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Record W1990606246 · doi:10.1037/a0026801

Perceptions of virtual reality among therapists who do not apply this technology in clinical practice.

2012· article· en· W1990606246 on OpenAlexaff
Deborah Schwartzman, Robert M. Segal, Martin Drapeau

Bibliographic record

VenuePsychological Services · 2012
Typearticle
Languageen
FieldComputer Science
TopicVirtual Reality Applications and Impacts
Canadian institutionsMcGill University
Fundersnot available
KeywordsVirtual realityPerceptionClinical PracticePsychologyMedicineApplied psychologyPsychotherapistPhysical therapyComputer scienceHuman–computer interaction

Abstract

fetched live from OpenAlex

Research has documented the usefulness of virtual reality (VR) in treating a number of psychopathologies. Despite its recognized clinical utility, VR remains underutilized in clinical practice. For the purpose of this study, 262 therapists who reported that they did not currently use VR in psychotherapy were surveyed about their perceptions of the use of this technology in clinical practice. Results suggest that reluctance in using this technology stems from beliefs about the required training, equipment, and financial costs and from unfamiliarity with the various benefits and applications of VR. The significance of promoting greater use of this new technology is 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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.032
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.054
GPT teacher head0.411
Teacher spread0.357 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations57
Published2012
Admission routes1
Has abstractyes

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