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Record W2055681669 · doi:10.1016/s0304-3959(02)00235-x

Catastrophizing is related to pain ratings, but not nociceptive flexion reflex threshold

2002· article· en· W2055681669 on OpenAlexfundaboutno aff
Christopher France, Janis L. France, Mustafa Al’Absi, Christopher Ring, David McIntyre

Bibliographic record

VenuePain · 2002
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsnot available
FundersNational Heart, Lung, and Blood InstituteMcGill University
KeywordsPain catastrophizingNociceptionPhysical therapyThreshold of painPsychologyPhysical medicine and rehabilitationMedicineChronic painAnesthesia

Abstract

fetched live from OpenAlex

Catastrophizing is reliably associated with increased reports of clinical and experimental pain. To test the hypothesis that catastrophizing may heighten pain experience by increasing nociceptive transmission through spinal gating mechanisms, the present study examined catastrophizing as a predictor of pain ratings and nociceptive flexion reflex (NFR) thresholds in 88 young adult men (n=47) and women (n=41). The NFR threshold was defined as the intensity of electrocutaneous sural nerve stimulation required to elicit a withdrawal response from the biceps femoris muscle of the ipsilateral leg. Participants completed an assessment of their NFR threshold and then provided pain ratings using both a numerical rating scale (NRS) and the short-form McGill pain questionnaire (SF-MPQ). Pain catastrophizing was assessed using the catastrophizing subscale of the coping strategies questionnaire (CSQ). Although catastrophizing was positively related to both NRS and SF-MPQ pain ratings, catastrophizing was not significantly related to NFR threshold. These findings suggest that differential modulation of spinal nociceptive input may not account for the relationship between catastrophizing and increased pain.

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)0.005
metaresearch head score (Gemma)0.004
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 score0.418
Threshold uncertainty score0.932

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.004
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)0.0010.001

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 head0.024
GPT teacher head0.291
Teacher spread0.267 · 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

Citations142
Published2002
Admission routes2
Has abstractyes

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