Learning and acting on social conventions is problematic for low-literates and non-natives, causing problems with societal participation and citizenship. Using the Situated Cognitive Engineering method, requirements for the design of social conventions learning software are derived from demographic information, adult learning frameworks and ICT learning principles. Evaluating a sample of existing Dutch social conventions learning applications on these requirements shows that none of them meet all posed criteria. Finally, Virtual Reality is suggested as a possible future technology improvement.
I remember the last conversations my former colleague José and I had one year ago. At that time, we were working in a small art gallery owned and controlled by a private company. We were placed in different positions, but both of us felt trapped and enslaved by the system. José went to India many times to learn wisdom from the wise religious thinkers. After returning, he quit smoking and became a vegetarian. He now lives at the border between two small European countries.
MULTIFILE
Alongside the growing number of older persons, the prevalence of chronic diseases is increasing, leading to higher pressure on health care services. eHealth is considered a solution for better and more efficient health care. However, not every patient is able to use eHealth, for several reasons. This study aims to provide an overview of: (1) sociodemographic factors that influence the use of eHealth; and (2) suggest directions for interventions that will improve the use of eHealth in patients with chronic disease. A structured literature review of PubMed, ScienceDirect, Association for Computing Machinery Digital Library (ACMDL), and Cumulative Index to Nursing and Allied Health Literature (CINAHL) was conducted using four sets of keywords: “chronic disease”, “eHealth”, “factors”, and “suggested interventions”. Qualitative, quantitative, and mixed-method studies were included. Four researchers each assessed quality and extracted data. Twenty-two out of 1639 articles were included. Higher age and lower income, lower education, living alone, and living in rural areas were found to be associated with lower eHealth use. Ethnicity revealed mixed outcomes. Suggested solutions were personalized support, social support, use of different types of Internet devices to deliver eHealth, and involvement of patients in the development of eHealth interventions. It is concluded that eHealth is least used by persons who need it most. Tailored delivery of eHealth is recommended
