Risk and maintenance factors in body‐focused repetitive behaviours
Bibliographic record
Abstract
Abstract Background Body‐focused repetitive behaviours (BFRBs), such as skin picking and trichotillomania, are conditions at the interface of dermatology and psychiatry. Objectives We asked individuals with various BFRBs about their habits and preferences preceding the onset of their BFRB(s). We also inquired about the emotions (positive, negative or mixed) accompanying the habit to explore predisposing and maintenance factors. Methods A sample of 201 individuals with mixed BFRBs were recruited online. We administered the Generic BFRB Scale (GBS‐36) and the newly developed Somatic and Habitual Predisposition to BFRB Scale as well as the Ambivalence Towards BFRB Rating. Results Most participants reported both positive and negative feelings towards engaging in BFRBs, with only a minority (41.8%) indicating predominantly negative feelings. The study speaks to somatic and habitual predisposing factors that are topographically related to specific conditions (e.g., dislike of one's skin and skin impurities preceding skin picking, dislike of one's nails and brittle nails preceding nail biting, tendency to scarring and injuries preceding lip‐cheek biting). Conclusions Our study speaks to important somatic and habitual predisposing factors in BFRBs. Positive feelings accompanying BFRBs may act as an important maintenance factor in BFRBs. Our results may inform new therapeutic approaches to treating or preventing BFRBs.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".