MétaCan
Menu
Back to cohort
Record W3201478950 · doi:10.2196/29799

Teleassessments for Enrollment of Adults With Physical or Mobility Disability in a Home-Based Exercise Trial in Response to COVID-19: Usability Study

2021· article· en· W3201478950 on OpenAlexvenueno aff
Jereme Wilroy, Byron Lai, Madison Currie, Hui‐Ju Young, Mohanraj Thirumalai, Tapan Mehta, John Giannone, James H. Rimmer

Bibliographic record

VenueJMIR Formative Research · 2021
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsnot available
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Child Health and Human DevelopmentNational Center for Advancing Translational SciencesUniversity of AlabamaUniversity of Alabama at Birmingham
KeywordsMedicinePhysical therapyTelehealthRandomized controlled trialData collectionDigital healthTelemedicineHealth care

Abstract

fetched live from OpenAlex

BACKGROUND: The Scale-Up Project Evaluating Responsiveness to Home Exercise And Lifestyle Tele-Health (SUPER-HEALTH) initiative is a large randomized controlled study that aims to overcome logistical barriers to exercise via telehealth for people with physical disabilities. However, at the start of the COVID-19 pandemic, enrollment was halted due to limited operations at the testing site, which included no onsite visits that involved participant data collection. In response to the limited operations, a modified data collection protocol was developed for virtual enrollment of study participants. OBJECTIVE: This paper presents feasibility data on using teleassessments to enroll people with mobility impairment into a home-based exercise trial. METHODS: The modified protocol replaced onsite enrollment and data collection visits with teleassessments using a computer tablet and testing equipment that was shipped to the participants' home address prior to the synchronous teleassessments conducted by an exercise physiologist through Zoom. The participants were mailed a teleassessment toolkit that included a digital blood pressure cuff, spirometer, hand dynamometer, mini disc cone, and measuring tape (to complete standardized testing). The teleassessment measures included resting blood pressure and heart rate, forced vital capacity, grip strength, Five Times Sit to Stand, and Timed Up and Go. Feasibility metrics included technological effectiveness, efficiency, and safety. The technological effectiveness of the telehealth assessment was determined by the percentage of sessions completed without technical issues with ≥90% criteria set a priori. Efficiency was measured by a session duration of ≤2 hours. Safety was measured by the number of adverse events related to the teleassessments reported. RESULTS: Data from 36 participants were included in this feasibility study, and 34 (94%) participants completed all teleassessments without technical issues. For efficiency, the teleassessment sessions were completed in a mean time of 65 minutes and a maximum session length of 110 minutes. There were no adverse events reported to indicate concerns with the safety of teleassessments. CONCLUSIONS: The modified teleassessment protocol, in response to COVID-19 restrictions, may be a feasible process for enrolling adults with mobility impairment into a home exercise trial who otherwise would have not been able to participate. TRIAL REGISTRATION: ClinicalTrials.gov NCT03024320; https://clinicaltrials.gov/ct2/show/NCT03024320.

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)0.047
metaresearch head score (Gemma)0.078
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 score0.047
Threshold uncertainty score0.246

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0470.078
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.116
GPT teacher head0.537
Teacher spread0.421 · 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

Citations11
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJMIR Formative ResearchSame topicTelemedicine and Telehealth ImplementationFrench-language works237,207