What question did this study set out to answer?

This study aims to evaluate the effectiveness of an AI-assisted educational course on drug allergy knowledge among non-specialists in various economies.

January 23, 2026Open Access

Bridging Global Disparities in Drug Allergy Through AI ‐Assisted Training for Non‐Specialists: Findings From the Multinational ADAPT ‐2 Course

Key Points

This study aims to evaluate the effectiveness of an AI-assisted educational course on drug allergy knowledge among non-specialists in various economies.
Non-allergist physicians participated in a standardized drug allergy educational course.
Training was delivered through AI-assisted video localization in Mandarin.
Knowledge and confidence were assessed pre-and post-training.
Subgroup analyses compared results between advanced and emerging economies.
Baseline knowledge (53.5% ± 17.2%) and confidence (47.5% ± 22.7%) scores were low.
Emerging economy participants showed lower initial knowledge compared to advanced economy participants (49.1% vs. 70.1%; p < 0.001).
Post-training knowledge improved significantly to 72.5% (p < 0.001) and confidence to 71.3% (p < 0.001) across all groups.
AI-assisted delivery was as effective as the English course and received high participant satisfaction (98.9% clarity).

Abstract

ABSTRACT Background Mislabelled drug allergy (DA) remains a global public health challenge. A prior randomised trial (ADAPT) demonstrated that an intensive educational course improved DA knowledge and confidence among non‐specialists. However, ADAPT was restricted to English‐speaking participants and its generalisability remains unknown. To address this, a multinational implementation study expanding ADAPT (ADAPT‐2) was performed. Methods Non‐allergist physicians from Colombo (Sri Lanka), Guangzhou and Shenzhen (Mainland China), Hong Kong (Special Administrative Region of China) and Perth (Australia) completed a standardised DA educational course. In Mainland China, training was delivered via AI‐assisted video localisation (converted into Mandarin while preserving the speaker's voice with lip‐synced adaptation). DA knowledge, confidence and practice were assessed before and after completion. Subgroup analyses compared pre–post changes between Advanced Economies (AE: Australia, Hong Kong) and Emerging Economies (EE: Mainland China, Sri Lanka). Results Of 181 participants, overall baseline knowledge (53.5% ± 17.2%) and confidence (47.5% ± 22.7%) scores were suboptimal. EE participants had a lower knowledge level than AE (49.1% ± 15.5% vs. 70.1% ± 12.7%; p 0.05) and achieved high participant satisfaction (98.9% as ‘somewhat clear’ or better in clarity). Conclusions Deficits in DA knowledge persist widely among non‐specialists, with marked disparities between AE and EE. ADAPT‐2 bridged these gaps by universal improvements in both DA knowledge and confidence. AI‐assisted training represents a scalable, equitable strategy for global implementation of standardised and evidence‐based DA education. Trial Registration ADAPT: NCT06399601

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Cite This Study

Mak et al. (Tue,) studied this question.

synapsesocial.com/papers/69730f34c8125b09b0d1ef54 https://doi.org/https://doi.org/10.1111/cea.70213

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