Clinical and experimental allergy : journal of the British Society for Allergy and Clinical Immunology · 2026
Bridging Global Disparities in Drug Allergy Through AI-Assisted Training for Non-Specialists: Findings From the Multinational ADAPT-2 Course.
СтатьяМногоцентровое исследованиеНазвание и аннотация: Перевод в очереди
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Mak Hugo W F, Meng Juan, Chung Freya K L, Lee Jasmine T Y, Aberathna Inoka Sepali, Amarasekara Uvini, Ranasinghe Thushali N D, Jayamali Jeewantha, Yang Qintai, Zhou Min, Chen Liang, Huang Jin-Xian, Shi Weihong, Kulkarni Rishabh, Peter Jonny Grant, Trubiano Jason A, Jeewandara Kamal Chandima, Lucas Michaela, Li Philip H
Аннотация
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 < 0.001). Following ADAPT-2, both knowledge (72.5% ± 16.0%, p < 0.001) and confidence (71.3% ± 17.5%, p < 0.001) scores significantly improved across all groups. ADAPT-2 delivered by AI-assisted video localisation was non-inferior to the English course in effectiveness (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.
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 < 0.001). Following ADAPT-2, both knowledge (72.5% ± 16.0%, p < 0.001) and confidence (71.3% ± 17.5%, p < 0.001) scores significantly improved across all groups. ADAPT-2 delivered by AI-assisted video localisation was non-inferior to the English course in effectiveness (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.