The Persistence of Digital Divides in the Use of Health Information: a Comparative Study in 28 European Countries

Overview

Journal Int J Public Health

Specialty Public Health

Date 2020 Apr 12

PMID 32277246

Citations 28

Authors

Javier Alvarez-Galvez

Jose A Salinas-Perez

Ilaria Montagni

Luis Salvador-Carulla

Affiliations

Soon will be listed here.

Abstract

Objectives: This study aimed to identify which are the socio-demographic factors that can describe health information users' profiles in Europe and assess which are the factors distinguishing users and non-users and their association with the use of health-related online information.

Methods: Data from the Flash Eurobarometer No. 404 (2014) was analysed through a multilevel logistic regression model and a propensity score matching.

Results: There were significant differences in the use of the Internet for health information according to gender, age, education, long-term illness and health-related knowledge. Thus, some digital divides persisted in the use of health information online. Results showed that a poor health status was associated with a higher use of the Internet for health purposes only for people having chronic conditions.

Conclusions: Findings show a need to increase people's eHealth literacy, especially for males over 45 years old not suffering from a long-term illness. In order to limit the misuse of poor or untrustworthy health information that might contribute to higher health disparities, special interest should be focused on population socio-demographic characteristics.

Citing Articles

Assessing Health Technology Literacy and Attitudes of Patients in an Urban Outpatient Psychiatry Clinic: Cross-Sectional Survey Study.

Tartaglia J, Jaghab B, Ismail M, Hansel K, Van Meter A, Kirschenbaum M JMIR Ment Health. 2025; 11():e63034.

PMID: 39753220 PMC: 11729776. DOI: 10.2196/63034.

Knowledge about COVID-19 vaccines among Aboriginal and Torres Strait Islander people, and attitudes to and behaviours regarding COVID-19 and influenza vaccination: a survey.

Spierings S, Oguoma V, Shakeshaft A, Walker J, Toombs M, Ward J Med J Aust. 2024; 222(1):30-37.

PMID: 39655627 PMC: 11725265. DOI: 10.5694/mja2.52551.

Factors influencing digital health literacy among older adults: a scoping review.

Shi Z, Du X, Li J, Hou R, Sun J, Marohabutr T Front Public Health. 2024; 12:1447747.

PMID: 39555039 PMC: 11566617. DOI: 10.3389/fpubh.2024.1447747.

User profiles in digitalized healthcare: active, potential, and rejecting - a cross-sectional study using latent class analysis.

Knochelmann A, Healy K, Frese T, Kantelhardt E, Mikolajczyk R, Meyer G BMC Health Serv Res. 2024; 24(1):1083.

PMID: 39289720 PMC: 11409736. DOI: 10.1186/s12913-024-11523-w.

Sociodemographic factors and health digital divide among urban residents: Evidence from a population-based survey in China.

Yang Y, Ma C Digit Health. 2024; 10:20552076241271812.

PMID: 39114114 PMC: 11304494. DOI: 10.1177/20552076241271812.

References

Devine T, Broderick J, Harris L, Wu H, Hilfiker S . Making Quality Health Websites a National Public Health Priority: Toward Quality Standards. J Med Internet Res. 2016; 18(8):e211. PMC: 4987491. DOI: 10.2196/jmir.5999. View

Gracia E, Herrero J . Internet use and self-rated health among older people: a national survey. J Med Internet Res. 2009; 11(4):e49. PMC: 2802559. DOI: 10.2196/jmir.1311. View

Stevenson F, Kerr C, Murray E, Nazareth I . Information from the Internet and the doctor-patient relationship: the patient perspective--a qualitative study. BMC Fam Pract. 2007; 8:47. PMC: 2041946. DOI: 10.1186/1471-2296-8-47. View

Bidmon S, Terlutter R . Gender Differences in Searching for Health Information on the Internet and the Virtual Patient-Physician Relationship in Germany: Exploratory Results on How Men and Women Differ and Why. J Med Internet Res. 2015; 17(6):e156. PMC: 4526954. DOI: 10.2196/jmir.4127. View

Kontos E, Blake K, Chou W, Prestin A . Predictors of eHealth usage: insights on the digital divide from the Health Information National Trends Survey 2012. J Med Internet Res. 2014; 16(7):e172. PMC: 4129114. DOI: 10.2196/jmir.3117. View

Norman C, Skinner H . eHealth Literacy: Essential Skills for Consumer Health in a Networked World. J Med Internet Res. 2006; 8(2):e9. PMC: 1550701. DOI: 10.2196/jmir.8.2.e9. View

Vance K, Howe W, Dellavalle R . Social internet sites as a source of public health information. Dermatol Clin. 2009; 27(2):133-6, vi. DOI: 10.1016/j.det.2008.11.010. View

Baumann E, Czerwinski F, Reifegerste D . Gender-Specific Determinants and Patterns of Online Health Information Seeking: Results From a Representative German Health Survey. J Med Internet Res. 2017; 19(4):e92. PMC: 5395693. DOI: 10.2196/jmir.6668. View

Risling T, Martinez J, Young J, Thorp-Froslie N . Evaluating Patient Empowerment in Association With eHealth Technology: Scoping Review. J Med Internet Res. 2017; 19(9):e329. PMC: 5640823. DOI: 10.2196/jmir.7809. View

10.

Austin P . An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies. Multivariate Behav Res. 2011; 46(3):399-424. PMC: 3144483. DOI: 10.1080/00273171.2011.568786. View

11.

Cepeda M, Boston R, Farrar J, Strom B . Comparison of logistic regression versus propensity score when the number of events is low and there are multiple confounders. Am J Epidemiol. 2003; 158(3):280-7. DOI: 10.1093/aje/kwg115. View

12.

Czaja S, Charness N, Fisk A, Hertzog C, Nair S, Rogers W . Factors predicting the use of technology: findings from the Center for Research and Education on Aging and Technology Enhancement (CREATE). Psychol Aging. 2006; 21(2):333-52. PMC: 1524856. DOI: 10.1037/0882-7974.21.2.333. View

13.

Estacio E, Whittle R, Protheroe J . The digital divide: Examining socio-demographic factors associated with health literacy, access and use of internet to seek health information. J Health Psychol. 2017; 24(12):1668-1675. DOI: 10.1177/1359105317695429. View

14.

Iverson S, Howard K, Penney B . Impact of internet use on health-related behaviors and the patient-physician relationship: a survey-based study and review. J Am Osteopath Assoc. 2008; 108(12):699-711. View

15.

Chou W, Oh A, Klein W . Addressing Health-Related Misinformation on Social Media. JAMA. 2018; 320(23):2417-2418. DOI: 10.1001/jama.2018.16865. View

16.

Tonsaker T, Bartlett G, Trpkov C . Health information on the Internet: gold mine or minefield?. Can Fam Physician. 2014; 60(5):407-8. PMC: 4020634. View

17.

Escoffery C . Gender Similarities and Differences for e-Health Behaviors Among U.S. Adults. Telemed J E Health. 2017; 24(5):335-343. DOI: 10.1089/tmj.2017.0136. View

18.

Renahy E, Parizot I, Chauvin P . Determinants of the frequency of online health information seeking: results of a web-based survey conducted in France in 2007. Inform Health Soc Care. 2010; 35(1):25-39. PMC: 3034225. DOI: 10.3109/17538150903358784. View

19.

Neter E, Brainin E . eHealth literacy: extending the digital divide to the realm of health information. J Med Internet Res. 2012; 14(1):e19. PMC: 3374546. DOI: 10.2196/jmir.1619. View

20.

Liu H, Zeng H, Shen Y, Zhang F, Sharma M, Lai W . Assessment Tools for Health Literacy among the General Population: A Systematic Review. Int J Environ Res Public Health. 2018; 15(8). PMC: 6122038. DOI: 10.3390/ijerph15081711. View