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Record W2297931573 · doi:10.1155/2011/817816

Changes in Perceived Pain Severity during Interdisciplinary Treatment for Chronic Pain

2011· article· en· W2297931573 on OpenAlexafffund
John Kowal, Keith G. Wilson, Celia M Geck, Peter R. Henderson, Joyce L. D’Eon

Bibliographic record

VenuePain Research and Management · 2011
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersCanadian Institutes of Health Research
KeywordsChronic painMedicinePhysical therapyPsychology

Abstract

fetched live from OpenAlex

BACKGROUND: There is good support for the effectiveness of interdisciplinary chronic pain management programs in improving functional outcomes; however, relatively little is known about patients who report deterioration following participation in such programs. OBJECTIVES: The present retrospective study investigated patients' reports of increased pain severity during participation in a cognitive-behaviourally oriented, outpatient treatment for chronic pain. METHODS: Participants (n=280) completed a four-week, group-based, interdisciplinary chronic pain self-management program at a rehabilitation hospital. They completed pre- and post-treatment questionnaires, which included global change ratings of pain severity and clinically-relevant measures, including pain intensity ratings, functional limitations, pain catastrophizing and self-efficacy. RESULTS: Statistically significant pre-post improvements were observed for all study variables. Almost all patients reported global improvement overall. Nevertheless, a subset of patients (n=99) reported increased pain severity on global ratings. These individuals were characterized by lower self-efficacy at baseline. CONCLUSIONS: Participants endorsed significant pre- and post-treatment improvements in all domains. Nevertheless, some participants reported deterioration. The findings shed light on variables associated with negative treatment outcomes and have practical applications for interdisciplinary chronic pain management programs.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.921
Threshold uncertainty score0.429

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.000
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)0.0000.000

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 head0.071
GPT teacher head0.374
Teacher spread0.303 · 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

Citations21
Published2011
Admission routes2
Has abstractyes

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