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Record W2102280036

Effort testing in patients with fibromyalgia and disability incentives.

2001· article· en· W2102280036 on OpenAlexaff
R GERVAIS, Anthony S. Russell, Paul Green, Lisa Allen, Robert Ferrari, Stephanie Pieschl

Bibliographic record

VenuePubMed · 2001
Typearticle
Languageen
FieldMedicine
TopicFibromyalgia and Chronic Fatigue Syndrome Research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsExaggerationMedicineFibromyalgiaPhysical therapyCognitionRheumatoid arthritisCognitive testClinical psychologyPsychiatryInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To examine whether symptom exaggeration is a factor in complaints of cognitive dysfunction using 2 new validated instruments in patients with fibromyalgia (FM). METHODS: Ninety-six patients with FM and 16 patients with rheumatoid arthritis (RA) were administered 2 effort or symptom validity tests designed to detect exaggerated memory complaints as part of a battery of psychological tests and self-report questionnaires. RESULTS: A large percentage of patients with FM who were on or seeking disability benefits failed the effort tests. Only 2 patients with FM who were working and/or not claiming disability benefits and no patient with RA scored below the cutoffs for exaggeration of memory difficulties. CONCLUSION: This study illustrates the importance of assessing for exaggeration of cognitive symptoms and biased responding in patients with FM presenting for disability related evaluations.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
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 integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.021
GPT teacher head0.240
Teacher spread0.218 · 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 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

Citations128
Published2001
Admission routes1
Has abstractyes

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