Tackling healthcare access barriers for individuals with autism from diagnosis to adulthood
Bibliographic record
Abstract
Most individuals with autism spectrum disorder (ASD)-a complex, life-long developmental disorder-do not have access to the care required to address their diverse health needs. Here, we review: (1) common barriers to healthcare access (shortage/cost of services; physician awareness; stigma); (2) barriers encountered primarily during childhood (limited screening/diagnosis; unclear referral pathways), transition to adulthood (insufficient healthcare transition services; suboptimal physician awareness of healthcare needs) and adulthood (shortage of services/limited insurance; communication difficulties with physicians; limited awareness of healthcare needs of aging adults); and (3) advances in research/program development for better healthcare access. A robust understanding of barriers to accessing healthcare across the lifespan of autistic individuals is critical to ensuring the best use of healthcare resources to improve social, physical, and mental health outcomes. Stakeholders must strengthen healthcare service provision by coming together to: better understand healthcare needs of underserved populations; strengthen medical training on care of autistic individuals; increase public awareness of ASD; promote research into/uptake of tools for ASD screening, diagnosis, and treatment; understand specific healthcare needs of autistic individuals in lower resource countries; and conduct longitudinal studies to understand the lifetime health, social, and economic impacts of ASD and enable the evaluation of novel approaches to increasing healthcare access. IMPACT: Despite the growing body of evidence, our understanding of barriers to healthcare encountered by individuals with ASD remains limited, particularly beyond childhood and in lower resource countries. We describe current and emerging barriers to healthcare access encountered by individuals with ASD across the lifespan. We recommend that stakeholders develop evidence-informed policies, programs, and technologies that address barriers to healthcare access for individuals with ASD and consider broad, equitable implementation to maximize impact.
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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 | 0.005 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".