Adaptation, cross-cultural validation, and assessment of measurement properties of the French-Canadian version of the Determinants of Implementation Behavior Questionnaire (DIBQ) for use regarding sexual health services in stroke rehabilitation
Bibliographic record
Abstract
BACKGROUND: Clinicians report that numerous personal and environmental factors affect their ability to address sexuality in their practice. However, no validated tool in any language exists to assess these factors. OBJECTIVES: To translate and cross-culturally validate the Determinants for Implementation Behavior Questionnaire (DIBQ) to sexual health (SH) services for Canadian French speaking stroke rehabilitation clinicians and assess its measurement properties. METHODS: The DIBQ was adapted for sexual health services and translated into Canadian French using a back-translation process. The resulting DIBQ-SH was pretested, improved, and was then sent to clinicians of seven rehabilitation centers in Quebec, Canada, for testing. Exploratory factor analysis, Cronbach's alpha, intraclass correlation coefficients (ICC), standard error of measurement (SEM), minimal detectable change (MDC), and floor and ceiling effects analysis were computed. RESULTS: A sample of 184 clinicians completed the DIBQ-SH. Factor analysis revealed a six-factor solution explaining 55.2% of the variance. Internal consistency for the total score (α = 0.94) and subscales "Capabilities" (α = 0.91), "Support and resources" (α = 0.87), "Emotions" (α = 0.83), "Planning and delivery" (α = 0.85), "Beliefs" (α = 0.83), and "Motivation" (α = 0.78) was considered "good" to "very good." Test-retest reliability was "good" for the total score and 5/6 subscales (ICC = 0.79-0.88), excluding the "Beliefs" subscale, which was "critical" (ICC = 0.59). SEM and MDC were also presented. CONCLUSION: The DIBQ-SH showed good measurement properties for assessing factors that influence provision of sexual health services among French Canadian speaking clinicians who provide services to persons with stroke.
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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 | 0.016 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".