MétaCan
Menu
Back to cohort
Record W1998436741 · doi:10.1186/1472-6882-12-s1-p225

P02.169. The effects of massage therapy on Multiple Sclerosis patients

2012· article· en· W1998436741 on OpenAlexaff
Brittany Schroeder, Kalyani Premkumar, Jennifer Doig

Bibliographic record

VenueBMC Complementary and Alternative Medicine · 2012
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsMedicineMassagePhysical therapyQuality of life (healthcare)Expanded Disability Status ScaleMultiple sclerosisPhysical medicine and rehabilitationAlternative medicineNursingPathology

Abstract

fetched live from OpenAlex

Twenty-four MS patients with scores ranging from 3.0 to 7.0 on the Expanded Disability Status Scale (EDSS) received four weeks of Swedish massage treatments. The Six-Minute-Walk-Test (6MWT) was used to assess their exercise capacity and leg function and the Hamburg Quality of Life in MS (HAQUAMS) instrument was used to assess changes in client QoL. These assessments were measured before and after a massage period and a rest period where no massages were employed. The results displayed no significant changes in 6MWT distances or HAQUAMS scores after massage or rest periods. However, clients’ personal health rating improved after massage and deteriorated when massages were removed. Client comments collected at the end of the study supported this change. The improvement in patient perception could have been due to an analgesic effect of massage that decreases pain. In addition, the relaxation induced by massage is very beneficial in stress management and thus symptom management for MS individuals. Although the results from this study display a limited significant change after massage treatments, it is important to note that no harm was being done. Thus, massage is a safe, non-invasive supplementary treatment option that may assist MS patients to manage the stress of their symptoms and improve quality of life.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.511

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 head0.151
GPT teacher head0.349
Teacher spread0.198 · 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
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueBMC Complementary and Alternative MedicineSame topicMultiple Sclerosis Research StudiesFrench-language works237,207