MétaCan
Menu
Back to cohort
Record W2138569161 · doi:10.1177/0269215510367975

Do Numerical Rating Scales and the Roland-Morris Disability Questionnaire capture changes that are meaningful to patients with persistent back pain?

2010· article· en· W2138569161 on OpenAlexfundno aff
Julia M. Hush, Kathryn M. Refshauge, Gerard Sullivan, Lorraine De Souza, James H. McAuley

Bibliographic record

VenueClinical Rehabilitation · 2010
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsnot available
FundersMcGill University
KeywordsRating scaleFacilitatorPhysical therapyBack painPsychologyFocus groupPhysical medicine and rehabilitationMedicineDevelopmental psychologyAlternative medicineSocial psychology

Abstract

fetched live from OpenAlex

OBJECTIVES: To investigate patients' views about two common outcome measures used for back pain: Numerical Rating Scales for pain and the Roland-Morris Disability Questionnaire. SUBJECTS: Thirty-six working adults who had previously sought primary care for back pain and who could speak and read English. METHOD: Eight focus groups were conducted to explore participants' views about the 11-point Numerical Rating Scales and the 24-item Roland-Morris Disability Questionnaire. Each group was led by a facilitator and an interview topic guide was used. Audio recordings of focus groups were transcribed verbatim. Framework analysis was used to chart participants' views and an interpretive analysis performed to explain the findings. RESULTS: Participants reported that neither the Roland-Morris nor the Numerical Rating Scales captured the complex personal experience of pain or relevant changes in their condition. The time-frame of assessment was identified as particularly problematic and the Roland-Morris did not capture relevant functional domains. CONCLUSION: This study provides empirical data that working adults with persistent back pain consider these clinical outcome measures largely inadequate. These measures currently used for back pain may contribute to misleading conclusions about treatment efficacy and patient recovery.

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)0.004
metaresearch head score (Gemma)0.028
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.028
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.015
GPT teacher head0.306
Teacher spread0.291 · 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.

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

Citations66
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueClinical RehabilitationSame topicMusculoskeletal pain and rehabilitationFrench-language works237,207