Using the Technology Acceptance Model to Explore User Experience, Intent to Use, and Use Behavior of a Patient Portal Among Older Adults With Multiple Chronic Conditions: Descriptive Qualitative Study

Portz, Jennifer Dickman; Bayliss, Elizabeth A.; Bull, Sheana; Boxer, Rebecca S.; Bekelman, David B.; Gleason, Kathy; Czaja, Sara J.

doi:10.2196/11604

Cited by 222 publications

(223 citation statements)

References 32 publications

(42 reference statements)

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“…Future research should explore how, if at all, frameworks such as the Ottawa Decision Support Framework [ 43 ] and models such as Technology Acceptance Model may help explain our findings [ 44 ]. Related, more research is needed to understand the various mechanisms by which electronic wearable devices to monitor health (ie, activity trackers or blood pressure monitors) and the sharing of information from these devices with health professionals may have an impact on subsequent medical decision making and behavioral outcomes such as cancer screening, weight management, and dietary patterns.…”

Section: Discussionmentioning

confidence: 99%

Use of Tablets and Smartphones to Support Medical Decision Making in US Adults: Cross-Sectional Study

Langford¹,

Orellana²,

Kalinowski³

et al. 2020

JMIR Mhealth Uhealth

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Background Tablet and smartphone ownership have increased among US adults over the past decade. However, the degree to which people use mobile devices to help them make medical decisions remains unclear. Objective The objective of this study is to explore factors associated with self-reported use of tablets or smartphones to support medical decision making in a nationally representative sample of US adults. Methods Cross-sectional data from participants in the 2018 Health Information National Trends Survey (HINTS 5, Cycle 2) were evaluated. There were 3504 responses in the full HINTS 5 Cycle 2 data set; 2321 remained after eliminating respondents who did not have complete data for all the variables of interest. The primary outcome was use of a tablet or smartphone to help make a decision about how to treat an illness or condition. Sociodemographic factors including gender, race/ethnicity, and education were evaluated. Additionally, mobile health (mHealth)- and electronic health (eHealth)-related factors were evaluated including (1) the presence of health and wellness apps on a tablet or smartphone, (2) use of electronic devices other than tablets and smartphones to monitor health (eg, Fitbit, blood glucose monitor, and blood pressure monitor), and (3) whether people shared health information from an electronic monitoring device or smartphone with a health professional within the last 12 months. Descriptive and inferential statistics were conducted using SAS version 9.4. Weighted population estimates and standard errors, univariate odds ratios, and 95% CIs were calculated, comparing respondents who used tablets or smartphones to help make medical decisions (n=944) with those who did not (n=1377), separately for each factor. Factors of interest with a P value of <.10 were included in a subsequent multivariable logistic regression model. Results Compared with women, men had lower odds of reporting that a tablet or smartphone helped them make a medical decision. Respondents aged 75 and older also had lower odds of using a tablet or smartphone compared with younger respondents aged 18-34. By contrast, those who had health and wellness apps on tablets or smartphones, used other electronic devices to monitor health, and shared information from devices or smartphones with health care professionals had higher odds of reporting that tablets or smartphones helped them make a medical decision, compared with those who did not. Conclusions A limitation of this research is that information was not available regarding the specific health condition for which a tablet or smartphone helped people make a decision or the type of decision made (eg, surgery, medication changes). In US adults, mHealth and eHealth use, and also certain sociodemographic factors are associated with using tablets or smartphones to support medical decision making. Findings from this study may inform future mHealth and other digital health interventions designed to support medical decision making.

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Section: Discussionmentioning

confidence: 99%

Use of Tablets and Smartphones to Support Medical Decision Making in US Adults: Cross-Sectional Study

Langford¹,

Orellana²,

Kalinowski³

et al. 2020

JMIR Mhealth Uhealth

View full text Add to dashboard Cite

show abstract

“…This was true for even those older adults without previous experience and/or low experience with technology who had difficulty with data entry issues. Thus, education and training are essential for older adults to successfully use navigational devices [42,43] as well as other technology [29,40] and this education will be most successful with hands on learning and practice with an actual device [27].…”

Section: Discussionmentioning

confidence: 99%

“…However, in a survey of older adults in Australia [28], many older adults were not sure how GPS worked or thought they may be too complicated to operate. When concerning technology, barriers include user interface and user experience preferences of older adults [29]. Thus, the TAM may be a useful modeling for understanding the technology acceptance behavior of older adults, paired with the characteristics, abilities and problems experienced by older adults [30].…”

Section: Introductionmentioning

confidence: 99%

Use of GPS for Older Adults to Decrease Driving Risk: Perceptions from Users and Non-Users

Dickerson¹

2020

Geriatrics

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Community mobility is important for social participation and quality of life. Thus, it is important to sustain older adults in their communities by supporting their ability to drive as long as possible. Use of global positioning system (GPS) technology may provide such support. This descriptive study examined 89 healthy community older adults’ perspective on using and programming a GPS after using it for wayfinding to unfamiliar destinations. Participants were equally divided between two age groups (60s, 70s) and familiarity with GPS (familiar, unfamiliar). The results showed age differences in problems following GPS directions and those who were familiar found it significantly easier to use. The majority of the unfamiliar group indicated an increased interest in using GPS and were significantly more interested in training to use a GPS. Preference for learning how to use a GPS included in-person delivery and practice with troubleshooting, using the menus and changing routes as topics critical for training. The implications of these results are discussed.

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“…We developed three semi-structured interview guides targeting each sample group: patients, convoy, and health care providers (Appendix II). The guide was first drafted by the principle investigator (J. D. P) based on our previous qualitative work with older adults regarding digital health 24 and refined by geriatric, palliative care, and digital health experts (R. S. B., D. B. B., S. C., and S.…”

Section: Data Collectionmentioning

confidence: 99%

Using Grounded Theory to Inform the Human-Centered Design of Digital Health in Geriatric Palliative Care

Portz

Ford

Doyon

et al. 2020

Journal of Pain and Symptom Management

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Context. Digital health offers innovative mechanisms to engage in palliative care, yet digital systems are typically designed for individual users, rather than integrating the patient's caregiving ''social convoy'' (i.e., family members, friends, neighbors, formal caregiving supports) to maximize benefit. As older adults with serious illness increasingly rely on the support of others, there is a need to foster effective integration of the social convoy in digitally supported palliative care. Objectives. Conduct a qualitative study examining patient, social convoy, and health care provider perspectives on digital health for palliative care to inform the design of future digital solutions for older adults with serious illness and their social convoy. Methods. Grounded theory approach using semi-structured interviews (N ¼ 81) with interprofessional health care providers, older adults with serious illness, and their social convoy participants at home, clinic, or Zoom. Interviews were conducted using question guides relevant to the participant group and audio-recorded for verbatim transcription. Two coders lead the inductive analysis using open and axial coding. Results. Thematic results aligned with the human-centered design framework, which is a participatory approach to the design process that incorporates multiple user stakeholders to develop health solutions. The human-centered design process and corresponding theme included the following: 1) Empathy: Patient, Caregiver, and Provider Experience reports participants' experience with managing serious illness, caregiving, social support, and technology use. 2) Define: Reactions to Evidence-Based Care Concepts and Barriers illustrates participants' perspectives on the domains of palliative care ranging from symptom management to psychosocial-spiritual care. 3) Ideation: Desired Features reports participant recommendations for designing digital health tools for palliative care domains. Conclusion. Digital health provides an opportunity to expand the reach of geriatric palliative care interventions. This paper documents human-centered preferences of geriatric palliative care digital health to ensure technologies are relevant and meaningful to health care providers, patients, and the caregiving social convoy.

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Using the Technology Acceptance Model to Explore User Experience, Intent to Use, and Use Behavior of a Patient Portal Among Older Adults With Multiple Chronic Conditions: Descriptive Qualitative Study

Cited by 222 publications

References 32 publications

Use of Tablets and Smartphones to Support Medical Decision Making in US Adults: Cross-Sectional Study

Use of Tablets and Smartphones to Support Medical Decision Making in US Adults: Cross-Sectional Study

Use of GPS for Older Adults to Decrease Driving Risk: Perceptions from Users and Non-Users

Using Grounded Theory to Inform the Human-Centered Design of Digital Health in Geriatric Palliative Care

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