Inducing an Anxiety Response Using a Contaminated Virtual Environment: Validation of a Therapeutic Tool for Obsessive–Compulsive Disorder
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 unwanted and repetitive thoughts triggering significant anxiety, as well as the presence of ritual behaviours or mental acts carried out in response to obsessions to reduce the associated distress. In the contamination subtype, individuals are scared of germs and bacteria, are excessively concerned with cleaning, fear contamination and the spread of disease, and may have a very strong aversion to bodily secretions. A few studies on virtual reality have been conducted with people suffering from OCD, but they all focus on the subtype characterized by checking rituals. The goal of this study is to confirm the potential of a “contaminated” virtual environment in inducing anxiety in 12 adults suffering from contamination-subtype OCD compared to 20 adults without OCD (N = 32) using a within-between protocol. Subjective (questionnaire) and objective (heart rate) measurements were compiled. Participants were immersed in a control virtual environment (empty and clean room) and a “contaminated” virtual environment (filthy public restroom) designed for the treatment of OCD. Immersions were conducted in a 6-wall CAVE-like system. As hypothesized, the results of repeated-measures ANCOVAs revealed the significant impact of immersion in a filthy public restroom for participants suffering from OCD on both measures. Presence was correlated with anxiety in OCD participants and no difference in presence was observed between groups. Unwanted negative side effects induced by immersions in virtual reality were higher in the OCD group. The clinical implications of the results and directions for further studies are discussed.
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.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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