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Record W2018503509 · doi:10.1097/bor.0b013e3280327944

Pool exercise for individuals with fibromyalgia

2007· review· en· W2018503509 on OpenAlexaff
S. E. Gowans, A. deHueck

Bibliographic record

VenueCurrent Opinion in Rheumatology · 2007
Typereview
Languageen
FieldMedicine
TopicFibromyalgia and Chronic Fatigue Syndrome Research
Canadian institutionsJoseph Brant HospitalUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsFibromyalgiaMoodMedicinePhysical therapyRandomized controlled trialAerobic exercisePhysical medicine and rehabilitationPhysical exerciseHydrotherapyAlternative medicinePsychiatryInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: The benefits of general aerobic exercise for individuals with fibromyalgia have been established. Recently, there have been a number of randomized controlled trials that evaluate the benefits of pool exercise for fibromyalgia. This review will integrate the results of eight pool exercise studies that have been published in the last 7 years. RECENT FINDINGS: Pool exercise has been evaluated against sedentary control groups, land-based exercise and immersion in a warm, mineralized pool. Pool exercise has been shown to be as effective as land-based exercise and may have greater benefits with respect to mood and sleep duration. Based on follow-up studies, exercise-induced improvements in physical function, pain and mood may persist for up to 2 years. Pool exercise may be better tolerated as an initial means of exercise by individuals with arthritis in weight-bearing joints (because of water buoyancy) or by individuals who fear exercise will exacerbate their pain. SUMMARY: Pool exercise can be an effective intervention for individuals with fibromyalgia. Future studies should reassess subjects at multiple time points to determine the time course of exercise-induced improvements and further explore the effects of pool exercise on mood and sleep quality.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.595
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.121
GPT teacher head0.437
Teacher spread0.316 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations52
Published2007
Admission routes1
Has abstractyes

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