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Record W2123170180 · doi:10.1097/ajp.0b013e3182608561

Activity Pacing in Chronic Pain

2012· review· en· W2123170180 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueClinical Journal of Pain · 2012
Typereview
Languageen
FieldMedicine
TopicCardiac pacing and defibrillation studies
Canadian institutionsLawson Health Research InstituteSt Joseph's Health Care
Fundersnot available
KeywordsMedicineChronic painPhysical medicine and rehabilitationNeuroscienceAnesthesiaPhysical therapyPsychology

Abstract

fetched live from OpenAlex

BACKGROUND: Activity pacing (AP) is a concept that is central to many chronic pain theories and treatments, yet there remains confusion regarding its definition and effects. OBJECTIVE: To review the current knowledge concerning AP and integrate this knowledge in a manner that allows for a clear definition and useful directions for future research. METHODS: A narrative review of the major theoretical approaches to AP and of the empirical evidence regarding the effects of AP interventions, followed by an integrative discussion. RESULTS: The concept of AP is derived from 2 main traditions: operant and energy conservation. Although there are common elements across these traditions, significant conceptual and practical differences exist, which has led to confusion. Little empirical evidence exists concerning the efficacy of AP as a treatment for chronic pain. DISCUSSION: Future research on AP should be based on a clear theoretical foundation, consider the context in which the AP behavior occurs and the type of pacing problem ("underactivity" vs. "overactivity"), and should examine the impact of AP treatment on multiple clinical outcomes. We provide a provisional definition of AP and specific recommendations that we believe will move the field forward.

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.

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)0.026
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.989
Threshold uncertainty score0.897

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0260.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.260
GPT teacher head0.505
Teacher spread0.245 · 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