Barriers to Care for Autistic Adults: A Qualitative Study Understood Through the Double Empathy Framework
Bibliographic record
Abstract
Communication challenges between autistic and neurotypical individuals often stem from fundamental differences in social cognition and expectations. These challenges are particularly impactful in contexts requiring collaboration and mutual understanding, such as healthcare settings. The double empathy phenomenon suggests the miscommunication in autistic-neurotypical pairs can be bidirectional. In healthcare settings, how autistic adults navigate cross-neurotype interactions with non-autistic clinicians is not well understood. The current study used Directed Content Analysis to qualitatively examine 118 autistic adults’ experiences with receiving a formal diagnosis and accessing support (e.g., therapy, accommodations). The results indicated that discrimination was a recurring barrier that prevented autistic adults from fully harnessing desired benefits from diagnosis (e.g., gaining access to resources, improving relationships, identity), therapy (e.g., goal-aligned therapy to support emotion regulation, advocacy, relationship boundaries, trauma), and accommodations (e.g., supporting emotional, social and sensory needs). These findings provide insights into how stakeholders can provide neurodivergent-affirming care and other universal design adaptations in school and work environments.
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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 | 0.014 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".