Artificial Intelligent Technologies and Elderly: Decoding the Stimuli towards the Artificial Intelligent Technology Adoption
Keywords:
Elderly, AI-based Technology, Innovations, Technology Adoption.Abstract
Technology has overtaken our lives, and we are bounded by the immense layers of digital and technology. It makes our lives easy-going and convenient, but it is far more complicated for those who cannot even imagine getting used to such an environment and are unfamiliar with them. Here the study gives a broad understanding of the insight of the elderly towards innovative, intelligent technologies. It also explores and explores the stimuli that motivate and encourage them to adopt AI-based advanced technologies. The study used a quantitative approach and applied Structural Equation Modelling to validate and establish the identified constructs. A total of 238 respondents were considered for the study. The findings will enable both the researchers and the practitioners to broaden their vision and acknowledge that technological innovations are possible across cohorts.
Downloads
References
Advani, V. (2020). What is Artificial Intelligence? How do AI work and the future of it? GreatLearning.
Anderson, M. and Perrin, A. (2017). Tech Adoption Climbs Among Older Adults —Pew Research Center: Internet, Science & Tech.
Arenas Gaitán, J., Peral Peral, B. and Ramón Jerónimo, M.Á. (2015). Elderly and Internet Banking: An Application of UTAUT2. 20(1), pp.1–23. Available at: https://idus.us.es/handle/11441/57220.
BANTZ, CR (1982). EXPLORING USES AND GRATIFICATIONS. Communication
Research, 9(3), pp.352–379.
Chen, K.Y., Harniss, M., Patel, S. and Johnson, K. (2013). Implementing technology-based embedded assessment in the home and community life of individuals ageing with disabilities: a participatory research and development study. Disability and Rehabilitation: Assistive Technology, 9(2), pp.112–120.
Cialdini, RB (2007). Influence, the Psychology of Persuasion. New York: Harper Business.
Davis, F.D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), pp.319–340.
Demiris, G., Thompson, H., Boquet, J., Le, T., Chaudhuri, S. and Chung, J. (2012). Older adults’ acceptance of a community-based telehealth wellness system. Informatics for Health and Social Care, 38(1), pp.27–36.
Department of Economics and Social Welfare, (2019). World Population Ageing. New York: United nations, pp.1–64.
Dupuy, L., Consel, C. and Sauzéon, H. (2016). Self-determination-based design to achieve acceptance of assisted living technologies for older adults. Computers in Human Behavior, 65, pp.508–521.
Elueze, I. and Quan-Haase, A. (2018). Privacy Attitudes and Concerns in the Digital Lives of Older Adults: Westin’s Privacy Attitude Typology Revisited. American Behavioral Scientist, 62(10), pp.1372–1391.
Feng, H., Fawaz, K. and Shin, K.G. (2017). Continuous Authentication for Voice Assistants. Proceedings of the 23rd Annual International Conference on Mobile Computing and Networking - MobiCom ’17.
Fischinger, D., Einramhof, P., Papoutsakis, K., Wohlkinger, W., Mayer, P., Panek, P., Hofmann, S., Koertner, T., Weiss, A., Argyros, A. and Vincze, M. (2016). Hobbit, a care robot supporting independent living at home: First prototype and lessons learned. Robotics and Autonomous Systems, 75, pp.60–78.
Flanagin, A. and Metzger, M. (2006). Internet use in the contemporary media environment. Human Communication Research, 27(1), pp.153–181.
Francis, J., Ball, C., Kadylak, T. and Cotten, S.R. (2019). Ageing in the Digital Age: Conceptualizing Technology Adoption and Digital Inequalities. In: Ageing and Digital Technology. pp.35–49.
Garg, V., Camp, L.J., Lorenzen-Huber, L., Shankar, K. and Connelly, K. (2013). Privacy concerns in assisted living technologies. annals of telecommunications - annales des télécommunications, 69(1-2), pp.75–88.
Ghosh, M. (2019). Analyzing the Engagement and Attitude of Elderly Towards Digital Platforms in India. Journal of Creative Communications, 14(3), pp.214–234.
Giger, J.T., Pope, ND, Vogt, H.B., Gutierrez, C., Newland, L.A., Lemke, J. and Lawler, M.J. (2015). Remote patient monitoring acceptance trends among older adults residing in a frontier state. Computers in Human Behavior, 44, pp.174–182.
Githens, Rod.P. (2007). ―Older adults and e-learning: Opportunities and Barriers‖ by Rod P. Githens. Quarterly Review of Distance Education, [online] 8(4), pp.329–338.
Gliem, J. A. & Gliem, R. R., (2003). Calculating, Interpreting, and Reporting Cronbach’s Alpha Reliability Coefficient for Likert-type Scales. Ohio State University, Columbus, s.n., pp. 82-88.
Hair, J., Black, W., Babin, B. and Anderson, R. (2010). MULTIVARIATE DATA ANALYSIS A Global Perspective. [online] Prentice Hall.
Heerink, M., Kröse, B., Evers, V. and Wielinga, B. (2009). Relating conversational expressiveness to social presence and acceptance of an assistive social robot. Virtual reality, 14(1), pp.77–84.
Hoy, M.B. (2018). Alexa, Siri, Cortana, and More: An Introduction to Voice Assistants. Medical Reference Services Quarterly, 37(1), pp.81–88.
Hu. L (2019). Grandma’s Robot: How AI Is Revolutionizing Elder Care.
Katz E, Blumler, J.G. and Gurevitch, M. (1974). Utilization of mass communication by the individual. The uses of mass communications: Current perspectives on gratifications research, pp.19–32.
Kowalski, J., Jaskulska, A., Skorupska, K., Abramczuk, K., Biele, C., Kopeć, W. and Marasek, K. (2019). Older Adults and Voice Interaction. Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems.
Leung, L. and Wei, R. (1998). The gratifications of pager use: sociability, information- seeking, entertainment, utility, and fashion and status. Telematics and Informatics, 15(4), pp.253–264.
Lombard, M., Ditton, T., Villanova, U., Crane, D., Davis, B., Gil-Egui, G., Horvath, K. and Rossman, J. (2000). Measuring Presence: A Literature-based Approach to the Development of a Standardized Paper-and-Pencil Instrument.
Luijkx, K., Peek, S. and Wouters, E. (2015). ―Grandma, You Should Do It—It’s Cool‖ Older Adults and the Role of Family Members in Their Acceptance of Technology. International Journal of Environmental Research and Public Health, [online] 12(12), pp.15470–15485.
MacKenzie, S.B. and Podsakoff, P.M. (2012). Common Method Bias in Marketing: Causes, Mechanisms, and Procedural Remedies. Journal of Retailing, 88(4), pp.542–555.
Martin, J., Mortimer, G. and Andrews, L. (2015). Re-examining online customer experience to include purchase frequency and perceived risk. Journal of Retailing and Consumer Services, 25, pp.81–95.
McLean, G., Al-Nabhani, K. and Wilson, A. (2018). Developing a Mobile Applications
Customer Experience Model (MACE)- Implications for Retailers. Journal of Business Research, 85, pp.325–336.
Ministry of Statistics and Programme Implementation (2017). Government of India | Ministry of Statistics and Programme Implementation | MOSPI.
Moon, Y. (2000). Intimate Exchanges: Using Computers to Elicit Self‐Disclosure from Consumers. Journal of Consumer Research, 26(4), pp.323–339.
Osei-Frimpong, K. and McLean, G. (2018). Examining online social brand engagement: A social presence theory perspective. Technological Forecasting and Social Change, 128, pp.10–21.
Perakakis, E., Mastorakis, G. and Kopanakis, I. (2019). Social Media Monitoring: An Innovative Intelligent Approach. Designs, [online] 3(2), p.24. Available at: https://www.mdpi.com/2411-9660/3/2/24/pdf.
Pecina, J.L., Vickers, K.S., Finnie, D.M., Hathaway, J.C., Hanson, G.J. and Takahashi, P.Y. (2011). Telemonitoring Increases Patient Awareness of Health and Prompts Health-Related Action: Initial Evaluation of the TELE-ERA Study. Telemedicine and e-Health, 17(6), pp.461–466.
Peek, S.T.M., Luijkx, K.G., Rijnaard, M.D., Nieboer, M.E., van der Voort, C.S., Aarts, S., van Hoof, J., Vrijhoef, H.J.M. and Wouters, E.J.M. (2015). Older Adults’ Reasons for Using Technology while Aging in Place. Gerontology, 62(2), pp.226–237.
Pino, M., Boulay, M., Jouen, F. and Rigaud, A.S. (2015). ―Are we ready for robots that care for us?‖ Attitudes and opinions of older adults toward socially assistive robots. Frontiers in Aging Neuroscience, 7.
Rauschnabel, P.A., He, J. and Ro, Y.K. (2018). Antecedents to the adoption of augmented reality smart glasses: A closer look at privacy risks. Journal of Business Research, 92, pp.374–384.
Rauschnabel, P.A., Rossmann, A. and tom Dieck, M.C. (2017). An adoption framework for mobile augmented reality games: The case of Pokémon Go. Computers in Human Behavior, 76, pp.276–286.
Reeder, B., Demiris, G. and Marek, K.D. (2013). Older adults’ satisfaction with a medication dispensing device in-home care. Informatics for Health and Social Care, [online] 38(3), pp.211–222.
Rese, A., Baier, D., Geyer-Schulz, A. and Schreiber, S. (2017). How augmented reality apps are accepted by consumers: A comparative analysis using scales and opinions. Technological
Forecasting and Social Change, 124, pp.306–319.
Risse, M. (2019). Human Rights and Artificial Intelligence: An Urgently Needed Agenda. Human Rights Quarterly, 41(1), pp.1–16.
Ruggiero, T.E. (2000). Uses and Gratifications Theory in the 21st Century. Mass Communication and Society, 3(1), pp.3–37.
Saracchini, R., Ortega, C.C. and Bordoni, L. (2015). A Mobile Augmented Reality Assistive Technology for the Elderly. Comunicar. Media Education Research Journal, 23(2)
Sayago, S., Neves, B.B. and Cowan, B.R. (2019). Voice assistants and older people. Proceedings of the 1st International Conference on Conversational User Interfaces - CUI ’19.
Schuitema, G., Anable, J., Skippon, S. and Kinnear, N. (2013). The role of instrumental, hedonic and symbolic attributes in the intention to adopt electric vehicles. Transportation Research Part A: Policy and Practice, 48, pp.39–49.
Shrestha, L.B. (2000). Population Ageing In Developing Countries. Health Affairs, 19(3), pp.204–212.
Tseng, K.C., Hsu, C.-L. and Chuang, Y.H. (2013). Designing an Intelligent Health Monitoring System and Exploring User Acceptance for the Elderly. Journal of Medical Systems, 37(6).
United Nations (2019). World Population Ageing 2019. Available at: https://www.un.org/en/development/desa/population/publications/pdf/ageing/WorldPopulatio nAgeing2019-Report.pdf.
van Hoof, J., Kort, H.S.M., Rutten, P.G.S. and Duijnstee, M.S.H. (2011). Ageing-in-place with the use of ambient intelligence technology: Perspectives of older users. International Journal of Medical Informatics, 80(5), pp.310–331.
Vaziri, D.D., Aal, K., Ogonowski, C., Von Rekowski, T., Kroll, M., Marston, H.R., Poveda, R., Gschwind, Y.J., Delbaere, K., Wieching, R. and Wulf, V. (2016). Exploring user experience and technology acceptance for a fall prevention system: results from a randomized clinical trial and a living lab. European Review of Aging and Physical Activity, 13(1).
Venkatesh, V. and Bala, H. (2008). Technology Acceptance Model 3 and a Research Agenda on Interventions. Decision Sciences, 39(2), pp.273–315.
Venkatesh, V. and Davis, F.D. (2000). A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Management Science, [online] 46(2), pp.186–204. Available at: https://www.jstor.org/stable/2634758?seq=1.
Venkatesh, V., Morris, M.G., Davis, G.B. and Davis, F.D. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, [online] 27(3), pp.425– 478.
Wang, S., Bolling, K., Mao, W., Reichstadt, J., Jeste, D., Kim, H.-C. and Nebeker, C. (2019). Technology to Support Aging in Place: Older Adults’ Perspectives. Healthcare, 7(2), p.60.
Waycott, J., Vetere, F. and Ozanne, E. (2019). Building Social Connections: A Framework for Enriching Older Adults’ Social Connectedness Through Information and Communication Technologies. In: Ageing and Digital Technology. pp.65–82.
Wu, J.H., Wang, S.C. and Tsai, H.H. (2010). Falling in love with online games: The uses and gratifications perspective. Computers in Human Behavior, 26(6), pp.1862–1871.
Downloads
Published
How to Cite
Issue
Section
License
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.
