Comparison of cognitive-behavioral treatments for tics and Tourette syndrome in youth and adults: A randomized controlled trial
Bibliographic record
Abstract
Current guidelines recommend the Comprehensive Behavioral Intervention for Tics (CBIT) to manage tics, which aims to reverse tic habits. Though CBIT has shown significant tic reduction in many, some patients remain non-responders. The Cognitive Psychophysiological treatment (CoPs) offers an alternative approach, focusing on modifying cognitive, behavioral, and physiological processes. Previous studies highlighted CoPs' effectiveness in reducing tics and improving neurocognitive performance. This paper presents the first direct trial comparing CoPs and CBIT. Our goal was to compare CBIT and CoPs in children and adults. We hypothesized that the CoPs group would show superior clinical improvement than the CBIT group. Ninety-eight participants were randomized into each of the two modalities, including 61 children and 37 adults Participants were evaluated pre-post, and at one- and six-months post-treatment using standardized scales. The manualized treatments included 12 to 14 sessions for an average duration (from randomization to follow-up) of 41 weeks. A linear mixed model was used to test treatment effects on outcome measures. Of 120 initial participants, 98 were randomized to CBIT or CoPs. About 23% shifted to teletherapy due to COVID-19. Both treatments lowered YGTSS scores, with no modality differences. The CoPs group showed significant GAF score increases, and teletherapy participants had higher scores than in-person. Clinical change between CBIT and CoPs was similar. Both CoPs and CBIT effectively address tic severity. While CoPs offer a holistic restructuring approach, it was not found superior to CBIT, underscoring the need for continued research for tic treatment.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".