The Adoption of New Treatment Modalities by Health Professionals and the Relative Weight of Empirical Evidence in Favor of Virtual Reality Exposure Versus Mindfulness in the Treatment of Anxiety Disorders
Bibliographic record
Abstract
Anxiety disorders are among the most prevalent mental disorders, and cognitive-behavioral therapy (CBT) with exposure exercises is considered as the gold-standard psychological intervention. New psychotherapeutic modalities have emerged in the last decade and, among them, mindfulness has been rapidly adopted by therapists. The adoption rate is slower for the use of virtual reality (VR) to conduct exposure. The goal of the present position paper is to contrast, for the treatment of anxiety disorders, the weight of empirical evidences supporting the use of exposure in VR with the use of mindfulness-based therapy (MBT). Based on the most recent meta-analyses, we found that CBT with exposure conducted in VR was more thoroughly researched and supported than MBT, receiving validation from roughly twice as many studies with high control (i.e., randomized, active controls with clinical samples). However, this conclusion is nuanced by reviewing gaps in the literature for both therapies. Potential factors influencing clinicians' choice of treatment and suggestions for future research directions are proposed.
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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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".