Hello everyone. My name is Rinku Mohan. Today we are going to discuss a topic that is increasingly significant in our rapidly changing world, the importance of digital inclusion for the aging population. This is closely related to my research on the digital exclusion of elderly inclusions, where we explore the challenges they face and the solutions needed to ensure no one is left behind the digital age. As life expectancy continues to rise around the world, the issue of aging has become more and more significant. This change brings both opportunities and challenges. The technology advancements have the power to transform lives, offering better living conditions and opportunities to connect socially. However, for many elderly individuals, navigating modern technologies can be a real challenge. The digital inclusion is crucial here by ensuring that everyone, regardless of their age, has access to and can use digital tools. Effectivity. We can promote social justice and equal development. It helps bridge gaps, foster connections, and improve the overall quality of the life of the. This research mainly focuses on the understanding of the digital divide among the elderly. We wanted to find out what causing all the others to struggle with technology, how their how this impact their lives, and why these challenges differ from one country to another. So the ultimate goal is to figure out ways to help them integrate better into today's digital world. And we explored three main questions. What is the current situation of the digital exclusion? How well are the older people able to use devices like smartphones, computers, and other digital tools? Secondly, what are the key reasons behind this difficulties? How do things like their income, health or age affect their ability to use technology? And how does this impact their everyday lives? And finally, how do these issues vary between different countries? Are all the peoples in wealthier countries facing the same struggles as those in the less wealthy ones? And by answering these questions, we hope to provide practical insights that can guide policies, programs, and community efforts to make the digital world more accessible for elderly, no matter where they live. Here is something interesting from the general knowledge about older age groups and their internet use. As people get older, their internet usage drops significantly. For example, in age groups like 45 to 54, 55 to 64 and 65, plus the number of internet users is about 10 percentage less compared to younger groups. This trend highlights how technology adoption becomes more of a challenge with age. Another point to note is the oldest dependency ratio the number of older people compared to the working age population in most countries except India. This ratio is above 50. This means that there are at least 50 older adults for every a hundred working a stupid For India, it's slightly lower at 37. Looking ahead. It is projected that by 2075, more than half the population in these countries will be senior citizens. This means that addressing the digital divide and preparing for an aging population will become more important in the future. For our research, we collected aging data from five high income countries and five lower and middle income countries. The higher income countries include United Kingdom Germany, Austria, France, Estonia, and the lower and middle income countries included India, Mexico, Brazil, Bulgaria, and Romania. We selected these countries to ensure a diverse representation of economic and cultural context. By comparing digital exclusion across these regions, we were able to see how challenges differ between the wealthier and less wealthy countries and gain deeper insights into the factors driving the digital divide. And we looked at the data from these sources over five years, from 2019 to 2023 to ensure we capture trends and changes over. Once we had the data, we analyzed it using various statistical methods. For example, principle component analysis, which help us to understand the key factors driving the digital exclusion and the test like five square and anova, which help us to find the patterns compared groups and see how digital exclusion varies between countries, income levels, and age. This combination of methods allowed us to identify the main barriers older adults face when using technology and how these challenges differ across the regions. This table Compass five higher income countries, Austria, Germany, France, Estonia, and uk focusing on population size, age, gender, and digital exclusion. The United Kingdom stands out with the largest group of participants while Austria has the smallest in terms of age, the median across all countries is the early seventies, but UK has a slightly younger population with a median age of 69. Gender wise, women are more represented in every country. Estonia, for example, has the highest proportion of women now when it comes to digital exclusion. Estonia and France has the highest rate around 30 percentage. While UK is doing much better with only 11 percentage of the population excluded. When we look at the age, the median across middle income countries ranges from 64 to 70 years with bacteria have the oldest group. The 55 to 64 group is the largest in most countries, especially in India and Mexico, where it accounts for nearly half the population. On the other hand, the 75 plus age group is much smaller, particularly in India and Mexico, where it's around 16 to 17 percentage. For gender, there is a fairly balanced split in most countries, though bras, Brazil has a slightly higher proportion of men at 55 percentage, while India and Mexico have more women at around 53 percentage, the most striking insight is digital exclusion in media. Which has the highest rate within staggering 91 percentage of the population display excluded highlighting a major challenge for connectivity. In contrast Mexico has the lowest exclusion rate at 33 percentage showing significant progress in digital access. Age and marital status are two key factors when it comes to digital exclusion. Let's start with age. Older age groups are significantly more likely to be digitally excluded, and this issue is even more pronounced in lower and middle income countries. In contrast, higher income countries tend to do a better job for including older populations in digital world. Now let's talk about merit status. Individuals without partners, whether single, divorced or widow without are more likely to be excluded. This 10 is noticeable in all countries, but the gap is much wider in middle income countries. So what does this mean overall? The most digitally excluded demographics are older adults and individuals without partners, and this is especially severe in middle income countries. These findings highlight the origin need for targeted efforts to close this digital divide. The factors affecting digital exclusion was identified using. A factor analysis which is a dimensional reduction technique used to identify the most important factors. And it suggests that three different factors are primarily causing digital exclusion among elderly, and among which socioeconomic factors highlight that the difference in country type education and math status are key socioeconomic drivers of digital exclusion. And the policy interventions targeting education and mal support can help bridge the digital gap. And the component two, which is health related issues, stress that the physical and health conditions are significant barriers to digital inclusion. And it suggests that the healthcare support systems that integrate digital literacy programs are necessary to bridge this gap. And the component three, which is age related limitations, emphasize the role of age and physical limitations in excluding individuals from the digital space, and it recommend age friendly technologies and accessibility enhancements. Variations of digital exclusion between higher income and middle income countries were identified by square test, and the result indicate that there is a strong association between country type and digital exclusion. This suggests that digital exclusion is not evenly distributed across countries and is strongly influenced by their economy classification. Higher income countries have better digital inclusion due to advanced infrastructure, affordability and widespread of digital literacy. The middle income countries face greater challenges included, including limited access to technology, poor infrastructure and affordability values, which amplify the digital exclusion rates. This slide presents the result of a I square test used to in investigate the relationship between age groups of different. It explores whether the age group significantly impacts digital inclusion or exclusion depending on the economy classification of the country. The highly significant Kai Square result confirms that age groups are associated with digital exclusion, and this association varies across higher and middle income countries. The older age groups in middle income countries are likely more affected by digital exclusion compared to en age groups or their counterparts in higher income countries. This could be due to lack of access to digital technologies, lower digital literacy among older operations, or infrastructure and affordability challenges in middle income countries. The ANO test was used to find the variation in the life satisfaction among digitally secured people in higher income countries. And result suggests that there is a significant difference in the variation of means across different countries. And the Austria has reported the higher rate for the displaced credit people, and the Estonia has got the lowest rating. Similarly while comparing the variation in the life satisfaction among the digitally excluded people in middle income countries, the Romania has got the highest rate, while the India has got the lowest rate for life satisfaction. To investigate the impact of digital exclusion and its interaction with country in terms of health rating, the two way an test was performed, and we can see that the digitally included people in all other countries, except Mexico is showing higher rating for health while comparing to the digitally excluded people. Final thought. The digital exclusion has many impacts, like it reduces access to essential services, social connections, and banking. Also, it affects quality of life of. The key findings include there are significant disparity in the digital exclusion rate between higher income countries and middle income countries where UK is having only 11 percentage and is having 91 percentage of people are digitally excluded, and the socioeconomic age related and health related challenges are found to be the primary con contributors of digital exclusion. And the successful programs like Austria's, digital Seniors, and India's Age digital literacy programs show promise, but it require expansion and tailored programs for rural areas and underserved demographics are also crucial. The recommendations include expand digital literacy programs to remote areas and include affordable devices and internet access, and focus on most excluded groups like 75 plus in higher income countries, and anger and early groups, inter middle income countries. Also encourage community based activities and public private collaborations to promote technology adoption. The future research should look into the cultural and healthcare related aspects of the digital exclusion and conduct longitudal studies to track progress and effectiveness of these interventions. Collaborative efforts, policy makers and organizations are essential to bridge the digital divide and support the elderly. Thank you all for joining me for the talk. I truly hope you found it valuable. It was a pleasure to share my insights on digital inclusion for elderly users. If you'd like to continue the conversation or collaborate in the future, please feel free to connect with me on LinkedIn. Also, if you would like to go further, please check out the research paper attached for a deeper dive into the findings. Looking forward to staying in touch and exploring new ideas together.