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Record W2156448090 · doi:10.3138/ptc.59.2.132

Examining the Pain Stages of Change Questionnaire in Chronic Pain

2007· article· en· W2156448090 on OpenAlexvenueno aff
Renee Williams, Eleni G. Hapidou, Chia-Yu A. Lin, Hira Abbasi

Bibliographic record

VenuePhysiotherapy Canada · 2007
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsPhysical therapyMedicineRehabilitationChronic painLocus of controlPain catastrophizingDepression (economics)ContemplationPsychologyPsychotherapist

Abstract

fetched live from OpenAlex

Purpose: This study examined the relationships of a readiness to adopt a self-management approach to chronic pain, measured by the Pain Stages of Change Questionnaire (PSOCQ), with other pain-related scales in patients attending a chronic pain management program and determined if these measures changed from admission to discharge. The PSOCQ consists of four stages: Pre-contemplation, Contemplation, Action and Maintenance. Method: A convenience sample of 140 patients (mean age = 43.8 years; SD = 8.3 years) with chronic pain completed the PSOCQ, the Pain Disability Index (PDI), the Pain Intensity Scale (PIS), the Center for Epidemiologic Studies-Depression Scale (CES-D) and the Multidimensional Health Locus of Control Scale (MHLC) at admission and discharge. The MHLC consists of three subscales: Internal, Chance and Powerful Others. Results: At discharge, Pearson correlation coefficients demonstrated that Pre-contemplation was positively associated with the PDI, the PIS and the CES-D and negatively associated with Internal MHLC, whereas Action and Maintenance showed the opposite findings. There were significant improvements in all measures, except the MHLC, over the four-week program. Conclusions: These findings provide support for the use of the PSOCQ in assessing patients' readiness to adopt a self-management approach to pain and in monitoring their progress in rehabilitation.

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)0.002
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 score0.824
Threshold uncertainty score0.542

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.022
GPT teacher head0.299
Teacher spread0.276 · 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

Citations7
Published2007
Admission routes1
Has abstractyes

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