Nurturing a Digital Learning Environment for Adults 55+

Being digitally competent means having competences in all areas of DigComp: Information and data literacy, Communication and collaboration, Digital content creation, Safety and Problem-solving. More than other demographic categories, adults 55+ have a wide range of levels of digitalization. Depending on their level of competences, individuals may join self-administered online courses to improve their skills, or they may need guidance from adult educators. Taking into consideration the above situation and willing to address adult learners regardless of their initial skill levels, the proposed educational programme is carefully designed for both: self-administrated and educator-led training. It comprises five totally innovative courses that can be separately taught or can be integrated into a complex programme delivered by adult education organizations. These courses are the result of an ERASMUS+ project “Digital Facilitator for Adults 55+”. Chapter 1 introduces the methodology for designing attractive and engaging educational materials for adults’ digital skills improvement. The methodology clarifies the inputs, the development process and the expected results. An ample explanation of the five phases of the 5E instructional strategy is presented to help adult educators build a sequence of coherent and engaging learning stages. With this approach, learners are supported to think, work, gather ideas, identify their own skill levels and needs, analyse their progress, and communicate with others under the guidance of educators. Following up on the proposed methodology, in Chapter 2 researchers from Formative Footprint (Spain), TEAM4Excellence (Romania), Voluntariat Pentru Viata (Romania) and Saricam Halk Egitimi Merkezi (Turkey) developed five course modules in line with the DIGCOMP - Digital Competence Framework for Citizens. These modules address the competence areas of information and data literacy, communication and collaboration, digital content creation, safety, and problem-solving. Each course module comprises digital textbooks, videos, interactive activities and means for evaluation developed using the 5E instructional model strategy. Understanding that accessibility is one of the main components of lifelong learning education, Chapter 3 of the manual provides an overview of the integration of educational materials, tools, instruments, video tutorials as well as DIFA55+ web app in the digital educational ecosystem. Finally, the authors formulate recommendations for usability and transferability that go beyond individuals, ensuring that educational materials are user-friendly and effective while making it easier to apply successful pedagogical approaches in other complementary educational contexts or projects.Grant Agreement—2021-1-RO01-KA220-ADU-000035297, Digital Facilitator for Adults 55

The relationship between serum asymmetric dimethylarginine levels and subjective sleep quality in normotensive patients with type 2 diabetes mellitus

Background/Aims: Poor sleep quality (SQ) is associated with increased cardiovascular mortality and morbidity. Additionally, asymmetric dimethylarginine (ADMA) is an independent predictor of cardiovascular mortality and morbidity. However, no sufficient data regarding the relationship between ADMA levels and SQ have been reported. The goal of the current study was to evaluate the association between SQ and ADMA levels in normotensive patients with type 2 diabetes mellitus. Methods: The study participants consisted of 78 normotensive type 2 diabetics. The SQ of all participants was assessed using the Pittsburgh Sleep Quality Index (PSQI). Patients with a global PSQI score > 5 were defined as "poor sleepers." Factors associated with poor SQ were analyzed using a multiple regression model. Serum ADMA levels were measured using high performance liquid chromatography. Results: The median ADMA levels of the poor sleepers were increased compared with patients defined as good sleepers (5.5 [4.2 to 6.6] vs. 4.4 [2.9 to 5.4], p < 0.01, respectively). However, the L-arginine/ADMA ratio was decreased in poor sleepers (p < 0.01). Global PSQI scores were positively correlated with ADMA levels (p < 0.01) and negatively correlated with the L-arginine/ADMA ratio (p = 0.02). ADMA levels were correlated with sleep latency (p < 0.01) and sleep efficiency (p = 0.01). Logistic regression analysis showed that ADMA levels (odds ratio [OR], 1.68; 95% confidence interval [CI], 1.16 to 2.44; p = 0.01) and body mass index (OR, 1.15; 95% CI, 1.01 to 1.31; p = 0.04) were associated with poor SQ independently of glomerular filtration rate, sex, age, duration of diabetes, hemoglobin A1c, total cholesterol, and systolic blood pressure. Conclusions: Self-reported SQ was independently associated with ADMA levels in normotensive patients with diabetes mellitus