Technology Acceptance Model Older Adults – Open Project Guidelines Open Project Guidelines Special Issues Research and Publication Revision Process Guidelines Document Processing Fees Award Qualifications
All published articles are made available worldwide under an open access license. There is no special permission to use all or part of the article published by , including figures and tables. For articles published under the Open Access Creative Common CC BY license, any part of the article may be reused without permission as long as the original article is clearly cited. For more information, see https:///openaccess.
Technology Acceptance Model Older Adults
Style papers represent the most advanced research with the greatest potential for significant impact on the field. A Concept Paper is a large original document that includes various methods or approaches, provides an overview of future research opportunities, and describes possible research applications.
Understanding Motivations To Use Online Streaming Services: Integrating The Technology Acceptance Model (tam) And The Uses And Gratifications Theory (ugt)
Feature papers are submitted at the individual invitation or recommendation of scientific editors and receive positive feedback from reviewers.
Editorials are based on recommendations from scientific editors of journals from around the world. The editors select a small number of recently published articles in the journal that they believe are of particular interest to readers or are important in research areas. The aim is to provide a snapshot of some of the exciting work published in the various research sections of the journal.
Submission received: March 14, 2024 / Revised: May 1, 2024 / Accepted: May 9, 2024 / Published: May 13, 2024
The Technology Acceptance Model (TAM) plays an important role in geriatric healthcare as a conceptual framework. The aim of this study is to identify the main aspects of TAM, practical applications, challenges of their applications, and suggest preventive measures in elderly health care. This descriptive survey was conducted using OpenAI’s ChatGPT, with an access date of January 10, 2024. The three open questions sent to ChatGPT and their responses were collected and quality checked for reliability from and previous studies. The main components of TAMs were identified as usefulness, ease of use, attitude to use, behavioral intention to use, project methods, style and organizational methods. TAM’s application areas include many technologies in geriatric health, such as telehealth, wearables, mobile health applications, and more. Challenges arising from TAM applications include technical literacy barriers, digital divide concerns, privacy and security concerns, resistance to change, lack of knowledge and information, health conditions and mental retardation, trust and loyalty concerns, lack of targeted interventions, age-related coping problems, and Integration into traditional health care. Finally, targeted interventions are important for the success of the technology in the elderly population. The results of this study should lead to a greater understanding of older health and technology adoption, and insights from natural language processing models such as ChatGPT are expected to provide new insights.
Enablers And Disablers For Contactless Payment Acceptance Among Malaysian Adults
The introduction of technology in health has made great progress, both challenges and opportunities, especially in the context of elderly health care [1, 2, 3, 4]. As the world population ages, there is an increasing demand for innovative solutions to meet the specific health needs associated with aging [5]. These needs include a number of age-related health challenges, including chronic conditions such as heart disease, cancer, cognitive decline, and cognitive impairment [3, 5]. Furthermore, there is a great need for health interventions that take into account issues such as mobility issues, social isolation, medication management and the general well-being of older people [6]. The unique health needs of the elderly span preventive, rehabilitative and palliative care, requiring a comprehensive approach that recognizes the many facets of aging-related health issues. In this context, technology plays an important role in finding solutions that improve quality of life, independence and overall health outcomes for the elderly population [7, 8, 9, 10, 11]. Addressing these unique health needs requires a thorough understanding of the processes of aging and the diverse health challenges that individuals face as they age [ 5 ].
In this country, the Technology Acceptance Model (TAM) is an important framework for understanding how people, especially the elderly, adopt and use health technologies. The Technology Acceptance Model (TAM) is a well-known and valid framework developed to understand and predict people’s acceptance and adoption of technology [3, 4]. Conceived by Fred Davis in the late 1980s, TAM emerged as a psychological model that attempts to explain the factors that influence users’ decisions to accept and use information technology [12]. Davis’ original work led to the development of the TAM into a comprehensive model used in many contexts, including health care [ 4 , 8 , 13 ]. TAM is based on the theory of intentional action and the theory of planned behavior, which states that people’s behavioral intention is the main determinant of their behavior [2, 4, 6]. In the context of technology acceptance, TAM suggests that ease of use and usefulness are important factors influencing people’s willingness to adopt and use a technology [ 2 , 14 , 15 , 16 ]. Ease of use refers to the user’s perception of how easy it is to use a technology, while usefulness refers to the belief that the technology improves their work or makes their life easier [ 15 , 16 ]. These two key factors shape users’ attitudes and behavioral intentions toward technology adoption [ 2 , 4 , 15 , 16 , 17 ]. Over the years, the TAM has been expanded and modified to include other factors and variables that affect technical acceptance [2, 3, 15, 16]. TAM2, TAM3, and the Unified Theory of Acceptance and Use of Technology (UTAUT) are examples of general models that consider social influence, cognitive instrumental processes and other contextual factors [4, 15, 16, 18]. In the health context, TAM has proven to be important for understanding how people, especially the elderly, approach and integrate health technologies into their lives [ 3 , 4 , 6 , 19 ]. It provides a structured framework for researchers and practitioners to assess the factors influencing technology adoption among older adults, contributing to the development and implementation of better and simpler health technologies to exploit their specific needs [3, 4 , 6, 8].
In the world of human technological progress, it is no exaggeration to say that ChatGPT is one of the most unique developments of our time. ChatGPT is a powerful research tool, offering real-time and interactive visualizations that allow dynamic exploration of various topics [20]. Its ability to access new information from a number of different sources allows research to benefit from new data [20]. ChatGPT’s multiple views, the ability to review text, and dynamic interaction make for comprehensive and meaningful exploration. There is a debate about the reliability of the data provided by ChatGPT, but the answers of the technical adaptation model can be verified by document verification and the strength of the research method. Incorporating AI perspectives, ChatGPT offers a unique analytical framework for the study of technology acceptance, especially in the context of the elderly [20]. In addition, the diverse perspectives, innovation and accessibility of ChatGPT demonstrate its contribution to making research more innovative and responsive. Overall, ChatGPT can be considered to improve the effectiveness, efficiency and quality of research, making it a useful tool for generating real-time insights and insights [20].
Traditional models of technology acceptance often overlook the unique considerations and factors that affect the aging population [21, 22]. To narrow this gap, this study uses insights provided by ChatGPT, an advanced artificial intelligence model, to gain a unique perspective on technology acceptance in this population. Using ChatGPT as the primary research tool, this study aims to identify key constructs, areas of application, and challenges in TAM for geriatric healthcare. In addition, based on these research results, the aim of the study is to propose preventive measures for the challenges of TAM in elderly health care. Therefore, the findings should inform future research, policy making, and the development of interventions to improve technology acceptance among the older population.
Pdf) Conceptualizing Mobile Health Application Use Intention And Adoption Among Iraqian Older Adults: From The Perspective Of Expanded Technology Acceptance Model
This study used a qualitative and descriptive design to examine the key components of the Technology Decision Model, its practical applications, challenges and partners in geriatric health care.
This study used OpenAI’s interactive ChatGPT as a learning tool (OpenAI, L.L.C., San Francisco, CA, USA), and used the latest GPT version integrated with Microsoft applications. OpenAI, founded in December 2015 by Elon Musk, Sam Altman, and others, aims to make artificial intelligence (AGI) useful for humans. The development of ChatGPT is based on the Generative Pre-trained Transformer (GPT) architecture, launched with GPT-1 in June 2018, which demonstrates the power of pre-training neural networks large-scale natural language processing (NLP). GPT-2, introduced in February 2019, showed significant progress with 1.5 billion parameters, although access was limited due to abuse concerns. GPT-3, announced in June 2020, marked a breakthrough with 175 billion parameters, expanding the boundaries of language modeling. ChatGPT, a special application of the GPT model called Chat AI, improves chat systems and chat bots. OpenAI continues to pioneer AI research and development, collaborating globally to advance NLP and conversational AI while paying attention to ethical considerations.
