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Record W2085563874 · doi:10.1016/j.pain.2011.07.024

Evaluation of the fear-avoidance model with health care workers experiencing acute/subacute pain

2011· article· en· W2085563874 on OpenAlexafffund
Marc Corbière, Sara Zaniboni, Marie‐France Coutu, Renée‐Louise Franche, Jaime Guzmán, Karlene Dawson, Annalee Yassi

Bibliographic record

VenuePain · 2011
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsFraser HealthUniversity of British ColumbiaSimon Fraser UniversityUniversité de Sherbrooke
FundersMichael Smith Health Research BC
KeywordsPain catastrophizingPsychological interventionChronic painDepression (economics)PsychologyDepressive symptomsClinical psychologyAcute painMedicinePhysical therapyPsychiatryAnxietyAnesthesia

Abstract

fetched live from OpenAlex

Studies in the literature do not show clear evidence supporting the relationship between pain and depressive symptoms in individuals experiencing acute/subacute pain compared to those experiencing chronic pain. However, more information is needed about which variables act as mediators in the pain-depression relationship in people having acute/subacute pain, before pain becomes chronic. Our objectives were to test the suitability of the fear-avoidance model in a sample of 110 health care workers experiencing acute/subacute pain using path analyses, to improve the model as needed, and to examine a model involving both pain catastrophizing and pain self-efficacy with work status as a final outcome. Overall, the results indicated that adjustments to the fear-avoidance model were required for people experiencing acute/subacute pain, in which fear-avoidance beliefs and depressive symptoms were concurrent rather than sequential. The catastrophizing concept was most closely associated with depressive symptoms, while pain self-efficacy was directly associated with fear-avoidance beliefs and indirectly to work outcomes. Assessing and modifying pain self-efficacy in acute/subacute pain patients is important for interventions aiming to decrease fear-avoidance and improve work outcomes.

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)0.010
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.672
Threshold uncertainty score0.361

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.001
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 head0.034
GPT teacher head0.307
Teacher spread0.274 · 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 designSimulation or modeling
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

Citations18
Published2011
Admission routes2
Has abstractyes

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