MétaCan
Menu
Back to cohort
Record W3157918851 · doi:10.1111/jcpp.13404

Annual Research Review: Achieving universal health coverage for young children with autism spectrum disorder in low‐ and middle‐income countries: a review of reviews

2021· review· en· W3157918851 on OpenAlexafffund
Gauri Divan, Supriya Bhavnani, Kathy Leadbitter, Ceri Ellis, Jayashree Dasgupta, Amina Abubakar, Mayada Elsabbagh, Syed Usman Hamdani, Chiara Servili, Vikram Patel, Jonathan Green

Bibliographic record

VenueJournal of Child Psychology and Psychiatry · 2021
Typereview
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
FundersMedical Research CouncilNational Institute for Health and Care ResearchWellcome TrustWorld Health OrganizationGrand Challenges CanadaAutism Speaks
KeywordsAutismAutism spectrum disorderPsychological interventionLow and middle income countriesContext (archaeology)PsychologySystematic reviewStigma (botany)PsychiatryGrey literatureLatin AmericansSocial stigmaMedicineMEDLINEDeveloping countryFamily medicinePolitical scienceEconomic growthGeography

Abstract

fetched live from OpenAlex

Background Autism presents with similar prevalence and core impairments in diverse populations. We conducted a scoping review of reviews to determine key barriers and innovative strategies which can contribute to attaining universal health coverage (UHC), from early detection to effective interventions for autism in low‐ and middle‐income countries (LAMIC). Methods A systematic literature search of review articles was conducted. Reviews relevant to the study research question were included if they incorporated papers from LAMIC and focused on children ( Results We identified 31 articles which reviewed data from over fifty countries across Africa, Latin America, Middle East, and Asia and addressed barriers across one or more of four inter‐related domains: (a) the social context and family experience for a child with autism; (b) barriers to detection and diagnosis; (c) access to appropriate evidence‐based intervention; and (d) social policy and legislation. Key barriers identified included: lack of appropriate tools for detection and diagnosis; low awareness and experienced stigma impacting demand for autism care; and the prevalence of specialist models for diagnosis and treatment which are not scalable in LAMIC. Conclusions We present a Theory of Change model which describe the strategies and resources needed to realize UHC for children with autism in LAMIC. We highlight the importance of harnessing existing evidence to best effect, using task sharing and adapted intervention strategies, community participation, and technology innovation. Scaling up these innovations will require open access to appropriate detection and intervention tools, systematic approaches to building and sustaining skills in frontline providers to support detection and deliver interventions embedded within a stepped care architecture, and community awareness of child development milestones.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.054
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.022
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.054
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0070.006
Bibliometrics0.0220.023
Science and technology studies0.0010.001
Scholarly communication0.0050.005
Open science0.0020.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0090.001

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.

Opus teacher head0.045
GPT teacher head0.402
Teacher spread0.357 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations111
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Child Psychology and PsychiatrySame topicAutism Spectrum Disorder ResearchFrench-language works237,207