“What Do You Like/Dislike About the Treatments You’re Currently Using?”
Bibliographic record
Abstract
Children with autism spectrum disorders (ASD) often participate in many treatments, requiring parents’ dedication of time, money, and energy, and necessitating dealing with multiple service providers. To learn about parents’ experience in seeking and using treatments for their child with ASD, the authors asked them, “What do you like/dislike about the treatment(s) you’re currently using?” In this web-based, qualitative study, participants consisted of 486 parents (92% mothers) of children (80% boys; children’s M age = 8.3 years) with autism ( n = 290, 59.7%), Asperger syndrome ( n = 115, 23.6%), or pervasive developmental disorder—not otherwise specified ( n = 81, 16.7%). The families lived in the United States, Canada, Australia, New Zealand, England, and Ireland. Parents’ written statements addressed more “dislikes” (70%) than “likes” (47%), and there were no universally liked or disliked interventions. Six themes emerged and are discussed: effectiveness of treatments, relationships with professionals, access to treatments, costs, medication concerns, and stress.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".