Test–retest reliability and responsiveness of a French Canadian Upper Limb Functional Index (ULFI-FC)
Bibliographic record
Abstract
PURPOSE: The Upper Limb Functional Index (ULFI) is a self-report questionnaire assessing activity limitations and participation restrictions resulting from an upper limb musculoskeletal disorder (MSD). A French Canadian version of the ULFI (ULFI-FC) has recently demonstrated good internal consistency, and convergent validity, as well as clinical applicability in a rehabilitation context where clinicians have important time constraints. This study aimed to examine the test-retest reliability and responsiveness of the ULFI-FC. METHODS: In order to study the ULFI-FC's responsiveness, 60 participants completed the ULFI-FC and a French Canadian version of the DASH (DASH-FC) twice at an interval of two to six weeks, based on the evolution of their upper limb MSD. Half of the sample also completed the ULFI-FC three days after the second assessment for the test-retest reliability analysis. RESULTS: The ULFI-FC demonstrated high test-retest reliability (ICC = 0.92-0.97) and good internal responsiveness (Cohen's d = 0.49-0.62; standardized responsive means = 0.60-0.88). External responsiveness was further supported by moderate correlations of change scores with the DASH-FC (r = 0.42-0.64). CONCLUSIONS: Study findings support the use of the ULFI-FC in rehabilitation as an outcome measure to monitor activity limitations and participation restrictions among French-speaking patients presenting with upper limb MSD. IMPLICATIONS FOR REHABILITATION: The ULFI-FC is a reliable and valid tool with good responsiveness to change for assessing activity limitations and participation restrictions in adults presenting with upper limb musculoskeletal disorders. This tool can thus be useful in clinical and research settings. By exploring meaningful activities that are affected by patients' upper limb musculoskeletal disorders, the tool's Patient Specific Index is particularly relevant for clinicians adhering to a patient-centered approach.
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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 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".