Applying the UTAUT2 framework to patients' attitudes toward healthcare task shifting with artificial intelligence.

BACKGROUND: Increasing patient loads, healthcare inflation and ageing population have put pressure on the healthcare system. Artificial intelligence and machine learning innovations can aid in task shifting to help healthcare systems remain efficient and cost effective. To gain an understanding of patients' acceptance toward such task shifting with the aid of AI, this study adapted the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), looking at performance and effort expectancy, facilitating conditions, social influence, hedonic motivation and behavioural intention. METHODS: This was a cross-sectional study which took place between September 2021 to June 2022 at the National Heart Centre, Singapore. One hundred patients, aged ≥ 21 years with at least one heart failure symptom (pedal oedema, New York Heart Association II-III effort limitation, orthopnoea, breathlessness), who presented to the cardiac imaging laboratory for physician-ordered clinical echocardiogram, underwent both echocardiogram by skilled sonographers and the experience of echocardiogram by a novice guided by AI technologies. They were then given a survey which looked at the above-mentioned constructs using the UTAUT2 framework. RESULTS: Significant, direct, and positive effects of all constructs on the behavioral intention of accepting the AI-novice combination were found. Facilitating conditions, hedonic motivation and performance expectancy were the top 3 constructs. The analysis of the moderating variables, age, gender and education levels, found no impact on behavioral intention. CONCLUSIONS: These results are important for stakeholders and changemakers such as policymakers, governments, physicians, and insurance companies, as they design adoption strategies to ensure successful patient engagement by focusing on factors affecting the facilitating conditions, hedonic motivation and performance expectancy for AI technologies used in healthcare task shifting.

Increased double strand breaks in diabetic ß-cells with a p21 response that limits apoptosis.

DNA damage and DNA damage response (DDR) pathways in ß-cells have received little attention especially in the context of type-2 diabetes. We postulate that p21 plays a key role in DDR by preventing apoptosis, associated through its overexpression triggered by DNA stand breaks (DSBs). Our results show that ß-cells from chronic diabetic mice had a greater extent of DSBs as compared to their non-diabetic counterparts. Comet assays and nuclear presence of γH2AX and 53bp1 revealed increased DNA DSBs in 16 weeks old (wo) db/db ß-cells as compared to age matched non-diabetic ß-cells. Our study of gene expression changes in MIN6 cell line with doxorubicin (Dox) induced DNA damage, showed that the DDR was similar to primary ß-cells from diabetic mice. There was significant overexpression of DDR genes, gadd45a and p21 after a 24-hr treatment. Western blot analysis revealed increased cleaved caspase3 over time, suggesting higher frequency of apoptosis due to Dox-induced DNA strand breaks. Inhibition of p21 by pharmacological inhibitor UC2288 under DNA damage conditions (both in Dox-induced MIN6 cells and older db/db islets) significantly increased the incidence of ß-cell apoptosis. Our studies confirmed that while DNA damage, specifically DSBs, induced p21 overexpression in ß-cells and triggered the p53/p21 cellular response, p21 inhibition exacerbated the frequency of apoptosis.