Low-Cost Virtual Reality to Support Imaginal Exposure Within PTSD Treatment: A Case Report Study Within a Community Mental Healthcare Setting
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
Revisiting what happened during (or after) a traumatic event is an important part of the treatment process in trauma-focused cognitive therapy (TF-CT). However, clinicians may have difficulty helping patients to intentionally retrieve these memories in order to engage with their content. As such, clinical tools to support the access and delivery of imaginal exposure content within treatment may prove to be particularly useful for therapists. This case report introduces work undertaken with Mr. A, a 38-year-old male, who 2 years prior had experienced a city centre assault. Initial assessment revealed a PCL-5 score of 64 and he met DSM-5 criteria for posttraumatic stress disorder (PTSD). Mr. A received 10 sessions of TF-CT wherein the traditional imaginal exposure components were implemented via a newly developed virtual reality (VR) development workflow called “VR Photoscan.” After 10 sessions, results showed PCL-5 scores decreased from 64 to 19 and Mr. A no longer met DSM-5 PTSD criteria. VR Photoscan was used during 4/10 sessions and included (1) reliving, (2) memory updating, and (3) stimulus discrimination activities. Mr. A also reported VR Photoscan as helpful regarding preparation for site visits. In conclusion, VR Photoscan technology provided a more visceral exposure experience which supported Mr. A to revisit the trauma memory. He reported high levels of satisfaction with the quality of the virtual environment and no issues using the VR technology. Produced with lower costs and shorter development times than typical computer-generated environments, VR Photoscan may be more easily implemented within routine care, although further research is required.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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