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Record W2810373023 · doi:10.1177/1043454218782138

Usability Testing of an Interactive Virtual Reality Distraction Intervention to Reduce Procedural Pain in Children and Adolescents With Cancer

2018· article· en· W2810373023 on OpenAlexafffund
Kathryn A. Birnie, Yalinie Kulandaivelu, Lindsay Jibb, Petra Hroch, Karyn Positano, S Robertson, Fiona Campbell, Oussama Abla, Jennifer Stinson

Bibliographic record

VenueJournal of Pediatric Oncology Nursing · 2018
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsUniversity of OttawaUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsDistractionUsabilityIntervention (counseling)Virtual realityPediatric cancerPsychologyHuman–computer interactionMedicineCancerComputer scienceNursingCognitive psychology

Abstract

fetched live from OpenAlex

PURPOSE: Needle procedures are among the most distressing aspects of pediatric cancer-related treatment. Virtual reality (VR) distraction offers promise for needle-related pain and distress given its highly immersive and interactive virtual environment. This study assessed the usability (ease of use and understanding, acceptability) of a custom VR intervention for children with cancer undergoing implantable venous access device (IVAD) needle insertion. METHOD: Three iterative cycles of mixed-method usability testing with semistructured interviews were undertaken to refine the VR. RESULTS: Participants included 17 children and adolescents (8-18 years old) with cancer who used the VR intervention prior to or during IVAD access. Most participants reported the VR as easy to use (82%) and understand (94%), and would like to use it during subsequent needle procedures (94%). Based on usability testing, refinements were made to VR hardware, software, and clinical implementation. Refinements focused on increasing responsiveness, interaction, and immersion of the VR program, reducing head movement for VR interaction, and enabling participant alerts to steps of the procedure by clinical staff. No adverse events of nausea or dizziness were reported. CONCLUSIONS: The VR intervention was deemed acceptable and safe. Next steps include assessing feasibility and effectiveness of the VR intervention for pain and distress.

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 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.220
Threshold uncertainty score0.418

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.022
GPT teacher head0.379
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations101
Published2018
Admission routes2
Has abstractyes

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