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Record W2159973908 · doi:10.1080/01924780902718608

Videoconference-Based Physiotherapy and Tele-Assessment for Homebound Older Adults: A Pilot Study

2009· article· en· W2159973908 on OpenAlexaff
Marie-Madeleine Bernard, Frederic Janson, Parminder Flora, Guy Faulkner, Liane Meunier-Norman, Mathias Fruhwirth

Bibliographic record

VenueActivities Adaptation & Aging · 2009
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsUniversity of TorontoUniversity of Saskatchewan
Fundersnot available
KeywordsTelerehabilitationVideoconferencingPhysical therapyMedicineRehabilitationRange of motionPhysical medicine and rehabilitationQuality of life (healthcare)TelemedicineNursingHealth careMultimediaComputer science

Abstract

fetched live from OpenAlex

Tele-rehabilitation may be one alternative for addressing the growing demand for rehabilitation among older adults because it may offer quality home-based care and promote autonomy among older adults. This pilot study assessed the effectiveness of videoconference-based physiotherapy to improve strength and range of motion in the old-old elderly, using a previously validated Videoconference Goniometer®. Seventeen homebound older adults (mean age 82.4, ±7.2) participated in a 10-week exercise program. Strength and range of motion were assessed at baseline and after 10 weeks. Significant improvements were found in measures of strength and range of motion following the 10-week program. This study demonstrates the feasibility of delivering and monitoring videoconference-based physiotherapy with this population of homebound older adults.

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)0.004
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.042
GPT teacher head0.378
Teacher spread0.337 · 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 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

Citations26
Published2009
Admission routes1
Has abstractyes

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