Using Electronically Delivered Therapy and Brain Imaging to Understand Obsessive-Compulsive Disorder Pathophysiology: Protocol for a Pilot Study
Bibliographic record
Abstract
BACKGROUND: Obsessive-compulsive disorder (OCD) is a debilitating and prevalent anxiety disorder. Although the basal ganglia and frontal cortex are the brain regions that are most commonly hypothesized to be involved in OCD, the exact pathophysiology is unknown. By observing the effects of proven treatments on brain activation levels, the cause of OCD can be better understood. Currently, the gold standard treatment for OCD is cognitive behavioral therapy (CBT) with exposure and response prevention. However, this is often temporally and geographically inaccessible, time consuming, and costly. Fortunately, CBT can be effectively delivered using the internet (electronically delivered CBT [e-CBT]) because of its structured nature, thus addressing these barriers. OBJECTIVE: The aims of this study are to implement an e-CBT program for OCD and to observe its effects on brain activation levels using functional magnetic resonance imaging (MRI). It is hypothesized that brain activation levels in the basal ganglia and frontal cortex will decrease after treatment. METHODS: Individuals with OCD will be offered a 16-week e-CBT program with exposure and response prevention mirroring in-person CBT content and administered through a secure web-based platform. The efficacy of the treatment will be evaluated using clinically validated symptomology questionnaires at baseline, at week 8, and after treatment (week 16). Using functional MRI at baseline and after treatment, brain activation levels will be assessed in the resting state and while exposed to anxiety-inducing images (eg, dirty dishes if cleanliness is an obsession). The effects of treatment on brain activation levels and the correlation between symptom changes and activation levels will be analyzed. RESULTS: The study received initial ethics approval in December 2020, and participant recruitment began in January 2021. Participant recruitment has been conducted through social media advertisements, physical advertisements, and physician referrals. To date, 5 participants have been recruited. Data collection is expected to conclude by January 2022, and data analysis is expected to be completed by February 2022. CONCLUSIONS: The findings from this study can further our understanding of the causation of OCD and help develop more effective treatments for this disorder. TRIAL REGISTRATION: ClinicalTrials.gov NCT04630197; https://clinicaltrials.gov/ct2/show/NCT04630197. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/30726.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".