Development of a Walking Safety Scale for Older Adults, Part I: Content Validity of the GEM Scale
Bibliographic record
Abstract
PURPOSE: The Grille d'évaluation de la sécurité à la marche (GEM scale) is a performance-based tool developed to fill the need for an objective assessment of walking safety for older adults. It underwent a three-phase process of content validation. METHOD: A mailed questionnaire was used to assess the representativeness of the walking items (5-point pertinence scale). Subsequently, two physiotherapist focus groups (n = 20) were held to further evaluate the relevance of the scale and the walking items. Finally, a pilot study was completed with 3 raters administering the GEM scale to 12 hospitalized patients. RESULTS: Comments and descriptive statistics (percentages) were analyzed from the questionnaire results and focus groups. On completion of the pilot study, which assessed 12 patients on the GEM scale, additional analyses were performed to address the theoretical background, the administration manual, the walking items, the scoring scale, and interpretation of the scale. Following each step, modifications were made to reflect the results of the analyses. CONCLUSION: The three-phase content-validation process demonstrated the relevance of this instrument and its representativeness as a walking safety assessment tool for older adults.
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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 | 0.010 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".