References
- U.S. Census Bureau. (2016). Facts for features: Older Americans month, May. Available from: https://www.census.gov/newsroom/facts-for-features/2016/cb16-ff08.html.
- Anderson M, Perrin A. Tech adoption climbs among older adults. Pew Research Center; 2017. Available from: https://www.pewresearch.org/internet/2017/05/17/tech-adoption-climbs-among-older-adults/.
- Hale TM, Cotten SR, Drentea P, Goldner M. Rural-urban differences in general and health-related internet use. Am Behav Sci. 2010;53(9):1304–25.
- DiMaggio P, Hargittai E. From the ‘digital divide’ to ‘digital inequality’: studying internet use as penetration increases. Princeton (NJ): Center for Arts and Cultural Policy Studies, Woodrow Wilson School, Princeton University; 2001.
- Howard P, Busch L, Sheets P. Comparing digital divides: internet access and social inequality in Canada and the United States. Can J Commun. 2010;35:1.
- Ono H, Zavodny M. Digital inequality: a five country comparison using microdata. Soc Sci Res. 2007;36(3):1135–55.
- Schreuers K, Quan-Haase A, Martin K. Problematizing the digital literacy paradox in the context of older adults’ ICT use: aging, media discourse, and self-determination. Can J Commun. 2017;42(2):360–377.
- Chen W, Wellman B. Minding the cyber-gap: the internet and social inequality. In: Romero M, Margolis E, editors. The Blackwell companion to social inequalities. Malden (MA): Blackwell Publishing Ltd; 2005. p. 523–45.
- Harvard Health. (2017). Help with online health. Available from: https://www.health.harvard.edu/staying-healthy/help-with-online-health
- Fox S, Duggan M. Health online 2013. Pew Research Center; 2013. Available from: https://www.pewresearch.org/internet/2013/01/15/health-online-2013/
- Hall AK, Bernhardt JM, Dodd V. Older adults’ use of online and offline sources of health information and constructs of reliance and self-efficacy for medical decision making. J Health Commun. 2015;20(7):751–8.
- Arning K, Ziefle M. Understanding age differences in PDA acceptance and performance. Comput Human Behav. 2007;23(6):2904–27.
- Dogruel L, Joeckel S, Bowman ND. The use and acceptance of new media entertainment technology by elderly users: Development of an expanded technology acceptance model. Behav Inf Technol. 2015;34(11):1052–63.
- Choi N. Relationship between health service use and health information technology use among older adults: analysis of the US National health Interview Survey. J Med Internet Res. 2011;13(2):e33.
- Jackson LA, Zhao Y, Kolenic III A, Fitzgerald HE, Harold R, Von Eye A. Race, gender, and information technology use: the new digital divide. Cyberpsychol Behav. 2008;11(4):437–42.
- Yardi S, Bruckman A. Income, race, and class: exploring socioeconomic differences in family technology use. In: Proceedings of the SIGCHI conference on human factors in computing systems. 2012, May 5–10; Austin, Texas, USA. p. 3041–50.
- Chung JE, Park N, Wang H, Fulk J, McLaughlin M. Age differences in perceptions of online community participation among non-users: an extension of the technology acceptance Model. Comput Human Behav. 2010;26(6):1674–84.
- Deng Z, Mo X, Liu S. Comparison of the middle-aged and older users’ adoption of mobile health services in China. Int J Med Inf. 2014;83(3):210–24.
- Heart T, Kalderon E. Older adults: are they ready to adopt health-related ICT? Int J Med Inf. 2013;82(11):e209–31.
- Charbonneau DH. Public library websites and adherence to senior-friendly guidelines. Public Libr Quart. 2014;33(2):121–30.
- Hart TA, Chaparro BS, Halcomb CG. Evaluating websites for older adults: adherence to ‘senior-friendly’ guidelines and end-user performance. Behav Inf Technol. 2008;27(3):191–9.
- Nahm ES, Preece J, Resnick B, Mills ME. Usability of health web sites for older adults: a preliminary study. CIN Comput Inform Nurs. 2004;22(6):326–34.
- Davis FD. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 1989;13(3):319–40.
- Choi G, Chung H. Applying the technology acceptance model to social networking sites (SNS): impact of subjective norm and social capital on the acceptance of SNS. Int J Hum Comput Interact. 2013;29(10):619–28.
- Schierz PG, Schilke O, Wirtz BW. Understanding consumer acceptance of mobile payment services: an empirical analysis. Electron Commer Res Appl. 2010;9(3):209–16.
- Park SY, Nam MW, Cha SB. University students’ behavioral intention to use mobile learning: evaluating the technology acceptance model. Br J Educ Technol. 2012;43(4):592–605.
- Pai FY, Huang KI. Applying the technology acceptance model to the introduction of healthcare information systems. Technol Forecast Soc Change. 2011;78(4):650–60.
- Rese A, Schreiber S, Baier D. Technology acceptance modeling of augmented reality at the point of sale: can surveys be replaced by an analysis of online reviews? J Retail Consum Serv. 2014;21(5):869–76.
- Chang CC, Yan CF, Tseng JS. Perceived convenience in an extended technology acceptance model: mobile technology and English learning for college students. Aust J Educ Technol. 2012;28(5):809–26.
- Lehtinen V, Näsänen J, Sarvas R. A little silly and empty-headed: older adults’ understandings of social networking sites. In: Proceedings of the 23rd British HCI Group Annual Conference on People and Computers: Celebrating People and Technology. British Computer Society; 2009, September. p. 45–54.
- Xie B, Watkins I, Golbeck J, Huang M. Understanding and changing older adults’ perceptions and learning of social media. Educ Gerontol. 2012;38(4):282–96.
- Suh B, Han I. The impact of customer trust and perception of security control on the acceptance of electronic commerce. Int J Electron Commer. 2003;7(3):135–61.
- Pikkarainen T, Pikkarainen K, Karjaluoto H, Pahnila S. Consumer acceptance of online banking: an extension of the technology acceptance model. Internet Res. 2004;14(3):224–35.
- Igbaria M, Schiffman SJ, Wieckowski TJ. The respective roles of perceived usefulness and perceived fun in the acceptance of microcomputer technology. Behav Inf Technol. 1994;13(6):349–61.
- Moon JW, Kim YG. Extending the TAM for a World-Wide-Web context. Inform Manag. 2001;38(4):217–30.
- Yoon C, Kim S. Convenience and TAM in a ubiquitous computing environment: the case of wireless LAN. Electron Commer Res Appl. 2007;6(1):102–12.
- Schepers J, Wetzels M. A meta-analysis of the technology acceptance model: investigating subjective norm and moderation effects. Inform Manag. 2007;44(1):90–103.
- Pan S, Jordan-Marsh M. Internet use intention and adoption among Chinese older adults: from the expanded technology acceptance model perspective. Comput Human Behav. 2010;26(5):1111–9.
- Chen K, Chan AH. Predictors of gerontechnology acceptance by older Hong Kong Chinese. Technovation. 2014;34(2):126–35.
- Chow M, Herold DK, Choo TM, Chan K. Extending the technology acceptance model to explore the intention to use second life for enhancing healthcare education. Comput Educ. 2012;59(4):1136–44.
- Ma Q, Chan AH, Chen K. Personal and other factors affecting acceptance of smartphone technology by older Chinese adults. Appl Ergon. 2016;54:62–71.
- Tsai HYS, Shillair R, Cotten SR, Winstead V, Yost E. Getting grandma online: are tablets the answer for increasing digital inclusion for older adults in the US? Educ Gerontol. 2015;41(10):695–709.
- Aggelidis VP, Chatzoglou PD. Using a modified technology acceptance model in hospitals. Int J Med Inf. 2009;78(2):115–26.
- Venkatesh V, Morris MG, Davis GB. User acceptance of information technology: toward a unified view. MIS Q. 2003;27(3):425–78.
- Salomon G. Cognitive effects with and of computer technology. Communic Res. 1990;17(1):26–44.
- Wijekumar KJ, Meyer BJ, Wagoner D, Ferguson L. Technology affordances: the ‘real story’ in research with K-12 and undergraduate learners. Br J Educ Technol. 2006;37(2):191–209.
- Roblyer MD, McDaniel M, Webb M, Herman J, Witty JV. Findings on Facebook in higher education: a comparison of college faculty and student uses and perceptions of social networking sites. Internet High Educ. 2010;13(3):134–40.
- Roblyer MD, Wiencke WR. Design and use of a rubric to assess and encourage interactive qualities in distance courses. Am J Distance Educ. 2003;17(2):77–98.
- Park J, Han SH, Kim HK, Cho Y, Park W. Developing elements of user experience for mobile phones and services: survey, interview, and observation approaches. Hum Factors Ergon Manuf Serv Ind. 2013;23(4):279–93.
- Paxton P. Is social capital declining in the United States? A multiple indicator assessment. AJS. 1999;105(1):88–127.
- Ellison NB, Steinfield C, Lampe C. The benefits of Facebook “friends”: social capital and college students’ use of online social network sites. J Comput Mediat Commun. 2007;12(4):1143–68.
- Bourdieu P, Wacquant LJ. An invitation to reflexive sociology. Chicago: University of Chicago Press; 1992.
- Kang H, An S. How direct-to-consumer drug websites convey disease information: analysis of stigma-reducing components. J Health Commun. 2013;18(12):1477–91.
- Ostry A, Young ML, Hughes M. The quality of nutritional information available on popular websites: a content analysis. Health Educ Res. 2008;23(4):648–55.
- Herring SC. Slouching toward the ordinary: current trends in computer-mediated communication. New Media Soc. 2004;6(1):26–36.
- Chan-Olmsted SM, Park JS. From on-air to online world: examining the content and structures of broadcast TV stations’ web sites. J Mass Commun Q. 2000;77(2):321–39.
- Neubaum G, Krämer NC. Let’s blog about health! Exploring the persuasiveness of a personal HIV blog compared to an institutional HIV website. Health Commun. 2015;30(9):872–83.
- Chuttur MY. Overview of the technology acceptance model: Origins, developments and future directions. Sprouts Work Papers Inform Syst. 2009;9(37):9–37.
- Benbasat I, Barki H. Quo vadis TAM? J Assoc Inform Syst. 2007;8(4):211–8.