MétaCan
Menu
Back to cohort
Record W4390122170 · doi:10.30574/ijsra.2023.10.2.0898

A study to assess the effectiveness of tele rehabilitation on knee pain for patient with osteoarthritis at selected community

2023· article· en· W4390122170 on OpenAlexaboutno aff
B Tamilarasi, P Saranya, S Babitha, R Rohitharaj, U Padmavathi, Santhosh Kumar C, Jolin Prathip P. M

Bibliographic record

VenueInternational Journal of Science and Research Archive · 2023
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsnot available
Fundersnot available
KeywordsPhysical therapyWOMACOsteoarthritisMedicineRehabilitationTelerehabilitationTest (biology)EveningKnee painPhysical medicine and rehabilitationTelemedicineAlternative medicineHealth care

Abstract

fetched live from OpenAlex

The aim of the study was to evaluate the effectiveness of tele rehabilitation on knee pain among patient with osteo arthritis. A pre-experimental one group pretest post test design is used to conduct the study. The study was done on 30 samples selected by purposive sampling technique from a selected community. The data was collected through questionnaire (Demographic variables) and WOMAC scale questionnaire. After obtaining the permission from the concerned authorities, the data was collected by conducting pretest by using western Ontario and MC Master university Arthritis index (WOMAC) scale and delivering rehabilitation services to the patient through video assisted demonstration on exercise and booklet on dos and don’ts issued to patients at outpatient department following which phone calls were made to every patients with OA in morning and evening to ensure patient participation in rehabilitative activities at home for 15 days and post test was done by using WOMAC scale. The study findings revealed that there was significant difference in the pain score before and after telerehabilitation. Hence the H1 is accepted which shows the difference in the pretest and post-test level of knee pain among patient with Osteoarthritis after Telerehabilitation.

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)0.018
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.526
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0180.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.071
GPT teacher head0.454
Teacher spread0.383 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Science and Research ArchiveSame topicTelemedicine and Telehealth ImplementationFrench-language works237,207