Table 1.
The details of the articles reviewed.
| Authors | Publication Year | Title | Journal | Research Design | Data Collection Method | Sample Number | Subjects (Age Group/Sex/etc.) | Location | Data Analysis |
|---|---|---|---|---|---|---|---|---|---|
| Ukonu & Ajaebili, 2021 [21] | 2021 | Socio-cultural determinants of women’s health information opportunities in Nsukka, southeast Nigeria | Asian Women | Quantitative | Survey | n = 591 | Reproductive-age women | America | Descriptive and correlation analysis |
| Boyce et al., 2021 [22] | 2021 | Exploring the factors in information seeking behavior: a perspective from multinational COPD online forums | Health Promotion International | Quantitative | Survey | n = 201 | Participants with chronic obstructive pulmonary disease (COPD). | America & other countries such as New Zealand, Australia, South Africa, the UK, Philippines, etc. | PLS-SEM (partial least squares structural equation modeling) |
| Özkan et al., 2021 [23] | 2021 | The relationship between health literacy level and media used as a source of health-related information | HLRP: Health Literacy Research and Practice | Quantitative | Survey | n = 6228 | Turkish citizen | Turkey | Descriptive and linear regression analysis |
| Augustaitis et al., 2021 [24] | 2021 | Online transgender health information seeking: facilitators, barriers and future directions | Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems | Qualitative | Online focus groups | n = 26 | Trans and/or nonbinary adults | America | Inductive open coding approach |
| Demirci et al., 2021 [25] | 2021 | Socio-demographic characteristics affect health information seeking on the Internet in Turkey | Health Information & Libraries Journal. | Quantitative | Survey | n = 19,389 | Turkish | Turkey | Logistic regression |
| Ghahramani & Wang, 2020 [11] | 2020 | Impact of smartphones on quality of life: a health information behavior perspective | Information Systems Frontiers | Quantitative | Survey | n = 3014 | American adults | America | Pearson’s correlation analysis, Preacher and Hayes Process macro |
| Lee et al., 2020 [26] | 2020 | Communication about health information technology use between patients and providers | Journal of General Internal Medicine | Quantitative | Survey | n = 970 | Adult residents in 34 Indiana counties with higher cancer mortality rates than the state average | America | Descriptive statistics and multivariable logistic regression |
| Lee, 2020 [27] | 2020 | Which individual characteristics influence mothers’ health information-seeking behavior? | Journal of the Korean Society for Library and Information Science | Quantitative | Survey | n = 851 | Among mothers of healthy infants and toddlers (currently living in the US or Korea) | America & Korea | Ordinal regression analyzes |
| Bernadas & Jiang, 2019 [28] | 2019 | Explaining online health information seeking of foreign domestic workers: a test of the comprehensive model of information seeking | Health and Technology | Quantitative | Survey | n = 300 | Filipino female foreign domestic workers (WFDs) in HK | Hong Kong | Multiple OLS regression |
| Nangsangna & Vroom, 2019 [17] | 2019 | Factors influencing online health information seeking behavior among patients in Kwahu West Municipal, Nkawkaw, Ghana | Online Journal of Public Health Informatics | Quantitative | Survey | n = 204 | Ghanaian residents who are over 16 | Ghana | Descriptive statistics, Chi-square test, and logistic regression |
| Zhang et al., 2019 [29] | 2019 | Why do patients follow physicians’ advice? The influence of patients’ regulatory focus on adherence: An empirical study in China | BMC Health Services Research | Quantitative | Survey | n = 336 | Chinese patients with health information seeking experience and hospital treatment experience | China | Structural equation modeling and confirmatory factor analysis |
| LaValley et al., 2017 [30] | 2017 | Where people look for online health information | Health Information & Libraries Journal | Quantitative | Survey | n = 3959 | American adults | America | Regression analysis |
| Maon et al., 2017 [4] | 2017 | Online health information seeking behavior pattern | Advanced Science Letters | Quantitative | Survey | n = 482 | Malaysian adults | Malaysia | Descriptive analysis |
| Osei Asibey et al., 2017 [5] | 2017 | The Internet use for health information seeking among Ghanaian university students: A cross-sectional study | International Journal of Telemedicine and Applications | Quantitative | Survey | n = 650 | Ghanaian university students | Ghana | Descriptive analysis |
| Manganello et al., 2017 [31] | 2017 | The relationship of health literacy with use of digital technology for health information: implications for public health practice | Journal of Public Health Management and Practice | Quantitative | Survey | n = 1350 | New York State adult residents | America | A weighted analysis |
| Sultan et al., 2017 [32] | 2017 | Health information seeking behavior of college students in the sultanate of Oman | Khyber Medical University Journal | Quantitative | Survey | n = 200 | Omani college students (adults) | Oman | Descriptive statistics and chi-square tests |
| Kim et al., 2017 [33] | 2017 | Seeking medical information using mobile Apps and the Internet: Are family caregivers different from the general public? | Journal of Medical Systems | Quantitative | Survey |
n = 3677 [n = 2425 (family caregivers) n = 1252 (Non-family caregivers)] |
American adults | America | Multivariate logistic regression |
| Xuexia et al., 2016 [9] | 2016 | Analysis of barriers to health information seeking and utilizing in patients with diabetes | Cross-Cultural Communication | N/A | N/A | N/A | N/A | China | N/A |
| Obasola & Agunbiade, 2016 [34] | 2016 | Online health information seeking pattern among undergraduates in a Nigerian University | SAGE Open | Quantitative | Survey | n = 400 | Nigerian undergraduate students | Nigeria | Descriptive analysis |
| Shneyderman et al., 2016 [35] | 2016 | Health information seeking and cancer screening adherence rates | Journal of Cancer Education | Quantitative | Survey | Did not indicate | American adults | America | Descriptive statistics and regression modeling |