Spanish language version of the "Medical Quality Video Evaluation Tool" (MQ-VET): Cross-cultural AI-supported adaptation and validation study.

Abstract

Background: The Medical Quality Video Evaluation Tool (MQ-VET) is a standardized instrument for assessing health-related video quality, yet it is only available in English. This study addresses the growing demand for a Spanish version to better support the increasing Spanish-speaking population seeking reliable digital health content.

Objective: To adapt and validate the MQ-VET into Spanish, ensuring robust psychometric reliability and validity through rigorous cross-cultural adaptation methods, augmented by the integration of artificial intelligence (AI) tools.

Materials and methods: Following international guidelines, the MQ-VET was translated, back-translated, and reviewed by experts. AI-based tools were employed to refine linguistic and cultural accuracy. Psychometric properties were evaluated by 60 participants (30 healthcare and 30 nonhealthcare professionals), focusing on reliability, agreement, and concurrent validity with the DISCERN instrument.

Results: The Spanish MQ-VET showed excellent reliability (Cronbach's alpha>0.90, ICC=0.81) and strong concurrent validity (Pearson r = 0.9435, Spearman r = 0.9482, p < 0.0001), alongside with a robust linear regression result (R²=0.8902). Bland-Altman analysis confirmed a robust agreement, and AI-driven tools performed the factorial analysis that revealed a clear three-factor structure explaining 81.1% of the variance.

Conclusions: The Spanish MQ-VET is a reliable and valid instrument for assessing the quality of health-related videos, applicable to both healthcare professionals and individuals outside the healthcare field. Leveraging AI-driven methodologies, it serves as a robust resource for enhancing digital health literacy and promoting critical appraisal of video content among Spanish-speaking populations.