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Data Sheet 1_A survey of the experiences of delivering physiotherapy services through telerehabilitation during the COVID-19 pandemic.pdf

2024· dataset· en· W6965141202 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2024
Typedataset
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Electron Microscopy Techniques and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsTelerehabilitationVideoconferencingTelehealthTelemedicinePhoneRehabilitationAdaptation (eye)Pandemic

Abstract

fetched live from OpenAlex

Introduction Physiotherapy services have been typically provided in-person since the profession usually involves a therapist providing hands-on assessment and treatments. The COVID-19 pandemic provided an opportunity to study physiotherapists’ adaptation to telerehabilitation (phone or videoconference). Objective This study aimed: (1) to explore how physiotherapists adapted to the transition to delivering telerehabilitation, (2) to assess physiotherapists’ perceptions of implementing telerehabilitation, and (3) to identify the challenges and facilitators of delivering telerehabilitation. Methods This study used an online survey distributed to physiotherapists within a large Canadian health authority. Closed-ended questions were analyzed with descriptive statistics. Results Seventy-five physiotherapists responded and data were collected. Compared prior to the pandemic to time during the pandemic, the use of a phone for delivering physiotherapy increased from 24.0% to 73.3% of physiotherapists while videoconference increased from 5.3% to 77.3%. Overall, the physiotherapists found videoconference to be a more effective delivery method than phone. Less than half felt that they could use videoconference to effectively treat pain (49.3%), upper extremity function (40.0%) or strength/range of motion (48.0%). Only 29.3% felt that they could effectively treat walking balance or mobility by videoconference. Technical barriers were identified with client comfort with the equipment reported by 90.7% of physiotherapists and positioning of the webcam by 76.0% of physiotherapists. A large proportion of physiotherapists agreed that they would continue the practice of telerehabilitation via phone (54.7%) and videoconference (68.0%). Conclusion The pandemic resulted in a dramatic shift to telerehabilitation for a profession that typically provides hands-on assessments and treatments. While there was increased uptake of telerehabilitation, many physiotherapists questioned their effectiveness using telerehabilitation to undertake activities that traditionally involve manual treatments or hands-on guidance/supervision. However, physiotherapists were committed to continuing telerehabilitation to meet patients’ needs after the pandemic.

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)0.000
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.006
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
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 head0.045
GPT teacher head0.399
Teacher spread0.354 · 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 designNot applicable
Domainnot available
GenreDataset

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
Published2024
Admission routes1
Has abstractyes

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