The Use of Repetitive Transcranial Magnetic Stimulation for Treatment of Obsessive-Compulsive Disorder: A Scoping Review. (Preprint)
Bibliographic record
Abstract
BACKGROUND Background: Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive procedure in which brain neural activity is stimulated by direct application of a magnetic field to the scalp. rTMS is considered a therapeutic tool in various neuropsychiatric conditions. Since its approval in Canada in 2002 and despite its wide and continuous usage for the management of depressive disorders, knowledge on the use of rTMS for Obsessive-Compulsive Disorder (OCD) is sparse. OBJECTIVE Objectives: This scoping review seeks to; (i) explore the relevant literature available regarding the use of rTMS as a mode of treatment for OCD; (ii) To evaluate the evidence to support the use of rTMS as a treatment option for OCD. METHODS Method: We electronically conducted data search in five research databases (MEDLINE, CINAHL, Psych INFO, SCOPUS, and EMBASE) using all identified keywords and index terms across all the data bases to identify empirical studies and randomized controlled trials. We included articles published with randomized control designs which aimed at the treatment of OCD with rTMS. Only full-text published articles written in English were reviewed. Review articles on treatment for conditions other than OCD were excluded. RESULTS NA CONCLUSIONS Conclusion: The application of rTMS as a treatment intervention for OCD looks promising despite diversity in terms of outcomes and clinical significance. Further studies with well-defined stimulation parameters are needed in order to be able to draw a definite conclusion of its clinical effectiveness in the treatment of OCD.
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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 | 0.006 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.011 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| 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".