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Record W4392636498

Are Cognitive Load and Focus of Attention Differentially Involved in Pain Management: An Experimental Study Using a Cold Pressor Test and Virtual Reality

2020· article· en· W4392636498 on OpenAlexaboutno aff
S. Dumoulin, Stéphane Bouchard, Claudie Loranger, Pamela Quintana, Véronique Gougeon, Lavoie KL

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2020
Typearticle
Languageen
FieldNeuroscience
TopicPain Management and Placebo Effect
Canadian institutionsnot available
Fundersnot available
KeywordsCold pressor testFocus (optics)Test (biology)CognitionVirtual realityPain managementPsychologyComputer scienceCognitive psychologyHuman–computer interactionNeuroscienceMedicineAnesthesiaPhysicsBiologyInternal medicineBlood pressure
DOInot available

Abstract

fetched live from OpenAlex

Stéphanie Dumoulin,1 Stéphane Bouchard,2– 4 Claudie Loranger,2,4 Pamela Quintana,2 Véronique Gougeon,5 Kim L Lavoie1,6 1Department of Psychology, Université du Québec à Montréal, Montréal, QC, Canada; 2Cyberpsychology Lab, Université du Québec en Outaouais, Gatineau, QC, Canada; 3School of Psychology, University of Ottawa, Ottawa, ON, Canada; 4Research Center, Centre Intégré de Santé et de Services Sociaux de l’Outaouais, Gatineau, QC, Canada; 5Department of Psychology, Université de Sherbrooke, Sherbrooke, QC, Canada; 6Montreal Behavioral Medicine Center, Research Center, CIUSSS-NIM Hôpital du Sacré-Coeur de Montréal, Montréal, QC, CanadaCorrespondence: Stéphane BouchardCyberpsychology Lab, Université du Québec en Outaouais, C.P. 1250, Succ. Hull, 283 Boul. Alexandre-Taché, 2 e Étage, Local C-2500, Gatineau, Quebec J8X 3X7, CanadaTel +1-819-595-3900 #2360Fax +1 819-595-2250Email stephane.bouchard@uqo.caObjective: The aim of this study is to assess whether distraction (lack of attentional focus) and attention (cognitive load) are differentially involved in the analgesic effect of virtual reality (VR) immersions during a cold pressor test (CPT).Methods: Thirty-one participants were randomly assigned to four experimental conditions (high and low cognitive load, attention with or without a reminder of the pain stimuli) and performed three CPTs. Pain was assessed based on the duration of the CPT (pain tolerance), a visual analog rating scale of perceived pain intensity during the CPT and the subjective pain scale of the Short form McGill Pain Questionnaire (SF-MPQ).Results: The statistical analyses revealed that VR immersions were associated with less pain compared to the baseline (all p < 0.001), but for the experimental manipulations, only the conditions where there was an increase in cognitive load (ie, from low cognitive load at Immersion 1 to high cognitive load at Immersion 2) were effective for increasing pain tolerance (significant Time X Conditions interaction). The interactions were not significant for pain intensity assessed with the VAS or the SF-MPQ.Conclusion: The results suggest that increases in cognitive load play an important role in the analgesic effect of VR immersion, although the combination of attentional focus and cognitive load may be important. Suggestions are given for designing a replication study.Keywords: virtual reality, pain, attention, cognitive load, distraction, cold pressor test, CPT

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)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.327
GPT teacher head0.504
Teacher spread0.177 · 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 designBench or experimental
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

Citations2
Published2020
Admission routes1
Has abstractyes

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