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Record W6922407244 · doi:10.13025/17425

Healthcare ‘Fit’ and autism: An examination of barriers to, and experiences of, physical healthcare for people on the autism spectrum

2021· other· en· W6922407244 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueARAN (University of Galway Research Repository) (Ollscoil na Gaillimhe – University of Galway) · 2021
Typeother
Languageen
FieldComputer Science
TopicEducational Robotics and Engineering
Canadian institutionsnot available
Fundersnot available
KeywordsHealth careAutismPsychological interventionSystematic reviewQuarter (Canadian coin)Health professionalsMEDLINE

Abstract

fetched live from OpenAlex

Autistic individuals experience substantial health inequities, reflected in poorer health outcomes and higher mortality rates. One suggested determinant of this health inequity is issues in access to healthcare. This thesis, therefore, aimed to examine the barriers to healthcare for autistic individuals and consider how access might be improved. Five empirical studies were completed. Study 1 comprised a systematic review of barriers to healthcare reported by autistic individuals, caregivers, and healthcare providers (HCPs). A taxonomy of barriers was developed comprising four themes: barriers associated with autism-related characteristics; other patient-related barriers; HCP-related barriers; and system-related barriers. Study 2 described the development and preliminary evaluation of a novel caregiver-report tool to assess barriers to care, which consisted of four factors: patient-related barriers, HCP-related barriers, system-related barriers, and barriers related to managing care. The most frequently occurring barriers included difficulties identifying or reporting pain/symptoms and a lack of HCP knowledge about autism. Study 3 described the development and preliminary evaluation of a physician-report tool to assess barriers to providing care to autistic individuals, which consists of three factors: patient-related barriers; HCP/family-related barriers, and system-related barriers. The most common barriers included insufficient patient supports, and communication difficulties. Study 4 describes the use of patient narratives to identify barriers occurring in challenging healthcare encounters for autistic individuals and assessed the impact these had on patients. Patient-related barriers occurred most often, followed by HCP-related barriers. More than a quarter of the described encounters were rated as high severity. Study 5 presents a systematic review of interventions aimed at improving access to, or experiences in, healthcare for autistic individuals. Interventions were mostly patient-focused with fewer studies targeting the HCP or the system. The data presented herein demonstrate that autistic individuals face substantial health inequities. Thus, models of healthcare must change to ensure optimal health for the entire autistic community.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.493
Threshold uncertainty score0.976

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.033
GPT teacher head0.273
Teacher spread0.240 · 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