Activity Pacing in Chronic Pain
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".