Ethics and acceptance of smart homes for older adults

References

• ONS. Overview of the UK population: November 2018; 2018. Available from: http://www.ons.gov.uk/ons/rel/pop-estimate/population-estimates-for-uk–england-and-wales–scotland-and-northern-ireland/mid-2014/sty—overview-of-the-uk-population.html
   Google Scholar
• Shahrestani S. (2017) Aging, Disability, and Assistive Internet of Things. In: Internet of Things and Smart Environments. Springer, Cham. https://doi.org/https://doi.org/10.1007/978-3-319-60164-9_1
   Google Scholar
• Organisation WH. Global health and aging; 2011. Available from: https://www.who.int/ageing/publications/global_health.pdf
   Google Scholar
• Ritchie R, Data: Hannah. Mortality risk of COVID-19 - Statistics and research;. Available from: https://ourworldindata.org/mortality-risk-covid
   Google Scholar
• org uk A. Dementia UK; 2014. Available from: https://www.alzheimers.org.uk/sites/default/files/migrate/downloads/dementia_uk_update.pdf
   Google Scholar
• Caul S Deaths registered weekly in England and Wales, provisional: week ending 25 September 2020. Office for National Statistics; 2020. Available from: https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/bulletins/deathsregisteredweeklyinenglandandwalesprovisional/latest#deaths-registered-by-age-group
   Google Scholar
• Ho FK, Petermann-Rocha F, Gray SR, Jani BD, Katikireddi SV, Niedzwiedz CL, Foster H, Hastie CE, Mackay DF, Gill JMR, et al. Is older age associated with COVID-19 mortality in the absence of other risk factors? General population cohort study of 470,034 participants. PloS One. 2020;15(11):e0241824. doi:https://doi.org/10.1371/journal.pone.0241824.
   PubMed Web of Science ®Google Scholar
• Rashidi P, Mihailidis A. A survey on ambient-assisted living tools for older adults. IEEE J Biomed Health Inf. 2013;17(3):579–90. doi:https://doi.org/10.1109/JBHI.2012.2234129.
   PubMed Web of Science ®Google Scholar
• P. Bruegger, A. Wilde and L. Guibert, “On the Development of a Resident Monitoring System: Usability, Privacy and Security aspects,” 2020 International Conferences on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics (Cybermatics), 2020, pp. 288–293. doi:https://doi.org/10.1109/iThings-GreenCom-CPSCom-SmartData-Cybermatics50389.2020.00062
   Google Scholar
• Cesta A, Cortellessa G, Fracasso F, Orlandini A, Turno M User needs and preferences on AAL systems that support older adults and their carers. J Ambient Intell Smart Environ. 2018 Jan;10(1):49–70. doi:https://doi.org/10.3233/AIS-170471.
   Web of Science ®Google Scholar
• P. Pirzada, N. White and A. Wilde, “Sensors in Smart Homes for Independent Living of the Elderly,“ 2018 5th International Multi-Topic ICT Conference (IMTIC), 2018, pp. 1–8. doi:https://doi.org/10.1109/IMTIC.2018.8467234
   Google Scholar
• Almeida A, Mulero R, Rametta P, Uroˇsevi´c V, Andri´c M, Patrono L. A critical analysis of an IoT—aware AAL system for elderly monitoring. Future Gener Comput Syst. 2019;97:598–619. Available from http://www.sciencedirect.com/science/article/pii/S0167739X18321769
   Web of Science ®Google Scholar
• H. Ghayvat, S. Mukhopadhyay, B. Shenjie, A. Chouhan and W. Chen, “Smart home based ambient assisted living: Recognition of anomaly in the activity of daily living for an elderly living alone,” 2018 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), 2018, pp. 1–5. doi:https://doi.org/10.1109/I2MTC.2018.8409885
   Google Scholar
• M. Ziefle and C. Röcker, “Acceptance of pervasive healthcare systems: A comparison of different implementation concepts,” 2010 4th International Conference on Pervasive Computing Technologies for Healthcare, 2010, pp. 1–6. doi:https://doi.org/10.4108/ICST.PERVASIVEHEALTH2010.8915
   Google Scholar
• Arthanat S, Wilcox J, Macuch M. Profiles and predictors of smart home technology adoption by older adults. OTJR Occup Particip Health. 2019;39(4):247–56. Available from. doi:https://doi.org/10.1177/1539449218813906. PMID: 30477397.
   PubMed Web of Science ®Google Scholar
• Lau J Building a national technology and innovation infrastructure for an aging society; 2005. Available from: https://dspace.mit.edu/handle/1721.1/38566
   Google Scholar
• Liu L, Stroulia E, Nikolaidis I, Cruz A, R´ıos-rinc´on AM. Smart homes and home health monitoring technologies for older adults: a systematic review. Int J Med Inform. 2016 Apr;91:44–59. doi:https://doi.org/10.1016/j.ijmedinf.2016.04.007.
   PubMed Web of Science ®Google Scholar
• Kavandi H, Jaana M. Factors that affect health information technology adoption by seniors: a systematic review. Health Soc Care Community. 2020;28(6):1827–42. Available from https://onlinelibrary.wiley.com/doi/abs/10.1111/hsc.13011
   PubMed Web of Science ®Google Scholar
• Ienca M, Wangmo T, Jotterand F, Kressig R, Elger B Ethical design of intelligent assistive technologies for dementia: a descriptive review; 2017. Available from: https://dspace.mit.edu/handle/1721.1/38566
   Google Scholar
• A. V. Dhukaram, C. Baber, L. Elloumi, B. van Beijnum and P. De Stefanis, “End-User perception towards pervasive cardiac healthcare services: Benefits, acceptance, adoption, risks, security, privacy and trust,” 2011 5th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth) and Workshops, 2011, pp. 478–484. doi:https://doi.org/10.4108/icst.pervasivehealth.2011.246116
   Google Scholar
• Fischer AJ, Dart EH, Leblanc H, Hartman KL, Steeves RO, Gresham FM. An investigation of the acceptability of videoconferencing within a School-based behavioral consultation framework. Psychol Sch. 2016;53(3):240–52. Available from https://onlinelibrary.wiley.com/doi/abs/10.1002/pits.21900
   Web of Science ®Google Scholar
• Ownsworth T, Theodoros D, Cahill L, Vaezipour A, Quinn R, Kendall M, Moyle W, Lucas K. Perceived usability and acceptability of videoconferencing for delivering community-based rehabilitation to individuals with acquired brain injury: a qualitative investigation. J Int Neuropsycholl Society. 2020;26(1):47–57. doi:https://doi.org/10.1017/S135561771900078X.
   PubMed Web of Science ®Google Scholar
• Stahl JE, Dixon RF. Acceptability and willingness to pay for primary care videoconferencing: a randomized controlled trial. J Telemed Telecare. 2010;16(3):147–51. doi:https://doi.org/10.1258/jtt.2009.090502.
   PubMed Web of Science ®Google Scholar
• Davis FD. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 1989;13(3):319–40. doi:https://doi.org/10.2307/249008.
   Web of Science ®Google Scholar
• Venkatesh V, Davis FD. A theoretical extension of the technology acceptance model: four longitudinal field studies. Manage Sci. 2000;46(2):186–204. doi:https://doi.org/10.1287/mnsc.46.2.186.11926.
   Web of Science ®Google Scholar
• Venkatesh V, Morris MG, Davis GB, Davis FD. User acceptance of information technology: toward a unified view. MIS Q. 2003;27(3):425–78. doi:https://doi.org/10.2307/30036540.
   Web of Science ®Google Scholar
• Fishbein M, Ajzen I. Belief, attitude, intention, and behavior: an introduction to theory and research. Addisson-Wesley; 1977. https://people.umass.edu/aizen/f&a1975.html
   Google Scholar
• Davis FD, Bagozzi RP, Warshaw PR. Extrinsic and intrinsic motivation to use computers in the workplace. J Appl Soc Psychol. 1992;22(14):1111–32. doi:https://doi.org/10.1111/j.1559-1816.1992.tb00945.x.
   Web of Science ®Google Scholar
• Ajzen I, et al. The theory of planned behavior. Organ Behav Hum Decis Process. 1991;50(2):179–211.
   Web of Science ®Google Scholar
• University of Western Ontario National Centre for Management Research, Development. Personal computing: towards a conceptual model of utilization. London (Ont.): National Centre for Management Research and Development; 1989.
   Google Scholar
• Rogers EM. Diffusion of Innovations. Marketing/Social science / The Free Press. Free Press; 1995. Available from https://books.google.co.uk/books?id=LpkPAQAAMAAJ
   Google Scholar
• Bandura A. Social foundations of thought and action. Englewood Cliffs, NJ. 1986;1986:23–28.
   Google Scholar
• Venkatesh V, Thong JY, Xu X. Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS Q. 2012;36(1):157–78. doi:https://doi.org/10.2307/41410412.
   Web of Science ®Google Scholar
• Goodhue DL, Thompson RL. Task-technology fit and individual performance. MIS Q. 1995;19(2):213–36. doi:https://doi.org/10.2307/249689.
   Web of Science ®Google Scholar
• Brown SA, Venkatesh V. Model of adoption of technology in households: a baseline model test and extension incorporating household life cycle. MIS Q. 2005;29(3):399–426. doi:https://doi.org/10.2307/25148690.
   Web of Science ®Google Scholar
• Venkatesh V, Brown SA. A longitudinal investigation of personal computers in homes: adoption determinants and emerging challenges. MIS Q. 2001;25(1):71–102. doi:https://doi.org/10.2307/3250959.
   Web of Science ®Google Scholar
• Golant SM. A theoretical model to explain the smart technology adoption behaviors of elder consumers (Elderadopt). J Aging Stud. 2017;42:56–73. Available from https://www.sciencedirect.com/science/article/pii/S0890406517302517
   PubMed Web of Science ®Google Scholar
• Mashal I, Shuhaiber A, Daoud M. Factors influencing the acceptance of smart homes in Jordan. Int J Electron Marketing Retailing. 2020;11(2):113–42. doi:https://doi.org/10.1504/IJEMR.2020.106842.
   Google Scholar
• Angioni M, Musso F. New perspectives from technology adoption in senior cohousing facilities. TQM J. 2020;32(4):761–77. doi:https://doi.org/10.1108/TQM-10-2019-0250.
   Google Scholar
• Conci M, Pianesi F, Zancanaro M Useful, social and enjoyable: mobile phone adoption by older people. In: IFIP Conference on Human-Computer Interaction. Springer; 2009. p. 63–76. https://doi.org/https://doi.org/10.1007/978-3-642-03655-2_7
   Google Scholar
• McCloskey DW. The importance of ease of use, usefulness, and trust to online consumers: an examina- tion of the technology acceptance model with older customers. JOEUC. 2006;18(3):47–65. doi:https://doi.org/10.4018/joeuc.2006070103.
   Google Scholar
• Guhr N, Werth O, Blacha PPH, Breitner MH. Privacy concerns in the smart home context. SN Appl Sci. 2020;2(2):247. doi:https://doi.org/10.1007/s42452-020-2025-8.
   Web of Science ®Google Scholar
• Pal D, Arpnikanondt C, Funilkul S, Razzaque MA Analyzing the adoption and diffusion of voice-enabled smart-home systems: empirical evidence from Thailand. Universal Access in the Information Society. 2020:1–19.
   Google Scholar
• Hong A, Nam C, Kim S. What will be the possible barriers to consumers’ adoption of smart home services? Telecomm Policy. 2020;44(2):101867. doi:https://doi.org/10.1016/j.telpol.2019.101867.
   Web of Science ®Google Scholar
• Shareef MA, Kumar V, Dwivedi YK, Kumar U, Akram MS, Raman R. A new health care system enabled by machine intelligence: elderly people’s trust or losing self control. Technol Forecast Soc Change. 2021;162:120334. Available from. doi:https://doi.org/10.1016/j.techfore.2020.120334.
   Web of Science ®Google Scholar
• Zhou J, Zhang B, Tan R, Tseng ML, Zhang Y. Exploring the systematic attributes influencing gerontechnology adoption for elderly users using a meta-analysis. Sustainability. 2020;12(7):2864. doi:https://doi.org/10.3390/su12072864.
   Web of Science ®Google Scholar
• Shuhaiber A, Mashal I, Alsaryrah O The role of smart homes’ attributes on users’ acceptance. In: 2019 International Conference on Electrical and Computing Technologies and Applications (ICECTA); 2019. p. 1–4. doi: https://doi.org/10.1109/ICECTA48151.2019.8959592
   Google Scholar
• Pal D, Funilkul S, Charoenkitkarn N, Kanthamanon P. Internet-of-things and smart homes for elderly healthcare: an end user perspective. IEEE Access. 2018;6:10483–96. doi:https://doi.org/10.1109/ACCESS.2018.2808472.
   Web of Science ®Google Scholar
• A. Shuhaiber, I. Mashal and O. Alsaryrah, “Smart Homes as an IoT Application: Predicting Attitudes and Behaviours,” 2019 IEEE/ACS 16th International Conference on Computer Systems and Applications (AICCSA), 2019, pp. 1–7. doi:https://doi.org/10.1109/AICCSA47632.2019.9035295
   Google Scholar
• Pal D, Papasratorn B, Chutimaskul W, Funilkul S. Embracing the smart-home revolution in Asia by the elderly: an end-user negative perception modeling. IEEE Access. 2019;7:38535–49. doi:https://doi.org/10.1109/ACCESS.2019.2906346.
   Web of Science ®Google Scholar
• Sen A. Inequality reexamined. Oxford University Press; 1992. Available at: https://books.google.co.uk/books?id=LOLnCwAAQBAJ
   Google Scholar
• Nikou S, Agahari W, Keijzer-Broers W, De Reuver M. Digital healthcare technology adoption by elderly people: a capability approach model. Telematics Inf. 2020;53:101315. doi:https://doi.org/10.1016/j.tele.2019.101315.
   Web of Science ®Google Scholar
• Marikyan D, Papagiannidis S, Alamanos E. Cognitive dissonance in technology adoption: a study of smart home users. Inf Syst Fronta J Res Innovation. 2020;1–23. doi:https://doi.org/10.1007/s10796-020-10042-3.
   Google Scholar
• Pal D, Triyason T, Funilkul S, Chutimaskul W. Smart homes and quality of life for the elderly: perspective of competing models. IEEE Access. 2018;6:8109–22. doi:https://doi.org/10.1109/ACCESS.2018.2798614.
   Web of Science ®Google Scholar
• Miskelly FG. Assistive technology in elderly care. Age Ageing. 2001;30(6):455–58. doi:https://doi.org/10.1093/ageing/30.6.455.
   PubMed Web of Science ®Google Scholar
• Van Hoof J, Kort HSM, Rutten PGS, Duijnstee MSH Ageing-in-place with the use of ambient intelligence technology: perspectives of older users. Int J Med Inform. 2011 May;80(5):310–31. doi:https://doi.org/10.1016/j.ijmedinf.2011.02.010.
   PubMed Web of Science ®Google Scholar
• Bailey C, Foran TG, Ni Scanaill C, Dromey B. Older adults, falls and technologies for independent living: a life space approach. Ageing Soc. 2011;31(5):829–48. doi:https://doi.org/10.1017/S0144686X10001170.
   Google Scholar
• Chou HK, Yan SH, Lin IC, Tsai MT, Chen CC, Woung LC, et al. A pilot study of the telecare medical support system as an intervention in dementia care: the views and experiences of primary caregivers. J Nurs Res. 2012;20(3):169–80. doi:https://doi.org/10.1097/jnr.0b013e318263d916.
   PubMedGoogle Scholar
• Doyle J, Bailey C, Dromey B, Scanaill CN. BASE - An interactive technology solution to deliver balance and strength exercises to older adults. In: 2010 4th International Conference on Pervasive Computing Technologies for Healthcare; 2010. p. 1–5. doi: https://doi.org/10.4108/ICST.PERVASIVEHEALTH2010.8881
   Google Scholar
• Uzor S, Baillie L, Skelton D. Senior designers: empowering seniors to design enjoyable falls rehabilitation tools. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. CHI ’12. New York, NY, USA: Association for Computing Machinery; 2012. p. 1179–88. doi:https://doi.org/10.1145/2207676.2208568.
   Google Scholar
• Al-Shaqi R, Mourshed M, Rezgui Y. Progress in ambient assisted systems for independent living by the elderly. SpringerPlus. 2016;5(1):624. doi:https://doi.org/10.1186/s40064-016-2272-8.
   PubMedGoogle Scholar
• Vassli LT, Farshchian BA. Acceptance of health-related ICT among elderly people living in the community: a systematic review of qualitative evidence. Int J Hum Comput Interact. 2018;34(2):99–116. doi:https://doi.org/10.1080/10447318.2017.1328024.
   Web of Science ®Google Scholar
• Coughlin JF, D’Ambrosio LA, Reimer B, Pratt MR Older adult perceptions of smart home technologies: implications for research, policy & market innovations in healthcare. In: 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE; 2007. p. 1810–15. doi: https://doi.org/10.1109/IEMBS.2007.4352665
   Google Scholar
• George Demiris and Marjorie Skubic and Marilyn Rantz and James Keller and Myra Aud and Brian Hensel and Zhihai He. Smart Home Sensors for the Elderly: A Model for Participatory Formative Evaluation. Human-Computer Interaction. 2006 01;6. Available at: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.118.8266
   Google Scholar
• Robinson EL, Park G, Lane K, Skubic M, Rantz M. Technology for healthy independent living: creating a tailored in-home sensor system for older adults and family caregivers. J Gerontol Nurs. 2020;46(7):35–40. doi:https://doi.org/10.3928/00989134-20200605-06.
   PubMed Web of Science ®Google Scholar
• Lee C, Coughlin JF. Perspective: older adults’ adoption of technology: an integrated approach to identifying determinants and barriers. J Prod Innovation Manage. 2015;32(5):747–59. Available from https://onlinelibrary.wiley.com/doi/abs/10.1111/jpim.12176
   Web of Science ®Google Scholar
• Panico F, Cordasco G, Vogel C, Trojano L, Esposito A Ethical issues in assistive ambient living technologies for ageing well. Multimedia Tools and Applications. 2020 Jul. doi:https://doi.org/10.1007/s11042-020-09313-7.
   Google Scholar
• Burrows A, Coyle D, Gooberman-Hill R. Privacy, boundaries and smart homes for health: an ethnographic study. Health Place. 2018;50:112–18. doi:https://doi.org/10.1016/j.healthplace.2018.01.006.
   PubMed Web of Science ®Google Scholar
• Maan C, Gunawardana U Barriers in acceptance of ambient assisted living technologies among older Australians. In: 2017 IEEE Life Sciences Conference (LSC); 2017. p. 222–25. doi: https://doi.org/10.1109/LSC.2017.8268183.
   Google Scholar
• Kaasinen E, Kymäläinen T, Niemela¨ M, Olsson T, Kanerva M, Ikonen V. A user-centric view of intelligent environments: user expectations, user experience and user role in building intelligent environments. Computers. 2012 Dec;2(1):1–33. doi:https://doi.org/10.3390/computers2010001.
   Google Scholar
• Sovacool BK, Del Rio DDF. Smart home technologies in Europe: a critical review of concepts, benefits, risks and policies. Renewable Sustainable Energy Rev. 2020;120:109663. doi:https://doi.org/10.1016/j.rser.2019.109663.
   Web of Science ®Google Scholar
• Cannizzaro S, Procter R, Ma S, Maple C, Triberti S. Trust in the smart home: findings from a nationally representative survey in the UK. PLoS One. 2020;15(5):e0231615. doi:https://doi.org/10.1371/journal.pone.0231615.
   PubMed Web of Science ®Google Scholar
• Guo X, Zhang X, Sun Y The privacy-personalization paradox in MHealth services acceptance of different age groups. Electron Commer Rec Appl. 2016 Mar;16(C):55–65. doi:https://doi.org/10.1016/j.elerap.2015.11.001.
   Google Scholar
• Demiris G, Oliver DP, Dickey G, Skubic M, Rantz M Findings from a participatory evaluation of a smart home application for older adults. Technol Health Care. 2008 May;16(2):111–18. doi:https://doi.org/10.3233/THC-2008-16205.
   PubMedGoogle Scholar
• Rahimpour M, Lovell NH, Celler BG, McCormick J. Patients’ perceptions of a home telecare system. Int J Med Inform. 2008;77(7):486–98. doi:https://doi.org/10.1016/j.ijmedinf.2007.10.006.
   PubMed Web of Science ®Google Scholar
• Courtney K. Privacy and senior willingness to adopt smart home information technology in residential care facilities. Methods Inf Med. 2008 Feb;47(1):76–81. doi:https://doi.org/10.3414/ME9104.
   PubMed Web of Science ®Google Scholar
• Chernbumroong S, Atkins A, Yu H. Perception of smart home technologies to assist elderly people. In: 4th International Conference on Software, Knowledge, Information Management and Applications; 2010. p. 90–97. Available at: http://eprints.staffs.ac.uk/id/eprint/1163
   Google Scholar
• Wilkowska W, Ziefle M Perception of privacy and security for acceptance of E-health technologies: ex- ploratory analysis for diverse user groups. In: 2011 5th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth) and Workshops. IEEE; 2011. p. 593–600. doi: https://doi.org/10.4108/icst.pervasivehealth.2011.246027.
   Google Scholar
• Wilkowska W, Ziefle M. Privacy and data security in E-health: requirements from the user’s perspective. Health Informatics J. 2012 Sep;18(3):191–201. doi:https://doi.org/10.1177/1460458212442933.
   PubMed Web of Science ®Google Scholar
• Demiris G, Thompson H, Boquet J, Le T, Chaudhuri S, Chung J. Older adults’ acceptance of a community- based telehealth wellness system. Inform Health Soc Care. 2013;38(1):27–36. doi:https://doi.org/10.3109/17538157.2011.647938.
   PubMed Web of Science ®Google Scholar
• Reeder B, Chung J, Lazar A, Joe J, Demiris G, Thompson HJ. Testing a theory-based mobility monitoring protocol using in-home sensors: a feasibility study. Res Gerontol Nurs. 2013;6(4):253–63. doi:https://doi.org/10.3928/19404921-20130729-02.
   PubMed Web of Science ®Google Scholar
• Joe J, Chaudhuri S, Chung J, Thompson H, Demiris G. Older adults’ attitudes and preferences regarding a multifunctional wellness tool: a pilot study. Inform Health Soc Care. 2016;41(2):143–58. Available from. doi:https://doi.org/10.3109/17538157.2014.965305. PMID: 25325513.
   PubMed Web of Science ®Google Scholar
• Hoque R, Sorwar G. Understanding factors influencing the adoption of mHealth by the elderly: an extension of the UTAUT model. Int J Med Inform. 2017;101:75–84. doi:https://doi.org/10.1016/j.ijmedinf.2017.02.002.
   PubMed Web of Science ®Google Scholar
• Chung J, Demiris G, Thompson HJ, Chen KY, Burr R, Patel S, Fogarty J. Feasibility testing of a home-based sensor system to monitor mobility and daily activities in Korean American older adults. Int J Older People Nurs. 2017;12(1):e12127. doi:https://doi.org/10.1111/opn.12127.
   Web of Science ®Google Scholar
• Chung J, Thompson HJ, Joe J, Hall A, Demiris G. Examining Korean and Korean American older adults’ perceived acceptability of home-based monitoring technologies in the context of culture. Inform Health Soc Care. 2017;42(1):61–76. Available from. doi:https://doi.org/10.3109/17538157.2016.1160244. PMID: 27100664.
   PubMed Web of Science ®Google Scholar
• Etemad-Sajadi R, Santos GGD Senior citizens’ acceptance of connected health technologies in their homes. Int J Health Care Qual Assur. 2019 Oct;32(8):1162–74. doi:https://doi.org/10.1108/ijhcqa-10-2018-0240.
   PubMed Web of Science ®Google Scholar
• Reeder B, Chung J, Lyden K, Winters J, Jankowski CM. Older women’s perceptions of wearable and smart home activity sensors. Inform Health Soc Care. 2020;45(1):96–109. doi:https://doi.org/10.1080/17538157.2019.1582054.
   PubMed Web of Science ®Google Scholar
• Ashraf A, Liu JH, Rauf Q Aging population perception and post adoption behavior about the usability of smart home technology of Pakistani culture. In: Proceedings of 2020 the 6th International Conference on Computing and Data Engineering; 2020. p. 179–88. https://doi.org/https://doi.org/10.1145/3379247.3379248
   Google Scholar
• Shirani F, Groves C, Henwood K, Pidgeon N, Roberts E. ‘I’m the smart meter’: perceptions of smart technology amongst vulnerable consumers. Energy Policy. 2020;144:111637. doi:https://doi.org/10.1016/j.enpol.2020.111637.
   Web of Science ®Google Scholar
• Schlomann A, Seifert A, Zank S, Rietz C. Assistive technology and mobile ICT usage among oldest-old cohorts: comparison of the oldest-old in private homes and in long-term care facilities. Res Aging. 2020;42(5–6):163–73. doi:https://doi.org/10.1177/0164027520911286.
   PubMed Web of Science ®Google Scholar
• Kadylak T, Cotten S. United States older adults’ willingness to use emerging technologies. Inf Commun Soc. 2020 Jan;23(5):1–15. doi:https://doi.org/10.1080/1369118X.2020.1713848.
   Web of Science ®Google Scholar
• Weck M, Afanassieva M Ageing people’s trust in digital assistive technology: ini- tial trust formation; 2020.
   Google Scholar
• Zou P, Stinson J, Parry M, Dennis CL, Yang Y, Lu Z A smartphone App (mDASHNa-CC) to support healthy diet and hypertension control for Chinese Canadian seniors: protocol for design, usability and feasibility testing. JMIR Res Protoc. 2020 Apr;9(4):e15545. doi:https://doi.org/10.2196/15545.
   PubMed Web of Science ®Google Scholar
• Lin TTC, Bautista JR, Core R. Seniors and mobiles: a qualitative inquiry of mHealth adoption among Singapore seniors. Inform Health Soc Care. 2020;45(4):360–73. Available from. doi:https://doi.org/10.1080/17538157.2020.1755974. PMID: 32484720.
   PubMed Web of Science ®Google Scholar
• Remmers H. Environments for ageing, assistive technology and self-determination: ethical perspectives. Inform Health Soc Care. 2010;35(3–4):200–10. doi:https://doi.org/10.3109/17538157.2010.528649.
   PubMed Web of Science ®Google Scholar
• Chung J, Demiris G, Thompson HJ. Ethical considerations regarding the use of smart home technologies for older adults: an integrative review. Annu Rev Nurs Res. 2016;34(1):155–81. Available from https://connect.springerpub.com/content/sgrarnr/34/1/155
   PubMedGoogle Scholar
• Jo TH, Ma JH, Cha SH. Elderly perception on the internet of things-based integrated smart-home system. Sensors. 2021;21(4):1284. Available from https://www.mdpi.com/1424-8220/21/4/1284.
   PubMed Web of Science ®Google Scholar
• Courtney KL, Demeris G, Rantz M, Skubic M. Needing smart home technologies: the perspectives of older adults in continuing care retirement communities. Inform Prim Care. 2008;16(3):195–201. doi:https://doi.org/10.14236/jhi.v16i3.694.
   PubMedGoogle Scholar
• Demiris G Privacy and social implications of distinct sensing approaches to implementing smart homes for older adults. In: 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society; 2009. p. 4311–14. doi: https://doi.org/10.1109/IEMBS.2009.5333800
   Google Scholar
• Offermann-van Heek J, Schomakers EM, Ziefle M. Bare necessities? How the need for care modulates the acceptance of ambient assisted living technologies. Int J Med Inform. 2019;127:147–56. doi:https://doi.org/10.1016/j.ijmedinf.2019.04.025.
   PubMed Web of Science ®Google Scholar
• Steele R, Lo A, Secombe C, Wong YK. Elderly persons’ perception and acceptance of using wireless sensor networks to assist healthcare. Int J Med Inform. 2009;78(12):788–801. doi:https://doi.org/10.1016/j.ijmedinf.2009.08.001.
   PubMed Web of Science ®Google Scholar
• Mulvenna M, Boger J, Bond R Ethical by design: a Manifesto. In: Proceedings of the European Conference on Cognitive Ergonomics 2017. ECCE 2017. New York, NY, USA: Association for Computing Machinery; 2017. p. 51–54. doi:https://doi.org/10.1145/3121283.3121300.
   Google Scholar
• Portet F, Vacher M, Golanski C, Roux C, Meillon B. Design and evaluation of a smart home voice interface for the elderly — Acceptability and objection aspects. Pers Ubiquitous Comput. 2012 Jan;17:1–18.
   Web of Science ®Google Scholar
• Birchley G, Huxtable R, Murtagh M, Meulen R, Flach P, Gooberman-Hill R. Smart homes, private homes? An empirical study of technology researchers’ perceptions of ethical issues in developing smart-home health technologies. BMC Med Ethics. 2017 Dec;18(1). doi:https://doi.org/10.1186/s12910-017-0183-z
   Google Scholar
• Sánchez VG, Taylor I, Bing-Jonsson PC. Ethics of smart house welfare technology for older adults: a systematic literature review. Int J Technol Assess Health Care. 2017;33(6):691–99. doi:https://doi.org/10.1017/S0266462317000964.
   PubMed Web of Science ®Google Scholar
• Vastenburg MH, Visser T, Vermaas M, Keyson DV. Designing acceptable assisted living services for elderly users. In: Aarts E, Crowley JL, De Ruyter B, Gerh¨auser H, Pflaum A, Schmidt J, et al., editors. Ambient intelligence. Berlin (Heidelberg): Springer Berlin Heidelberg; 2008. 1–12. https://doi.org/https://doi.org/10.1007/978-3-540-89617-3_1
   Google Scholar
• Peek ST, Wouters EJ, Van Hoof J, Luijkx KG, Boeije HR, Vrijhoef HJ. Factors influencing acceptance of technology for aging in place: a systematic review. Int J Med Inform. 2014;83(4):235–48. doi:https://doi.org/10.1016/j.ijmedinf.2014.01.004.
   PubMed Web of Science ®Google Scholar
• Calvaresi D, Cesarini D, Sernani P, Marinoni M, Dragoni AF, Sturm A Exploring the ambient assisted living domain: a systematic review. J Ambient Intell Humaniz Comput. 2016 May;8(2):239–57. doi:https://doi.org/10.1007/s12652-016-0374-3.
   Web of Science ®Google Scholar
• Sun N, Rau PLP. The acceptance of personal health devices among patients with chronic conditions. Int J Med Inform. 2015;84(4):288–97. doi:https://doi.org/10.1016/j.ijmedinf.2015.01.002.
   PubMed Web of Science ®Google Scholar
• Ma J, Wpa H. Health smart homes: new challenges. Stud Health Technol Inform. 2017;245(MEDINFO 2017: Precision Healthcare through Informatics):166–69. doi:https://doi.org/10.3233/978-1-61499-830-3-166.
   PubMedGoogle Scholar
• Perry J, Beyer S, Holm S. Assistive technology, telecare and people with intellectual disabilities: ethical considerations. J Med Ethics. 2009;35(2):81–86. doi:https://doi.org/10.1136/jme.2008.024588.
   PubMed Web of Science ®Google Scholar
• Zaad L, Allouch SB The influence of control on the acceptance of ambient intelligence by elderly people: an explorative study. In: European Conference on Ambient Intelligence. Berlin, Heidelberg: Springer; 2008. p. 58–74. https://doi.org/https://doi.org/10.1007/978-3-540-89617-3_5
   Google Scholar
• Tetteh N, Amponsah O. Sustainable adoption of smart homes from the Sub-Saharan African perspective. Sustainable Cities and Soc. 2020;63:102434. doi:https://doi.org/10.1016/j.scs.2020.102434.
   Web of Science ®Google Scholar
• Baraka K, Ghobril M, Malek S, Kanj R, Kayssi A Low cost Arduino/Android-based energy-efficient home automation system with smart task scheduling. In: 2013 Fifth International Conference on Com- putational Intelligence, Communication Systems and Networks; 2013. p. 296–301. doi: https://doi.org/10.1109/CICSYN.2013.47
   Google Scholar
• Andersson L. Loneliness and perceived responsibility and control in elderly community residents. J Soc Behav Pers. 1992;7:431.
   Google Scholar
• Holmén K, Ericsson K, Andersson L, Winblad B. Loneliness among elderly people living in Stockholm: a population study. J Adv Nurs. 1992;17(1):43–51. Available from https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1365-2648.1992.tb01817.x
   PubMed Web of Science ®Google Scholar
• Embarak F, Ismail NA, Othman S. A systematic literature review: the role of assistive technology in supporting elderly social interaction with their online community. J Ambient Intell Humaniz Comput. 2020;1–14. https://doi.org/https://doi.org/10.1007/s12652-020-02420-1
   Google Scholar
• Lindberg RS, De Troyer O Towards a reference model of guidelines for the elderly based on technol- ogy adoption factors. In: Proceedings of the 6th EAI International Conference on Smart Objects and Technologies for Social Good; 2020. p. 30–35. https://doi.org/https://doi.org/10.1145/3411170.3411240
   Google Scholar
• Yeh SC, Lo S. Living alone, social support, and feeling lonely among the elderly. Social Behav Personality Int J. 2004 Jan;32(2):129–38. doi:https://doi.org/10.2224/sbp.2004.32.2.129.
   Web of Science ®Google Scholar
• Chen K, Chan AH A review of technology acceptance by older adults. Gerontechnology. 2011.
   Google Scholar
• McLean A Ethical frontiers of ICT and older users: cultural, pragmatic and ethical issues. Ethics Inf Technol. 2011 Jun;13(4):313–26. doi:https://doi.org/10.1007/s10676-011-9276-4.
   Web of Science ®Google Scholar
• Rubeis G. The disruptive power of Artificial Intelligence. Ethical aspects of gerontechnology in elderly care. Arch Gerontol Geriatr. 2020;91:104186. Available from http://www.sciencedirect.com/science/article/pii/S0167494320301801
   PubMed Web of Science ®Google Scholar
• Upchurch M 7. In: Gender Bias in Research. John Wiley & Sons, Ltd; 2020. p. 139–54. Available from: https://onlinelibrary.wiley.com/doi/abs/10.1002/9781119315063.ch7
   Google Scholar
• Ameen N, Willis R, Hussain Shah M. An examination of the gender gap in smartphone adoption and use in Arab countries: a cross-national study. Comput Human Behav. 2018;89:148–62. Available from http://www.sciencedirect.com/science/article/pii/S0747563218303753
   Web of Science ®Google Scholar
• Chiu CJ, Liu CW. Understanding older adult’s technology adoption and withdrawal for elderly care and education: mixed method analysis from national survey. J Med Internet Res. 2017 Nov;19(11):e374. Available from http://www.jmir.org/2017/11/e374/
   PubMed Web of Science ®Google Scholar
• Strengers Y, Kennedy J, Arcari P, Nicholls L, Gregg M. Protection, productivity and pleasure in the smart home: emerging expectations and gendered insights from Australian early adopters. In: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems. CHI ’19. New York, NY, USA: Association for Computing Machinery; 2019. p. 1–13. doi:https://doi.org/10.1145/3290605.3300875.
   Google Scholar
• Bardzell S, Bardzell J Towards a feminist HCI methodology: social science, feminism, and HCI. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. CHI ’11. New York, NY, USA: Association for Computing Machinery; 2011. p. 675–84. doi:https://doi.org/10.1145/1978942.1979041.
   Google Scholar
• Bell G. Making life: a brief history of human-robot interaction. Consumption Markets Cult. 2018;21(1):22–41. doi:https://doi.org/10.1080/10253866.2017.1298555.
   Web of Science ®Google Scholar
• Rode JA. A theoretical agenda for feminist HCI. Interact Comput. 2011;23(5):393–400. doi:https://doi.org/10.1016/j.intcom.2011.04.005.
   Web of Science ®Google Scholar
• Kneale L, Demiris G. Lack of diversity in personal health record evaluations with older adult participants: a systematic review of literature. BMJ Health Care Inf. 2016;23(4). doi: https://doi.org/10.14236/jhi.v23i4.881
   Google Scholar
• Eisma R, Dickinson A, Goodman J, Syme A, Tiwari L, Newell AF. Early user involvement in the development of information technology-related products for older people. Universal Access Inf Soc. 2004;3(2):131–40. doi:https://doi.org/10.1007/s10209-004-0092-z.
   Google Scholar
• Peek STM, Wouters EJ, Luijkx KG, Vrijhoef HJ What it takes to successfully implement technology for aging in place: focus groups with stakeholders. J Med Internet Res. 2016 May;18(5):e98. doi:https://doi.org/10.2196/jmir.5253.
   PubMed Web of Science ®Google Scholar
• Foster MV, Sethares KA. Facilitators and barriers to the adoption of telehealth in older adults: an integrative review. CIN: Comput Inf Nurs. 2014;32:523–33.
   PubMedGoogle Scholar
• Brown A, O’Connor S. Mobile health applications for people with dementia: a systematic review and synthesis of qualitative studies. Inform Health Soc Care. 2020;45(4):343–59. Available from. doi:https://doi.org/10.1080/17538157.2020.1728536. PMID: 32237937.
   PubMed Web of Science ®Google Scholar
• Gamberini L, Alcan˜iz Raya M, Barresi G, Fabregat M, Ibanez F, Gon¸calves F, et al. Cognition, technology and games for the elderly: an introduction to eldergames project. Psychol J. 2006 Jan;4:285. http://www.psychnology.org/File/PNJ4(3)/PSYCHNOLOGY_JOURNAL_4_3_GAMBERINI.pdf
   Google Scholar
• Leikas J. Aesthetic well-being and ethical design of technology. Cham: Springer International Publishing; 2020. 155–66. Available from https://doi.org/https://doi.org/10.1007/978-3-030-53483-7_10
   Google Scholar
• Blumendorf M, Feuerstack S, Albayrak S Multimodal user interfaces for smart environments; 2008.
   Google Scholar
• Wan Q, Li Y, Li C, Pal R Gesture recognition for smart home applications using portable radar sensors. In: 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society; 2014. p. 6414–17. doi: https://doi.org/10.1109/EMBC.2014.6945096.
   Google Scholar
• Zuo F, De With PHN Real-time face recognition for smart home applications. In: 2005 Digest of Technical Papers. International Conference on Consumer Electronics, 2005. ICCE; 2005. p. 35–36. doi: https://doi.org/10.1109/ICCE.2005.1429704.
   Google Scholar
• Farivar S, Abouzahra M, Ghasemaghaei M. Wearable device adoption among older adults: a mixed-methods study. Int J Inf Manage. 2020 Dec;55:102209. Available from doi:https://doi.org/10.1016/j.ijinfomgt.2020.102209.
   PubMed Web of Science ®Google Scholar
• Lloyd K Bias amplification in artificial intelligence systems. arXiv preprint arXiv:180907842. 2018.
   Google Scholar
• Buolamwini J, Gebru T Gender shades: intersectional accuracy disparities in commercial gender classifi- cation. In: Conference on fairness, accountability and transparency; 2018. p. 77–91.
   Google Scholar
• Wang L, Wong A Implications of computer vision driven assistive technologies towards individuals with visual impairment. arXiv preprint arXiv:190507844. 2019.
   Google Scholar
• Klare BF, Burge MJ, Klontz JC, Bruegge RWV, Jain AK. Face recognition performance: role of demo- graphic information. IEEE Trans Inf Forensics Secur. 2012;7(6):1789–801. doi:https://doi.org/10.1109/TIFS.2012.2214212.
   Web of Science ®Google Scholar
• Wright D, Shank DB. Smart home technology diffusion in a living laboratory. J Tech Writing Commun. 2020;50(1):56–90. doi:https://doi.org/10.1177/0047281619847205.
   Google Scholar
• Astell AJ, McGrath C, Dove E. ‘That’s for old so and so’s!’: does identity influence older adults’ technology adoption decisions? Ageing Soc. 2020;40(7):1550–76. doi:https://doi.org/10.1017/S0144686X19000230.
   Web of Science ®Google Scholar