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Record W4213020369 · doi:10.1186/s40900-022-00336-y

Expert guidance for the rehabilitation of children with arthrogryposis: protocol using an integrated knowledge translation approach

2022· article· en· W4213020369 on OpenAlexafffund
Noémi Dahan‐Oliel, Sarah Cachecho, Alicja Fąfara, Francis Lacombe, Ani Samargian, André Bussières

Bibliographic record

VenueResearch Involvement and Engagement · 2022
Typearticle
Languageen
FieldMedicine
TopicNeurogenetic and Muscular Disorders Research
Canadian institutionsCentre de réadaptation Lethbridge-Layton-MackayMcGill UniversityShriners Hospitals for Children - Canada
FundersFonds de Recherche du Québec - Santé
KeywordsKnowledge translationRehabilitationArthrogryposis multiplex congenitaPsychosocialMedicineDelphi methodInternational Classification of Functioning, Disability and HealthArthrogryposisMedical educationPhysical therapyKnowledge managementPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Arthrogryposis multiplex congenita (AMC) is a group of rare congenital disorders characterized by multiple joint contractures present at birth. Contractures can affect different body areas and impact activities of daily living, mobility and participation. Although early rehabilitation is crucial to promote autonomy and participation in children with AMC, empirical evidence to inform best practice is scarce and clinical expertise hard to develop due to the rarity of AMC. Preliminary research involving stakeholders in AMC (youth with AMC, parents, and clinicians) identified priorities in pediatric rehabilitation. Scoping reviews on these priorities showed a lack of high quality evidence related to rehabilitation in AMC. The objective of this project is to provide rehabilitation expert guidance on the assessment and treatment of children with AMC in the areas of muscle and joint function, pain, mobility and self-care, participation and psychosocial wellbeing. METHODS: An integrated knowledge translation approach will be used throughout the project. Current rehabilitation practices in AMC will be identified using a clinician survey. Using the Grading of Recommendations, Assessment, Development and Evaluations framework (GRADE) approach, a panel of interdisciplinary expert clinicians, patient and family representatives, and researchers will develop expert guidance on the assessment and treatment for pediatric AMC rehabilitation based on findings from the scoping reviews and survey results. Consensus on the guidance statements will be sought using a modified Delphi process with a wider panel of international AMC experts, and statements appraised using the Appraisal of Guidelines for Research and Evaluation II (AGREE II) tool. Theoretical facilitators and barriers toward implementing clinical guidance into practice will be identified among rehabilitation clinicians and managers to inform the design of dissemination and implementation strategies. DISCUSSION: This multi-phase project will provide healthcare users and providers with research-based, expert guidance for the rehabilitation of children with AMC and will contribute to family-centered practice.

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)0.004
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.742
Threshold uncertainty score0.540

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.285
GPT teacher head0.443
Teacher spread0.158 · 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 designOther design
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

Citations10
Published2022
Admission routes2
Has abstractyes

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