Abstract
Health facilities worldwide have been struggling for years with the low number of care personnel compared to the demand for assistance, even before the recent pandemic emergency. This problem has made the caregivers a category characterized by a high-workload job, with consequent risks of stress and burnout. In these cases, technology can often help people mitigate these issues, but only if it is accepted and perceived as useful by users. This study investigates caregivers’ perceived usefulness, a key factor of the Technology Acceptance, of an innovative IoT patient monitoring system, called smart-bed, able to provide valuable information about patients without being in contact with them. The study carries out a series of focus groups with employees from hospitals, elderly retirement homes and home-care assistance. Through a thematic analysis of the discussion topics that emerged, the reasons to perceive the IoT system useful are investigated and analyzed, together with caregivers desired functions and the possible limitations that these technologies could have if inserted in this context. In addition to providing an overview of these elements for this particular system, the results bring some reflections relevant to IoT in healthcare environments, therefore contributing to the design of future technologies that will take into account the wishes and needs of users.
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Krick, T., Huter, K., Domhof, D., et al.: Digital technology and nursing care: a scoping review on acceptance, effectiveness and efficiency studies of informal and formal care technologies. BMC Health Serv. Res. 19 (2019). https://doi.org/10.1186/s12913-019-4238-3
Büssing, A., Falkenberg, Z., Schoppe, C., et al.: Work stress associated cool down reactions among nurses and hospital physicians and their relation to burnout symptoms. BMC Health Serv. Res. 17 (2017). https://doi.org/10.1186/s12913-017-2445-3
Hämmig, O.: Explaining burnout and the intention to leave the profession among health professionals - a cross-sectional study in a hospital setting in Switzerland. BMC Health Serv. Res. 18 (2018). https://doi.org/10.1186/s12913-018-3556-1
Zhou, J., Wiggermann, N.: The effects of hospital bed features on physical stresses on caregivers when repositioning patients in bed. Appl. Ergon. 90 (2021). https://doi.org/10.1016/j.apergo.2020.103259
Gunningberg, L., Carli, C.: Reduced pressure for fewer pressure ulcers: can real-time feedback of interface pressure optimise repositioning in bed? Int. Wound J. 13, 774–779 (2016). https://doi.org/10.1111/iwj.12374
Kashani, M.H., Madanipour, M., Nikravan, M., et al.: A systematic review of IoT in healthcare: applications, techniques, and trends. J. Network Comput. Appl. 192 (2021). https://doi.org/10.1016/j.jnca.2021.103164
Ullah, F., Habib, M.A., Farhan, M., et al.: Semantic interoperability for big-data in heterogeneous IoT infrastructure for healthcare. Sustain. Cities Soc. 34, 90–96 (2017). https://doi.org/10.1016/j.scs.2017.06.010
Najafizadeh, A., Salajegheh, A., Rahmani, A.M., Sahafi, A.: Privacy-preserving for the internet of things in multi-objective task scheduling in cloud-fog computing using goal programming approach. Peer-to-Peer Network. Appl. 14(6), 3865–3890 (2021). https://doi.org/10.1007/s12083-021-01222-2
Papert, M., Pflaum, A.: Development of an ecosystem model for the realization of Internet of Things (IoT) services in supply chain management. Electron. Mark. 27(2), 175–189 (2017). https://doi.org/10.1007/s12525-017-0251-8
Haass, R., Dittmer, P., Veigt, M., Lütjen, M.: Reducing food losses and carbon emission by using autonomous control - a simulation study of the intelligent container. Int. J. Product. Econ. 164, 400–408 (2015). https://doi.org/10.1016/j.ijpe.2014.12.013
Jiang, H., Shen, F., Chen, S., et al.: A secure and scalable storage system for aggregate data in IoT. Fut. Gener. Comput. Syst. 49, 133–141 (2015). https://doi.org/10.1016/j.future.2014.11.009
Al Shorman, O., Al Shorman, B., Al-Khassaweneh, M., Alkahtani, F.: A review of internet of medical things (IoMT) - based remote health monitoring through wearable sensors: a case study for diabetic patients. Indonesian J. Electric. Eng. Comput. Sci. 20, 414–422 (2020). https://doi.org/10.11591/ijeecs.v20.i1.pp414-422
Garai, Á., Péntek, I., Adamkó, A.: Revolutionizing healthcare with IoT and cognitive, cloud-based telemedicine. Acta Polytechnica Hungarica 16, 163–181 (2019). https://doi.org/10.12700/APH.16.2.2019.2.10
Scarpato, N., Pieroni, A., Di Nunzio, L., Fallucchi, F.: E-health-IoT universe: a review. Int. J. Adv. Sci. Eng. Inform. Technol. 7, 2328–2336 (2017). https://doi.org/10.18517/ijaseit.7.6.4467
Rahaman, A., Islam, M.M., Islam, M.R., et al.: Developing IoT based smart health monitoring systems: a review. Revue d’Intelligence Artificielle 33, 435–440 (2019). https://doi.org/10.18280/ria.330605
Manyika, J., Chui, M., Bisson, P., et al.: The Internet of Things: mapping the value beyond the hype. McKinsey Global Inst. 144 (2015)
Carcary, M., Maccani, G., Doherty, E., Conway, G.: Exploring the determinants of IoT adoption: findings from a systematic literature review. In: Zdravkovic, J., Grabis, J., Nurcan, S., Stirna, J. (eds.) BIR 2018. LNBIP, vol. 330, pp. 113–125. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-99951-7_8
Thangaraj, M., Ponmalar, P.P., Anuradha, S.: Internet of Things (IOT) enabled smart autonomous hospital management system - a real world health care use case with the technology drivers. In: 2015 IEEE International Conference on Computational Intelligence and Computing Research ICCIC 2015 (2015). https://doi.org/10.1109/ICCIC.2015.7435678
Singh, R.P., Javaid, M., Haleem, A., Suman, R.: Internet of Things (IoT) applications to fight against COVID-19 pandemic. Diabetes Metab. Synd. Clin. Res. Rev. 14, 521–524 (2020). https://doi.org/10.1016/j.dsx.2020.04.041
Ghosh, A.M., Halder, D., Hossain, S.A.: Remote health monitoring system through IoT. In: 2016 5th International Conference on Informatics, Electronics and Vision (ICIEV), pp. 921–926, May 2016. http://doi.org/10.1109/ICIEV.2016.7760135
Albahri, A.S., Alwan, J.K., Taha, Z.K., et al.: IoT-based telemedicine for disease prevention and health promotion: State-of-the-Art. J. Network Comput. Appl. 173 (2021). https://doi.org/10.1016/j.jnca.2020.102873
Sodhro, A.H., Pirbhulal, S., Sangaiah, A.K.: Convergence of IoT and product lifecycle management in medical health care. Future Gener. Comput. Syst. 86, 380–391 (2018). https://doi.org/10.1016/j.future.2018.03.052
Chiuchisan, I., Costin, H.N., Geman, O.: Adopting the internet of things technologies in health care systems. In: EPE 2014 - Proceedings of the 2014 International Conference and Exposition on Electrical and Power Engineering, pp. 532–535 (2014). https://doi.org/10.1109/ICEPE.2014.6969965
Dhariwal, K., Mehta, A.: Architecture and plan of Smart hospital based on Internet of Things (IOT). Int. Res. J. Eng. Technol. 4, 1976–1980 (2017)
Catarinucci, L., De Donno, D., Mainetti, L., et al.: An IoT-aware architecture for smart healthcare systems. IEEE Internet of Things J. 2, 515–526 (2015). https://doi.org/10.1109/JIOT.2015.2417684
Yousefi, R., Ostadabbas, S., Faezipour, M., et al.: A smart bed platform for monitoring and Ulcer prevention. In: Proceedings - 2011 4th International Conference on Biomedical Engineering and Informatics, BMEI 2011, vol. 3, pp. 1362–1366 (2011). https://doi.org/10.1109/BMEI.2011.6098589
Brush, Z., Bowling, A., Tadros, M., Russell, M.: Design and control of a smart bed for pressure ulcer prevention. In: 2013 IEEE/ASME International Conference on Advanced Intelligent Mechatronics: Mechatronics for Human Wellbeing, AIM 2013, pp. 1033–1038 (2013). https://doi.org/10.1109/AIM.2013.6584230
Hong, Y.S.: Smart Care Beds for Elderly Patients with Impaired Mobility. Wireless Communications and Mobile Computing 2018 (2018). https://doi.org/10.1155/2018/1780904
Sivanantham, A.: Measurement of heartbeat, respiration and movements detection using Smart Bed. In: 2015 IEEE Recent Advances in Intelligent Computational Systems, RAICS 2015, pp. 105–109 (2016). https://doi.org/10.1109/RAICS.2015.7488397
Hart, A., Tallevi, K., Wickland, D., et al.: A contact-free respiration monitor for smart bed and ambulatory monitoring applications. In: 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2010, pp. 927–930 (2010). https://doi.org/10.1109/IEMBS.2010.5627525
Fischer, M., Renzler, M., Ussmueller, T.: Development of a smart bed insert for detection of incontinence and occupation in elder care. IEEE Access 7, 118498–118508 (2019). https://doi.org/10.1109/ACCESS.2019.2931041
Nakajima, R., Sakaguchi, K.: Service vision design for Smart Bed SystemTM of paramount bed. Fujitsu Sci. Tech. J. 54, 9–14 (2018)
Centrella Smart+ Hospital Bed | Hillrom. https://www.hillrom.com/en/products/centrella-smart-bed/. Accessed 21 Jan 2022
iBed Wireless | Stryker. https://www.stryker.com/us/en/acute-care/products/ibed-wireless.html. Accessed 21 Jan 2022
Economides, A.A.: User perceptions of Internet of Things (IoT) systems. In: Obaidat, M.S. (ed.) ICETE 2016. CCIS, vol. 764, pp. 3–20. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-67876-4_1
Davis, F.D.: Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quar. Manage. Inf. Syst. 13, 319–339 (1989). https://doi.org/10.2307/249008
Ammenwerth, E.: Technology acceptance models in health informatics: TAM and UTAUT. Stud. Health Technol. Inform. 263, 64–71 (2019). https://doi.org/10.3233/SHTI190111
Venkatesh, V., Sykes, T.A., Zhang, X.: Just what the doctor ordered”: A revised UTAUT for EMR system adoption and use by doctors. In: Proceedings of the Annual Hawaii International Conference on System Sciences https://doi.org/10.1109/HICSS.2011.1
Legris, P., Ingham, J., Collerette, P.: Why do people use information technology? a critical review of the technology acceptance model. Inform. Manage. 40, 191–204 (2003). https://doi.org/10.1016/S0378-7206(01)00143-4
Granić, A., Marangunić, N.: Technology acceptance model in educational context: a systematic literature review. Br. J. Educ. Technol. 50, 2572–2593 (2019). https://doi.org/10.1111/bjet.12864
Tubaishat, A.: Perceived usefulness and perceived ease of use of electronic health records among nurses: application of technology acceptance model. Inform. Health Social Care 43, 379–389 (2018). https://doi.org/10.1080/17538157.2017.1363761
Salloum, S.A., Alhamad, A.Q.M., Al-Emran, M., Monem, A.A., Shaalan, K.: Exploring students’ acceptance of e-learning through the development of a comprehensive technology acceptance model. IEEE Access 7, 128445–128462 (2019). https://doi.org/10.1109/ACCESS.2019.2939467
Rahimi, B., Nadri, H., Afshar, H.L., Timpka, T.: A systematic review of the technology acceptance model in health informatics. Appl. Clin. Inform. 9, 604–634 (2018). https://doi.org/10.1055/S-0038-1668091
Holden, R.J., Karsh, B.T.: The technology acceptance model: its past and its future in health care. J. Biomed. Inform. 43(1), 159–172 (2010). https://doi.org/10.1016/j.jbi.2009.07.002
Tsourela, M., Nerantzaki, D.M.: An internet of things (IoT) acceptance model. assessing consumer’s behavior toward IoT products and applications. Fut. Internet 12, 1–23 (2020). https://doi.org/10.3390/fi12110191
Kang, J.-Y., Kong, Y.-W., Kim, E.-B., et al.: Relationships among Nursing Students’ recognition, perceived usefulness, and intention to accept IoT. koreascience.or.kr 7, 1–5 (2021). https://doi.org/10.13106/kjfhc.2021.vol7.no7.1
Martínez-Caro, E., Cegarra-Navarro, J.G., García-Pérez, A., Fait, M.: Healthcare service evolution towards the Internet of Things: an end-user perspective. Technol. Forecast. Soc. Change 136, 268–276 (2018). https://doi.org/10.1016/j.techfore.2018.03.025
Ben Arfi, W., Ben Nasr, I., Khvatova, T., Ben Zaied, Y.: Understanding acceptance of eHealthcare by IoT natives and IoT immigrants: an integrated model of UTAUT, perceived risk, and financial cost. Technol. Forecast. Soc. Change 163 (2021). https://doi.org/10.1016/j.techfore.2020.120437
Bhattacherjee, A., Hikmet, N.: Reconceptualizing organizational support and its effect on information technology usage: evidence from the health care sector. J. Comput. Inform. Syst. 48, 69–76 (2008). https://doi.org/10.1080/08874417.2008.11646036
Kinalski, D.D.F., de Paula, C.C., de Padoin, M.S.M., et al.: Focus group on qualitative research: experience report. Revista brasileira de enfermagem 70, 424–429 (2017). https://doi.org/10.1590/0034-7167-2016-0091
Maguire, M.: Education BD-AIJ of H, 2017 undefined doing a thematic analysis: a practical, step-by-step guide for learning and teaching scholars. AISHE-J. All Ireland J. Teach. Learn. High. Educ. 9, 3351 (2017)
Deb, S., Claudio, D.: Alarm fatigue and its influence on staff performance. IIE Trans. Healthcare Syst. Eng. 5, 183–196 (2015). https://doi.org/10.1080/19488300.2015.1062065
Johnson, K.R., Hagadorn, J.I., Sink, D.W.: Alarm safety and alarm fatigue. Clin. Perinatol. 44, 713–728 (2017). https://doi.org/10.1016/j.clp.2017.05.005
Ng, J.H.Y., Luk, B.H.K.: Patient satisfaction: concept analysis in the healthcare context. Patient Educ. Couns. 102, 790–796 (2019). https://doi.org/10.1016/j.pec.2018.11.013
Downey, C.L., Chapman, S., Randell, R., et al.: The impact of continuous versus intermittent vital signs monitoring in hospitals: a systematic review and narrative synthesis. Int. J. Nurs. Stud. 84, 19–27 (2018). https://doi.org/10.1016/j.ijnurstu.2018.04.013
Metcalf, A.Y., Wang, Y., Habermann, M.: Hospital unit understaffing and missed treatments: primary evidence. Manage. Dec. 56, 2273–2286 (2018). https://doi.org/10.1108/MD-09-2017-0908
Tourigny, L., Baba, V.V., Monserrat, S.I., Lituchy, T.R.: Burnout and absence among hospital nurses: an empirical study of the role of context in Argentina. Eur. J. Int. Manage. 13, 198–223 (2019). https://doi.org/10.1504/EJIM.2019.098147
Chismar, W.G., Wiley-Patton, S.: Does the extended technology acceptance model apply to physicians. In: Proceedings of the36th Annual Hawaii International Conference on System Sciences HICSS 2003 (2003). https://doi.org/10.1109/HICSS.2003.1174354
Acknowledgement
The study was supported by a grant from SMACT scpa competence centre [N. H82C20001350001, I.O.BED project] to the Human Inspired Technology Research Centre (HIT). We also thank Dr Ilaria De Barbieri and Dr Mario Degan for the support of the University Hospital or Padua for the research of the study participants.
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Bacchin, D., Pernice, G.F.A., Sardena, M., Malvestio, M., Gamberini, L. (2022). Caregivers’ Perceived Usefulness of an IoT-Based Smart Bed. In: Streitz, N.A., Konomi, S. (eds) Distributed, Ambient and Pervasive Interactions. Smart Environments, Ecosystems, and Cities. HCII 2022. Lecture Notes in Computer Science, vol 13325. Springer, Cham. https://doi.org/10.1007/978-3-031-05463-1_18
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