), mental health disorders (SR, 1.20 [95% CI, 1.10-1.30]), and metabolic disorders (SR, 1.42 [95% CI, 1.24-1.61]). Among the 5374 patients with positive test results, 359 (7%) were hospitalized for respiratory, hypotensive, or COVID-19–specific illness. Of these, 99 (28%) required intensive care unit services, and 33 (9%) required mechanical ventilation. The case fatality rate was 0.2% (8 of 5374). The number of patients with a diagnosis of Kawasaki disease in early 2020 was 40% lower (259 vs 433 and 430) than in 2018 or 2019. Conclusions and Relevance In this large cohort study of US pediatric patients, SARS-CoV-2 infection rates were low, and clinical manifestations were typically mild. Black, Hispanic, and Asian race/ethnicity; adolescence and young adulthood; and nonrespiratory chronic medical conditions were associated with identified infection. Kawasaki disease diagnosis is not an effective proxy for multisystem inflammatory syndrome of childhood.

OBJECTIVE To evaluate the content and construct validity of the existing PROMIS Pediatric Parent-Proxy Peer Relationships Measure in 5- to 12-year-old children with autism spectrum disorder (ASD). METHOD Parents of 121 children aged 5 to 12 years who met DSM-IV criteria for ASD completed the Peer Relationships Measure using computerized adaptive testing (CAT). Parents also completed the Social Responsiveness Scale, Second Edition (SRS-2) and a demographic form. Intelligence quotient test results were extracted from clinical or research records. Five parents participated in semi-structured interviews about their child's peer relationships and the item content on the Peer Relationships Measure. RESULTS The children in the sample were primarily male (87%). The sample was racially and ethnically diverse, and parents were predominantly highly educated. The mean T-score (SD) on the Peer Relationships Measure was 36 (8), with a range from 15 to 62. For 98% of subjects, the CAT required administration of 5 items to reach a standard error of measurement of less than 4 T-score units. The Peer Relationships Measure demonstrated a large correlation with the SRS-2 (r = -0.60, p < .0001). In semi-structured interviews, parents reported that the items on the Peer Relationships Measure were relevant to the peer relationships of their child with ASD, but they reported a few challenges related to variability in their children's peer relationships over time and to somewhat limited knowledge of relationships in school. CONCLUSION The PROMIS Pediatric Parent-Proxy Peer Relationships Measure may be an efficient, precise, and valid measure of peer relationships for 5- to 12-year-old children with ASD.

Social, psychological, and behavioral factors are recognized as key contributors to health, but they are rarely measured in a systematic way in health care settings. Electronic health records (EHRs) can be used in these settings to routinely collect a standardized set of social, psychological, and behavioral determinants of health. The expanded use of EHRs provides opportunities to improve individual and population health, and offers new ways for the psychological community to engage in health promotion and disease prevention efforts. This article addresses 3 issues. First, it discusses what led to current efforts to include measures of psychosocial and behavioral determinants of health in EHRs. Second, it presents recommendations of an Institute of Medicine committee regarding inclusion in EHRS of a panel of measures that meet a priori criteria. Third, it identifies new opportunities and challenges these recommendations present for psychologists in practice and research. (PsycINFO Database Record

The National Heart, Lung, and Blood Institute convened a working group in January 2015 to explore issues related to an integrated data network for congenital heart disease research. The overall goal was to develop a common vision for how the rapidly increasing volumes of data captured across numerous sources can be managed, integrated, and analyzed to improve care and outcomes. This report summarizes the current landscape of congenital heart disease data, data integration methodologies used across other fields, key considerations for data integration models in congenital heart disease, and the short- and long-term vision and recommendations made by the working group.

ObjectivesContent elucidation for patient-reported outcomes (PROs) in paediatric cancer survivorship is understudied. We aimed to compare differences in the contents of five PRO domains that are important to paediatric cancer survivorship through semistructured interviews with paediatric cancer survivors and caregivers, and identified new concepts that were not covered in the item banks of the Patient-Reported Outcomes Measurement Information System (PROMIS).DesignSemistructured interviews to collect qualitative PRO data from survivors and caregivers.SettingA survivorship care clinic of a comprehensive cancer centre in the USA.ParticipantsThe study included 51 survivors (ResultsFor pain and meaning and purpose, ‘Hurt a lot’ and ‘Purpose in life’ were top concepts for survivors and caregivers, respectively. For fatigue and psychological stress, ‘Needed to sleep during the day’/‘Trouble doing schoolwork’ and ‘Felt worried’ were top concepts for survivors, and ‘Felt tired’ and ‘Felt distress’/‘Felt stressed’ for caregivers. Survivors reported more physically relevant contents (eg, ‘Hard to do sport/exercise’; 0.78 vs 0.23, p=0.007) for pain, fatigue and stress, whereas caregivers used more emotionally relevant concepts (eg, ‘Too tired to enjoy things I like to do’; 0.31 vs 0.05, p=0.025). Both groups reported positive thoughts for meaning and purpose (eg, ‘Have goals for myself’). One (psychological stress, meaning and purpose) to eleven (fatigue) new concepts were generated.ConclusionsImportant PRO contents in the form of meaningful concepts raised by survivors and caregivers were different and new concepts emerged. PRO measures are warranted to include survivorship-specific items by accounting for the child’s and the caregiver’s viewpoints.

OBJECTIVES: To determine the association of antibiotic use with weight outcomes in a large cohort of children. METHODS: Health care data were available from 2009 to 2016 for 35 institutions participating in the National Patient-Centered Clinical Research Network. Participant inclusion required same-day height and weight measurements at 0 to RESULTS: Among 1 792 849 children with a same-day height and weight measurement at CONCLUSIONS: Antibiotic use at

In the original publication of the article, two of the author names “L. A. Schroder, F. Metzner” and email address of the authors “J. Devine, J. Moon, A. C. Haller” were missed out. The correct author group with affiliations are provided in this correction.

OBJECTIVE: The purpose of this study is to describe the psychometric evaluation and item response theory calibration of the PROMIS Pediatric Positive Affect item bank, child-report and parent-proxy editions. METHODS: The initial item pool comprising 53 items, previously developed using qualitative methods, was administered to 1,874 children 8–17 years old and 909 parents of children 5–17 years old. Analyses included descriptive statistics, reliability, factor analysis, differential item functioning, and construct validity. A total of 14 items were deleted, because of poor psychometric performance, and an 8-item short form constructed from the remaining 39 items was administered to a national sample of 1,004 children 8–17 years old, and 1,306 parents of children 5–17 years old. The combined sample was used in item response theory (IRT) calibration analyses. RESULTS: The final item bank appeared unidimensional, the items appeared locally independent, and the items were free from differential item functioning. The scales showed excellent reliability and convergent and discriminant validity. Positive affect decreased with children’s age and was lower for those with a special health care need. After IRT calibration, we found that 4 and 8 item short forms had a high degree of precision (reliability) across a wide range of the latent trait (>4 SD units). CONCLUSION: The PROMIS Pediatric Positive Affect item bank and its short forms provide an efficient, precise, and valid assessment of positive affect in children and youth.

Objective: To develop the Patient Reported Outcome Measurement Information System (PROMIS) Pediatric Sleep Health item pool and evaluate its content validity. Participants: Participants included 8 ...

The purpose of this study was to assess whether there is an association between oral thrush or other Candida-related conditions in infancy and early childhood caries (ECC) diagnosed by pediatricians.We conducted a retrospective cohort study using electronic health records from six national children's hospitals that participate in the PEDSnet research network. There were 1,012,668 children with a visit at ages one to 12 months and another visit at ages 13 to 71 months. The independent variables were diagnosis of thrush or Candida-related conditions in the first year of life, while the dependent variable was diagnosis of ECC between 13 to 71 months old.Oral thrush detection was strongly associated with ECC, particularly between 13 and 36 months (rate ratio between 2.7 [95 percent confidence interval (95% CI) equals 2.5 to 2.9; P.001] and 3.0 [95% CI, equals 2.8 to 3.4; P.001]). A similar trend was observed with other Candida-related conditions.Oral thrush may be a risk factor for early childhood caries.

Study objectives To develop and evaluate the measurement properties of child-report and parent-proxy versions of the Patient-Reported Outcomes Measurement Information System (PROMIS) Pediatric Sleep Disturbance and Sleep-Related Impairment item banks. Methods A national sample of 1104 children (8-17 years old) and 1477 parents of children 5-17 years old was recruited from an internet panel to evaluate the psychometric properties of 43 sleep health items. A convenience sample of children and parents recruited from a pediatric sleep clinic was obtained to provide evidence of the measures' validity; polysomnography data were collected from a subgroup of these children. Results Factor analyses suggested two dimensions: sleep disturbance and daytime sleep-related impairment. The final item banks included 15 items for Sleep Disturbance and 13 for Sleep-Related Impairment. Items were calibrated using the graded response model from item-response theory. Of the 28 items, 16 are included in the parallel PROMIS adult sleep health measures. Reliability of the measures exceeded 0.90. Validity was supported by correlations with existing measures of pediatric sleep health and higher sleep disturbance and sleep-related impairment scores for children with sleep problems and those with chronic and neurodevelopmental disorders. The sleep health measures were not correlated with results from polysomnography. Conclusions The PROMIS Pediatric Sleep Disturbance and Sleep-Related Impairment item banks provide subjective assessments of child's difficulty falling and staying asleep as well as daytime sleepiness and its impact on functioning. They may prove useful in the future for clinical research and practice. Future research should evaluate their responsiveness to clinical change in diverse patient populations.

The United States has poorer child health outcomes than other wealthy nations despite greater per capita spending on health care for children. To better understand this phenomenon, we examined mortality trends for the US and nineteen comparator nations in the Organization for Economic Cooperation and Development for children ages 0-19 from 1961 to 2010 using publicly available data. While child mortality progressively declined across all countries, mortality in the US has been higher than in peer nations since the 1980s. From 2001 to 2010 the risk of death in the US was 76 percent greater for infants and 57 percent greater for children ages 1-19. During this decade, children ages 15-19 were eighty-two times more likely to die from gun homicide in the US. Over the fifty-year study period, the lagging US performance amounted to over 600,000 excess deaths. Policy interventions should focus on infants and on children ages 15-19, the two age groups with the greatest disparities, by addressing perinatal causes of death, automobile accidents, and assaults by firearm.

Objective This article reviews the data available in 3 large databases for use in conducting studies of children with autism spectrum disorder (ASD). Methods The article describes the data structure, data elements, and strengths and weaknesses of the 3 data sets. Results Each of the 3 data sets, the Interactive Autism Network (IAN), the Autism Treatment Network (ATN), and PEDSnet have large cohorts of children with ASD. IAN has strengths in patient-reported measures, ATN in clinical characterization, and PEDSnet in health care encounters and electronic medical record data. Conclusion The data sets described here have potential for further studies that could help improve the care and well-being of children with ASD and their families.

* Abbreviations: MDD — : major depressive disorder PCOR — : Patient-Centered Outcomes Research RCT — : randomized controlled trial Nationally, the lifetime and 12-month prevalences of adolescent major depressive disorder (MDD) have been reported to be 11.7% and 8.2%, respectively.1,2 Recent data have also shown increases in prevalence from 2004 to 2015.3 These trends, coupled with a limited availability of pediatric and adolescent mental health specialists, have resulted in an increased demand for frontline pediatric providers to manage depression. Clinical management involves the use of pharmacological and psychotherapy interventions. Decisions on the most appropriate treatment course for a specific patient are typically based on the biomedical knowledge base composed of research studies as well as the judicious application of clinical experience and wisdom. Findings from randomized controlled trials (RCTs) that were rigorously performed and transparently reported in peer-reviewed medical journals are the most influential type of evidence, affecting both clinical decision-making and guideline development. The RCT has the reputation of being the gold standard for evidence generation because of its capacity to balance confounders (both measured and unmeasured) between groups, thereby strengthening the validity of treatment effect estimation. However, even this powerful study design has limitations of which practicing clinicians should … Address correspondence to Kamila B. Mistry, PhD, MPH, Agency for Healthcare Research and Quality, 5600 Fishers Ln, Room #06N03, Rockville, MD 20857. E-mail: kamila.mistry{at}ahrq.hhs.gov