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Record W4360985150 · doi:10.3389/fresc.2023.1139432

TelereHUB-CHILD: An online integrated knowledge translation tool to optimize telerehabilitation evidence-based practices for children with disabilities and their families

2023· article· en· W4360985150 on OpenAlexafffund
Tatiana Ogourtsova

Bibliographic record

VenueFrontiers in Rehabilitation Sciences · 2023
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsMcGill UniversityCentre for Interdisciplinary Research in RehabilitationJewish Rehabilitation Hospital
FundersCentre for Interdisciplinary Research in RehabilitationMcGill University
KeywordsTelerehabilitationKnowledge translationPresentation (obstetrics)Medical educationPsychologyRehabilitationEvidence-based practiceMedicineHealth careMultimediaTelemedicineKnowledge managementComputer scienceAlternative medicinePhysical therapy

Abstract

fetched live from OpenAlex

Background Pediatric telerehabilitation has been quickly adopted by clinicians during the pandemic. This precipitated shift in the model of healthcare delivery is significant and compounded by clinicians' training and knowledge needs related to evidence-based practices. This instigated a knowledge translation initiative TelereHUB-CHILD—an online platform designed for clinicians, patients, and families. The aim of this brief report is to describe its development, including the roles of key stakeholders in these processes. Methods Following a systematic review on telerehabilitation, a series of co-creation activities with clinical ( n = 24 rehabilitation professionals) and parent-partners ( n = 4 parents of children with disabilities) were undertaken. Clinical partners were engaged in five web-activities. These were designed to gather their feedback regarding training and knowledge needs, present preliminary findings of the systematic review and explore their perceived importance and usefulness with respect to different sections of TelereHUB-CHILD, including Tele-treatments , Tele-Assessments , and Resources . Parent-partners were engaged asynchronously to provide feedback on the content and presentation of the Patient/Family Information section. Results Clinical partners reported moderate-high usefulness and importance with each section of the tool and the presented features. As per partners' feedback, the Tele-treatments section provides standardized summaries outlining the effectiveness of the tele-treatment approach and the level of the evidence for each outcome of interest, according to the different diagnosis groups and professional discipline. For patients/family, common questions and answers can be explored in three user-friendly formats, including printable learning briefs, onsite accordions, and animation videos. The Tele-assessments section outlines existing measures by professional discipline. Resources offer preparatory forms for families and clinicians, questionnaires, and other learning material. Conclusion TelereHUB-CHILD was co-developed with key stakeholders. It can guide telerehabilitation evidence-based practices, empower patients and families, and pinpoint research and practice gaps.

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)0.003
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.418
Threshold uncertainty score0.875

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.145
GPT teacher head0.409
Teacher spread0.264 · 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
Published2023
Admission routes2
Has abstractyes

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