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Record W1996605546 · doi:10.1016/j.pain.2004.12.034

The influence of acute anxiety on assessment of nociceptive flexion reflex thresholds in healthy young adults

2005· article· en· W1996605546 on OpenAlexafffund
Douglas J. French, Christopher France, Janis L. France, Lori F. Arnott

Bibliographic record

VenuePain · 2005
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsUniversité de Moncton
FundersNational Heart, Lung, and Blood InstituteCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsNociceptionAnxietyMedicineReflexAnesthesiaPhysical medicine and rehabilitationPsychologyPhysical therapyInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

The nociceptive flexion reflex (NFR) is a polysynaptic withdrawal reflex that occurs in response to painful stimulation. In human studies, NFR responsiveness has been used as a direct measure of nociception as well as an indirect measure of supraspinal modulation of nociceptive transmission. Previous studies have suggested that anxiety may influence NFR responding, and therefore it has been recommended that anxiety be reduced by familiarizing participants with assessment methodology prior to formal NFR assessment. The present study was designed to assess the influence of anxiety on NFR threshold. Using a repeated measures design, 40 men and women completed an NFR threshold assessment twice within session one, and twice again during a second session conducted 24h later. Within each assessment session, state anxiety was measured at the beginning of the session and immediately following each NFR threshold assessment. Results indicated that although anxiety increased in response to NFR threshold assessment and was positively related to subjective pain reports, anxiety was not related to observed NFR threshold levels. These findings suggest that individual differences in anxiety do not significantly affect NFR threshold level determinations under standard testing conditions.

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)0.004
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.483
Threshold uncertainty score0.222

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.009
GPT teacher head0.339
Teacher spread0.330 · 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

Citations71
Published2005
Admission routes2
Has abstractyes

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