Effectiveness of In Virtuo Exposure and Response Prevention Treatment Using Cognitive–Behavioral Therapy for Obsessive–Compulsive Disorder: A Study Based on a Single-Case Study Protocol
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Obsessive-compulsive disorder (OCD) is characterized by the presence of distressing, recurrent and intrusive thoughts, impulses, or doubts as well as behavioral or mental rituals. OCD has various subtypes, including the fear of contamination in which individuals fear bacteria, germs, disease, or bodily secretions, and engage in clinically significant cleaning and avoidance rituals. Cognitive-behavioral therapy (CBT) is an effective treatment for OCD and involves, among other therapeutic strategies, exposing patients to feared stimuli while preventing them to engage in compulsive behaviors. In recent years, virtual reality (VR) has shown the potential of in virtuo exposure with people suffering from anxiety disorders and OCD. The objective of this pilot study is to examine the effectiveness of a CBT program where exposure in conducted in virtuo. Three adults suffering from OCD with a dominant subtype of contamination were enrolled in a single-case design with multiple baselines across participants. The presence and intensity of obsessions and compulsions were assessed daily during baselines of 3-, 4-, or 5-week, and a 12-session treatment. Follow-up information was gathered after 4 and 8 months. Treatment outcome is assessed with visual inspection of the graphs and ARMA time-series analyses. Clinical information, self-reports, and details of the treatment are provided for each patient. Statistical analyses for the time-series data revealed a statistically significant improvement in all three participants, but global improvement is considered positive for only two. This study innovates in proving preliminary support for the usefulness of VR in the CBT of OCD with contamination features.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it