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Record W1990266321 · doi:10.1097/ajp.0b013e31814da407

Fear-avoidance Beliefs About Back Pain in Patients With Acute LBP

2007· article· en· W1990266321 on OpenAlexaboutno aff
Emmanuel Coudeyre, Florence Tubach, François Rannou, Gabriel Baron, F. Coriat, Sylvie Brin, Michel Revel, Serge Poiraudeau

Bibliographic record

VenueClinical Journal of Pain · 2007
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePhysical therapyLow back painRating scalePhysical medicine and rehabilitationPsychologyAlternative medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: We aimed to assess fear-avoidance beliefs in patients with acute low back pain (LBP) and to identify features of patients and general practitioners (GPs) associated with patients' fear-avoidance beliefs. METHODS: A cross-sectional study conducted in primary care practice in France. A total of 709 GPs completed a self-administered questionnaire assessing fear-avoidance beliefs [the Fear-Avoidance Beliefs Questionnaire (FABQ)] and 2,727 patients with acute LBP completed a self-administered questionnaire assessing pain, perceived handicap and disability (on the Quebec Back Pain Disability Scale) and fear-avoidance beliefs (on the FABQ). RESULTS: Patients' FABQ mean scores were 16.8+/-5.0 for physical activities (FABQ Physical) and 19.5+/-10.9 for occupational activities (FABQ Work). From multivariate analysis, the following factors were associated with patients' FABQ Phys and Work scores: having a GP with a high rating on the FABQ Phys (P=0.0001 and 0.02 for FABQ Phys and Work, respectively), no sport practice (vs. occasional: P=0.0003 and 0.03; vs. usual/competition: P=0.0001 and 0.004), disability score (Quebec) (P=0.0001 for both FABQ scores), and pain intensity (P=0.0012 and 0.0013). CONCLUSIONS: High levels of fear-avoidance beliefs occur early in LBP patients, and key messages on this topic should probably be delivered at a very early stage of the disease.

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)0.021
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score0.712

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0210.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.014
GPT teacher head0.338
Teacher spread0.325 · 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

Citations48
Published2007
Admission routes1
Has abstractyes

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