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Record W2621541383 · doi:10.1097/ajp.0000000000000526

Pain-related Activity Management Patterns and Function in Patients With Fibromyalgia Syndrome

2017· article· en· W2621541383 on OpenAlexaff
Mélanie Racine, Santiago Galán, Rocío de la Vega, Catarina Tomé‐Pires, Ester Solé, Warren R. Nielson, Jordi Miró, Dwight E. Moulin, Mark P. Jensen

Bibliographic record

VenueClinical Journal of Pain · 2017
Typearticle
Languageen
FieldMedicine
TopicFibromyalgia and Chronic Fatigue Syndrome Research
Canadian institutionsLawson Health Research InstituteWestern University
Fundersnot available
KeywordsFibromyalgiaMedicinePhysical therapyDemographicsPain managementChronic painPain catastrophizingPhysical medicine and rehabilitationNociceptionInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: To clarify the importance of avoidance, pacing, and overdoing pain-related activity management patterns as predictors of adjustment in patients with fibromyalgia syndrome. METHODS: A total of 119 tertiary care patients with fibromyalgia syndrome who agreed to be part of an activity management pain program completed a survey, which requested information about demographics, pain intensity and pain interference, psychological and physical function, and pain-related activity management patterns. Hierarchical regression analyses were used to identify the unique contributions of the 3 different pain-related activity management patterns (avoidance, pacing, and overdoing) to the prediction of pain interference, psychological function, and physical function. RESULTS: The avoidance pattern was a significant and unique predictor of worse psychological and physical function as well as greater pain interference. Pacing was significantly associated with less pain interference and better psychological function, whereas overdoing was not found to predict patient functioning. DISCUSSION: The findings confirm the importance of pain-related activity management patterns as predictors of patient function, and support the necessity of addressing these factors in chronic pain treatment. In addition, the results suggest that targeting increases in activity pacing and decreases in pain avoidance, specifically, might yield the best patient outcomes. However, further research to evaluate this possibility is necessary.

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)0.001
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 score0.046
Threshold uncertainty score0.402

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
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 integrity0.0000.001
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 head0.026
GPT teacher head0.324
Teacher spread0.298 · 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

Citations40
Published2017
Admission routes1
Has abstractyes

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