The Generic BFRB Scale-8 (GBS-8): a transdiagnostic scale to measure the severity of body-focused repetitive behaviours
Bibliographic record
Abstract
BACKGROUND: Body-focused repetitive behaviours (BFRBs) such as skin picking and hair pulling are frequent but under-diagnosed and under-treated psychological conditions. As of now, most studies use symptom-specific BFRB scales. However, a transdiagnostic scale is needed in view of the high co-morbidity of different BFRBs. AIMS: We aimed to assess the reliability as well as concurrent and divergent validity of a newly developed transdiagnostic BFRB scale. METHOD: For the first time, we administered the 8-item Generic BFRB Scale (GBS-8) as well as the Repetitive Body Focused Behavior Scale (RBFBS), modified for adults, in 279 individuals with BFRBs. The GBS-8 builds upon the Skin Picking Scale-Revised (SPS-R), but has been adapted to capture different BFRBs concurrently. A total of 170 participants (61%) were re-assessed after 6 weeks to determine the test-retest reliability of the scale. RESULTS: = .74) with the RBFBS was good (correlational indexes for concurrent validity were significantly higher than that for discriminant validity). DISCUSSION: The GBS-8 appears to be a reliable and valid global measure of BFRBs. We recommend usage of the scale in combination with specific BFRB scales to facilitate comparability across studies on obsessive-compulsive spectrum disorders.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".