CRISIS AFAR: An International Collaborative Study of the Impact of the COVID-19 Pandemic on Youth with Autism and Neurodevelopmental Conditions
Bibliographic record
Abstract
Abstract Importance Heterogeneous mental health outcomes during the COVID-19 pandemic are recognized in the general population, but it has not been systematically assessed in youth with neurodevelopmental disorders (NDD), including autism spectrum (ASD). Objective Identify subgroups of youth with ASD/NDD based on the pandemic impact on symptoms and service changes, as well as predictors of outcomes. Design, Setting, and Participants This is a naturalistic observational study conducted across 14 North American and European clinical and/or research sites. Parent responses on the Coronavirus Health and Impact Survey Initiative (CRISIS) adapted for Autism and Related Neurodevelopmental Conditions (AFAR) were cross-sectionally collected from April to October 2020. The sample included 1275, 5-21 year-old youth with ASD and/or NDD who were clinically well-characterized prior to the pandemic. Main Outcomes and Measures To identify impact subgroups, hierarchical clustering analyzed eleven AFAR factors measuring pre- to pandemic changes in clinically relevant symptoms and service access. Random forest classification assessed the relative contribution in predicting subgroup membership of 20 features including socio-demographics, pre-pandemic service, and clinical severity along with indices of COVID-19 related experiences and environments empirically-derived from AFAR parent responses and global open sources. Results Clustering analyses revealed four ASD/NDD impact subgroups. One subgroup - broad symptom worsening only (20% of the aggregate sample) - included youth with worsening symptoms that were above and beyond that of their ASD/NDD peers and with similar service disruptions as those in the aggregate average. The three other subgroups showed symptom changes similar to the aggregate average but differed in service access: primarily modified services (23%), primarily lost services (6%), and average services/symptom changes (53%). Pre-pandemic factors (e.g., number of services), pandemic environments and experiences (e.g., COVID-19 cases, related restrictions, COVID-19 Worries), and age emerged in unique combinations as distinct protective or risk factors for each subgroup. Together they highlighted the role of universal risk factors, such as risk perception, and the protective role of services before and during the pandemic, in middle childhood. Conclusions and Relevance Concomitant assessment of changes in both symptoms and services access is critical to understand heterogeneous impact of the pandemic on ASD/NDD youth. It enabled the delineation of pathways to risk and resilience that include universal and ASD/NDD specific contributors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".