Adaptation, Cross-Cultural Validation and Assessment of Measurement Properties of the French-Canadian Version of the Knowledge, Comfort, Approach and Attitude Towards Sexuality Scale (KCAASS) for Use in Stroke Rehabilitation
Bibliographic record
Abstract
This study aimed to adapt and translate the Knowledge, Comfort, Approach and Attitude towards Sexuality Scale (KCAASS) for stroke rehabilitation clinicians who are Canadian French speakers and to determine its measurement properties. The KCAASS was adapted for stroke rehabilitation by three occupational therapists and translated into Canadian French using a back-translation process. After being pretested, the resulting KCAASS-Stroke-FrCan was disseminated to seven rehabilitation centers in Quebec, Canada. Exploratory factor analysis, Cronbach alphas, intraclass correlation coefficients (ICCs), standard error of measurement (SEM), and minimal detectable change (MDC) were computed. 199 clinicians participated. Factor analysis revealed a four-factor solution. Internal consistency for the total score (α = 0.942) and subscales “Knowledge” (α = 0.834), “Comfort” (α = 0.966), and “Approach” (α = 0.836) were very good, and critical for “Attitude” (α = 0.628). Test–retest reliability was very good (0.81; p < 0.001) for the total score, good for “Knowledge” (0.69; p < 0.001) and “Comfort” (0.74; p < 0.001), very good for “Approach” (0.82; p < 0.001), and poor for “Attitude” (0.37; p = 0.003). SEM and MDC were presented. The KCAASS-Stroke-FrCan showed good measurement properties to assess stroke rehabilitation clinicians’ training needs and educational interventions.
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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 | 0.021 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 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) | 0.002 | 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".