Technological capital within aging United States-based populations: challenges and recommendations for online intervention uptake

ABSTRACT

Aging adults experience a disproportionate number of health-related problems. We applied a technological capital framework to assess how participation in web-delivered interventions is influenced by resources, perceived support, technology skills, and an overall environment conducive to making a change. Specifically, we conducted an in-depth examination of the uses and attitudes regarding online health information technologies among 41 middle-aged and older adults (‘digital immigrants’). Situated in a six-year community ethnography, this qualitative study identifies potential barriers confronting middle-aged and older adults’ engagement with online interventions and extends existing work on the four factors comprising technological capital (awareness, knowledge, access, and technological capacity). We found six major themes related to ICT use: literacy, comfort, adoption willingness, infrastructure, information security, and support availability. We provide evidence-based recommendations for overcoming barriers, and recommendations for assessing and teaching information technology skills across the lifespan without being ageist.

KEYWORDS:

• Technological capital
• health information technology
• information communication technology
• digital divide
• privacy
• security
• life span
• health communication

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 We use the term ‘HealthIT’ in this article to describe the assortment of technologies that store, share, and analyze health information – including a variety of tools that help people maintain and/or improve health, from physician-initiated systems that store, track, and coordinate health information to patient- or expert- initiated e-Health tools such as websites, apps, and devices. However, we did not use the word ‘HealthIT’ with our participants.

Additional information

Funding

The research was funded, in part, by the Bowling Green State University Office of the Vice President for Research and Economic Development 2013 Building Strength Program and the Bowling Green State University Service Learning Community (2013), and also by the Optimal Aging Institute, Bowling Green State University, which has core funding from Medical Mutual of Ohio.

Additionally, this research was supported in part by the Center for Family and Demographic Research, Bowling Green State University, which has core funding from the Eunice Kennedy Shriver National Institute of Child Health and Human Development [R24HD050959]. This work was also partially supported by the University of Texas at Austin/Portugal International Collaboration for Emerging Technologies (CoLab) and Portuguese Foundation of Science and Technology (FCT).