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Record W4412006942 · doi:10.2196/69660

Ethics and Equity Challenges in Telerehabilitation for Older Adults: Rapid Review

2025· review· en· W4412006942 on OpenAlexaffvenue
Mirella Veras, Louis-Pierre Auger, Jennifer Sigouin, Nahid Gheidari, Michelle Nelson, William C. Miller, Anne Hudon, Dahlia Kairy

Bibliographic record

VenueJMIR Aging · 2025
Typereview
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsUniversité de MontréalUniversity of British ColumbiaPublic Health OntarioLunenfeld-Tanenbaum Research InstituteUniversity of TorontoMontreal Neurological Institute and HospitalMcGill UniversityUniversity of ManitobaCentre for Interdisciplinary Research in Rehabilitation
Fundersnot available
KeywordsPreprintTelerehabilitationEquity (law)Coronavirus disease 2019 (COVID-19)GerontologyPsychologyMedicinePhysical medicine and rehabilitationPolitical scienceTelemedicineComputer scienceWorld Wide WebHealth careInfectious disease (medical specialty)Law

Abstract

fetched live from OpenAlex

Background: The integration of technology in rehabilitation is transforming health care delivery for older adults, especially through telerehabilitation, which addresses barriers to in-person care. Objective: This rapid review explores the ethical and equity concerns associated with telerehabilitation for older adults, focusing on challenges such as internet access, technology adoption, and digital literacy. Methods: Conducted according to Cochrane Rapid Review guidelines, this review used the Metaverse Equitable Rehabilitation Therapy framework, focusing on equity and ethics. Studies included telerehabilitation services for adults aged 55 years and older, published between 2010 and 2023. Screening was conducted independently by 2 researchers using Rayyan (Qatar Computing Research Institute, Hamad Bin Khalifa University), with full-text review by additional team members. Searches were performed in Medline and CINAHL. Results: From 323 papers retrieved, 49 studies met the inclusion criteria. The included studies were published between 2013 and 2023. Disparities in socioeconomic status, geographic location, and racial and ethnic backgrounds were found to impact telerehabilitation use. Additionally, ethical concerns around privacy, security, and autonomy were often inadequately addressed. Conclusions: This review emphasizes the need for culturally appropriate, accessible, and inclusive telerehabilitation services that integrate ethical and equity considerations into their design and delivery.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.624
Threshold uncertainty score0.932

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.211
GPT teacher head0.521
Teacher spread0.310 · 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 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

Citations12
Published2025
Admission routes2
Has abstractyes

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