MétaCan
Menu
Back to cohort
Record W4417457946 · doi:10.1186/s40900-025-00827-8

Gross motor functional classification for arthrogryposis multiplex congenita: protocol for co-development involving public with lived and professional experience

2025· article· en· W4417457946 on OpenAlexaff
Lauren C. Hyer, Susan Sienko, Cathleen E. Buckon, Daniel Natera‐de Benito, Maureen Donohoe, Kristen Donlevie, Melissa Emblin, Alicja Fąfara, Noémi Dahan‐Oliel

Bibliographic record

VenueResearch Involvement and Engagement · 2025
Typearticle
Languageen
FieldMedicine
TopicNeurogenetic and Muscular Disorders Research
Canadian institutionsShriners Hospitals for Children - CanadaUniversité de MontréalMcGill University Health Centre
Fundersnot available
KeywordsArthrogryposis multiplex congenitaArthrogryposisGross motor skillConstruct (python library)Construct validityMedical diagnosisReliability (semiconductor)Protocol (science)Delphi method

Abstract

fetched live from OpenAlex

BACKGROUND: Children with arthrogryposis multiplex congenita (AMC), a group of over 400 conditions characterized by congenital joint contractures, present with a wide range of gross motor functioning and mobility due to the heterogeneity of underlying diagnoses and physical involvement. Existing classification systems for AMC focus primarily on etiology and anatomical distribution but do not describe differences in gross motor functioning. In contrast, condition-specific functional classification systems have improved communication, treatment planning, and research by stratifying individuals based on functional ability. To date, no such classification system exists for AMC. This study aims to co-develop and evaluate the Gross Motor Functional Classification for Arthrogryposis Multiplex Congenita (GMFC-AMC), a condition-specific tool to support clinical and research needs. METHODS: This multi-phase study involves stakeholders with lived and professional experience in AMC from multiple countries. Phase 1 includes the initial drafting of the GMFC-AMC by an expert panel. In Phase 2, nominal group techniques are used to refine the draft. Phase 3 employs Delphi surveys to achieve international consensus on relevance, clarity, and comprehensibility. In Phase 4, the GMFC-AMC is translated and culturally adapted into French and Spanish following a structured cross-cultural adaptation process. Finally, Phase 5 evaluates reliability and construct validity across three languages. Inter-rater and test-retest reliability will be examined using video ratings of children with AMC. Construct validity will be assessed through correlations with established measures, including the Gillette Functional Assessment Questionnaire and the Pediatric Evaluation of Disability Inventory – Computer Adaptive Test. DISCUSSION: The GMFC-AMC will address a critical gap in functional classification for children and youth with AMC by providing a standardized language for describing gross motor functioning. By engaging international stakeholders throughout the development process and ensuring rigorous testing of its psychometric properties, the GMFC-AMC is expected to be a reliable, valid, and meaningful tool across diverse clinical and cultural contexts. This classification will facilitate clearer communication, improve care planning, and enable stratification for future longitudinal and interventional studies in AMC populations. TRIAL REGISTRATION: Clinical trial number not applicable.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.622
Threshold uncertainty score0.901

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.449
GPT teacher head0.494
Teacher spread0.045 · 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 designNot applicable
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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueResearch Involvement and EngagementSame topicNeurogenetic and Muscular Disorders ResearchFrench-language works237,207