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Spine school for patients with low back pain: interdisciplinary approach

2015· article· en· W2263629570 on OpenAlexaboutno aff
Janaina Moreno Garcia, Pola Maria Poli de Araújo, Maria Stella Peccin, Ricardo E.A.S. Diniz, Roger Amorim Santos Diniz, Império Lombardi

Bibliographic record

VenueColuna/Columna · 2015
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineVisual analogue scaleQuality of life (healthcare)Physical therapyInternal medicine

Abstract

fetched live from OpenAlex

<sec><title>OBJECTIVE:</title><p> To analyze and evaluate an interdisciplinary educational treatment - Spine School.</p></sec><sec><title>METHODS:</title><p> This study is a non-controlled clinical trial. Twenty one individuals (19 women) aged 27-74 years diagnosed with chronic low back pain were enrolled and followed-up by a rheumatologist and an orthopedist. The evaluations used were SF36, Roland Morris, canadian occupational performance measure (COPM) and visual analogue scale (VAS) of pain that were performed before and after seven weeks of treatment.</p></sec><sec><title>RESULTS:</title><p> We found statistically significant improvements in vitality (mean 48.10 vs. 81.25) p=0.009 and limitations caused by physical aspects (mean 48.81 vs. 81.25) p=0.038 and perception of pain (mean 6.88 vs. 5.38) p=0.005. Although the results were suggestive of improvement, there were no statistical significant differences in the domains social aspects (average 70.82 vs. 92.86) p=0.078, emotional aspects (average 52.38 vs. 88.95) p=0.078, and the performance satisfaction (mean 4.94 vs. 8.24) p=0.074.</p></sec><sec><title>CONCLUSION:</title><p> The Interdisciplinary Spine School was useful for improvement in some domains of quality of life of people with low back pain.</p></sec>

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)0.001
metaresearch head score (Gemma)0.001
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 score0.480
Threshold uncertainty score0.634

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.013
GPT teacher head0.272
Teacher spread0.259 · 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

Citations1
Published2015
Admission routes1
Has abstractyes

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