Prospective Study Of Development Research Articles

The developmental cascade of early parenting, emergence of executive functioning, and emotional symptoms across childhood.

Many studies focus on proximal associations between parental sensitivity and emotional well-being in early childhood, with less data examining how parenting in infancy predicts children's emotional trajectories across childhood, in particular negative emotional symptoms of anxiety and depression. Thus, this study utilized data from The Family Life Project (N=1015), a prospective study of child development in rural poverty, and assessed whether sensitive parenting in the first 4 years of life predicted child internalizing emotional symptoms (i.e., anxiety and depression) from kindergarten to fifth grade and whether early child executive functioning mediated this relationship. Path models indicated that observation of sensitive parenting predicted a decrease in teachers' report of child negative emotional symptoms over time and predicted fewer negative emotional symptoms in fifth grade. Moreover, though executive functioning performance did not mediate change in symptoms over time, executive functioning did mediate the relationship between sensitive parenting and fifth-grade symptoms, suggesting that executive functioning is one mechanism by which early sensitive parenting buffers long-term emotional development. Findings highlight the importance of early parenting and executive functioning in development of anxiety and depression symptoms and suggests potential targets for transdiagnostic intervention.

Editorial Comment

No AccessJournal of UrologyAdult Urology1 Apr 2021Editorial CommentThis article comments on the following:Prostate Radiofrequency Focal Ablation (ProRAFT) Trial: A Prospective Development Study Evaluating a Bipolar Radiofrequency Device to Treat Prostate Cancer Nathan Perlis Nathan PerlisNathan Perlis Urologic Oncology, Sprott Department of Surgery, Princess Margaret Cancer Center, University Health Network, University of Toronto, Toronto, Ontario, Canada More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000001567.01AboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail "Editorial Comment." The Journal of Urology, 205(4), pp. 1098–1099 © 2021 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetailsRelated articlesJournal of UrologyDec 14, 2020, 12:00:00 AMProstate Radiofrequency Focal Ablation (ProRAFT) Trial: A Prospective Development Study Evaluating a Bipolar Radiofrequency Device to Treat Prostate Cancer Volume 205Issue 4April 2021Page: 1098-1099 Advertisement Copyright & Permissions© 2021 by American Urological Association Education and Research, Inc.MetricsAuthor Information Nathan Perlis Urologic Oncology, Sprott Department of Surgery, Princess Margaret Cancer Center, University Health Network, University of Toronto, Toronto, Ontario, Canada More articles by this author Expand All Advertisement Loading ...

CONECT-6: a case-finding tool to identify patients with complex health needs

BackgroundEarly identification of patients with chronic conditions and complex health needs in emergency departments (ED) would enable the provision of services better suited to their needs, such as case management. A case-finding tool would ultimately support ED teams to this end and could reduce the cost of services due to avoidable ED visits and hospitalizations. The aim of this study was to develop and validate a short self-administered case-finding tool in EDs to identify patients with chronic conditions and complex health needs in an adult population.MethodsThis prospective development and initial validation study of a case-finding tool was conducted in four EDs in the province of Quebec (Canada). Adult patients with chronic conditions were approached at their third or more visit to the ED within 12 months to complete a self-administered questionnaire, which included socio-demographics, a comorbidity index, the reference standard INTERMED self-assessment, and 12 questions to develop the case-finding tool. Significant variables in bivariate analysis were included in a multivariate logistic regression analysis and a backward elimination procedure was applied. A receiver operating characteristic (ROC) curve was developed to identify the most appropriate threshold score to identify patients with complex health needs.ResultsTwo hundred ninety patients participated in the study. The multivariate analysis yielded a six-question tool, COmplex NEeds Case-finding Tool – 6 (CONECT-6), which evaluates the following variables: low perceived health; limitations due to pain; unmet needs; high self-perceived complexity; low income; and poor social support. With a threshold of two or more positive answers, the sensitivity was 90% and specificity 66%. The positive and negative predictive values were 49 and 95% respectively.ConclusionsThe case-finding process is the essential characteristic of case management effectiveness. This study presents the first case-finding tool to identify adult patients with chronic conditions and complex health needs in ED.

Electronic Health Record-Based Prediction of 1-Year Risk of Incident Cardiac Dysrhythmia: Prospective Case-Finding Algorithm Development and Validation Study.

BackgroundCardiac dysrhythmia is currently an extremely common disease. Severe arrhythmias often cause a series of complications, including congestive heart failure, fainting or syncope, stroke, and sudden death.ObjectiveThe aim of this study was to predict incident arrhythmia prospectively within a 1-year period to provide early warning of impending arrhythmia.MethodsRetrospective (1,033,856 individuals enrolled between October 1, 2016, and October 1, 2017) and prospective (1,040,767 individuals enrolled between October 1, 2017, and October 1, 2018) cohorts were constructed from integrated electronic health records in Maine, United States. An ensemble learning workflow was built through multiple machine learning algorithms. Differentiating features, including acute and chronic diseases, procedures, health status, laboratory tests, prescriptions, clinical utilization indicators, and socioeconomic determinants, were compiled for incident arrhythmia assessment. The predictive model was retrospectively trained and calibrated using an isotonic regression method and was prospectively validated. Model performance was evaluated using the area under the receiver operating characteristic curve (AUROC).ResultsThe cardiac dysrhythmia case-finding algorithm (retrospective: AUROC 0.854; prospective: AUROC 0.827) stratified the population into 5 risk groups: 53.35% (555,233/1,040,767), 44.83% (466,594/1,040,767), 1.76% (18,290/1,040,767), 0.06% (623/1,040,767), and 0.003% (27/1,040,767) were in the very low-risk, low-risk, medium-risk, high-risk, and very high-risk groups, respectively; 51.85% (14/27) patients in the very high-risk subgroup were confirmed to have incident cardiac dysrhythmia within the subsequent 1 year.ConclusionsOur case-finding algorithm is promising for prospectively predicting 1-year incident cardiac dysrhythmias in a general population, and we believe that our case-finding algorithm can serve as an early warning system to allow statewide population-level screening and surveillance to improve cardiac dysrhythmia care.

Machine learning model predicts short-term mortality among prehospital patients: A prospective development study from Finland

AimTo show whether adding blood glucose to the National Early Warning Score (NEWS) parameters in a machine learning model predicts 30-day mortality more precisely than the standard NEWS in a prehospital setting. MethodsIn this study, vital sign data prospectively collected from 3632 unselected prehospital patients in June 2015 were used to compare the standard NEWS to random forest models for predicting 30-day mortality. The NEWS parameters and blood glucose levels were used to develop the random forest models. Predictive performance on an unknown patient population was estimated with a ten-fold stratified cross-validation method. ResultsAll NEWS parameters and blood glucose levels were reported in 2853 (79%) eligible patients. Within 30 days after contact with ambulance staff, 97 (3.4%) of the analysed patients had died. The area under the receiver operating characteristic curve for the 30-day mortality of the evaluated models was 0.682 (95% confidence interval [CI], 0.619–0.744) for the standard NEWS, 0.735 (95% CI, 0.679–0.787) for the random forest-trained NEWS parameters only and 0.758 (95% CI, 0.705–0.807) for the random forest-trained NEWS parameters and blood glucose. The models predicted secondary outcomes similarly, but adding blood glucose into the random forest model slightly improved its performance in predicting short-term mortality. ConclusionsAmong unselected prehospital patients, a machine learning model including blood glucose and NEWS parameters had a fair performance in predicting 30-day mortality.

Preschool Neuropsychological Predictors of School-aged Sluggish Cognitive Tempo and Inattentive Behaviors.

Sluggish cognitive tempo (SCT) is characterized by excessive daydreaming, slowed thinking, and mental confusion and 'fogginess'. A growing body of research supports the empirical differentiation of sluggish cognitive tempo (SCT) from the inattentive (IN) behaviors that characterize attention-deficit/hyperactivity disorder (ADHD). Further SCT and IN are uniquely associated with clinical correlates across academic, social, and emotional domains; however, there is limited understanding of how neuropsychological functioning contributes to SCT and/or IN behaviors. The two broad domains of neuropsychological functioning that have been most frequently examined in relation to SCT behaviors are processing speed and executive functions (EF). The present study tested whether EF and processing speed measured when children were on average age five years were predictive of teacher-rated IN and SCT behaviors in 1st - 3rd grades. Participants included 1,022 children from the Family Life Project, an ongoing prospective longitudinal study of child development in low-income, non-metropolitan communities. EF and processing speed uniquely made independent contributions to the prediction of IN and SCT. In secondary analyses that focused on specific facets of EF and processing speed, inhibitory control and working memory abilities predicted lower IN but not SCT behaviors, whereas slower processing speed significantly predicted both greater SCT and IN behaviors. These results are discussed as they inform developmental models of SCT and IN.

A cloud-computing platform for developing and evaluating vocal biomarkers based on home audio recordings: Resources for large-scale data processing and analysis

This presentation describes the design and construction of a comprehensive cloud-computing platform for implementing and evaluating vocal biomarkers, both for assessing typical development of speech and language and detecting deviations in autism. As part of a prospective longitudinal study of early vocal development (NIH P50 MH100029), whole-day home audio recordings were collected from more than 300 children every month from birth to three years using LENA, providing long-term, large-scale sampling of each child's natural environment. The database contains more than 40 000 h of raw audio data, post-processed acoustic measures, event timing statistics, hand-coded and automated annotations, as well as sociodemographic and clinical metadata, the storage, integration and processing of which has presented significant new challenges. Flexible cloud solutions have been adopted to allow secure cross-platform shared access and referencing of the data. Customized modular “C” code libraries for physical modeling, spectral analysis, temporal event labeling, voice activity detection, speaker diarization and developmental profiling have been developed, based on standard BLAS/LAPACK libraries optimized for device-independent virtual machines, and integrated with an interactive graphical interface for signal analysis and labeling. Resources and specific challenges for large-scale analysis of infant vocalizations will be discussed.

Screening for Opioid and Stimulant Exposure In Utero Through Targeted and Untargeted Metabolomics Analysis of Umbilical Cords.

Neonatal abstinence syndrome is an array of signs and symptoms experienced by a newborn due to abrupt discontinuation of intrauterine exposure to certain drugs, primarily opioids. In the United States, the incidence of neonatal abstinence syndrome has tripled over the past decade. The current standard of care for drug testing includes the analysis of infant urine and meconium. Sample collection is associated with several limitations, including diaper media interferences, limited sample amount, sample heterogeneity, and the need for professional staff for collection. Umbilical cord tissue has emerged as a convenient sample matrix for testing owing to its universal availability. The purpose of this study was to examine umbilical cords using an untargeted metabolomics approach to determine the detected drugs and validate an analytical method to confirm and quantify the identified drugs. A metabolomics analysis was performed with 21 umbilical cords to screen for drugs and drug metabolites by liquid chromatography-mass spectrometry. Drugs were identified using the National Institute of Standards and Technology database, and an analytical method was developed and validated using secondary liquid chromatography-mass spectrometry instrument for positive confirmation and quantitative analysis. Twenty-one random umbilical cords from women were tested: 4 were positive for cocaine and the primary and secondary metabolites; one was positive for methadone, the primary metabolite; 3 were positive for cotinine, the metabolite of nicotine; and 5 were positive for acetyl norfentanyl. Our research is a prospective method development study using untargeted and targeted approaches to characterize steady-state drug metabolite levels in the umbilical cord matrix at the time of delivery. By characterizing drug type and concentration, this methodology can be used to develop a reliable complementary testing method for meconium toxicology screens.

Prospective clinical study of transverse development with orthodontics with self-ligating brackets.

Orthodontics with low friction, low force, passive self-ligating brackets produces alveolar-dental remodeling, resulting in an increase in the transverse diameter of the dental arches, especially in the premolar sector. The aim of this study was to compare the modifications of the transverse diameter in the pre- and post-dental alignment cast models with orthodontics with passive self-ligating brackets in patients with moderate to severe dental discrepancy. The study included 28 patients of both sexes aged 16 to 48 years with dental discrepancies between -6 and -16 mm, treated with self-ligating Damon brackets and thermally activated Nickel- Titanium-Copper arches. With a digital pachymeter, Mitutoyo brand, five measurements were taken per dental arch: distance between canines (C), first premolars (1PM), second premolars (2 PM), first molars (1M) and second molars (2M), before and after orthodontic alignment. The variations were statistically evaluated by Student T Test for paired samples. Average distance between teeth varied with dental alignment in both jaws. The greatest increases in transverse diameter were recorded in the premolar areas. Minor though statistically significant variations also occurred in the 2M of the maxilla and in the C of the mandible In alignment with passive self-ligating brackets, there is an increase in the transverse diameter due to the development of the dental arches, mainly in the premolar sector of both jaws and also at the level of the canines in the mandible.

Long-term prospective study of development of hepatocellular carcinoma in compensated cirrhosis

Long-term prospective study of development of hepatocellular carcinoma in compensated cirrhosis

Using Serum Metabolomics to Predict Development of Anti-drug Antibodies in Multiple Sclerosis Patients Treated With IFNβ.

Background: Neutralizing anti-drug antibodies (ADA) can greatly reduce the efficacy of biopharmaceuticals used to treat patients with multiple sclerosis (MS). However, the biological factors pre-disposing an individual to develop ADA are poorly characterized. Thus, there is an unmet clinical need for biomarkers to predict the development of immunogenicity, and subsequent treatment failure. Up to 35% of MS patients treated with beta interferons (IFNβ) develop ADA. Here we use machine learning to predict immunogenicity against IFNβ utilizing serum metabolomics data.Methods: Serum samples were collected from 89 MS patients as part of the ABIRISK consortium—a multi-center prospective study of ADA development. Metabolites and ADA were quantified prior to and after IFNβ treatment. Thirty patients became ADA positive during the first year of treatment (ADA+). We tested the efficacy of six binary classification models using 10-fold cross validation; k-nearest neighbors, decision tree, random forest, support vector machine and lasso (Least Absolute Shrinkage and Selection Operator) logistic regression with and without interactions.Results: We were able to predict future immunogenicity from baseline metabolomics data. Lasso logistic regression with/without interactions and support vector machines were the most successful at identifying ADA+ or ADA– cases, respectively. Furthermore, patients who become ADA+ had a distinct metabolic response to IFNβ in the first 3 months, with 29 differentially regulated metabolites. Machine learning algorithms could also predict ADA status based on metabolite concentrations at 3 months. Lasso logistic regressions had the greatest proportion of correct classifications [F1 score (accuracy measure) = 0.808, specificity = 0.913]. Finally, we hypothesized that serum lipids could contribute to ADA development by altering immune-cell lipid rafts. This was supported by experimental evidence demonstrating that, prior to IFNβ exposure, lipid raft-associated lipids were differentially expressed between MS patients who became ADA+ or remained ADA–.Conclusion: Serum metabolites are a promising biomarker for prediction of ADA development in MS patients treated with IFNβ, and could provide novel insight into mechanisms of immunogenicity.

Development and validation of an ICU-specific pressure injury risk assessment scale.

Critically ill patients are at high risk for pressure injury (PI) due to critical illness combined with multiple interventions and therapies. It is hence important to gain more knowledge about the risk factors associated with pressure injury development and methods for decreasing its prevalence. To develop and validate a clinical useful ICU-specific PI risk assessment scale based on the RAPS. The study was designed as a prospective instrument development and validation study. The Risk Assessment Pressure Ulcer Scale (RAPS), which in Sweden is a commonly used PI risk assessment scale, was used as a starting point. Development was then performed in different steps; adaption of items and response options to ICU care, discussion with ICU staff members to enhance clinical relevance and usability, test of interrater reliability, revision of instrument, a new test with 300 patients followed by statistical evaluation. The final version of the RAPS-ICU consists of six items: failure of vital organs, mobility, moisture, sensory perception, level of consciousness and special treatment in the form of mechanical ventilation, continuous dialysis and/or inotropic drugs. A total score was reached by summing all responses. Each of the items was found to be significant associated with PI development as well as the total score (p<0.001). The total score also showed a high interrater reliability (ICC=0.96), good sensitivity and acceptable specificity with AUC=0.71 and ICU staff perceived the RAPS-ICU as relevant and easy to use in clinical practice. The RAPS-ICU is a valid and clinically useful tool to identify patients at risk to develop pressure injury at ICU.

Association between maternal exposure to the pesticide dichlorodiphenyltrichloroethane (DDT) and risk of obesity in middle age.

Background:Obesity is a malnourishment epidemic worldwide. A meta-analysis of prospective human studies across the world demonstrated a consistent positive association between maternal exposure to the pesticide dichlorodiphenyltrichloroethane (DDT) and its metabolite dichlorodiphenyldichloroethylene (DDE) and children with obesity. The present study evaluates the association of maternal exposure to DDT and DDE with the risk of obesity in daughters during their mid-life in a prospective birth cohort with up to 53 years of follow-up.Methods:Gravidas’ blood was collected during their 1959–1967 enrollment into the prospective Child Health and Development Studies birth cohort in California. Their daughters aged 44–53 years had their height, weight, and waist circumference measured during a home visit to evaluate associations of daughters’ adiposity and relative risk of overweight and obesity with their mothers’ prenatal serum levels of DDT and DDE quantified by gas chromatograph-tandem mass spectrometer (n=511).Results:Maternal o,p’-DDT was positively associated with body mass index (beta=0.59 kg/m2 per ln ng/ml (95th percentile confidence interval, 95CI: 0.17, 1.00)) and waist circumference (beta=1.19 cm per ln ng/ml (95CI: 0.26, 2.13)) in multivariable models. Maternal o,p’-DDT was positively associated with a 26% (95CI: 6–49%) to 31% (95CI: 6–62%) higher risk of overweight and the same magnitude of additional risk for obesity, based on waist circumference and BMI definitions respectively, in multivariable models.Conclusions:These data indicate maternal DDT exposure is significantly associated with increased obesity risk among middle-aged women independent of the obesity definition, confounding, and obesity risk factors. Our findings suggest that policies supporting the use of DDT for malaria vector abatement need to consider the obesity risk as a health cost when weighing the benefits of using DDT in malaria vector control.

Biofeedback Treatment App for Pediatric Migraine: Development and Usability Study.

The objective of this study was to develop and investigate the usability of a biofeedback treatment smartphone app for adolescent migraine sufferers. Biofeedback is effective in treating pediatric migraine. However, biofeedback is not widely used due to the necessity of a trained therapist and specialized equipment. Emerging digital technology, including smartphones and wearables, enables new ways of administering biofeedback. In a prospective open-label development and usability study, 10 adolescent migraine sufferers used a newly developed biofeedback app with wearable sensors that measured their muscle tension, finger temperature, and heart rate. Three iterative rounds of usability testing, including a 2-week home testing period, were completed. A biofeedback algorithm, combining and optimizing the 3 physiological modalities, and several algorithms for sham-treatment were created. Usability was evaluated statistically and summarized thematically. Five of ten participants completed all 3 rounds of usability testing. A total of 72 biofeedback sessions were completed. Usability scoring was consistently high, with median scores ranging from 3.5 to 4.5 on a 5-point scale. The biofeedback optimization algorithm correlated excellently to the raw physiological measurements (r=0.85, P<.001). The intervention was safe and tolerable. We developed an app for young migraine sufferers to receive therapist-independent biofeedback. The app underwent a rigorous development process as well as usability and feasibility testing. It is now ready for clinical trials.

Long-term prospective study of development of hepatocellular carcinoma in compensated cirrhosis

Background and Aims: Hepatocellular carcinoma (HCC) is the 5th incident solid tumor in males and the 2nd for mortality. With the aim of identifying clinical/biologic risk factors for HCC development, we started in 2013 a prospective study in patients with liver cirrhosis undergoing hepatic venous pressure gradient (HVPG) measurement (ClinicalTrials.gov:NCT03083002). Method: 445 consecutive patients with liver cirrhosis prospectively enrolled from July 2013 (66.5% CP-A, 23.2% CP-B, 10.3% CP-C) when undergoing HVPG/transjugular liver biopsy, were followed-up every 6 months with US and blood tests. Etiology, portal vein thrombosis, HVPG,esophageal varices, Child-Pugh,MELD Score, time to HCC development were recorded. Incident cases of HCC were biopsied for pathological and transcriptomic characterization. Independent risk factors for HCC were evaluated by Cox regression analysis. Results: Median follow-up was 40 months. 61 patients died during follow-up, 34 developed HCC (incidence 4-5% per year). Preliminary results of analysis of hepatic and circulating biomarkers of angiogenesis, portal hypertension and fibrosis as predictive factors for HCC development indicate marked activation of angiogenesis as related with HCC risk. At univariate analysis HVPG>15 (but not HVPG>10 or >20 mmHg), F2/F3 esophageal varices, viral vs. non-viral etiology,and albumin were statistically associated with HCC development (HVPG/F2-F3 varices collinear). In HVPG>15 multivariate model, none of these factors was significantly associated with HCC development while in F2/F3 esophageal varices model,the latter were independently linked with it (HR 2.258,95% CI:1.135-4.494). Albumin only had borderline significance (.586, CI% .337-1.018). Conclusion: Neither HVPG>10,>15 or >20 was independently associated with HCC development. Previous data indicating HVPG>10 as a significant risk factor for HCC were influenced by the cohort studied, which was free of varices at enrollment. In a cohort of compensated patients with liver cirrhosis not selected for absence of varices, more severe portal hypertension as indicated by F2/F3 varices was the only independent risk factor for HCC development.

Polymer electrolyte membrane fuel cell flow field designs and approaches for performance enhancement

Polymer electrolyte membrane fuel cells are carbon-free electrochemical energy conversion devices that are appropriate for use as a power source on vehicles and mobile devices emerging with their high energy density, lightweight structure, quick startup and lower operating temperature capabilities. However, they need more developments in the aspects of reactant distribution, less pressure drops, precisely balanced water content and heat management to achieve more reliable and higher overall cell performance. Flow field development is one of the most important fields of study to increase cell performance since it has decisive effects on performance parameters, including bipolar plate, and thus fuel cell weight. In this study, recent developments on conventional flow field designs to eliminate their weaknesses and innovative design approaches and flow field architectures are obtained from patent databases, and both numerical and experimental scientific studies. Fundamental designs that create differences are introduced, and their effects on the performance are discussed with regard to origin, objective, innovation strategy of design besides their strength and probable open development ways. As a result, significant enhancements and design strategies on flow field designs in polymer electrolyte membrane fuel cells are summarized systematically to guide prospective flow field development studies.

Monitoring young lifestyles (MyLife) - a prospective longitudinal quantitative and qualitative study of youth development and substance use in Norway

PurposeThe Monitoring Young Lifestyles (MyLife) project was initiated as an integrated quantitative and qualitative prospective investigation of correlates, causes, and consequences of adolescent substance use and other addictive behaviours in...

OC08.02: A prospective controlled study for Caesarean section niche development with hysteroscopic correlation in symptomatising patients

OC08.02: A prospective controlled study for Caesarean section niche development with hysteroscopic correlation in symptomatising patients

Friendship Quality Moderates the Relation Between Maternal Anxiety and Trajectories of Adolescent Internalizing Symptoms.

The current study examined the moderating role of friendship quality on the relation between maternal anxiety and internalizing symptoms in a 3-year prospective study of adolescent development. Participants included 177 adolescents (M age = 16.05, SD age = 0.91) and their mothers. Mothers reported their own levels of anxiety; youth completed self-reports of internalizing symptoms and friendship quality. Positive friendship quality moderated the relation between maternal anxiety and initial levels of internalizing symptoms. Maternal anxiety was associated with steeper increases in internalizing symptoms over time, but only for those with greater negative peer interactions. Findings underscore the important role of both parental and peer relationships in the development of internalizing symptoms and highlight specific avenues for clinical interventions.

Using Repeated-Measures Data to Make Stronger Tests of the Association between Executive Function Skills and Attention Deficit/Hyperactivity Disorder Symptomatology in Early Childhood.

Theoretical models of Attention deficit/hyperactivity disorder (ADHD) have long implicated executive function (EF) skills as contributing to the etiology, maintenance, and changes in ADHD symptomatology over time. Although there is interest making within-person inferences (i.e., deficits in EF skills give rise to ADHD behaviors), most of the evidence has been derived from studies that conflated between- and within-person sources of variance. Here, we use repeated-measures data to test within-person association between EF skills and ADHD behaviors. Participants included 1160 children from the Family Life Project, an ongoing prospective longitudinal study of child development in low-income, nonmetropolitan communities. We tested the magnitude of the association between EF skills and ADHD behaviors when children were 3, 4, and 5years old. Consistent with meta-analyses, unadjusted bivariate associations between EF and ADHD (which reflect combined between- and within-person variation) were of moderate magnitude (rs = -0.20 to -0.30). However, after controlling for all time-invariant, between-person sources of variation, the within-person associations between EF skills and ADHD behaviors were weak (βs - 0.04 to -0.05, ps = 0.01). These results suggest that EF skills may contribute less prominently to ADHD behaviors in early childhood than is commonly assumed and provoke broader questions about developmental models of ADHD.