JMIR Publications

ABSTRACT

Background:

Artificial intelligence (AI) is rapidly transforming healthcare by enhancing diagnostic accuracy, optimizing clinical workflows, and supporting decision‑making across virtually all health disciplines. As health systems worldwide integrate AI‑driven tools, educating future professionals about AI becomes a critical priority to ensure safe, ethical, and effective adoption. Despite growing evidence that health students recognize the importance of AI for their future practice, existing surveys measuring AI readiness and attitudes are only available in English, limiting their use in French-speaking settings. To bridge this gap and enable comparable, evidence‑based assessment of AI perceptions among French health students, rigorous cross‑cultural adaptation of validated instruments is essential.

Objective:

The aim of this study was to translate, culturally adapt, and linguistically validate five established English‑language questionnaires measuring health students’ perceptions of artificial intelligence for use across all French health training programs.

Methods:

We followed established cross‑cultural adaptation guidelines, including forward translation by two independent bilingual translators, reconciliation into a single French draft, and backward translation by a third bilingual translator. An expert panel reviewed all versions to ensure conceptual equivalence and adapt items for applicability across all health professions. Finally, cognitive testing was conducted with seven French health students to assess clarity and comprehension, with

Results:

During forward translation, wording discrepancies arose for 148 of 201 expressions (73.6%), yet only two items (<1%) required resolution due to meaning differences. In the backward translation step, 195 of 201 expressions (97.0%) were accurately rendered back into English; six items (3.0%) exhibited semantic discrepancies and were revised. Cognitive testing with seven French health students led to minor wording modifications in 48 of 201 expressions (23.9%) to improve clarity. All participants unanimously approved the final French versions of the five questionnaires.

Conclusions:

We produced five French‑language questionnaires that preserve conceptual equivalence with their English originals and that demonstrate strong content validity and linguistic clarity. These five questionnaires fill a critical gap for evaluating AI perceptions among French health students and support future psychometric testing and curriculum development.