MétaCan
Menu
Back to cohort

A comparison of the effects of deep tissue massage and therapeutic massage on chronic low back pain

2012· article· en· W108269080 on OpenAlexaboutno aff
Mateusz Wojciech Romanowski, Joanna Romanowska

Bibliographic record

VenueStudies in health technology and informatics · 2012
Typearticle
Languageen
FieldMedicine
TopicComplementary and Alternative Medicine Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMassageMedicinePhysical therapyChronic painPhysical medicine and rehabilitationAlternative medicinePathology

Abstract

fetched live from OpenAlex

INTRODUCTION: This study compared the effectiveness of two different kind of massage: therapeutic and deep tissue on chronic low back pain. METHODS: The research was made on 26 patient aged from 60 to 75 years who were separated into 2 groups: I [n=13] and II [n=13]. Group I had therapeutic massage [TM] which uses effleurage, petrissage, tapping and friction. Group II had deep tissue massage [DTM] which uses oblique pressure, a combination of lengthening and cross-fiber strokes, anchor and stretch, freeing muscle from entrapment. TM and DTM lasted for 10 days, each 30 min and were made by qualify massage therapist. Both groups did not have other treatment. Outcome measures obtained at baseline and after treatment consisted of Modified Oswestry Low Back Pain Disability Index [ODI], Quebec Back Pain Disability Scale[QBPD] and Visual Analog Scale [VAS]. RESULTS: There was not statistically significant differences between groups according to age and BMI. Statistically significant differences were noted after TM in every test [ODI p=0.010; QBPD p<0.001; VAS p<0.001] and after DTM in every test [ODI p<0.001; QBPD p<0.001; VAS p<0.001]. DTM was statistically significant better therapy than TM in ODI [p=0.038] and VAS [p=0.015]. Further research is needed to verify the results.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.198
Threshold uncertainty score0.313

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.000
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 head0.047
GPT teacher head0.407
Teacher spread0.360 · 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

Citations17
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueStudies in health technology and informaticsSame topicComplementary and Alternative Medicine StudiesFrench-language works237,207