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Record W4251574846 · doi:10.2196/preprints.31305

What we learned about using telerehabilitation combined with exergames, from clinicians and chronic stroke survivors: A multiple case study (Preprint)

2021· preprint· en· W4251574846 on OpenAlexaboutno aff
Dorra Rakia Allegue, Dahlia Kairy, Johanne Higgins, Philippe Archambault, François Michaud, William C. Miller, Shane N. Sweet, Michel Tousignant

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsnot available
Fundersnot available
KeywordsTelerehabilitationRehabilitationStroke (engine)MedicineIntervention (counseling)Physical therapyMotivational interviewingTelemedicineChronic strokePhysical medicine and rehabilitationTelehealthNursingHealth care

Abstract

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BACKGROUND In Canada, chronic stroke survivors have difficulty accessing community-based rehabilitation services, due to lack of resources. VirTele, a personalized remote rehabilitation program combining virtual reality exergames and telerehabilitation, was developed to offer chronic stroke survivors the opportunity to pursue rehabilitation of their affected upper extremity (UE) at home, while receiving ongoing monitoring by a clinician. OBJECTIVE The objectives of this study were to: 1) Explore the determinants of VirTele use among chronic stroke survivors and clinicians; 2) Identify indicators of support of psychological needs by clinicians, during VirTele intervention; and 3) explore indicators of empowerment among stroke survivors. METHODS This multiple case study involved three chronic stroke survivors participating in a VirTele intervention and their respective clinicians (physiotherapists). VirTele is a two-month remote rehabilitation intervention, using non immersive virtual reality exergames and telerehabilitation aimed at improving UE deficits in chronic stroke survivors. Study participants had autonomous access to Jintronix exergames, which they were asked to use 5 times a week for 30 minutes periods. VirTele also included videoconference sessions with a clinician, 1 to 3 times a week (1-hour duration), using the Reacts application. During these sessions, the clinician was able to engage in motivational interviewing, supervise the stroke survivors’ use of the exergames and monitor the use of the affected UE through activities of daily life. Semi-directed interviews were conducted 4 to5 weeks after the end of the VirTele intervention. Two interview guides, adapted for clinicians and stroke survivors respectively, were developed to facilitate the interview administration while allowing new codes to emerge. All interviews were audiotaped and transcribed verbatim. RESULTS Three stroke survivors (2 females and 1 male), with a mean age of 58.8 years (SD=19,4), and two physiotherapists participated in the study. Five major determinants of VirTele use emerged from the qualitative analyses, namely the technology performance (usefulness, perception of exergames), effort (ease of use), entourage support (encouragement), facilitators (stroke survivors’ safety, trust and understating of instructions), and challenges (miscommunication, exergames limits). At the end of the VirTele intervention, both clinicians demonstrated support of psychological needs, in terms of autonomy, competence and relatedness, all of which were reflected as empowerment indicators in the three-stroke survivors. Lessons learned from using telerehabilitation combined with exergames were provided, which will be relevant to other researchers and transferable to other populations and contexts. CONCLUSIONS This multiple case study provided a first glimpse at the impact that motivational interviewing can have on adherence to exergames and behavior modification of UE use in stroke survivors. Five major determinants of VirTele use have been identified, namely technology performance, effort, entourage support, facilitators and challenges. Lessons learned from these determinants may serve as a model to guide the implementation of similar interventions. INTERNATIONAL REGISTERED REPORT RR2-10.2196/14629

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)0.004
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0090.003
Scholarly communication0.0050.005
Open science0.0020.003
Research integrity0.0050.003
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 head0.040
GPT teacher head0.329
Teacher spread0.289 · 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 designQualitative
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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Citations1
Published2021
Admission routes1
Has abstractyes

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