Table 2.
Characteristics of included studies.
| Author | Year | Country | Sample size, n | Design | Study aim | Measure | CCATa,b score, points (% of total) |
| Roque et al [34] | 2016 | United States | 109 | Cross-sectional | To validate a new tool for measuring mobile device proficiency across the life span by assessing both basic and advanced proficiencies related to smartphone and tablet use | MDPQc, CPQd-12 | 37 (93) |
| Zambianchi et al [24] | 2019 | Italy and Sweden | 638 | Cross-sectional | To examine the determinants of attitudes towards and use of ICTse in older adults | S-ZTPIf, ATTQg | 38 (95) |
| Schneider et al [23] | 2018 | Germany | 577 | RCTh | To examine whether there are any differences in use of an online psychological intervention between generational groups based on Deprexis user data, responses on a questionnaire, and data in the EVIDENT study | APOIi | 40 (100) |
| Nagle et al [9] | 2012 | Germany | 52 | Cross-sectional | To get a better understanding of the factors affecting older adults' intention towards and usage of computers | UTAUTj | 34 (85) |
| Yoon et al [33] | 2015 | United States | 209 | Cross-sectional | To examine predictors of computer use and computer anxiety in older Korean Americans | CASk | 38 (95) |
| Cherid et al [35] | 2020 | Canada | 401 | Cross-sectional | To identify the current level of technology adoption, health, and eHealth literacy among older adults with a recent fracture, to determine if the use of electronic interventions would be feasible and acceptable in this population | eHEALSl | 39 (98) |
| Xie and Bo [36] | 2011 | United States | 146 | Cross-sectional | To examine the effects of a theory-driven eHealth literacy intervention for older adults | eHEALS | 39 (98) |
| Tennant et al [37] | 2015 | United States | 393 | Cross-sectional | To explore the extent to which sociodemographic, social determinants, and electronic device use influence eHealth literacy and use of Web 2.0 for health information among baby boomers and older adults | eHEALS | 36 (90) |
| Hoogland et al [38] | 2020 | United States | 198 | Cross-sectional | To examine age differences in eHealth literacy and use of technology devices/HITm in patients with cancer and characterize receptivity towards using home-based HIT to communicate with the oncology care team | eHEALS | 36 (90) |
| Price-Haywood et al [39] | 2017 | United States | 247 | Cross-sectional | To examine relationships between portal usages, interest in health-tracking tools, and eHealth literacy and to solicit practical solutions to encourage technology adoption. | eHEALS | 37 (93) |
| Paige et al [40] | 2018 | United States | 830 | Cross-sectional | To examine the structure of eHEALS scores and the degree of measurement invariance among US adults representing the following generations: millennials (18-35 years old), Generation X (36-51 years old), baby boomers (52-70 years old), and the silent generation (71-84 years old) | eHEALS | 38 (95) |
| Aponte et al [41] | 2017 | United States | 20 | Cross-sectional | To explore the experiences of older Hispanics with type 2 diabetes in using the internet for diabetes management | eHEALS | 37 (93) |
| Xie and Bo [42] | 2011 | United States | 124 | Cross-sectional | To generate scientific knowledge about the potential impact of learning methods and information presentation channels on older adults' eHealth literacy | eHEALS | 39 (98) |
| Sudbury-Riley and Lynn [25] | 2017 | United States, United Kingdom, New Zealand | 996 | Cross-sectional | To examine the factorial validity and measurement invariance of the eHEALS among baby boomers in the United States, the United Kingdom, and New Zealand who had used the internet to search for health information in the last 6 months | eHEALS | 35 (88) |
| Noblin et al [43] | 2017 | United States | 181 | Cross-sectional | To determine the willingness of older adults to use health information from a variety of sources | eHEALS | 38 (95) |
| Cajita et al [44] | 2018 | United States | 129 | Cross-sectional | To examine factors that influence intention to use mobile technology in health care (mHealth) among older adults with heart failure | TAMn | 37 (93) |
| Lin et al [45] | 2019 | Iran | 468 | Longitudinal | To examine the temporal associations between eHealth literacy, insomnia, psychological distress, medication adherence, quality of life, and cardiac events among older patients with heart failure | eHEALS | 39 (98) |
| Chu et al [32] | 2009 | United States | 137 | RCT | To measure the psychosocial influences of computer anxiety, computer confidence, and computer self-efficacy in older adults at 6 meal congregate sites | CAS | 40 (100) |
| Rosenberg et al [46] | 2009 | Sweden | 157 | Cross-sectional | To measure the perceived difficulty in everyday technology use such as remote controls, cell phones, and microwave ovens by older adults with or without cognitive deficits | ETUQo | 37 (93) |
| Stellefson et al [47] | 2017 | United States | 283 | Cross-sectional | To examine the reliability and internal structure of eHEALS data collected from older adults aged ≥50 years responding to items over the telephone | eHEALS | 36 (90) |
| Chung et al [48] | 2015 | United States | 866 | Cross-sectional | To test the psychometric aspects of the eHEALS for older adults using secondary data analysis | eHEALS | 36 (90) |
| Li et al [49] | 2020 | China | 1201 | Cross-sectional | To examine the associations among health-promoting lifestyles, eHealth literacy, and cognitive health in older adults | eHEALS | 37 (93) |
| Choi et al [29] | 2013 | United States | 980 | Mixed methods | To examine internet use patterns, reasons for discontinued use, eHealth literacy, and attitudes toward computer or internet use among low-income homebound individuals aged ≥60 years in comparison to their younger counterparts (homebound adults <60 years old) | eHEALS, ATC/IQp | 37 (93) |
| Moore et al [8] | 2015 | United States | 30 | Cross-sectional | To offer design considerations in developing internet-based hearing health care for older adults by analyzing and discussing the relationship between chronological age, computer skills, and the acceptance of internet-based hearing health care | TAM | 35 (88) |
| Hoque et al [31] | 2017 | Bangladesh | 300 | Cross-sectional | To develop a theoretical model based on the UTAUT and then empirically test it to determine the key factors influencing elderly users’ intention to adopt and use mHealth services | UTAUT | 36 (90) |
| Niehaves et al [30] | 2014 | Germany | 150 | Cross-sectional | To study the intentions of the elderly with regard to internet use and identify important influencing factors | UTAUT | 35 (88) |
| Aponte et al [41] | 2017 | United States | 100 | Cross-sectional | To examine the validity of the Spanish version of the eHEALS with an older Hispanic population from a number of Spanish-language countries living in New York City | eHEALS | 37 (93) |
aCCAT: Crowe Critical Appraisal Tool.
bTotal CCAT score is 40 points.
cMDPQ: Mobile Device Proficiency Questionnaire.
dCPQ: Computer Proficiency Questionnaire.
eICTs: information and communication technologies.
fS-ZTPI: Swedish Zimbardo Time Perspective Inventory.
gATTQ: Attitudes Toward Technologies Questionnaire.
hRCT: randomized controlled trial.
iAPOI: Attitudes towards Psychological Online Interventions.
jUTAUT: Unified Theory of Acceptance and Use of Technology.
kCAS: Computer Attitude Scale.
leHEALS: eHealth Literacy Scale.
mHIT: health information technology.
nTAM: Adapted Technology Acceptance Model.
oETUQ: Everyday Technology Use Questionnaire.
pATC/IQ: Attitudes Toward Computer/Internet Questionnaire.