Development of a French-Canadian version of the Life-Space Assessment (LSA-F): content validity, reliability and applicability for power mobility device users
Bibliographic record
Abstract
PURPOSE: To examine the measurement properties of the French-Canadian version of the Life-Space Assessment questionnaire (LSA-F) for power mobility device (PMD) users. METHODS: Content validity, test-retest reliability of telephone interviews (2-week interval) and applicability were examined with PMD users presenting neurological, orthopedic or medically complex conditions. Translation/back-translation from English to French and cultural adaptation was performed and pretested with five bilingual users. Test-retest reliability was examined with 40 French-speaking users, age 50 and over, who had been using a subsidized PMD for 2-15 months. Audio-taped interviews were coded to judge content validity and applicability. RESULTS: Content validity results confirmed equivalent meaning for most questions. The test-retest reliability was excellent for the composite score (intra-class correlation coefficient = 0.87) and revealed moderate to substantial concordance for 18/20 items (k = 0.47-0.73; P(a) > 57.5%). The applicability of the LSA-F is satisfactory considering an acceptable burden of assessment, low refusal of the telephone interview format (8%; n = 4), reasonable administration time (9.2 +/- 3.9 min) and a normally distributed composite score. CONCLUSIONS: The LSA-F is a valid measure with regards to its content, stable over a period of 2 weeks and applicable for a population of middle-aged and older French-Canadian speaking adults who use PMDs.
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".