Experience of undergraduate nursing students participating in artificial intelligence + project task driven learning at different stages: a qualitative study.

BACKGROUND: Artificial intelligence is a growing phenomenon that will soon facilitate wide-scale changes in many professions, and is expected to play an important role in the field of medical education. This study explored the realistic feelings and experiences of nursing undergraduates participating in different stages of artificial intelligence + project task driven learning, and provide a basis for artificial intelligence participation in nursing teaching. METHODS: We conducted face-to-face semi-structured interviews with nursing undergraduates participating in Nursing Research Course which adopts artificial intelligence + project task driven learning from a medical university in Ningxia from September to November 2023, to understand their experience of using artificial intelligence for learning and the emotional changes at different stages. The interview guide included items about their personal experience and feelings of completing project tasks through dialogue with artificial intelligence, and suggestions for course content. Thematic analysis was used to analyze interview data. This study followed the COREQ checklist. RESULTS: According to the interview data, three themes were summarized. Undergraduate nursing students have different experiences in participating in artificial intelligence + project task driven learning at different stages, mainly manifested as diverse emotional experiences under initial knowledge deficiency, the individual growth supported by external forces during the adaptation period, and the expectations and suggestions after the birth of the results in the end period. CONCLUSIONS: Nursing undergraduates can actively adapt to the integration of artificial intelligence into nursing teaching, dynamically observe students' learning experience, strengthen positive guidance, and provide support for personalized teaching models, better leveraging the advantages of artificial intelligence participation in teaching.

Dietary diversity, diet quality, and oxidative stress in older adults.

This cross-sectional study aimed to explore the relationship between diet quality, dietary diversity, and oxidative stress levels in older adults in parts of the Ningxia Hui Autonomous Region in northwestern China. A total of 335 participants voluntarily participated in the study from April to July 2021. Laboratory tests and questionnaires were used to obtain general characteristics, dietary conditions, and indicators of oxidative stress. The dietary diversity scores of the participants were 5.20±1.39, the diet quality indices were 56.91±11.14, and most had poor diet quality. The levels of the oxidative stress markers malondialdehyde, superoxide dismutase, 8-iso-prostaglandin F2α, and total antioxidant capacity were 4.77±1.77, 40.33±9.85, 763.10±245.41, and 1.02±0.14, respectively. The results showed that the diet quality scores of participants were related to dietary diversity and whether the scores passed or not was significantly related to total antioxidant capacity.

Two-decade reconstruction of algal blooms in China's Lake Taihu.

The algal blooming in the inland lakes has become a critically important issue for its impacts not only on local natural and social environments, but also on global human community. However, the occurrences of blooming on larger spatial scale and longer time scale have rarely been studied. As the third largest freshwater lake in China, Lake Taihu has drawn increasing attention from both public and scientific communities concerning its degradation. Using available satellite images, we reconstructed the spatial and temporal patterns of algal blooms in Lake Taihu through the pasttwo decades. The blooming characteristics over the past two decades were examined with the dynamic of initial blooming date being highlighted. The initial blooming dates were gradually becoming later and later from 1987 to 1997. Since 1998, however, the initial blooming date came earlier and earlier year by year, with approximately 11.42 days advancement per year. From 1987 to 2007, the annual duration of algal blooms lengthened year by year, in line with the substantial increases in the occurrences of algal blooms in spring and summer months. The algal blooms usually occur in northern bays and spread to center and south parts of Lake Taihu. The increases in previous winter's mean daily minimum temperature partially contributed to the earlier blooming onset. However, human activities, expressed as total gross domestic product (GDP) and population, outweighed the climatic contribution on the initial blooming date and blooming duration. This study may provide insights for the policy makers who try to curb the algal blooming and improve the water quality of inland freshwater lakes.