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Record W4409714647 · doi:10.1186/s12913-025-12741-6

Insights into healthcare services for youth with autism spectrum disorder transitioning to adulthood: a focus on rural Atlantic Canada

2025· article· en· W4409714647 on OpenAlexaffabout
Parisa Ghanouni, Tara Naimpally

Bibliographic record

VenueBMC Health Services Research · 2025
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent and Pediatric Healthcare
Canadian institutionsDalhousie University
Fundersnot available
KeywordsAutism spectrum disorderHealth administrationNursing researchHealth informaticsMedicinePublic healthHealth services researchHealth careYoung adultFocus (optics)PsychiatryAutismNursingGerontologyEconomic growth

Abstract

fetched live from OpenAlex

Individuals with neurodevelopmental disabilities, such as autism spectrum disorder (ASD) often require unique healthcare services. As adolescents age out of the pediatric health system, accessing appropriate healthcare becomes more challenging during the transition to adulthood. This challenge is amplified for individuals with ASD living in rural areas where access to healthcare services is limited. The aim of this qualitative study was to explore the experiences of stakeholders, including individuals with ASD, parents of individuals with ASD, and service providers, during the transition to adulthood in rural communities. MethodsWe recruited 26 individuals including 16 youth, 6 parents and 4 service providers through convenience and snowball sampling methods from Canadian Atlantic provinces. Semi-structured interviews were conducted, focusing on barriers and challenges encountered during the transition.ResultsThematic analysis was employed to identify patterns and themes within the data. Three central themes emerged from the data including transport to and from care, limited resources, and continuity of care.ConclusionThe findings underscore the significant challenges faced by individuals with ASD and their families during the transition to adulthood in rural areas. By understanding and addressing these challenges, stakeholders can work towards implementing informed policies to ensure equitable access to healthcare services for individuals with ASD transitioning to adulthood in rural areas.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.404

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0210.004
Scholarly communication0.0040.001
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.041
GPT teacher head0.425
Teacher spread0.385 · 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 designQualitative
Domainnot available
GenreEmpirical

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

Citations1
Published2025
Admission routes2
Has abstractyes

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