Presentation
DH16 - Using the Integrated Model as the Foundation of Intrinsic Motivation
DescriptionGlobally, we are quickly approaching a point where the older adult population will double in 2050 (World Health Organization, 2022). As older adults continue to age and live longer than before, their susceptibility to chronic health conditions such as diabetes or heart conditions increases throughout their lifetime. As of 2017, about 85% of American older adults had at least one chronic illness, and ~60% had at least two (National Institute on Aging, 2023). Many tools are available to assist older adults in managing health conditions and medications, preventing chronic illness, and maintaining wellness to continue their activities of daily living as well as recreational activities. Digital health portals have the potential to act as a communication platform, electronic health record, appointment management system, and include many more features. However, for digital health portals to be effective, older adults must be motivated to utilize them with the intent to encourage self-care and sustained usage.
What do older adults need to be motivated to adopt their digital health portal effectively? We explored this question in a study including 26 American older adults aged 60 -85 who logged into their digital health portal at least twice a year. The first part of the study consisted of multiple surveys assessing technology readiness and technology experience. Then, older adults were interviewed using a semi-structured interview that included questions about their usual digital health portal usage (e.g., why did you start using your digital health portal or what activities do you track in your digital health portal). The interview structure was a modified version of the Technology Readiness Index 2.0 (Parasuraman & Colby, 2015). The modifications were made to collect data related to digital health technology. Once the interviews were conducted, we organized the responses using Self Determination Theory (SDT; Deci & Ryan, 1985) and the Unified Theory of Acceptance of Use of Technology (UTAUT; Venkatesh et al., 2003) model.
SDT is a framework focused on intrinsic motivation and how people are motivated to change and grow. SDT can be useful in understanding how to design digital health portals that support intrinsic motivation, leading to long-term usage. To support digital health portal design, SDT can be used to provide insights about sources of intrinsic and extrinsic facilitators through the concepts of autonomy, competence, and relatedness. Autonomy refers to the choice to do something, competence is the sense of mastery over skills needed to complete a task, and relatedness is a sense of belonging with others. When all three factors are fulfilled, there is a foundation for intrinsic motivation and self-determination.
UTAUT is a model focused on technology acceptance and can be used to assess and design digital health portals that are easier to use and support usage of its features. It contains extrinsic factors influencing the intention to use technology, such as performance expectancy, effort expectancy, social influence, and facilitating conditions. We used the UTAUT model to categorize facilitators and barriers of technology adoption. Performance expectancy and effort expectancy are like perceived usefulness (how useful something is) and perceived ease of use (how easily something can be used). Social influence is the degree “to which an individual perceives that important others believe he or she should use the new system” (Venkatesh et al., 2003, p. 431). Facilitating conditions are the extent to which an individual perceives that they receive adequate support to use a system. When competence is established, performance expectancy and effort expectancy facilitate the usage of digital health portals.
We proposed that combining the concepts of motivation and technology acceptance in the SDT & UTAUT Integrated Model yields a framework to identify whether an older adult was intrinsically motivated to adopt or if they lacked motivators or facilitators in certain areas. The integration of the theory and model highlights aspects of motivation and technology acceptance. The UTAUT model is only effective when an older adult is already motivated to adopt digital health portals. The concepts of SDT allow us to understand why some older adults may be more motivated than others, whereas UTAUT was used to understand more about technology acceptance and initial adoption. We used this framework to analyze the older adults’ responses.
After analyzing the data, we found that when factors of either SDT or UTAUT were missing, frustration or demotivation occurred. All the responses were coded using the concepts of the Integrated SDT-UTAUT Model. Overall, our Integrated SDT-UTAUT Model represents the foundation of intrinsic motivation—whether the older adult has the necessary support and facilitators for adopting their digital health portal. We found that older adults had many facilitators, including convenience, viewing test results, appointment tracking, and receiving recommendations from others. This shows that both perceived usefulness and autonomy are important in the motivation for adopting digital health portals. All 26 older adults were willing to adopt a digital health portal for their self-monitoring needs.
We also explored whether the older adults were encouraged to use their digital health portal by someone else, whether they felt supported when using it, or if they had questions about where they would look for assistance, such as a clinician. Of the 26 older adults, 24 shared that they had a positive experience using their digital health portal. We found that most of the older adults chose to adopt, and most had the necessary skills to utilize their digital health portal features efficiently. We also asked participants what features should be implemented to enhance their experience using the digital health portal interface. The older adults preferred uniform design across their digital health portals, such as interfaces with the same standard features. They also shared that a customizable screen (e.g., what should be added to their initial home page, hiding unused features) would allow them to tailor the interface to their needs.
In general, motivation must already be present in some capacity for facilitators or motivators to be effective in intrinsic motivation. Missing aspects for motivation or technology acceptance could be identified using the SDT & UTAUT Integrated Model. Important factors were whether the older adults found the digital health portal to be useful, as well as easy to use. We also found high social influence to use a digital health portal. By using the Integrated Model, it gives us a high-level summary on how motivated an older adult may be to accept new health technology and what is necessary to push them towards acceptance.
In the future, the Integrated SDT-UTAUT Model could be applied to different forms of digital health technology and demographic groups. When the user is self-determined, they are more likely to adopt the technology long-term. Designing with the intention for long-term usage depends on intrinsic motivation after the initial adoption of the new health technology. The Integrated Model identifies aspects where clinicians could be used to facilitate the adoption of digital health technology; clinicians should be more proactive in promoting current digital health technology, such as health portals and educational websites.
References:
Deci, E. L., & Ryan, R. M. (1985). Intrinsic Motivation and Self-Determination in Human Behavior. Springer US. https://doi.org/10.1007/978-1-4899-2271-7
Parasuraman, A., & Colby, C. L. (2015). An updated and streamlined Technology Readiness Index: TRI 2.0. Journal of Service Research, 18(1), 59–74. https://doi.org/10.1177/1094670514539730
Talking With Your Older Patients. (n.d.). National Institute on Aging. Retrieved September 29, 2023, from https://www.nia.nih.gov/health/talking-your-older-patients
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540
World Health Organization. (2022, October 1). Ageing and health. World Health Organization. https://www.who.int/news-room/fact-sheets/detail/ageing-and-health
What do older adults need to be motivated to adopt their digital health portal effectively? We explored this question in a study including 26 American older adults aged 60 -85 who logged into their digital health portal at least twice a year. The first part of the study consisted of multiple surveys assessing technology readiness and technology experience. Then, older adults were interviewed using a semi-structured interview that included questions about their usual digital health portal usage (e.g., why did you start using your digital health portal or what activities do you track in your digital health portal). The interview structure was a modified version of the Technology Readiness Index 2.0 (Parasuraman & Colby, 2015). The modifications were made to collect data related to digital health technology. Once the interviews were conducted, we organized the responses using Self Determination Theory (SDT; Deci & Ryan, 1985) and the Unified Theory of Acceptance of Use of Technology (UTAUT; Venkatesh et al., 2003) model.
SDT is a framework focused on intrinsic motivation and how people are motivated to change and grow. SDT can be useful in understanding how to design digital health portals that support intrinsic motivation, leading to long-term usage. To support digital health portal design, SDT can be used to provide insights about sources of intrinsic and extrinsic facilitators through the concepts of autonomy, competence, and relatedness. Autonomy refers to the choice to do something, competence is the sense of mastery over skills needed to complete a task, and relatedness is a sense of belonging with others. When all three factors are fulfilled, there is a foundation for intrinsic motivation and self-determination.
UTAUT is a model focused on technology acceptance and can be used to assess and design digital health portals that are easier to use and support usage of its features. It contains extrinsic factors influencing the intention to use technology, such as performance expectancy, effort expectancy, social influence, and facilitating conditions. We used the UTAUT model to categorize facilitators and barriers of technology adoption. Performance expectancy and effort expectancy are like perceived usefulness (how useful something is) and perceived ease of use (how easily something can be used). Social influence is the degree “to which an individual perceives that important others believe he or she should use the new system” (Venkatesh et al., 2003, p. 431). Facilitating conditions are the extent to which an individual perceives that they receive adequate support to use a system. When competence is established, performance expectancy and effort expectancy facilitate the usage of digital health portals.
We proposed that combining the concepts of motivation and technology acceptance in the SDT & UTAUT Integrated Model yields a framework to identify whether an older adult was intrinsically motivated to adopt or if they lacked motivators or facilitators in certain areas. The integration of the theory and model highlights aspects of motivation and technology acceptance. The UTAUT model is only effective when an older adult is already motivated to adopt digital health portals. The concepts of SDT allow us to understand why some older adults may be more motivated than others, whereas UTAUT was used to understand more about technology acceptance and initial adoption. We used this framework to analyze the older adults’ responses.
After analyzing the data, we found that when factors of either SDT or UTAUT were missing, frustration or demotivation occurred. All the responses were coded using the concepts of the Integrated SDT-UTAUT Model. Overall, our Integrated SDT-UTAUT Model represents the foundation of intrinsic motivation—whether the older adult has the necessary support and facilitators for adopting their digital health portal. We found that older adults had many facilitators, including convenience, viewing test results, appointment tracking, and receiving recommendations from others. This shows that both perceived usefulness and autonomy are important in the motivation for adopting digital health portals. All 26 older adults were willing to adopt a digital health portal for their self-monitoring needs.
We also explored whether the older adults were encouraged to use their digital health portal by someone else, whether they felt supported when using it, or if they had questions about where they would look for assistance, such as a clinician. Of the 26 older adults, 24 shared that they had a positive experience using their digital health portal. We found that most of the older adults chose to adopt, and most had the necessary skills to utilize their digital health portal features efficiently. We also asked participants what features should be implemented to enhance their experience using the digital health portal interface. The older adults preferred uniform design across their digital health portals, such as interfaces with the same standard features. They also shared that a customizable screen (e.g., what should be added to their initial home page, hiding unused features) would allow them to tailor the interface to their needs.
In general, motivation must already be present in some capacity for facilitators or motivators to be effective in intrinsic motivation. Missing aspects for motivation or technology acceptance could be identified using the SDT & UTAUT Integrated Model. Important factors were whether the older adults found the digital health portal to be useful, as well as easy to use. We also found high social influence to use a digital health portal. By using the Integrated Model, it gives us a high-level summary on how motivated an older adult may be to accept new health technology and what is necessary to push them towards acceptance.
In the future, the Integrated SDT-UTAUT Model could be applied to different forms of digital health technology and demographic groups. When the user is self-determined, they are more likely to adopt the technology long-term. Designing with the intention for long-term usage depends on intrinsic motivation after the initial adoption of the new health technology. The Integrated Model identifies aspects where clinicians could be used to facilitate the adoption of digital health technology; clinicians should be more proactive in promoting current digital health technology, such as health portals and educational websites.
References:
Deci, E. L., & Ryan, R. M. (1985). Intrinsic Motivation and Self-Determination in Human Behavior. Springer US. https://doi.org/10.1007/978-1-4899-2271-7
Parasuraman, A., & Colby, C. L. (2015). An updated and streamlined Technology Readiness Index: TRI 2.0. Journal of Service Research, 18(1), 59–74. https://doi.org/10.1177/1094670514539730
Talking With Your Older Patients. (n.d.). National Institute on Aging. Retrieved September 29, 2023, from https://www.nia.nih.gov/health/talking-your-older-patients
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540
World Health Organization. (2022, October 1). Ageing and health. World Health Organization. https://www.who.int/news-room/fact-sheets/detail/ageing-and-health
Event Type
Poster Presentation
TimeTuesday, March 264:45pm - 6:15pm CDT
LocationSalon C
Digital Health
Simulation and Education
Hospital Environments
Medical and Drug Delivery Devices
Patient Safety Research and Initiatives