Cognitive psychophysiological treatment of bodily‐focused repetitive behaviors in adults: An open trial
Bibliographic record
Abstract
BACKGROUND: Body-focused repetitive behaviors (BFRBs), such as hair pulling, skin picking, and nail biting, are repetitive, destructive, and nonfunctional habits that cause significant distress. Separate BFRBs form a cohesive group and could be assessed as part of the Tourette/tic spectrum or obsessive-compulsive spectrum of disorders. The treatment of choice is either antidepressant or behavioral treatment, both of which have shown effectiveness. The cognitive psychophysiological (CoPs) model focuses on the tension and emotional build up that triggers habits by addressing cognitive-behavioral, emotional and psychophysiological processes preceding onset rather than the habit itself. The CoPs approach has already shown efficacy in treatment of tic and Tourette disorder. OBJECTIVE: The aim of the current open trial was to view whether BFRBs can be validly assessed on a standard tic scale (Tourette Symptom Global Scale; TSGS) and evaluate the efficacy of the CoPs intervention on 64 participants (54 completers) with 1 of 3 subtypes of BFRBs (hair pulling, nail biting, and skin picking) compared to a waitlist control. METHOD: Participants were assessed at baseline on an adapted TSGS and after receving 14 weeks of CoPs therapy with six months follow up. RESULTS: The TSGS was reliably and validly adapted to measure BFRBs. The CoPs intervention was effective for all BRFB subtypes with a large effect size (intention-to-treat g = 1.54; completers g = 2.04), with 74% of patients showing clinically significant improvement. Mood and self-esteem also improved posttreatment. The decrease in symptoms was maintained at the 6-month follow-up, with a further decrease in perfectionism. CONCLUSION: BFRBs can be reliably assessed as a tic spectrum disorder rather than as part of the obsessive-compulsive spectrum. The CoPs model may offer a complementary treatment for BFRBs.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".