IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i5p1850-d1344761.html
   My bibliography  Save this article

Wearables and Their Potential to Transform Health Management: A Step towards Sustainable Development Goal 3

Author

Listed:
  • Lydia Izu

    (Department of Computing Sciences, Nelson Mandela University, Gqeberha 6001, South Africa)

  • Brenda Scholtz

    (Department of Computing Sciences, Nelson Mandela University, Gqeberha 6001, South Africa)

  • Ifeoluwapo Fashoro

    (Department of Computing Sciences, Nelson Mandela University, Gqeberha 6001, South Africa)

Abstract

In the era of rapid technological advancement, wearables have emerged as a promising tool for enhancing health and well-being. The convergence of health and technology drives an unprecedented change in the approach to health and well-being management. This paper aims to provide a comprehensive understanding of the potential role of wearables in actualising health and well-being, thereby paving the way for a healthier and more sustainable future. Using the Affordance Theory lens, this paper delves into the transformative potential of wearables in health and well-being management, thereby promoting Sustainable Development Goal 3 to ensure healthy lives and well-being for all at all ages. The thematic analysis of online reviews on wearable devices captured through web scraping was carried out to explore the potential of these devices in the management of health and well-being. The paper explored how wearables, often integrated into everyday life, can monitor vital signs, track fitness metrics, and even provide therapeutic benefits for health and well-being. The findings reveal that wearables can empower individuals to take charge of their health by leveraging real-time data and personalised feedback, promoting a proactive and preventive approach to health management and resource-effective healthcare. Furthermore, the paper highlights how wearables can contribute to long-term health outcomes for the present generation without exerting excessive strain on the resources for future generations.

Suggested Citation

  • Lydia Izu & Brenda Scholtz & Ifeoluwapo Fashoro, 2024. "Wearables and Their Potential to Transform Health Management: A Step towards Sustainable Development Goal 3," Sustainability, MDPI, vol. 16(5), pages 1-23, February.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:5:p:1850-:d:1344761
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/5/1850/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/16/5/1850/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Raquel Benbunan-Fich, 2019. "An affordance lens for wearable information systems," European Journal of Information Systems, Taylor & Francis Journals, vol. 28(3), pages 256-271, May.
    2. Papa, Armando & Mital, Monika & Pisano, Paola & Del Giudice, Manlio, 2020. "E-health and wellbeing monitoring using smart healthcare devices: An empirical investigation," Technological Forecasting and Social Change, Elsevier, vol. 153(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Huarng, Kun-Huang & Yu, Tiffany Hui-Kuang & Lee, Cheng fang, 2022. "Adoption model of healthcare wearable devices," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    2. Arfi, Wissal Ben & Nasr, Imed Ben & Kondrateva, Galina & Hikkerova, Lubica, 2021. "The role of trust in intention to use the IoT in eHealth: Application of the modified UTAUT in a consumer context," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    3. Zhang, Wenqing & Liu, Liangliang, 2022. "Exploring non-users' intention to adopt ride-sharing services: Taking into account increased risks due to the COVID-19 pandemic among other factors," Transportation Research Part A: Policy and Practice, Elsevier, vol. 158(C), pages 180-195.
    4. Brem, Alexander & Viardot, Eric & Nylund, Petra A., 2021. "Implications of the coronavirus (COVID-19) outbreak for innovation: Which technologies will improve our lives?," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    5. Basile, L.J. & Carbonara, N. & Panniello, U. & Pellegrino, R., 2024. "The role of big data analytics in improving the quality of healthcare services in the Italian context: The mediating role of risk management," Technovation, Elsevier, vol. 133(C).
    6. Secundo, Giustina & Riad Shams, S.M. & Nucci, Francesco, 2021. "Digital technologies and collective intelligence for healthcare ecosystem: Optimizing Internet of Things adoption for pandemic management," Journal of Business Research, Elsevier, vol. 131(C), pages 563-572.
    7. Henkens, Bieke & Verleye, Katrien & Larivière, Bart, 2021. "The smarter, the better?! Customer well-being, engagement, and perceptions in smart service systems," International Journal of Research in Marketing, Elsevier, vol. 38(2), pages 425-447.
    8. Nguyen Bac Nguyen & João Carlos Rosmaninho Menezes, 2021. "The thirty-year evolution of customer-to-customer interaction research: a systematic literature review and research implications," Service Business, Springer;Pan-Pacific Business Association, vol. 15(3), pages 391-444, September.
    9. Belfiore, Alessandra & Cuccurullo, Corrado & Aria, Massimo, 2022. "IoT in healthcare: A scientometric analysis," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    10. Del Giudice, Manlio & Scuotto, Veronica & Papa, Armando & Singh, Sanjay Kumar, 2023. "The ‘bright’ side of innovation management for international new ventures," Technovation, Elsevier, vol. 125(C).
    11. Ávila-Robinson, Alfonso & Islam, Nazrul & Sengoku, Shintaro, 2022. "Exploring the knowledge base of innovation research: Towards an emerging innovation model," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    12. Chauhan, Ankur & Jakhar, Suresh Kumar & Jabbour, Charbel Jose Chiappetta, 2022. "Implications for sustainable healthcare operations in embracing telemedicine services during a pandemic," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    13. Francesca Iandolo & Francesca Loia & Irene Fulco & Chiara Nespoli & Francesco Caputo, 2021. "Combining Big Data and Artificial Intelligence for Managing Collective Knowledge in Unpredictable Environment—Insights from the Chinese Case in Facing COVID-19," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 12(4), pages 1982-1996, December.
    14. Pascal Fechner & Fabian König & Jannik Lockl & Maximilian Röglinger, 2024. "How Artificial Intelligence Challenges Tailorable Technology Design," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 66(3), pages 357-376, June.
    15. Calabrese, Armando & Costa, Roberta & Ghiron, Nathan Levialdi & Tiburzi, Luigi & Pedersen, Esben Rahbek Gjerdrum, 2021. "How sustainable-orientated service innovation strategies are contributing to the sustainable development goals," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    16. Secinaro, Silvana & Brescia, Valerio & Lanzalonga, Federico & Santoro, Gabriele, 2022. "Smart city reporting: A bibliometric and structured literature review analysis to identify technological opportunities and challenges for sustainable development," Journal of Business Research, Elsevier, vol. 149(C), pages 296-313.
    17. Lim, Chun Hsion & Lim, Steven & How, Bing Shen & Ng, Wendy Pei Qin & Ngan, Sue Lin & Leong, Wei Dong & Lam, Hon Loong, 2021. "A review of industry 4.0 revolution potential in a sustainable and renewable palm oil industry: HAZOP approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    18. Gupta, Brij B. & Gaurav, Akshat & Kumar Panigrahi, Prabin, 2023. "Analysis of security and privacy issues of information management of big data in B2B based healthcare systems," Journal of Business Research, Elsevier, vol. 162(C).
    19. Xing, Fei & Peng, Guochao & Zhang, Bingqian & Li, Shuyang & Liang, Xinting, 2021. "Socio-technical barriers affecting large-scale deployment of AI-enabled wearable medical devices among the ageing population in China," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    20. Jorge Morato & Sonia Sanchez-Cuadrado & Ana Iglesias & Adrián Campillo & Carmen Fernández-Panadero, 2021. "Sustainable Technologies for Older Adults," Sustainability, MDPI, vol. 13(15), pages 1-35, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:16:y:2024:i:5:p:1850-:d:1344761. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.