Literature DB >> 31328567

Using Technology Adoption Theory and a Lifespan Approach to Develop a Theoretical Framework for eHealth Literacy: Extending UTAUT.

Kate Magsamen-Conrad1, Fang Wang2, Dinah Tetteh3, Yen-I Lee4.   

Abstract

Advancements in health information technology (HealthIT) and the electronic exchanges of health information have "revolutionized" health systems in the US. However, adopting technological developments into the healthcare system has the potential to benefit populations with more resources, further exacerbating health status disparities. Efficacious utilization of HealthIT requires eHealth literacy. Although eHealth literacy is comprised of six factors, new research indicates that the components related to technology literacy may be more impactful in eHealth literacy among certain populations (e.g., older populations who shoulder a greater illness-management burden). Recognizing the importance of technology literacy in eHealth literacy across the lifespan, we investigate generational differences in New Communication Technology (NCT) use and eHealth literacy, especially considering how NCT adoption theory might systematically inform scholars' understanding of eHealth literacy. Participants included 525 adults primarily in the Midwestern United States. We found significant differences between generational groups across all variables. We found that UTAUT determinants such as performance expectancy and effort expectancy explained 38% of the variance in eHealth literacy, controlling for age, sex, level of education, and prior online health information seeking. Finally, we engaged with early critiques of UTAUT, finding that when applying UTAUT in voluntary (vs. mandatory) contexts, scholars should reconsider variables previously dismissed, such as attitude. In doing this, we extend UTAUT in three ways: new contexts (voluntary NCT adoption), endogenous theoretical mechanisms (eHealth literacy), and exogenous variables (attitude; lifespan). These findings underscore a need for a targeted approach to improve eHealth literacy and health self-management across generations.

Entities:  

Mesh:

Year:  2019        PMID: 31328567     DOI: 10.1080/10410236.2019.1641395

Source DB:  PubMed          Journal:  Health Commun        ISSN: 1041-0236


  6 in total

Review 1.  Adherence to r-hGH Therapy in Pediatric Growth Hormone Deficiency: Current Perspectives on How Patient-Generated Data Will Transform r-hGH Treatment Towards Integrated Care.

Authors:  Martin O Savage; Luis Fernandez-Luque; Selina Graham; Paula van Dommelen; Matheus Araujo; Antonio de Arriba; Ekaterina Koledova
Journal:  Patient Prefer Adherence       Date:  2022-07-11       Impact factor: 2.314

2.  Generation Gaps in Digital Health Literacy and Their Impact on Health Information Seeking Behavior and Health Empowerment in Hungary.

Authors:  Orsolya Papp-Zipernovszky; Mária Dóra Horváth; Peter J Schulz; Márta Csabai
Journal:  Front Public Health       Date:  2021-05-13

3.  Determinants of the behavioral intention to use a mobile nursing application by nurses in China.

Authors:  Minghao Pan; Wei Gao
Journal:  BMC Health Serv Res       Date:  2021-03-12       Impact factor: 2.655

4.  Acceptance of clinical decision support system to prevent venous thromboembolism among nurses: an extension of the UTAUT model.

Authors:  Huixian Zha; Kouying Liu; Ting Tang; Yue-Heng Yin; Bei Dou; Ling Jiang; Hongyun Yan; Xingyue Tian; Rong Wang; Weiping Xie
Journal:  BMC Med Inform Decis Mak       Date:  2022-08-19       Impact factor: 3.298

5.  The Perceptions and Experiences of Mobile Health Technology by Older People in Guangzhou, China: A Qualitative Study.

Authors:  Jiong Tu; Manxuan Shen; Jiudi Zhong; Gang Yuan; Miaohong Chen
Journal:  Front Public Health       Date:  2021-06-25

6.  Framing the numerical findings of Cochrane plain language summaries: two randomized controlled trials.

Authors:  Ivan Buljan; Ružica Tokalić; Marija Roguljić; Irena Zakarija-Grković; Davorka Vrdoljak; Petra Milić; Livia Puljak; Ana Marušić
Journal:  BMC Med Res Methodol       Date:  2020-05-06       Impact factor: 4.615

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.