Máltai Tanulmányok | Az ápolási robotok alkalmazásának lehetősége az idősek tartós ápolásában

Megosztás

Szöveg beállítások

A következő évtizedekben megduplázódik a világ időskorú lakossága. Ápoló robotok alkalmazásával a munkaerőhiány és az idősekkel szembeni előítéletek problémája is megoldódhatna, de készek vagyunk-e elfogadni, hogy egy mesterséges asszisztens intelligens otthonunk részeként társa legyen idős szeretteinknek?

Cikk felolvasása00:00

Absztrakt

A WHO előrejelzése szerint 2030-ra a világon minden hatodik ember hatvanévesnél idősebb lesz, ami növeli a tartós ápolás iránti igényt. Egyidejűleg a világ népességének mintegy felét érinti az ageizmus, amely az idősekkel szemben megjelenő sztereotípiákban, előítéletekben és diszkriminációban nyilvánul meg. A cikk hipotézise, hogy a mesterséges intelligencia fejlődésével a robottechnológiák lehetőséget kínál(hat)nak az előítéletek és a humánerőforrás-hiány csökkentésére, illetve ezáltal az ápolás minőségének javítására. A cikk az MI alkalmazásának kiegészítő lehetőségeit vizsgálja az időskori tartós ápolás vonatkozásában. Két területre fókuszál: a tartós ápolásban jelen lévő humánerőforrás hiányára és a tartós ápolási ellátást igénylő idősek integritásának fenntartására, emberi méltóságuk megőrzésére és emberi jogaik védelmére. E kihívások kezelése átfogó, emberi jogi alapú megközelítést igényel, hogy a robotápolás etikus és méltányos megvalósítása biztosított legyen a tartós időskori gondozásban.

Kulcsszavak: mesterséges intelligencia, robot, ápoló robot, tartós ápolás, ageizmus

DOI: 10.56699/MT.2024.4.2

A világ népességének hatvanöt éven felüli korcsoportja növekszik a leggyorsabban. Az előrejelzések szerint a világ időskorú lakosainak száma a 2019-es 702 millióról 2050-re több mint másfél milliárdra nő (UN, 2019). Erre a tendenciára válaszul az Egészségügyi Világszervezet átfogó stratégiát és cselekvési tervet dolgozott ki (WHO, 2017). Az Európai Bizottság Aging 2021 jelentése (European Commission – Economic Policy Committee, 2021) szerint az időskori eltartottak száma a 2019-es körülbelül 30,8 millióról 2030-ra 33,7 millióra, 2050-re pedig 38,1 millióra fog nőni, ami

Csatlakozzon ingyen és olvasson tovább!

Regisztráljon honlapunkon hogy ingyenesen hozzáférjen a Máltai Tanulmányok összes rovatának archívumához teljes terjedelemben.

Csatlakozom Regisztráció részletei

Már regisztrált tag vagyok, bejelentkezem.

Felhasznált irodalom

Felhasznált irodalom

Abbott, Rebecca – Orr, Noreen – McGill, Paige – Whear, Rebecca – Bethel, Alison – Garside, Ruth – Stein, Ken – Thompson-Coon, Jo (2019): How do “robopets” impact the health and well-being of residents in care homes? A systematic review of qualitative and quantitative evidence, International Journal of Older People Nursing, 14 (3), e12239. DOI: https://doi.org/10.1111/opn.12239
Becker, Ulrich – Reinhard, Hans-Joachim (2018): Long-Term Care in Europe. A Juridical Approach, Cham: Springer. DOI: https://doi.org/10.1007/978-3-319- 70081-6
Bellman, Richard (1978): An Introduction to Artificial Intelligence: Can Computers Think?, San Francisco: Boyd & Fraser Pub Co.
Brownell, Patricia (2010): Social issues and social policy response to abuse and neglect of older adults, in Gutman, Gloria – Spencer, Charmaine (szerk.): Aging, Ageism and Abuse, Amsterdam: Elsevier, 1–15. DOI: https://doi. org/10.1016/B978-0-12-381508-8.00001-1
Corbin, Juliet – Strauss, Anselm (2008): Basics of Qualitative Research: Techniques and Procedures for Developing Grounded Theory, London: Sage Publications, Inc. DOI: https://doi.org/10.4135/9781452230153
Dilip, Golda – Guttula, Ramakrishna – Rajeyyagari, Sivaram et al. (2022): Artificial intelligence-based smart comrade robot for elders healthcare with strait rescue system, Journal of Healthcare Engineering. DOI: https://doi. org/10.1155/2022/9904870
Eurofound (2020): Long-term care workforce: Employment and working conditions. Publications Office of the European Union, https://www.eurofound.europa.eu/ publications/customised-report/2020/long-term-care-workforce-employment- and-working-conditions (letöltve: 2024. 07. 10.).
Eurofound (2021): Living conditions and quality of life: Wages in long-term care and other social services 21% below average, https://www.eurofound.europa.eu/publications/article/2021/wages-in-long-term-care-and-other-social-services-21- below-average (letöltve: 2024. 07. 10.).
European Commission (2021): Study on exploring the incidence and costs of informal long-term care in the EU, https://ec.europa.eu/social/main.jsp?catId=738&langId=en&pubId=8423&furtherPubs=yes (letöltve: 2024. 07. 10.).
European Commission (2022): Commission Staff Working Document. Accompanying the document Commission proposal for a Council Recommendation on access to affordable high-quality long-term care, https://www.parlament.gv.at/PAKT/EU/XXVII/ EU/11/20/EU_112004/imfname_11176305.pdf (letöltve: 2024. 07. 10.).
European Commission – Economic Policy Committee (2021): The 2021 Ageing Report – Economic and budgetary projections for the EU Member States (2019-2070). Publications Office of the European Union, https://ec.europa.eu/info/sites/ default/files/economy-finance/ip148_en.pdf (letöltve: 2024. 07. 10.)
European Parliament (2017): European civil law rules in robotics, https://www. europarl.europa.eu/RegData/etudes/STUD/2016/571379/IPOL_ STU(2016)571379_EN.pdf (letöltve: 2024. 07. 10.).
Eurostat (2022): Population structure and ageing – Statistics Explained, https://ec.europa.eu/eurostat/statistics-explained/index. php?title=Population_structure_and_ageing (letöltve: 2024. 07. 10.).
Garmann-Johnsen, Niels F. – Mettler, Tobias – Sprenger, Michaela (2014): Service robotics in healthcare: A perspective for information systems researchers?, in Proceedings of the 35th International Conference on Information Systems (ICIS 2014), Auckland, New Zealand.
Goher, Khaled M. – Mansouri, Nazanin – Fadlallah, Sulaiman O. (2017): Assessment of personal care and medical robots from older adults’ perspective, Robotics and Biomimetics, 4 (1), 5. DOI: https://doi.org/10.1186/s40638-017-0061-7
Gran, Anne-Britt – Booth, Peter – Bucher, Taina (2021): To be or not to be algorithm aware: A question of a new digital divide?, Information, Communication & Society, 24 (12), 1779–1796. DOI: https://doi. org/10.1080/1369118X.2020.1736124
Hajdú, József (2020): Dignity of elderly persons and digitalised social care, in Yearbook – Human Rights Protection – The Right to Human Dignity, 3, Novi Sad: Institute of Criminological and Sociological Research, 569–596.
Ho, Anita (2020): Are we ready for artificial intelligence health monitoring in elder care?, BMC Geriatrics, 20, 358. DOI: https://doi.org/10.1186/s12877-020-01764-9
Hsu, Eric L. (2021): Technogenarians: Ageing and robotic care 1., in Elliott, Anthony (szerk.): The Routledge Social Science Handbook of AI, London: Routledge, 266–280. DOI: https://doi.org/10.4324/9780429198533-19
IEEE (2024): Technical Committee for Robot Ethics, https://www.ieee-ras.org/robot- ethics (letöltve: 2024. 11. 04.).
Johnsson, Jesper – Björnsson, Ola – Andersson, Peder et al. (2020): Artificial neural networks improve early outcome prediction and risk classification in out-of- hospital cardiac arrest patients admitted to intensive care, Critical Care, 24 (1), 474. DOI: https://doi.org/10.1186/s13054-020-03103-1
Johnston, Carolyn (2022): Ethical design and use of robotic care of the elderly, Journal of Bioethical Inquiry, 19 (1), 11–14. DOI: https://doi.org/10.1007/s11673-022- 10181-z
Kang, Hee Sun – Makimoto, Kiyoko – Konno, Rie – Koh, In Soon (2020): Review of outcome measures in PARO robot intervention studies for dementia care, Geriatric Nursing, 41 (3), 207–214. DOI: https://doi.org/10.1016/j.gerinurse.2019.09.003
Khan, Zeashan Hameed – Siddique, Afifa – Lee, Chang Won (2020): Robotics utilization for healthcare digitization in global COVID-19 management, International Journal of Environmental Research and Public Health, 17 (11), 3819. DOI: https://doi.org/10.3390/ijerph17113819
Kornfeld-Matte, Rosa (2015): Autonomy and care of older persons. Report of the independent expert on the enjoyment of all human rights by older persons, United Nations General Assembly, https://www.refworld.org/reference/themreport/ unhrc/2015/en/106781 (letöltve: 2024. 07. 10.).
Krittanawong, Chayakrit – Zhang, Hong Ju – Wang, Zhen – Aydar. Mehmet – Kitai, Takeshi (2017): Artificial intelligence in precision cardiovascular medicine, Journal of the American College of Cardiology, 69 (21), 2657–2664. DOI: https://doi. org/10.1016/j.jacc.2017.03.571
Le, Minh Hung – Chen, Jingyu – Wang, Liang et al. (2017): Automated diagnosis of prostate cancer in multi-parametric MRI based on multimodal convolutional neural networks, Physics in Medicine & Biology, 62 (16), 6497–6514. DOI: https://doi.org/10.1088/1361-6560/aa7731
Lee, Hwang-Jae – Lee, Suhyun – Chang, Won Hyuk et al. (2017): A wearable hip assist robot can improve gait function and cardiopulmonary metabolic efficiency in elderly adults, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 25 (9), 1549–1557. DOI: https://doi.org/10.1109/TNSRE.2017.2664801
Lee, Su-Hyun – Lee, Hwang-Jae – Chang, Won Hyuk et al. (2017): Gait performance and foot pressure distribution during wearable robot-assisted gait in elderly adults, Journal of Neuroengineering and Rehabilitation, 14 (1), 123. DOI: https://doi. org/10.1186/s12984-017-0333-z
Liu, Yun – Kohlberger, Timo – Norouzi, Mohammad – Dahl, George E. et al. (2019): Artificial intelligence-based breast cancer nodal metastasis detection: Insights into the black box for pathologists, Archives of Pathology & Laboratory Medicine, 143 (7), 859–868. DOI: https://doi.org/10.5858/arpa.2018-0147-OA
Mannheim, Ittay – Zaalen, Yvonne von – Wouters, Eveline J. M. (2021): Ageism in applying digital technology in healthcare: Implications for adoption and actual use, in Wouters, Eveline J. M. (szerk.): Digital Transformations in Care for Older People: Critical Perspectives, London, Routledge, 72–90. DOI: https://doi. org/10.4324/9781003155317-7
Martinez-Martin, Ester – Pobil, Angel P. Del (2018): Personal robot assistants for elderly care: An overview, in Kacprzyk, Janusz – Jain, Lakhmi C. (szerk.): Intelligent Systems Reference Library, 132, New York, Springer, 77–91. DOI: https://doi. org/10.1007/978-3-319-62530-0_5
Neves, Barbara Barbosa – Amaro, Fausto (2012): Too old for technology? How the elderly of Lisbon use and perceive ICT, The Journal of Community Informatics, 8 (1), 1–12. DOI: https://doi.org/10.15353/joci.v8i1.3061
Neves, Barbara Barbosa – Petersen, Alan – Vered, Mor – Carter, Adrian – Omori, Maho (2023): Artificial intelligence in long-term care: Technological promise, aging anxieties, and sociotechnical ageism, Journal of Applied Gerontology, 42 (6). DOI: https://doi.org/10.1177/07334648231157370
Neves, Barbara Barbosa – Waycott, Jenny – Malta, Sue (2018): Old and afraid of new communication technologies? Reconceptualising and contesting the ‘age-based digital divide’, Journal of Sociology, 54 (2). DOI: https://doi. org/10.1177/1440783318766119
Patel, Tejal A. – Puppala, Mamta – Ogunti, Richard O. et al. (2017): Correlating mammographic and pathologic findings in clinical decision support using natural language processing and data mining methods, Cancer, 123 (1), 114–121. DOI: https://doi.org/10.1002/cncr.30245
Prescott, Tony J. – Caleb-Solly, Praminda (2017): Robotics in social care: a connected care ecosystem for independent living, Report, EPSRC UK Robotics and Autonomous Systems Network White Papers, London, EPSRC UK Robotics and Autonomous Systems Network. DOI: https://doi.org/10.31256/WP2017.3
Robert, Nancy (2019): How artificial intelligence is changing nursing, Nursing Management (Springhouse), 50 (9), 30–39. DOI: https://doi.org/10.1097/01. NUMA.0000578988.56622.21
Rubeis, Giovanni (2020): The disruptive power of artificial intelligence. Ethical aspects of gerontechnology in elderly care, Archives of Gerontology and Geriatrics, 91, 104186. DOI: https://doi.org/10.1016/j.archger.2020.104186
Savla, G. – Moore, D. – Palmer, B. (2007): Assessment: neuropsychological, Elsevier eBooks, 99–108. DOI: https://doi.org/10.1016/b0-12-370870-2/00014-7
Sharkey, Amanda – Sharkey, Noel (2010): Granny and the robots: Ethical issues in robot care for the elderly, Ethics and Information Technology, 14, 27–40. DOI: https://doi.org/10.1007/s10676-010-9234-6
Shen, Yang – Guo, Dejun – Long, Fei – Mateos, Luis A. et al. (2021): Robots under COVID-19 pandemic: A comprehensive survey, IEEE Access, 9. DOI: https://doi. org/10.1109/ACCESS.2020.3045792
SPC – EC DG EMPL (2021): 2021 Long-Term Care Report: Trends, challenges and opportunities in an ageing society, Volume I., https://www.europeansources.info/ record/2021-long-term-care-report-trends-challenges-and-opportunities-in-an- ageing-society/ (letöltve: 2024. 07. 10.).
Song, Won-Kyung – Song, Won-Jin – Kim, Yale – Kim, Jongbae (2013): Usability test of KNRC self-feeding robot, IEEE International Conference on Rehabilitation Robotics, 6650501.
Stead, William W. (2018): Clinical implications and challenges of artificial intelligence and deep learning, JAMA, 320 (11), 1107–1108. DOI: https://doi.org/10.1001/ jama.2018.11029
Tanaka, Masaaki – Ishii, Akira – Yamano, Emi et al. (2012): Effect of a human- type communication robot on cognitive function in elderly women living alone, Medical Science Monitor, 18 (9), CR550. DOI: https://doi.org/10.12659/ MSM.883350
UN (2019): World Population Prospects 2019. Highlights, New York: United Nations, Department of Economic and Social Affairs, https://population.un.org/wpp/ publications/files/wpp2019_highlights.pdf (letöltve: 2024. 07. 10.).
Vallor, Shannon (2011): Carebots and caregivers: Sustaining the ethical ideal of care in the twenty-first century, Philosophy & Technology, 24 (3), 251–268. DOI: https://doi.org/10.1007/s13347-011-0015-x
Wang, Rosalie H. – Sudhama, Aishwarya – Begum, Momotaz – Huq, Rajibul – Mihailidis, Alex (2017): Robots to assist daily activities: views of older adults with Alzheimer’s disease and their caregivers, International Psychogeriatrics, 29 (1), 67–79. DOI: https://doi.org/10.1017/S1041610216001435
WHO (2017): Global Strategy and Action Plan on Ageing and Health, Geneva, World Health Organization.
WHO (2021a): Global Report on Ageism, Geneva, World Health Organization, https://www.who.int/teams/social-determinants-of-health/demographic-change-and-healthy-ageing/combatting-ageism/global-report-on- ageism (letöltve: 2024. 07. 10.).
WHO (2021b): Kicking off a Global Conversation About Ageism: Launch of the First UN Global Report on Ageism, Geneva, World Health Organization, https://www.who. int/news-room/events/detail/2021/03/18/default-calendar/kicking-off-a- global-conversation-about-ageism (letöltve: 2024. 07. 10.).
WHO (2022a): Ageing and Health, Geneva, World Health Organization, https://www.who.int/news-room/fact-sheets/detail/ageing-and-health (letöltve: 2024. 07. 10.).
WHO (2022b): Ageism in Artificial Intelligence for Health: WHO Policy Brief, Geneva, World Health Organization.
Zigante, Valentina (2021): The role of new technologies in modernising long-term care systems: A scoping review, Research Note for the Social Situation Monitor, European Union.

Hajdú JózsefMengxuan Chen

Absztrakt

Csatlakozzon ingyen és olvasson tovább!

Ajánló