Baby Boomers’ Adoption of Consumer Health Technologies: Survey on Readiness and Barriers

Background As they age, baby boomers (born 1946-1964) will have increasing medical needs and are likely to place large demand on health care resources. Consumer health technologies may help stem rising health care needs and costs by improving provider-to-patient communication, health monitoring, and information access and enabling self-care. Research has not explored the degree to which baby boomers are ready for, or are currently embracing, specific consumer health technologies This study explores how baby boomers’ readiness to use various technologies for health purposes compares to other segments of the adult population. Objective The goals of the study are to (1) examine what technologies baby boomers are ready to use for health purposes, (2) investigate barriers to baby boomers’ use of technology for health purposes, and (3) understand whether readiness for and barriers to baby boomers’ use of consumer health technologies differ from those of other younger and older consumers. Methods Data were collected via a survey offered to a random sample of 3000 subscribers to a large pharmacy benefit management company. Respondents had the option to complete the survey online or by completing a paper-based version of the survey. Results Data from 469 respondents (response rate 15.63%) were analyzed, including 258 baby boomers (aged 46-64 years), 72 younger (aged 18-45 years), and 139 older (age >64 years) participants. Baby boomers were found to be similar to the younger age group, but significantly more likely than the older age group to be ready to use 5 technologies for health purposes (health information websites, email, automated call centers, medical video conferencing, and texting). Baby boomers were less ready than the younger age group to adopt podcasts, kiosks, smartphones, blogs, and wikis for health care purposes. However, baby boomers were more likely than older adults to use smartphones and podcasts for health care purposes. Specific adoption barriers vary according to the technology. Conclusions Baby boomers have commonalities with and distinctions from both younger and older adults in their readiness to adopt specific consumer health technologies and the barriers they experience to adoption. Baby boomers’ nuances regarding readiness to adopt and the barriers associated with the various forms of consumer health technology should be taken into account by those interested in promoting consumer health technologies use among baby boomers when developing applications, choosing technologies, preparing users for use, and in promotional tactics.

[1]  Barbara Wejnert Integrating models of diffusion of innovations: a Conceptual Framework. , 2002 .

[2]  Nicole Beebe,et al.  Improving Organizational Information Security Strategy via Meso-Level Application of Situational Crime Prevention to the Risk Management Process , 2010, Commun. Assoc. Inf. Syst..

[3]  Joseph F. Coughlin,et al.  Old Age, New Technology, and Future Innovations in Disease Management and Home Health Care , 2006 .

[4]  Viswanath Venkatesh,et al.  Model of Adoption and Technology in Households: A Baseline Model Test and Extension Incorporating Household Life Cycle , 2005, MIS Q..

[5]  V. Venkatesh,et al.  AGE DIFFERENCES IN TECHNOLOGY ADOPTION DECISIONS: IMPLICATIONS FOR A CHANGING WORK FORCE , 2000 .

[6]  Marion Gray,et al.  Baby boomers' use and perception of recommended assistive technology: A systematic review , 2009, Disability and rehabilitation. Assistive technology.

[7]  J. Strother Call Centers in Health Care: Effect on Patient Satisfaction , 2006, 2006 IEEE International Professional Communication Conference.

[8]  BJ Fogg,et al.  Creating persuasive technologies: an eight-step design process , 2009, Persuasive '09.

[9]  Richard Pak,et al.  Age-Sensitive Design of Online Health Information: Comparative Usability Study , 2009, Journal of medical Internet research.

[10]  Hyeoun-Ae Park,et al.  Development of a Health Information Technology Acceptance Model Using Consumers’ Health Behavior Intention , 2012, Journal of medical Internet research.

[11]  T. Bodenheimer,et al.  Patient self-management of chronic disease in primary care. , 2002, JAMA.

[12]  Thomas S. Tullis,et al.  Online Viewing and Aesthetic Preferences of Generation Y and the Baby Boom Generation: Testing User Web Site Experience Through Eye Tracking , 2011, Int. J. Electron. Commer..

[13]  Dorte Vistisen,et al.  Global healthcare expenditure on diabetes for 2010 and 2030. , 2010, Diabetes research and clinical practice.

[14]  J. J. Po-An Hsieh,et al.  ScholarWorks @ Georgia State University , 2016 .

[15]  Lazelle E Benefield,et al.  Technology for long-term care. , 2010, Research in gerontological nursing.

[16]  Tammie Lindquist,et al.  The boomers are coming: a total cost of care model of the impact of population aging on health care costs in the United States by Major Practice Category. , 2007, Health services research.

[17]  A. Shankar,et al.  The status of baby boomers' health in the United States: the healthiest generation? , 2013, JAMA internal medicine.

[18]  Elena Karahanna,et al.  Reconceptualizing Compatability Beliefs in Technology Acceptance Research , 2006, MIS Q..

[19]  C. Cowan,et al.  Health spending projections through 2017: the baby-boom generation is coming to Medicare. , 2008, Health affairs.

[20]  Mallory O. Johnson,et al.  The shifting landscape of health care: toward a model of health care empowerment. , 2011, American journal of public health.

[21]  Gary L. Kreps,et al.  Consumers’ Perceptions About and Use of the Internet for Personal Health Records and Health Information Exchange: Analysis of the 2007 Health Information National Trends Survey , 2010, Journal of medical Internet research.

[22]  Cynthia LeRouge,et al.  User profiles and personas in the design and development of consumer health technologies , 2013, Int. J. Medical Informatics.

[23]  Alex Mihailidis,et al.  The Acceptability of Home Monitoring Technology Among Community-Dwelling Older Adults and Baby Boomers , 2008, Assistive technology : the official journal of RESNA.

[24]  C. Manfredi,et al.  Factors Influencing Medical Information Seeking Among African American Cancer Patients , 2002, Journal of health communication.

[25]  D. Bouwhuis,et al.  When do older adults consider the Internet? An exploratory study of benefit perception , 2004 .

[26]  D. Bouwhuis,et al.  Older adults' motivated choice for technological innovation: evidence for benefit-driven selectivity. , 2006, Psychology and aging.

[27]  Ray Jones,et al.  Development of a Questionnaire and Cross-Sectional Survey of Patient eHealth Readiness and eHealth Inequalities , 2013, Medicine 2.0.

[28]  Pamela F. Wendt,et al.  Silver surfers: Training and evaluating internet use among older adult learners , 1999 .

[29]  Colin Mathers,et al.  The health of aging populations in China and India. , 2008, Health affairs.

[30]  Ron Weber Editor's Comments Volume 28 Iss. 2 , 2004 .

[31]  V. Freedman,et al.  Health and functioning among baby boomers approaching 60. , 2009, The journals of gerontology. Series B, Psychological sciences and social sciences.

[32]  Detmar W. Straub,et al.  Information Technology Adoption Across Time: A Cross-Sectional Comparison of Pre-Adoption and Post-Adoption Beliefs , 1999, MIS Q..

[33]  June Forkner-Dunn,et al.  Internet-based Patient Self-care: The Next Generation of Health Care Delivery , 2003, Journal of medical Internet research.

[34]  Alexander Johannes Aloysius Maria van Deursen,et al.  Internet skills performance tests: are people ready for eHealth? , 2011 .

[35]  Steven J Katz,et al.  The emerging role of online communication between patients and their providers , 2004, Journal of General Internal Medicine.

[36]  N. Selwyn,et al.  Older adults' use of information and communications technology in everyday life , 2003, Ageing and Society.

[37]  Patrick Y. K. Chau,et al.  Understanding Individual Adoption of Instant Messaging: An Empirical Investigation , 2005, J. Assoc. Inf. Syst..

[38]  Kar Yan Tam,et al.  The Effects of Post-Adoption Beliefs on the Expectation-Confirmation Model for Information Technology Continuance , 2006, Int. J. Hum. Comput. Stud..

[39]  Hans van der Heijden,et al.  User Acceptance of Hedonic Information Systems , 2004, MIS Q..

[40]  David Meyer,et al.  The role of perceived enjoyment and social norm in the adoption of technology with network externalities , 2008, Eur. J. Inf. Syst..

[41]  Paul Jen-Hwa Hu,et al.  Information Technology Acceptance by Individual Professionals: A Model Comparison Approach , 2001, Decis. Sci..