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Record W4281627983 · doi:10.3138/ptc-2021-0039

Remotely Supervised Exercise Programmes to Improve Balance, Mobility, and Activity Among People with Moderate to Severe Traumatic Brain Injury: Description and Feasibility

2022· article· en· W4281627983 on OpenAlexafffundvenue
Jennifer O’Neil, Mary Egan, Shawn Marshall, Martin Bilodeau, Luc G. Pelletier, Heidi Sveistrup

Bibliographic record

VenuePhysiotherapy Canada · 2022
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversity of OttawaBruyère
FundersCanadian Institute for Military and Veteran Health ResearchUniversity of Ottawa
KeywordsTelerehabilitationPhysical therapyVideoconferencingRehabilitationMedicineTraumatic brain injuryPhysical medicine and rehabilitationBalance (ability)TelemedicineHealth careMultimediaComputer sciencePsychiatry

Abstract

fetched live from OpenAlex

Purpose: Further investigation into the feasibility of using videoconferencing and activity tracking devices to provide high-intensity home-based exercise programmes for people with a moderate or severe traumatic brain injury (TBI) is needed to inform clinical implementation and patient adoption. This study aimed to (1) determine if home-based telerehabilitation exercise programmes were feasible for people with a moderate or severe TBI and (2) better understand the lived experience of people with a TBI and their family partners with this programme. Methods: A mixed-methods approach consisting of measures of feasibility and semi-structured interviews was used. Five participants with moderate to severe TBI and their family partners completed two high-intensity home-based exercise programmes delivered remotely by a physiotherapist (i.e., daily and weekly). Results: Telerehabilitation services in home-based settings were feasible for this population. Adherence and engagement were high. Dyads were satisfied with the use of technology to deliver physiotherapy sessions. Conclusion: Telerehabilitation provides a delivery option that allows people with TBI to spend energy on therapy rather than on travelling. A pre-programme training on key components, such as the use of technology, safety precautions, and communication methods, likely improved the overall feasibility. Further research is needed to better understand the effectiveness of such a programme on balance, mobility, and physical activity levels.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.719
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.033
GPT teacher head0.312
Teacher spread0.280 · 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 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

Citations9
Published2022
Admission routes3
Has abstractyes

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