Evidence map›Paper›PMID 31293243›Full record

ArticleJournal of medical Internet research2019

Identification and Quantification of Gaps in Access to Autism Resources in the United States: An Infodemiological Study.

Michael Ning, Jena Daniels, Jessey Schwartz, Kaitlyn Dunlap, Peter Washington, Haik Kalantarian, Michael Du, Dennis P Wall

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

36 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Building Capacity: A Systematic Review of Training in the Diagnosis of Autism for Community-Based Clinicians.Autism research : official journal of the International Society for Autism Research · 2025
    Pooled it
  2. Article
  3. Article
  4. Prior Diagnoses and Age of Diagnosis in Children Later Diagnosed with Autism.Journal of autism and developmental disorders · 2026
    Article
  5. The Power of ECHO Autism: Improving Confidence and Holistic Care for Autistic Adults.Journal of intellectual disability research : JIDR · 2026
    Article
  6. The Influence of Policy on Early Diagnosis and Other Autism Services: A Narrative Review.Review journal of autism and developmental disorders · 2025
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Utility of the Language Use Inventory in Young Children at Elevated Likelihood of Autism.Journal of speech, language, and hearing research : JSLHR · 2024
    Article
  13. Unlocking autism's complexity: theFrontiers in integrative neuroscience · 2024
    Article
  14. Review
  15. Article
  16. Article
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  18. Article
  19. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Michael NingDivision of Systems Medicine, Department of Pediatrics, Stanford University, Stanford, CA, United States.ORCID 0000-0002-8334-1104
Jena DanielsDivision of Systems Medicine, Department of Pediatrics, Stanford University, Stanford, CA, United States.ORCID 0000-0002-7912-8482
Jessey SchwartzDivision of Systems Medicine, Department of Pediatrics, Stanford University, Stanford, CA, United States.ORCID 0000-0003-4916-7891
Kaitlyn DunlapDivision of Systems Medicine, Department of Pediatrics, Stanford University, Stanford, CA, United States.ORCID 0000-0003-4423-5269
Peter WashingtonDivision of Systems Medicine, Department of Pediatrics, Stanford University, Stanford, CA, United States.ORCID 0000-0003-3276-4411
Haik KalantarianDivision of Systems Medicine, Department of Pediatrics, Stanford University, Stanford, CA, United States.ORCID 0000-0002-7107-7908
Michael DuDivision of Systems Medicine, Department of Pediatrics, Stanford University, Stanford, CA, United States.ORCID 0000-0002-9655-3835
Dennis P WallDivision of Systems Medicine, Department of Pediatrics, Stanford University, Stanford, CA, United States.ORCID 0000-0002-7889-9146

Funding

POSTDOCTORAL TRAINING IN MEDICAL INFORMATION SCIENCEST15LM007033 · NLM · STANFORD UNIVERSITY · PI SYLVIA KATINA PLEVRITIS · 1985 to 2026
$25.5M
QuBBD: Wearable artificial intelligence for bid data-driven healthcare in child development R01EB025025 · NIBIB · STANFORD UNIVERSITY · PI WALL, DENNIS PAUL · 2017 to 2019
$1.1M
Evaluation of machine learning to mobilize detection and therapy of developmental delay in childrenR21HD091500 · NICHD · STANFORD UNIVERSITY · PI WALL, DENNIS PAUL · 2017 to 2018
$432k
NIBIB NIH HHS R01 EB025025NICHD NIH HHS R21 HD091500NLM NIH HHS T15 LM007033
6 · The paper itself

Abstract

backgroundAutism affects 1 in every 59 children in the United States, according to estimates from the Centers for Disease Control and Prevention's Autism and Developmental Disabilities Monitoring Network in 2018. Although similar rates of autism are reported in rural and urban areas, rural families report greater difficulty in accessing resources. An overwhelming number of families experience long waitlists for diagnostic and therapeutic services.

objectiveThe objective of this study was to accurately identify gaps in access to autism care using GapMap, a mobile platform that connects families with local resources while continuously collecting up-to-date autism resource epidemiological information.

methodsAfter being extracted from various databases, resources were deduplicated, validated, and allocated into 7 categories based on the keywords identified on the resource website. The average distance between the individuals from a simulated autism population and the nearest autism resource in our database was calculated for each US county. Resource load, an approximation of demand over supply for diagnostic resources, was calculated for each US county.

resultsThere are approximately 28,000 US resources validated on the GapMap database, each allocated into 1 or more of the 7 categories. States with the greatest distances to autism resources included Alaska, Nevada, Wyoming, Montana, and Arizona. Of the 7 resource categories, diagnostic resources were the most underrepresented, comprising only 8.83% (2472/28,003) of all resources. Alarmingly, 83.86% (2635/3142) of all US counties lacked any diagnostic resources. States with the highest diagnostic resource load included West Virginia, Kentucky, Maine, Mississippi, and New Mexico.

conclusionsResults from this study demonstrate the sparsity and uneven distribution of diagnostic resources in the United States, which may contribute to the lengthy waitlists and travel distances-barriers to be overcome to be able to receive diagnosis in specific regions. More data are needed on autism diagnosis demand to better quantify resource needs across the United States.

Indexed as

Autistic DisorderChildCrowdsourcingFemaleHumansMaleUnited Statesautismautism spectrum disordercrowdsourcingepidemiologyinfodemiologyprevalenceresources

Identifiers

PMID31293243
PMCPMC6652124

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.