“They Looked at Me as a Person, Not Just a Diagnosis”: A Qualitative Study of Patient and Parent Satisfaction with a Specialized Primary Care Clinic for Autistic Adults
Bibliographic record
Abstract
BACKGROUND: Autistic adults have complex physical and mental healthcare needs that necessitate specialized approaches to healthcare. One promising approach is to embed providers with specialized training or specialty clinics for autistic adults within general primary care facilities. We previously found that autistic adults who received their healthcare through one specialty clinic designed with and for autistic adults had better continuity of care and more preventive service utilization than national samples of autistic adults. OBJECTIVE: To characterize factors that increased or decreased satisfaction with healthcare received through a specialty clinic for autistic adults. METHODS: We conducted 30-60-minute semi-structured interviews with autistic adults (N=9) and parents of autistic adults (N=12). We conducted an inductive thematic analysis, using a phenomenological approach. RESULTS: Factors that increased participants' satisfaction included: (1) receiving personalized care from the provider; (2) spending quality time with the provider; and (3) having strong, positive patient-provider relationships. Factors that decreased participants' satisfaction included: (1) lack of access to services due to scarcity of trained providers; (2) difficulty at times communicating with the provider; and (3) system-level barriers such as policies, practices, or procedures. CONCLUSION: Our findings highlight the importance of providers using personalized approaches to care that meet patients' sensory and communication needs and spending quality time with patients to establish strong, positive patient-provider relationships. Our findings also underscore the critical scarcity of healthcare providers who are trained to deliver care for the growing population of autistic adults.
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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 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".