Psychometric properties of functional mobility outcome measures in children with arthrogryposis multiplex congenita
Bibliographic record
Abstract
AIM: To establish the construct validity, agreement, and minimal important difference (MID) of widely used mobility measures in arthrogryposis multiplex congenita (AMC). METHOD: Participants (n = 248, 126 males, mean age 10 years 10 months, standard deviation 3 years 11 months) with AMC were assessed using the Functional Mobility Scale (FMS), Gillette Functional Assessment Questionnaire (FAQ), Functional Independence Measure for Children (WeeFIM), and Patient-Reported Outcomes Measurement Information System (PROMIS). Convergent and discriminant validity were evaluated using Spearman's rank correlations, while known-groups validity was examined using analysis of variance. Cohen's kappa and distribution-based methods were used to estimate agreement and MIDs respectively. RESULTS: Robust convergent (ρ = 0.66-0.82, 95% confidence interval [CI] 0.54-0.86) and discriminant (ρ = 0.06-0.31, 95% CI -0.11 to 0.43) validity were found for all four mobility measures. Known-groups validity was supported by significant mean differences across AMC subtypes (amyoplasia, distal arthrogryposis, central nervous system/syndromic; p < 0.001). The measures also showed weak to good agreement in classifying mobility. A difference of one and two levels on the FMS and FAQ respectively, was found to be minimally important. For the PROMIS and WeeFIM, estimated MID values were 3.19 to 4.34 and 14.24 respectively. INTERPRETATION: The robust construct validity, agreement, and MIDs provide clinicians and researchers with evidence-based benchmarks for assessing mobility in children with AMC.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".