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Record W6907713764 · doi:10.25384/sage.c.4548701

Use of real-time videoconferencing to deliver physical therapy services: A scoping review of published and emerging evidence

2019· other· en· W6907713764 on OpenAlexaboutno aff

Bibliographic record

VenueSage Journals Data · 2019
Typeother
Languageen
FieldSocial Sciences
TopicInformation Systems Theories and Implementation
Canadian institutionsnot available
Fundersnot available
KeywordsTelehealthVideoconferencingTelemedicineDescriptive statisticsInclusion (mineral)Clinical trialTelerehabilitationMEDLINEData extraction

Abstract

fetched live from OpenAlex

AbstractIntroductionTelehealth may be a viable means to deliver physical therapy services across a range of practice settings and health conditions; however, there is limited uptake of telehealth in clinical practice. The purpose of this study is to examine and describe trends, gaps and opportunities in published and emerging evidence regarding the use of real-time videoconferencing to deliver physical therapy services.MethodsFour databases and three trial registries were searched using terms for physical therapy and telehealth. Inclusion criteria were primary studies, systematic reviews and published trial registries that had the following features: physical therapy assessment and/or treatment, real-time videoconferencing and English language. Title/abstract, full text screening and data extraction were completed by pairs of independent reviewers. Descriptive statistics stratified by published research and trial registry records were used to summarize study characteristics.ResultsA total of 100 studies (80 published and 20 trial registries) were included. Australia, Canada and the US have the highest proportion of published and emerging research (63.0%). The majority of conditions studied were musculoskeletal (42.0%). Computers were the most common videoconferencing technology used (31.0%) and only 14.0% of studies reported using a secure platform. The majority of studies examined health outcomes (64.0%) and process outcomes (65.0%), while only 32.0% reported system outcomes.DiscussionResearch in the field of telehealth and physical therapy is growing and becoming increasingly diverse with the advancements in technology.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.820
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.133
GPT teacher head0.429
Teacher spread0.296 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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