In studying the effectiveness of telemedicine in managing chronic illnesses compared to in-person visits, the study can be based on several theories. These theories include the technology acceptance model (TAM), the self-efficacy theory, and the health belief model (HBM).
Process and Logic in Selecting the Frameworks
The selection of the frameworks was based on the literature review conducted, checking the relevance of the frameworks to the research question, and determining the compatibility of the frameworks with the research methodology. These considerations led to the selection of HBM, TAM, and self-efficacy theories to form the foundation of the study in answering the research question. The technology acceptance model (TAM) suggests that the perception of usefulness and ease of use of technology, such as telemedicine, affects the adoption and continued use of the technology (Kamal, Shafiq, & Kakria, 2020). In the case of telemedicine, the perception of usefulness and ease of use in managing chronic diseases can influence its adoption and continued use in older adults.
The health belief model (HBM) posits that individuals’ health-related behaviors are influenced by their perceptions of susceptibility to a health threat, the severity of the threat, and their perceived control over the threat. In this context, older adults with chronic diseases may be more likely to adopt telemedicine if they perceive it to effectively manage their chronic conditions and increase their perceived control over their health. The self-efficacy theory states that an individual’s beliefs about their ability to perform a behavior influence their actual behavior (Alpar & Driebe, 2021). In this context, older adults with chronic diseases may be more likely to adopt telemedicine and use it effectively if they believe that they can use technology and understand how it can benefit them in managing their chronic conditions (Söylemez et al., 2022). By incorporating these theories, the theoretical framework for the PICOT question can provide a comprehensive understanding of the factors that influence the adoption and effectiveness of telemedicine in managing chronic diseases in older adults.
Assumptions and Components of the Framework
This framework assumes that older adults with chronic diseases are more likely to adopt telemedicine if they perceive it to be valuable and easy to use. However, if they deem it a challenge, they are less likely to accept its use (Kamal, Shafiq, & Kakria, 2020). The other assumption of this framework is that the use of telemedicine is likely to increase the perceived control that older adults have over their health and, in the process, can reduce the susceptibility that they have to various threats (An et al., 2021). The other primary assumption is that older adults are more likely to utilize the use of telemedicine in a way that is effective if they believe that they are capable of using it and they understand the various ways that it can benefit them in the process of managing chronic conditions.
As mentioned earlier, the critical components of the framework are TAM, HBM, and self-efficacy theories. These theories help understand how older adults relate to the proposed technology and the likelihood that they will adopt it to manage their chronic illnesses. The three components of the framework also help understand how effective the use of the technology can be for older adults with mobility issues.
Application of the Phenomenon to the Framework
The phenomenon under study is telemedicine’s effectiveness in managing chronic illnesses such as diabetes. The TAM components relate directly to users’ perception of the usefulness and ease of use of the technology (Kamal, Shafiq, & Kakria, 2020). As mentioned earlier, older adults who may not be able to honor appointments due to mobility issues are likely to adopt telemedicine if they think that the technology is easy to use and valuable in managing their illnesses (An et al., 2021). The element of the phenomenon related to the influence of older adults’ perceptions of susceptibility to health threats, the severity of the threats, and their perceived control over the threats apply to the HBM component of the framework (Alpar & Driebe, 2021). Older adults with chronic diseases are more likely to adopt telemedicine if they perceive that it can help reduce their perceived susceptibility to health threats and increase their perceived control over their health. The element of the phenomenon related to the influence of older adults’ beliefs about their ability to use technology and understand how it can benefit them in managing their chronic conditions applies to the self-efficacy component of the framework (Söylemez et al., 2022). Older adults are more likely to use telemedicine effectively if they believe they can use technology and understand how it can benefit them in managing their chronic conditions.
Regarding the sample selection criteria, the framework reveals that the study needs to focus on older adults with chronic illnesses since they act as the primary target for telemedicine services. The sample should also focus on individuals who have used telemedicine in dealing with their illnesses (Kamal, Shafiq, & Kakria, 2020). In addition, the sample population should have a positive perception of the ease of use and usefulness of the technology. The population should also view technology positively in dealing with various health threats that they may be dealing with due to chronic illnesses. In addition, it is essential to ensure that the sample population positively believes in their ability to apply the technology and comprehend its benefits in dealing with chronic conditions.
Discussion, Analysis, and Critique of Research that Uses the Framework
Research that uses this framework can start by searching the relevant literature using reputable databases such as PubMed and CINAHL. A review of the studies follows this to determine if they are relevant to the research question. Such research should also evaluate the methods to determine if they are appropriate for the research question and if the data collected is reliable. The results should also be evaluated to determine if they have evidence for the framework and if they effectively address the research question. This is followed by critiquing the conclusions arrived at by the studies in terms of whether they contribute new findings in the field of telemedicine.
References
Alpar, P., & Driebe, T. (2021). Patients’ attitudes toward apps for the management of chronic disease. Lecture Notes in Information Systems and Organisation, 22-37. https://doi.org/10.1007/978-3-030-86790-4_2
Kamal, S. A., Shafiq, M., & Kakria, P. (2020). Investigating acceptance of telemedicine services through an extended technology acceptance model (TAM). Technology in Society, 60, 101212. https://doi.org/10.1016/j.techsoc.2019.101212
An, M. H., You, S. C., Park, R. W., & Lee, S. (2021). Using an extended technology acceptance model to understand the factors influencing Telehealth utilization after flattening the COVID-19 curve in South Korea: Cross-sectional survey study. JMIR Medical Informatics, 9(1), e25435. https://doi.org/10.2196/25435
Söylemez, B. A., Özgül, E., Küçükgüçlü, Ö., & Yener, G. (2022). Telehealth applications used for self-efficacy levels of family caregivers for individuals with dementia: A systematic review and meta-analysis. Geriatric Nursing, 49, 178-192. https://doi.org/10.1016/j.gerinurse.2022.12.001
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