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Dispositional empathy modulates vicarious effects of dynamic pain expressions on spinal nociception, facial responses and acute pain

2012· article· en· W1600016105 on OpenAlexafffund
Jean‐Philippe Mailhot, Étienne Vachon‐Presseau, Philip L. Jackson, Pierre Rainville

Bibliographic record

VenueEuropean Journal of Neuroscience · 2012
Typearticle
Languageen
FieldNeuroscience
TopicPain Management and Placebo Effect
Canadian institutionsUniversité LavalUniversité de MontréalInstitut Universitaire de Gériatrie de Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPsychologyEmpathyNociceptionFacilitationFacial expressionNoxious stimulusAudiologyNeuroscienceMedicineCommunicationSocial psychology

Abstract

fetched live from OpenAlex

Pain communication is thought to promote automatic vicarious self-protective responses as well as empathic concern towards others' suffering. This duality was recently highlighted in a study showing that highly empathic individuals display increased vicarious facilitation of low-level pain processing (nociceptive flexion reflex, NFR) combined with an unexpected reduced facilitation of self-pain perception (pain ratings) while viewing static pictures evoking pain in others. The present study sought to test further the moderating effects of dispositional empathy on vicarious responses induced by viewing dynamic pain expressions. Twenty-four healthy volunteers viewed 1-s videos showing different levels of pain expression before noxious electric shocks were delivered to the sural nerve. Viewing stronger pain expressions generally increased shock-pain unpleasantness ratings, the amplitude of the NFR, and facial responses (corrugator muscle) to the noxious stimulation. However, self-pain ratings (intensity and unpleasantness) increased less or were reduced following clips of pain expression in individuals scoring higher on the Empathy Quotient. These results suggest that vicarious processes facilitate low-level defensive responses, while the experience of self-pain and the associated negative affect may be partly tuned-down by higher-order empathic processes.

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)0.009
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.930
Threshold uncertainty score0.926

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.018
GPT teacher head0.276
Teacher spread0.258 · 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 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

Citations38
Published2012
Admission routes2
Has abstractyes

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