Empowering patients through social media: The benefits and challenges
Abstract
This article explores the range of social media platforms used by patients and examines the benefits and challenges of using these tools from a patient perspective. A literature review was performed to investigate the use of social media technology by patients. The MEDLINE database was searched using the terms “social media” and “patient.” The search was conducted in September 2012 and yielded 765 abstracts. Initially, 63 abstracts were selected. All articles dating from 2004 through 2012 were included. Only 12 articles were found to be relevant for the purposes of the review. The results of this research found that there appears to be an increase in the use of social media by patients across the healthcare spectrum. The research indicates a promising future for the use of social media by patients; however, evidence related to the efficacy and effectiveness of social media is currently limited. Various challenges have also been identified relating to privacy and security concerns, usability, the manipulation of identity, and misinformation. The use of social media technology is an emerging trend for patients who are seeking health information. Conclusions are that such technology holds promise for improving patient engagement and empowerment and community building. Social media has a future in healthcare, especially with regard to patient engagement and empowerment; however, there are several challenges to overcome before the technology can achieve its potential.
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Patients are educating themselves about their health online and using SNSs to investigate their disease, their therapy and also their healthcare provider.
“Studies have shown that patients are educating themselves about their health online and using SNSs to investigate their disease, their therapy and also their healthcare provider [26, 27].”
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Griffiths, F. E., Armoiry, X., Atherton, H., Bryce, C., Buckle, A., Cave, J. A. K., Court, R. A., Hamilton, K., Dliwayo, T. R., Dritsaki, M., et al. (2018) · Health Services and Delivery Research · doi:10.3310/hsdr06090 · Cited by 22 · see citing works
Toward a maturity model for the application of social media in healthcare
Pour, M. J., & Jafari, S. M. (2019) · Online information review (Print) · doi:10.1108/oir-02-2018-0038 · Cited by 14 · see citing works
Rivera-Romero, O., Konstantinidis, S. T., Denecke, K., Gabarrón, E., Petersen, C. C., Househ, M. S., Merolli, M., & Mayer, M. Á. (2020) · Yearbook of Medical Informatics · doi:10.1055/s-0040-1701981 · Cited by 20 · see citing works
Self-citationPark, M. S., Oh, H., & You, S. (2020) · Library & Information Science Research · doi:10.1016/j.lisr.2020.101030 · Cited by 20 · see citing works
Patient journey mapping: Integrating digital technologies into the journey
Borycki, E. M., Kushniruk, A. W., Wagner, E., Kletke, R., & |, |. (2020) · Knowledge Management & E-Learning An International Journal · doi:10.34105/j.kmel.2020.12.029 · Cited by 20 · see citing works
Self-citationEthics, Medicine, and Information Technology
Goodman, K. W. (2015) · Cambridge University Press eBooks · doi:10.1017/cbo9781139600330 · Cited by 40 · see citing works
Conley, C. C., Goyal, N. G., & Brown, S.-A. N. (2020) · Cardio-Oncology · doi:10.1186/s40959-020-00072-w · Cited by 19 · see citing works
Patient expectations for recovery after elective surgery: a common-sense model approach
Gehring, M. B., Lerret, S. M., Johnson, J., Rieder, J., Nelson, D. A., Copeland, L. A., Titan, A. L., Hawn, M. T., Morris, M. S., Whittle, J., et al. (2019) · Journal of Behavioral Medicine · doi:10.1007/s10865-019-00097-2 · Cited by 18 · see citing works
Purohit, A. K., Barev, T., Schöbel, S., Janson, A., & Holzer, A. (2023) · Hawaii International Conference on System Sciences (HICSS) · doi:10.24251/hicss.2023.499 · Cited by 18 · see citing works
- Authors
- Househ, M., Borycki, E., & Kushniruk, A.
- Affiliations
- King Saud bin Abdulaziz University for Health Sciences (SA)
- University of Victoria (CA)
- Venue
- Health Informatics Journal
- Publisher
- SAGE Publications
- Published
- 2014-02-18
- Volume
- 20
- Issue
- 1
- Pages
- 50-58
- ISSN
- 1355-4743 (ISSN-L)
- 1460-4582
- 1741-2811
- OpenAlex
- W2169205257
- Cited by
- 342
- References
- 17
- Citations by year
- 2026: 7 · 2025: 18 · 2024: 33 · 2023: 26 · 2022: 27 · 2021: 44 · 2020: 49 · 2019: 28 · 2018: 35 · 2017: 21 · 2016: 26 · 2015: 19 · 2014: 9
- FWCI
- 31.93
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Health Informatics Journal (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Health › Social Media in Health Education
- Health Sciences › Health Professions › General Health Professions › Health Literacy and Information Accessibility
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Keywords
- social media, patient empowerment, patient engagement, health information seeking, privacy and security, identity manipulation, misinformation, usability, online health communities, patient-physician communication
- MeSH terms
- Humans, Patient Participation, Patients, Power, Psychological, Consumer Health Information, Social Media
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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