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).
OBJECTIVE We examined whether relative availability of fast-food restaurants and supermarkets mediates the association between worse neighborhood socioeconomic conditions and risk of developing type 2 diabetes (T2D). RESEARCH DESIGN AND METHODS As part of the Diabetes Location, Environmental Attributes, and Disparities Network, three academic institutions used harmonized environmental data sources and analytic methods in three distinct study samples: (1) the Veterans Administration Diabetes Risk (VADR) cohort, a national administrative cohort of 4.1 million diabetes-free veterans developed using electronic health records (EHRs); (2) Reasons for Geographic and Racial Differences in Stroke (REGARDS), a longitudinal, epidemiologic cohort with Stroke Belt region oversampling (N = 11,208); and (3) Geisinger/Johns Hopkins University (G/JHU), an EHR-based, nested case-control study of 15,888 patients with new-onset T2D and of matched control participants in Pennsylvania. A census tract–level measure of neighborhood socioeconomic environment (NSEE) was developed as a community type-specific z-score sum. Baseline food-environment mediators included percentages of (1) fast-food restaurants and (2) food retail establishments that are supermarkets. Natural direct and indirect mediating effects were modeled; results were stratified across four community types: higher-density urban, lower-density urban, suburban/small town, and rural. RESULTS Across studies, worse NSEE was associated with higher T2D risk. In VADR, relative availability of fast-food restaurants and supermarkets was positively and negatively associated with T2D, respectively, whereas associations in REGARDS and G/JHU geographies were mixed. Mediation results suggested that little to none of the NSEE–diabetes associations were mediated through food-environment pathways. CONCLUSIONS Worse neighborhood socioeconomic conditions were associated with higher T2D risk, yet associations are likely not mediated through food-environment pathways.
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. Lay SummaryAfter only a five-minute observation, trainee clinicians noted whether or not they believed that a child attending an autism evaluation would be diagnosed with autism. When they indicated a child was autistic, they were correct in 86% of cases, but when they indicated a child was not autistic, they missed 29% of children ultimately diagnosed. These findings suggest that clinical judgments of suspected autism should be taken seriously, but lack of practitioner concern should not be used to rule out autism.
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