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Record W2066319638 · doi:10.2217/pmt.13.9

Self-Management Interventions for Chronic Pain

2013· article· en· W2066319638 on OpenAlex
Elizabeth Mann, Sandra LeFort, Elizabeth G. VanDenKerkhof

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

VenuePain Management · 2013
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsKingston General HospitalMemorial University of NewfoundlandQueen's University
Fundersnot available
KeywordsPsychological interventionSelf-managementChronic painMedicineCoping (psychology)Pain managementVariety (cybernetics)Mental healthQuality of life (healthcare)NursingPhysical therapyClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

SUMMARY Individuals living with chronic pain face daily challenges of managing symptoms, modifying roles and responsibilities, and coping with the negative emotional consequences of pain. Self-management interventions teach a variety of strategies to meet these challenges and build participants' self-efficacy for their use. These interventions have been delivered in individual, group and online formats for a variety of different pain conditions. The evidence supports the efficacy of self-management interventions in improving pain, mental health and health-related quality of life outcomes. Acceptance of the chronic nature of their pain is a necessary step before individuals are ready to self-manage. Clinicians can play a critical role in supporting self-management through answering questions, providing advice, addressing barriers and facilitators, and encouraging self-management efforts.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.734
Threshold uncertainty score0.618

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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)0.0010.000

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 head0.012
GPT teacher head0.286
Teacher spread0.275 · 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