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Record W4406518278 · doi:10.1016/j.physio.2025.101464

Best practice recommendations for physiotherapists providing telerehabilitation to First Nations people: a modified Delphi study

2025· article· en· W4406518278 on OpenAlexafffundabout
Débora Petry Moecke, Travis Holyk, Kristin L. Campbell, Kendall Ho, Pat G. Camp

Bibliographic record

VenuePhysiotherapy · 2025
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsUniversity of British Columbia HospitalUniversity of British ColumbiaSpinal Cord Injury BC
FundersCanadian Institutes of Health ResearchReseau canadien de recherche respiratoireUniversity of British Columbia
KeywordsTelerehabilitationDelphi methodPhysical therapyDelphiPhysical medicine and rehabilitationBest practiceMedicineTelemedicineComputer scienceHealth carePolitical scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Objectives This study aimed to develop best practice recommendations for physiotherapists providing telerehabilitation to First Nations people. Design Modified Delphi study. Participants Eighteen experts from four groups were selected: (a) physiotherapists who provide telerehabilitation to First Nations people, (b) Carrier Sekani Family Services leaders (CSFS, First Nations-led health organization/research partners), (c) telehealth experts from British Columbia (BC), Canada, and (d) First Nations individuals (end users) with experience in telerehabilitation. Methods Panelists rated recommendations on telehealth best practices in two rounds using an online questionnaire. Recommendations were synthesized from a scoping review and two qualitative studies. Each statement was rated on a four-point Likert scale indicating whether it was essential, useful, not useful, or unnecessary for inclusion in the best practices. Statements endorsed by ≥80% of panel members were considered for inclusion in the final document. Results Following the Delphi process, 77 recommendations covering foundational components, information technology utilization, professional expertise, therapeutic relationships, cultural safety, and the telehealth visit were validated for inclusion in the policy document. Participants also validated the methodology. Conclusion The recommendations offer a valuable resource for continuing education and professional development, empowering physiotherapists to enhance their skills and competencies in delivering culturally competent telerehabilitation to the First Nations population. The adoption of these best practices ensures that First Nations people are getting the best standard of care, potentially enhancing uptake and experiences with telehealth. It also enables healthcare organizations and policymakers to monitor adherence to established standards and identify areas for improvement. Contribution of the Paper •This paper provides best practice recommendations for physiotherapists delivering telerehabilitation to First Nations people, addressing unique cultural aspects and virtual relationship building. •The study offers physiotherapists expert guidance to enhance the quality and cultural appropriateness of telerehabilitation services for First Nations populations. •The recommendations serve as a valuable resource for continuing education and professional development, enabling physiotherapists to deliver culturally competent and effective care. •These best practices facilitate accountability and quality assurance, helping healthcare organizations and policymakers monitor adherence to standards and identify areas for improvement.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.523
Threshold uncertainty score0.765

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.043
GPT teacher head0.462
Teacher spread0.419 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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".

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Citations0
Published2025
Admission routes3
Has abstractyes

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