Using fuction-based CBT with parent involvement to treat OCD in two school-age children with high-functioning autism
Bibliographic record
Abstract
Obsessive Compulsive Disorder (OCD) involves excessive worry coupled with engaging in rituals that are believed to help alleviate the worry. Pervasive Developmental Disorders (PODs) are characterized by impairments in social interaction, communication, and the presence of repetitive and/or restrictive behaviours (American Psychiatric Association, 2000). Research suggests that as many as 81% of children with a POD also meet criteria for a diagnosis ofOCD. Currently, only a handful of studies have investigated the use of Cognitive Behavioural Therapy (CBT) in treating OCD in children with autism (Reaven & Hepburn, 2003 ; Sze & Wood, 2007; Lehmkuhl, Storch, Bodtish & Geflken, 2008). In these case studies. the use of a multi-modal CBT treatment package was successful in alleviating OCD behaviours. The current study used function-based CBT with parent involvement and behavioural supplements to treat 2 children with POD and OCD. Using a multiple baseline design across behaviours and participants, parents reported that their child 's anxiety was alleviated and these gains were maintained at 6-month follow-up. According to results of the Children 's Yale-Brown Obsessive Compulsive Scale (Goodman, Price, Rasmussen, Riddle, & Rapoport, 1986) from preto post-test, OCD behaviours of the children decreased II"om the severe to the mild range. In addition, the parents rated the family's level of interference related to their child 's OCD as substantially lower. Last, the CBT treatment received high ratings of consumer satisfaction.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".