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Record W2027076763 · doi:10.1089/g4h.2012.0008

Reducing Anxiety Using Self-Help Virtual Reality Cognitive Behavioral Therapy

2012· article· en· W2027076763 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGames for Health Journal · 2012
Typearticle
Languageen
FieldComputer Science
TopicVirtual Reality Applications and Impacts
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsPhobiasExposure therapyVirtual Reality Exposure TherapyVirtual realityAnxietySpecific phobiaPsychologyRelaxation (psychology)Clinical psychologyPsychotherapistAnxiety disorderComputer scienceHuman–computer interactionPsychiatrySocial psychology

Abstract

fetched live from OpenAlex

Virtual reality (VR) software has been used successfully for the treatment of various phobias and anxieties. The delivery of this software is often performed using expensive head-mounted VR displays with a therapist present to manipulate the VR scenario. The purpose of this study was to determine the effectiveness of self-help VR software delivered using red/blue anaglyph glasses, for the treatment of spider phobia. Participants used the software on their own without having a researcher or therapist present. The software provided instruction on the use of progressive muscle relaxation in conjunction with VR exposure therapy. Exposure therapy is the gold standard treatment for anxiety and phobia. For VR exposure therapy to be effective, the environment must produce a real fear response. Participants' physiological responses indicate that the VR software successfully produced a fear response. Self-report questionnaires indicated that the participants' level of fear for spiders decreased after taking part in four sessions.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.971
Threshold uncertainty score0.608

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.116
GPT teacher head0.413
Teacher spread0.297 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it