FAST CBT for pediatric OCD: A multiple-baseline controlled pilot trial of parent training in exposure and response prevention delivered via telehealth
Bibliographic record
Abstract
Objective The current study utilized a single case series, non-concurrent multiple baseline design to examine the efficacy of training parents via telehealth videoconferencing in exposure and response prevention (ERP) for home delivery of the treatment for their children and adolescents with obsessive compulsive disorder (OCD). Method There were nine participants aged 8 to 14 years who had received a primary diagnosis of OCD. The design involved a series of AB replications, whereby following pre-treatment assessments participants were randomly assigned to either a 2-week (n = 4) or 3-week (n = 5) baseline condition with weekly monitoring of their child’s OCD symptoms. Following baseline, parents participated four weekly telehealth parent-training modules in delivering FAST (Families Accessing Skills Training) cognitive behavior therapy (CBT) with ERP (CBT-ERP) to children with OCD via videoconferencing with the clinician. Primary outcome measures were OCD symptom severity, diagnostic severity, and global functioning, which were assessed post-treatment and at 2 month follow-up. Results The stability of the baseline period from pre-treatment to week 2 (for the 2-week condition) or to week 3 (for the 3-week condition) was established as there were no significant differences across baseline scores for parent target obsessions or parent target compulsions ratings. Significant improvements on the primary outcomes of clinician assessed symptom severity, diagnostic ratings, and global functioning were observed from baseline to post-treatment, and continued to 2 months follow-up. Conclusion These data suggest that brief, parent training in FAST CBT-ERP via telehealth provides an overall effective intervention that is likely to be of most benefit to children and youth who are mild to moderate in severity.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".