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Reducing the age of first autism diagnosis facilitates access to critical early intervention services. A current "waitlist crisis" for autism diagnostic evaluation thus demands that we consider novel use of available clinical resources. Previous work has found that expert autism clinicians can identify autism in young children with high specificity after only a brief observation; rapid identification by non-experts remains untested. In the current study, 252 children ages 12-53 months presented for a comprehensive autism diagnostic evaluation. We found that junior clinicians in training to become autism specialists (n = 29) accurately determined whether or not a young child would be diagnosed with autism in the first five minutes of the clinic visit in 75% of cases. Specificity of brief observations was high (0.92), suggesting that brief observations may be an effective tool for triaging young children toward autism-specific interventions. In contrast, the lower negative predictive value (0.71) of brief observations, suggest that they should not be used to rule out autism. When trainees expressed more confidence in their initial impression, their impression was more likely to match the final diagnosis. These findings add to a body of literature showing that clinical observations of suspected autism should be taken seriously, but lack of clinician concern should not be used to rule out autism or overrule other indicators of likely autism, such as parent concern or a positive screening result.

Dementia-related behavioral and psychology symptoms (BPSD) are undertreated and have negative consequences. However, families do not have access to disease information, tailored problem-solving  and effective management strategies, and with COVID-19, are more socially isolated and distressed. To address this dementia care gap, we describe a Phase III efficacy trial testing an online platform, WeCareAdvisor, and design modifications necessitated by COVID-19. WeCareAdvisor provides caregivers with disease information, daily tips, and a systematic approach for describing behaviors, investigating underlying causes, creating tailored strategies, and evaluating their effectiveness (DICE). The trial will enroll 326 caregivers nationwide, randomly assign them to immediately receive WeCareAdvisor (treatment), or a 3-month waitlist (control) and evaluate short (1- and 3-month) and long-term (6-month) outcomes for caregiver distress with and confidence managing BPSD, and BPSD occurrences. We will also evaluate utilization patterns with different prompting conditions: high-intensity (telephone and email reminders), low-intensity (email reminders), or no reminders to use WeCareAdvisor. COVID-19 necessitated design modifications resulting in greater inclusivity of caregivers from diverse races, ethnicities, and geographic areas. Key modifications include shifting from in-home, in-person interviewing to telephone; adjusting tool functionality from operating on a grant-funded iPad to caregivers' personal internet-capable devices; and expanding recruitment from one metropolitan area to nationwide. Study modifications necessitated by COVID-19 facilitate national outreach, easier tool adoption, and enable more diverse caregivers to participate. This study addresses a critical dementia care need, and design modifications may shorten timeline from efficacy testing to commercialization.

BackgroundAutism spectrum disorder (ASD) affects one in 54 children in the United States of America, and supporting people with ASD across the lifespan presents challenges that impact individuals, families, and communities and can be quite costly. The American Academy of Pediatrics has issued recommendations for routine ASD screening at 18 and 24 months, but some research suggests that few pediatricians perform high-fidelity, standardized screening universally. Furthermore, the United States Preventive Services Task Force (USPSTF) found insufficient evidence to recommend for or against universal ASD screening. The objective of this study is to test the hypothesis that children with ASD who have high fidelity; standardized screening will achieve superior outcomes at 5 years of age compared to children receiving usual care ASD detection strategies.MethodsThis is a cluster-randomized, controlled clinical trial in 3 sites in the USA. Pediatric practices will be randomized to implement universal, standardized, high-fidelity toddler screening or usual care, with randomization stratified by the practice size. The study will enroll 3450 children, approximately half in each group. From this sample, we anticipate 100 children to be diagnosed with ASD. Children in both groups receiving an ASD diagnosis will be administered the Early Start Denver Model, an evidence-based early intervention addressing social, communication, and cognitive functioning. Treatment will last for 1 year, with up to 20 h per week of therapy for children with ASD.ResultsPrimary outcomes measured at baseline, following treatment, and at 4 and 5 years of age include ASD symptom severity (Brief Observation of Social Communication Change (BOSCC)) and cognitive functioning (Mullen Scales of Early Learning (MSEL) and Differential Abilities Scale-II (DAS-II)). Secondary outcomes in children include measures of adaptive functioning, ASD symptoms, and kindergarten readiness; secondary analyses will also examine stress and empowerment among parents. Several novel exploratory measures will be included as well. The study will utilize a modified intention-to-treat analysis.ConclusionsThis trial will evaluate the impact of universal, standardized, high-fidelity screening for ASD among children at 18 months of age, with a goal of providing evidence to support this strategy to detect ASD in toddlers in order to start treatment as young as possible and maximize outcomes.Ethics and disseminationThis study was approved by the Institutional Review Board at Drexel University (IRB protocol: 1607004653). All findings will be provided by the principal investigator via email; data will be available through the NIMH Data Archive ( https://nda.nih.gov/ ).Trial registrationClinicalTrials.gov NCT03333629 . Registered on November 7, 2017.

Diagnosticians report that autism spectrum disorder (ASD) is immediately apparent in some, but not all, children ultimately diagnosed. Clinicians' initial diagnostic impressions have implications for ASD early detection, yet the literature raises questions about their accuracy. This study explores diagnostic impressions of ASD specialists made within the first 5 minutes of meeting a young child and investigates factors associated with the match between initial impressions and final diagnoses. Participants were children (n = 294, aged 12-53 months) referred for an ASD evaluation as part of multi-site ASD screening studies. After 5 minutes observing each child, clinicians with expertise diagnosing ASD recorded if they thought the child would meet criteria for ASD following a complete evaluation, and recorded their confidence in this impression. Clinicians' initial impressions matched the final diagnosis in 81% of cases. Ninety-two percent of cases initially thought to have ASD met criteria following a full evaluation; however, 24% of cases initially thought not to have ASD also met criteria, suggesting a high miss rate. Clinicians were generally confident in their initial impressions, reporting highest confidence for children initially thought correctly not to have ASD. ASD behavioral presentation, but not demographic characteristics or developmental level, were associated with matching initial impression and final diagnosis, and confidence. Brief observations indicating ASD should trigger referral to intervention services, but are likely to under-detect positive cases and should not be used to rule out ASD, highlighting the need to incorporate information beyond initial clinical impression. LAY SUMMARY: When children come in for an autism evaluation, clinicians often form early impressions-before doing any formal testing-about whether the child has autism. We studied how often these early impressions match the final diagnosis, and found that clinicians could not easily rule out autism (many children who initially appeared not to have autism were ultimately diagnosed), but were generally accurate ruling in autism (when a child appeared to have autism within 5 minutes, they were almost always so diagnosed).

BackgroundAir pollution exposure is ubiquitous with demonstrated effects on morbidity and mortality. A growing literature suggests that prenatal air pollution exposure impacts neurodevelopment. We posit that the Environmental influences on Child Health Outcomes (ECHO) program will provide unique opportunities to fill critical knowledge gaps given the wide spatial and temporal variability of ECHO participants.ObjectivesWe briefly describe current methods for air pollution exposure assessment, summarize existing studies of air pollution and neurodevelopment, and synthesize this information as a basis for recommendations, or a blueprint, for evaluating air pollution effects on neurodevelopmental outcomes in ECHO.MethodsWe review peer-reviewed literature on prenatal air pollution exposure and neurodevelopmental outcomes, including autism spectrum disorder, attention deficit hyperactivity disorder, intelligence, general cognition, mood, and imaging measures. ECHO meta-data were compiled and evaluated to assess frequency of neurodevelopmental assessments and prenatal and infancy residential address locations. Cohort recruitment locations and enrollment years were summarized to examine potential spatial and temporal variation present in ECHO.DiscussionWhile the literature provides compelling evidence that prenatal air pollution affects neurodevelopment, limitations in spatial and temporal exposure variation exist for current published studies. As >90% of the ECHO cohorts have collected a prenatal or infancy address, application of advanced geographic information systems-based models for common air pollutant exposures may be ideal to address limitations of published research.ConclusionsIn ECHO we have the opportunity to pioneer unifying exposure assessment and evaluate effects across multiple periods of development and neurodevelopmental outcomes, setting the standard for evaluation of prenatal air pollution exposures with the goal of improving children's health.

ObjectiveTo determine whether cerebral small vessel disease or disability modify the effect of SBP treatment on cognitive and vascular outcomes in older patients with recent lacunar stroke.MethodsParticipants aged at least 65 years of the Secondary Prevention of Small Subcortical Strokes Trial were randomized to a higher (130-149 mmHg) or lower (

Background We aimed to determine whether cerebral white matter hyperintensities ( WMHs ) can distinguish stroke survivors susceptible to rapid kidney function decline from intensive blood pressure ( BP ) lowering. Methods and Results The SPS3 (Secondary Prevention of Small Subcortical Strokes) trial randomized participants with recent lacunar stroke to systolic BP targets of 130 to 149 and

Background We aimed to determine whether cerebral white matter hyperintensities ( WMHs ) can distinguish stroke survivors susceptible to rapid kidney function decline from intensive blood pressure ( BP ) lowering. Methods and Results The SPS3 (Secondary Prevention of Small Subcortical Strokes) trial randomized participants with recent lacunar stroke to systolic BP targets of 130 to 149 and

A causal decomposition analysis allows researchers to determine whether the difference in a health outcome between two groups can be attributed to a difference in each group's distribution of one or more modifiable mediator variables. With this knowledge, researchers and policymakers can focus on designing interventions that target these mediator variables. Existing methods for causal decomposition analysis either focus on one mediator variable or assume that each mediator variable is conditionally independent given the group label and the mediator‐outcome confounders. In this article, we propose a flexible causal decomposition analysis method that can accommodate multiple correlated and interacting mediator variables, which are frequently seen in studies of health behaviors and studies of environmental pollutants. We extend a Monte Carlo‐based causal decomposition analysis method to this setting by using a multivariate mediator model that can accommodate any combination of binary and continuous mediator variables. Furthermore, we state the causal assumptions needed to identify both joint and path‐specific decomposition effects through each mediator variable. To illustrate the reduction in bias and confidence interval width of the decomposition effects under our proposed method, we perform a simulation study. We also apply our approach to examine whether differences in smoking status and dietary inflammation score explain any of the Black‐White differences in incident diabetes using data from a national cohort study. [ABSTRACT FROM AUTHOR]

Objective To evaluate whether child pedestrian safety training in a smartphone-based virtual reality (VR) environment is not inferior to training in a large, semi-immersive VR environment with demonstrated effectiveness. Methods Five hundred 7- and 8-year-old children participated; 479 were randomized to one of two conditions: Learning to cross streets in a smartphone-based VR or learning in a semi-immersive kiosk VR. The systems used identical virtual environments and scenarios. At baseline, children's pedestrian skills were assessed in both VR systems and through a vehicle approach estimation task (judging speed/distance of oncoming traffic on monitor). Training in both conditions comprised at least six 30-min sessions in the randomly assigned VR platform and continued for up to 25 visits until adult-level proficiency was obtained. Following training and again 6 months later, children completed pedestrian safety assessments identical to baseline. Three outcomes were considered from assessments in each VR platform: Unsafe crossings (collisions plus close calls), time to contact (shortest time between child and oncoming simulated traffic), and missed opportunities (unselected safe opportunities to cross). Results Participants achieved adult-level street-crossing skill through VR training. Training in a smartphone-based VR system was generally not inferior to training in a large semi-immersive VR system. There were no adverse effects. Conclusions Seven- and 8-year-old children can learn pedestrian safety through VR-based training, including training in a smartphone-based VR system. Combined with recent meta-analytic results, the present findings support broad implementation and dissemination of child pedestrian safety training through VR, including smartphone-based VR systems. [ABSTRACT FROM AUTHOR]

This study investigated changes in glycemic control following a small increase in time spent outdoors. Women participants with type 2 diabetes (N = 46) wore an iBUTTON temperature monitor and a pedometer for 1 week and recorded their morning fasting blood glucose (FBG) daily. They went about their normal activities for 2 days (baseline) and were asked to add 30 min of time outdoors during Days 3-7 (intervention). Linear mixed effects models were used to test whether morning FBG values were different on days following intervention versus baseline days, and whether steps and/or heat exposure changed. Results were stratified by indicators of good versus poor glycemic control prior to initiation of the study. On average, blood glucose was reduced by 6.1 mg/dL (95% CI - 11.5, - 0.6) on mornings after intervention days after adjusting for age, BMI, and ambient weather conditions. Participants in the poor glycemic control group (n = 16) experienced a 15.8 mg/dL decrease (95% CI - 27.1, - 4.5) in morning FBG on days following the intervention compared to a 1.6 mg/dL decrease (95%CI - 7.7, 4.5) for participants in the good glycemic control group (n = 30). Including daily steps or heat exposure did not attenuate the association between intervention and morning FBG. The present study suggests spending an additional 30 min outdoors may improve glycemic control; however, further examination with a larger sample over a longer duration and determination of mediators of this relationship is warranted., Author(s): Molly B. Richardson [sup.1] , Courtney Chmielewski [sup.2] , Connor Y. H. Wu [sup.3] , Mary B. Evans [sup.4] , Leslie A. McClure [sup.5] , Kathryn W. Hosig [sup.1] [...]

BackgroundThe effect of intensive blood pressure (BP) lowering on kidney function among individuals with established cerebrovascular disease and preserved estimated glomerular filtration rate (eGFR) is not established.Methods and resultsAmong 2610 participants randomized to a lower (30%) using linear mixed models and logistic regression, respectively. We assessed associations of both treatment and kidney function decline with stroke, major vascular events, and the composite of stroke, death, major vascular events, or myocardial infarction using multivariable Cox regression, separately and jointly including a test for interaction. Analyses were conducted by treatment arm. Mean age was 63±11 years; 949 participants (36%) were diabetic; and mean eGFR was 80±19 mL·min(-1)·1.73 m(-2). At 9 months, achieved systolic BP was 137±15 versus 127±14 mm Hg in the higher versus lower BP group, and differences were maintained throughout follow-up (mean, 3.2 years). Compared with the higher target, the lower BP target had a -0.50-mL·min(-1)·1.73 m(-2) per year (95% confidence interval [CI], -0.79 to -0.21) faster eGFR decline. Differences were most pronounced during the first year (-2.1 mL·min(-1)·1.73 m(-2); 95% CI, -0.97 to -3.2), whereas rates of eGFR decline did not differ after year 1 (-0.095; 95% CI, -0.47 to 0.23). A total of 313 patients (24%) in the lower BP group had rapid kidney function decline compared with 247 (19%) in the higher BP group (odds ratio, 1.4; 95% CI, 1.1-1.6). Differences in rapid decline by treatment arm were apparent in the first year (odds ratio, 1.4; 95% CI, 1.1-1.8) but were not significant after year 1 (odds ratio, 1.0; 95% CI, 0.73-1.4). Rapid decline was associated with higher risk for stroke, major vascular events, and composite after full adjustment among individuals randomized to the higher BP target (stroke hazard ratio, 1.93; 95% CI, 1.15-3.21) but not the lower BP arm (stroke hazard ratio, 0.93; 95% CI, 0.50-1.75; all P for interaction

Objectives Adiposity may have a role in the risk of dementia. Fewer studies have focused on the relationship between change in adiposity and cognitive decline. Our study aimed to explore the association between the change in adiposity and cognitive function in Black and White older adults. Methods The participants were 12,204 older adults without cognitive impairment (62.8 ± 8.0 years) in the United States. The percent body mass index change (%BMI change) and percent waist circumference change (%WC change) were measured at 2 in-home visits (first: 2003–2007, second: 2013–2016). Cognitive status was assessed by the Six-Item Screener annually. Memory and executive function were measured by word list learning, MOCA recall and orientation, and letter and animal fluency every 2 years. Logistic regression or linear regression models were used to estimate the relationship between percent change in adiposity and cognitive function. Results After 12.7 ± 1.7 years, a greater decrease in %BMI change or %WC change was significantly associated with a higher risk of cognitive impairment. Compared to older adults with −5% ≤ change ≤ 5% from baseline, a significantly higher risk of cognitive impairment and greater loss in memory and executive function were found among those who experienced more than a 10% decline in %BMI change or %WC change. Older adults who experienced a 5%–10% decrease in %BMI change had a higher risk of cognitive impairment and greater loss of memory compared to those with −5% ≤ change ≤ 5%. Discussion A greater decrease in %BMI (>5%) and %WC (>10%) change was associated with greater cognitive loss observed over time. [ABSTRACT FROM AUTHOR]