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Randomised controlled trial of the effects of a self-management patient education program on overall quality of life and knee pain of older people with mild to moderate knee(s) osteoarthritis

2017· article· en· W2608426889 on OpenAlexaff
Alhadi M. Jahan

Bibliographic record

VenueInternational Journal of Clinical Trials · 2017
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsOsteoarthritisMedicinePhysical therapyQuality of life (healthcare)Randomized controlled trialPopulationKnee painInternal medicineAlternative medicineNursing

Abstract

fetched live from OpenAlex

Background: Knee osteoarthritis (OA) is the most important chronic rheumatic disease affecting human beings. It is more common among the older population. The objective of OA treatment is to control the symptoms, such as pain, mobility problems and consequently, to improve overall quality of life. Although, self-management patient education programs, such as educational workshops and other learning activities are effective approaches in some chronic diseases, the evidence for arthritis is still inconclusive. The aim of this trial is to compare the effectiveness of an OA of the knee self-management education program with a control group, as determined by improvements in pain and quality of life. Methods: In this study, we will perform a two-group, randomized (1:1 ratio), controlled study with repeated-measures to examine the differences between the two groups over time. The research sample will be selected from the patients who are referred to a physiotherapy department with a diagnosed mild to moderate knee(s) OA, aging from 45 to 65 years. Conclusions: Positive findings of this trial will pave the road for new methods of cooperation between patients and healthcare providers. Also, patient education ensures that patients are well-informed about their own health and they could avoid any deterioration and disability due to bad practices. Finally, an increased understanding helps patients to make informed decisions about their healthcare avenues.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0060.004
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0140.001

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 head0.046
GPT teacher head0.414
Teacher spread0.368 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
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".

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Citations1
Published2017
Admission routes1
Has abstractyes

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