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Due to comprehensive social distancing measures related to the COVID-19 pandemic, medical faculties worldwide have made a virtue of necessity in resorting to online teaching. Medical faculties grapple with how to convey clinical competencies to students in this context. There is a need for research not only to map but also to explain the effect of these secondary measures on students' learning and mental wellbeing. During a period of ongoing comprehensive social distancing measures in Germany, we translated a competency-based curriculum including obstetrics, paediatrics, and human genetics to an e-learning course based on online patient and teacher encounters. In our qualitative study on students' and teachers' views, we identify potential enablers and drivers as well as barriers and challenges to undergraduate medical education under lockdown. In summer 2020, we conducted six focus group interviews to investigate medical students' and teachers' perspectives, experiences and attitudes. All focus groups were videotaped, transcribed verbatim and coded. To guide our deductive and inductive analysis, we applied the theoretical framework of Regmi and Jones. Content analysis was performed in a multi-perspective group. We identified five major themes contributing to a successful use of clinical competency-based e-learning under lockdown: Communication (with teachers, students, and patients), Mental wellbeing, Structure and self-organization, Technical issues, and Learning and commitment. We discuss enablers and potential barriers within all themes and their overlap and link them in an explanatory model. In our setting, students and teachers find e-learning holds strong potential and especially in times of COVID-19 it is greatly appreciated. We broaden the understanding of the impact of distant learning on acquiring competencies, on attitudes, and on mental wellbeing. Our model may serve for a thoughtful, necessary transition to future e-learning and hybrid programs for a competency-based medical education with ongoing social distancing measures.

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The highest genetic type 1 diabetes risk is conferred by HLA class II haplotypes defined by alleles at the HLA-DR and -DQ loci. The combination of HLA-DQA1*03:01 and DQB1*03:02 alleles (summarized as ‘HLA-DQ8′) is reported to be among the two most prevalent HLA class II haplotypes in Caucasian type 1 diabetes patients. This classification is based on conventional genotyping of exon 2 of the DQ gene locus and excludes exon 3. In this study, HLA genotyping on the type 1 diabetes susceptibility loci HLA-DRB1, DQA1 and DQB1 was performed using a high-resolution next generation sequencing method. In addition to the routinely examined exon 2, exon 3 was also sequenced. Samples from 229 children with type 1 diabetes were included and compared to a cohort of 9,786 controls. In addition to previously described HLA-DQ haplotypes in type 1 diabetes patients, we found that as well as HLA-DQA1*03:01,HLA-DQA1*03:03 also contributed to HLA-DQ8. HLA-DQA1*03:03 differs from HLA-DQA1*03:01 by one nucleotide substitution in exon 3 at position 160, leading to a single amino acid replacement. DRB1*04:05 was exclusively associated with DQA1*03:03 whereas the DRB1*04:01 haplotype comprised either DQA1*03:01 or DQA1*03:03. Significantly increased type 1 diabetes risk was confirmed for all these haplotypes with only minor differences between DQA1*03:01 and DQA1*03:03 alleles. This study identified the HLA-DQA1*03:03 allele as an addition to the already known type 1 diabetes risk haplotypes, and can contribute to more precise HLA genotyping approaches.