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Research Articles

Interplay of Perceptions of Aging, Care, and Technology Acceptance in Older Age

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Pages 1003-1015 | Received 22 Jun 2021, Accepted 01 Nov 2021, Published online: 23 Apr 2022

References

  • Albina, E. M., & Hernandez, A. A. (2018). Assessment of the elderly on perceived needs, benefits and barriers: Inputs for the design of intelligent assistive technology. In 16th International Conference on ICT and Knowledge Engineering (ICT&KE) (pp. 1–10), IEEE. https://doi.org/10.1109/ICTKE.2018.8612447
  • Bleustein, C., Rothschild, D. B., Valen, A., Valatis, E., Schweitzer, L., & Jones, R. (2014). Wait times, patient satisfaction scores, and the perception of care. The American Journal of Managed Care, 20(5), 393–400.
  • Bouma, H., Fozard, J. L., Bouwhuis, D. G., & Taipale, V. (2007). Gerontechnology in perspective. Gerontechnology, 6(4), 190–216. https://doi.org/10.4017/gt.2007.06.04.003.00
  • Bright, A. K., & Coventry, L. (2013). The 6th International Conference, Assistive technology for older adults: psychological and socio-emotional design requirements. In Proceedings of on Pervasive Technologies Related to Assistive Environments (pp. 1–4). ACM. https://doi.org/10.1145/2504335.2504344
  • Cheng, J., Chen, X., & Shen, M. (2013). A framework for daily activity monitoring and fall detection based on surface electromyography and accelerometer signals. IEEE Journal of Biomedical and Health Informatics, 17(1), 38–45. https://doi.org/10.1109/TITB.2012.2226905
  • Chin, W. W. (2010). How to write up and report PLS analyses. In V. Esposito Vinzi, W. J. Chin, J. Henseler, & H. Wang (Eds.), Handbook of partial least squares, Springer handbooks of computational statistics (pp. 655–669). Springer. https://doi.org/10.1007/978-3-540-32827-8_29
  • Climent-Pérez, P., Spinsante, S., Mihailidis, A., & Florez-Revuelta, F. (2020). A review on video-based active and assisted living technologies for automated lifelogging. Expert Systems with Applications, 139, 112847. https://doi.org/10.1016/j.eswa.2019.112847
  • Cook, D. J., Augusto, J. C., & Jakkula, V. R. (2009). Ambient intelligence: Technologies, applications, and opportunities. Pervasive and Mobile Computing, 5(4), 277–298. https://doi.org/10.1016/j.pmcj.2009.04.001
  • Dix, A. (2009). Human-computer interaction. In L. Liu & M. T. Öszu (Eds.), Encyclopedia of database systems (pp. 1327–1331). Springer US.
  • Driessen, J., Castle, N. G., & Handler, S. M. (2018). Perceived benefits, barriers, and drivers of telemedicine from the perspective of skilled nursing facility administrative staff stakeholders. Journal of Applied Gerontology, 37(1), 110–120. https://doi.org/10.1177/0733464816651884
  • Eggenberger, E., Myllymäki, J., Kolb, C., Martschin, R., Bollheimer, L. C., & Sieber, C. (2013). We cannot care alone: volunteers in dementia care at Nürnberg General Hospital. Zeitschrift Fur Gerontologie Und Geriatrie, 46(3), 226–232. https://doi.org/10.1007/s00391-013-0480-1
  • Emile, M., d’Arripe-Longueville, F., Cheval, B., Amato, M., & Chalabaev, A. (2015). An ego depletion account of aging stereotypes’ effects on health-related variables. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 70(6), 876–885. https://doi.org/10.1093/geronb/gbu168
  • Eurostat (2019). Eurostat European yearbook (2019th ed., pp. 1–226). Publications Office of the European Union. https://ec.europa.eu/eurostat/de/web/products-statistical-books/-/ks-ha-19-001
  • Fausset, C. B., Mayer, A. K., Rogers, W. A., & Fisk, A. D. (2009). Understanding aging in place for older adults: A needs analysis. Proceedings of the Human Factors and Ergonomics Society, Annual Meeting, 53(8), 521–525. https://doi.org/10.1518/107118109X12524442635347
  • Findler, L., Vilchinsky, N., & Werner, S. (2007). The multidimensional attitudes scale toward persons with disabilities (MAS) construction and validation. Rehabilitation Counseling Bulletin, 50(3), 166–176. https://doi.org/10.1177/00343552070500030401
  • Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (1998). Multivariate data analysis (5th ed.). Upper Saddle River, NJ: Prentice Hall.
  • Hair, J. R. Jr., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM). Sage Publications.
  • Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8
  • Holman, H., & Lorig, K. (2004). Patient self-management: A key to effectiveness and efficiency in care of chronic disease. Public Health Reports, 119(3), 239–243. https://doi.org/10.1016/j.phr.2004.04.002
  • Hristova, A., Bernardos, A. M., & Casar, J. R. (2008). Context-aware services for ambient assisted living: A case-study. In First International Symposium on Applied Sciences on Biomedical and Communication Technologies ISABEL ’08 (pp. 1–5). https://doi.org/10.1109/ISABEL.2008.4712593
  • Jacobs, A. H., & Bollheimer, C. (2019). Frailty. In W. Maetzler, R. Dodel, & A. Jacobs (Eds.), Neurogeriatrie (pp. 49–68), Springer. https://doi.org/10.1007/978-3-662-57358-7_5
  • Kumari, P., Mathew, L., & Syal, P. (2017). Increasing trend of wearables and multimodal interface for human activity monitoring: A review. Biosensors & Bioelectronics, 90, 298–307. https://doi.org/10.1016/j.bios.2016.12.001
  • Legris, P., Ingham, J., & Collerette, P. (2003). Why do people use information technology? A critical review of the technology acceptance model. Information & Management, 40(3), 191–204. https://doi.org/10.1016/S0378-7206(01)00143-4
  • Lin, C.-C., Chiu, M.-J., Hsiao, C.-C., Lee, R.-G., & Tsai, Y.-S. (2006). Wireless health care service system for elderly with dementia. IEEE Transactions on Information Technology in Biomedicine, 10(4), 696–704. https://doi.org/10.1109/TITB.2006.874196
  • Liu, L., Stroulia, E., Nikolaidis, I., Miguel-Cruz, A., & Rincon, A. R. (2016). Smart homes and home health monitoring technologies for older adults: A systematic review. International Journal of Medical Informatics, 91, 44–59. https://doi.org/10.1016/j.ijmedinf.2016.04.007
  • McAdams, E., Krupaviciute, A., Gehin, C., Dittmar, A., Delhomme, G., Rubel, P., Fayn, J., & McLaughlin, J. (2011). Wearable electronic systems: Applications to medical diagnostics/monitoring. In A. Bonfiglio & D. De Rossi (Eds), Wearable monitoring systems (pp. 179–203). Springer. https://doi.org/10.1007/978-1-4419-7384-9_9
  • Mubashir, M., Shao, L., & Seed, L. (2013). A survey on fall detection: Principles and approaches. Neurocomputing, 100, 144–152. https://doi.org/10.1016/j.neucom.2011.09.037
  • Offermann-van Heek, J., & Ziefle, M. (2018). HELP? Attitudes towards care and assistive technologies from the perspective of people with disabilities. In International Conference on Computers Helping People with Special Needs (pp. 552–558). Springer. https://doi.org/10.1007/978-3-319-94274-2_79
  • Offermann-van Heek, J., Wilkowska, W., Brauner, P., & Ziefle, M. (2019). Guidelines for integrating social and ethical user requirements in lifelogging technology development. In 5th International Conference on Information and Communication Technologies for Ageing Well and e-Health (pp. 67–79). Scitepress. https://doi.org/10.5220/0007692900670079
  • Peek, S. T., Wouters, E. J., Van Hoof, J., Luijkx, K. G., Boeije, H. R., & Vrijhoef, J. H. (2014). Factors influencing acceptance of technology for aging in place: A systematic review. International Journal of Medical Informatics, 83(4), 235–248. https://doi.org/10.1016/j.ijmedinf.2014.01.004
  • Poli, A., Cosoli, G., Scalise, L., & Spinsante, S. (2020). Impact of wearable measurement properties and data quality on ADLs classification accuracy. IEEE Sensors Journal, 21(13), 14221–14231. https://doi.org/10.1109/JSEN.2020.3009368
  • Power, M. J., & Green, A. M. (2010). The attitudes to disability scale (ADS): Development and psychometric properties. Journal of Intellectual Disability Research, 54(9), 860–874. https://doi.org/10.1111/j.1365-2788.2010.01317.x
  • Rahimi, B., Nadri, H., Afshar, H. L., & Timpka, T. (2018). A systematic review of the technology acceptance model in health informatics. Applied Clinical Informatics, 9(3), 604–634. https://doi.org/10.1055/s-0038-1668091
  • Rashidi, P., & Mihailidis, A. (2013). A survey on ambient-assisted living tools for older adults. IEEE Journal of Biomedical and Health Informatics, 17(3), 579–590. https://doi.org/10.1109/JBHI.2012.2234129
  • Ringle, C. M., Wende, S., & Becker, J.-M. (2015). SmartPLS 3. SmartPLS GmbH. http://www.smartpls.com.
  • Ryan, R. M., & Frederick, C. (1997). On energy, personality, and health: Subjective vitality as a dynamic reflection of well-being. Journal of Personality, 65(3), 529–565. https://doi.org/10.1111/j.1467-6494.1997.tb00326.x
  • Schomakers, E.-M., Offermann-van Heek, J., & Ziefle, M. (2018). Attitudes towards aging and the acceptance of ICT for aging in place. In International Conference on Human Aspects of IT for the Aged Population (pp. 149–169). Springer. https://doi.org/10.1007/978-3-319-92034-4_12
  • Stone, E. E., & Skubic, M. (2015). Fall detection in homes of older adults using the Microsoft Kinect. IEEE Journal of Biomedical and Health Informatics, 19(1), 290–301. https://doi.org/10.1109/JBHI.2014.2312180
  • Terrill, A. L., Molton, I. R., Ehde, D. M., Amtmann, D., Bombardier, C. H., Smith, A. E., & Jensen, M. P. (2016). Resilience, age, and perceived symptoms in persons with long-term physical disabilities. Journal of Health Psychology, 21(5), 640–649. https://doi.org/10.1177/1359105314532973
  • Tsai, T. C., Orav, E. J., & Jha, A. K. (2015). Patient satisfaction and quality of surgical care in US hospitals. Annals of Surgery, 261(1), 2–8. https://doi.org/10.1097/SLA.0000000000000765
  • Turner, M., Kitchenham, B., Brereton, P., Charters, S., & Budgen, D. (2010). Does the technology acceptance model predict actual use? A systematic literature review. Information and Software Technology, 52(5), 463–479. https://doi.org/10.1016/j.infsof.2009.11.005
  • United Nations (2019). World population prospects: Highlights (ST/ESA/SER.A/423) (pp. 1–46). United Nations, Department of Economic and Social Affairs, Population Division.
  • van den Berg, N., Schumann, M., Kraft, K., & Hoffmann, W. (2012). Telemedicine and telecare for older patients–A systematic review. Maturitas, 73(2), 94–114. https://doi.org/10.1016/j.maturitas.2012.06.010
  • Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204. https://doi.org/10.1287/mnsc.46.2.186.11926
  • Weston, R., & Gore, P. A. (2006). A brief guide to structural equation modeling. The Counseling Psychologist, 34(5), 719–751. https://doi.org/10.1177/0011000006286345
  • Wey, S. (2004). One size does not fit all: Person-centred approaches to the use of assistive technology. In M. Marshall (Ed.) Perspectives on rehabilitation and dementia (pp. 202–210). Jessica Kingsley Publishers.
  • Wiles, J. L., Leibing, A., Guberman, N., Reeve, J., & Allen, R. E. S. (2012). The meaning of ‘ageing in place’ to older people. The Gerontologist, 52(3), 357–366. https://doi.org/10.1093/geront/gnr098
  • Wilkowska, W., Offermann-van Heek, J., Brauner, P., & Ziefle, M. (2019). Wind of change? Attitudes towards aging and use of medical technology. In 5th International Conference on Information and Communication Technologies for Ageing Well and e-Health (pp. 80–91). Scitepress. https://doi.org/10.5220/0007693000800091
  • Wong, P. T. (2000). Meaning of life and meaning of death in successful aging. In A. Torner (Ed.), Death attitudes and the older adult: Theories, concepts, and applications (pp. 23–35). Psychology Press.
  • World Health Organization (2019). Primary health care on the road to universal health coverage: 2019 Global monitoring report. https://www.who.int/healthinfo/universal_health_coverage/report/uhc_report_2019.pdf
  • Wurm, S., Tesch-Römer, C., & Tomasik, M. J. (2007). Longitudinal findings on aging-related cognitions, control beliefs, and health in later life. The Journals of Gerontology. Series B, Psychological Sciences and Social Sciences, 62(3), 156–164. doi: 10.1093/geronb/62.3.P156.
  • Ziefle, M. (2013). Ungewissheit und Unsicherheit bei der Einführung neuer Technologien [Uncertainty and insecurity in the introduction of new technologies]. In S. Jeschke, E. M. Jakobs, & A. Dröge (Eds.), Exploring uncertainty (pp. 84–104). Springer Gabler. https://doi.org/10.1007/978-3-658-00897-0_5
  • Zigel, Y., Litvak, D., & Gannot, I. (2009). A method for automatic fall detection of elderly people using floor vibrations and sound-proof of concept on human mimicking doll falls. IEEE Transactions on Bio-Medical Engineering, 56(12), 2858–2867. https://doi.org/10.1109/TBME.2009.2030171

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