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Record W4405998647 · doi:10.1016/j.jdrv.2024.12.011

Treatment strategies for skin picking disorder: Efficacy of pharmacological and nonpharmacological approaches—A systematic review and evidence mapping

2025· review· en· W4405998647 on OpenAlexaff
Andy D. Lee, Chloe Devoy, Ryan S.Q. Geng, Mehul Nimpal, Kevin Wang, Liz Dennett, Katharine Hibbard, Tarek Turk, Sebastian Straube, Marlene Dytoc

Bibliographic record

VenueJAAD reviews. · 2025
Typereview
Languageen
FieldPsychology
TopicObsessive-Compulsive Spectrum Disorders
Canadian institutionsUniversity of AlbertaUniversity of CalgaryUniversity of Toronto
Fundersnot available
KeywordsSystematic reviewMedicinePsychologyIntensive care medicineComputer scienceMEDLINEBiology

Abstract

fetched live from OpenAlex

Skin picking disorder (SPD), classified in the DSM-5 under Obsessive-Compulsive and Related Disorders, is characterized by repetitive skin picking that leads to tissue damage.Despite its prevalence, there are currently no Food and Drug Administration-approved treatments.This systematic review aimed to assess both pharmacological and non-pharmacological interventions for SPD.A comprehensive literature search identified 25 randomized controlled trials comprising 3,407 participants (mean age 29.6 years; predominantly women).Treatments included pharmacological agents, cognitive-behavioral therapies, behavioral modification techniques, self-help tools, and neurostimulation.Outcome measures were primarily derived from validated scales such as the Skin Picking Scale, Skin Picking Impact Scale, and the Yale-Brown Obsessive Compulsive Scale.Pharmacological treatments averaged a 49.1% reduction in symptoms, with fluoxetine achieving a notably high (98.3%)reduction in patients with acne excori ee.Other promising agents included memantine, dronabinol, and N-acetylcysteine.Cognitive and behavioral therapies achieved a 39.8% average reduction, with cognitive behavioral therapy alone reducing symptoms by 51%.Behavioral modification approaches such as habit reversal training demonstrated a 45% reduction.Self-help tools and neurostimulation therapies showed moderate efficacy.( JAAD Reviews 2025;3:124-7.)

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.320
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0100.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.157
GPT teacher head0.433
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations3
Published2025
Admission routes1
Has abstractyes

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