Sociotechnical Challenges and Progress in Using Social Media for Health
Open accessAbstract
Social media tools that connect patients, caregivers, and health providers offer great potential for helping people access health advice, receive and give social support, manage or cope with chronic conditions, and make day-to-day health decisions. These systems have seen widespread adoption, but often fail to support the goals as fully as designers and users would like. Through Ackerman's lens of the "sociotechnical gap" and computer supported cooperative work (CSCW) as a science of the artificial, we review contemporary sociotechnical challenges and progress for using social media to support health. These challenges include a tension between privacy and sharing, policy information credibility, accessibility, and tailoring in social spaces. Those studying, building, deploying, and using social media systems to further health goals will benefit from approaching this work by borrowing from Ackerman's framing of CSCW. In particular, this requires acknowledgment that technical systems will not fully meet our social goals, and then adopting design and educational approaches that are appropriate to fill this gap, building less-nuanced systems as partial solutions and tools for advancing our understanding, and by working with the CSCW research community to develop and pursue key lines of inquiry.
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Concerns about online searching, privacy, and professionalism have been suggested as barriers to doctors' use of social media.
“While concerns about online searching [22,23], privacy [24], and professionalism [25] have been suggested as barriers to the use of social media by doctors, the slow adoption of social media also represents a possible lost opportunity for the medical profession at large to engage with patients and the general community.”
From How Doctors View and Use Social Media: A National Survey (2014) · cites this paper as [24]
Health care organizations experience barriers regarding privacy, confidentiality, reputation management, and the dissemination of inaccurate health information.
“Health care organizations also experience barriers regarding privacy, confidentiality, reputation management, and the dissemination of inaccurate health information [55-57].”
From Improving the Theoretical Understanding Toward Patient-Driven Health Care Innovation Through Online Value Cocreation: Systematic Review (2020) · cites this paper as [56]
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- Authors
- Munson, S. A., Cavusoglu, H., Frisch, L., & Fels, S.
- Affiliations
- University of Washington (US)
- University of British Columbia (CA)
- Corresponding author
- Munson, Sean A
- Venue
- Journal of Medical Internet Research
- Publisher
- JMIR Publications Inc.
- Published
- 2013-10-22
- Volume
- 15
- Issue
- 10
- Pages
- e226
- ISSN
- 1438-8871 (ISSN-L)
- PMC
- PMC3806390
- OpenAlex
- W1964745528
- Cited by
- 57
- References
- 86
- Citations by year
- 2025: 3 · 2024: 3 · 2023: 1 · 2022: 4 · 2021: 4 · 2020: 2 · 2019: 2 · 2018: 7 · 2017: 10 · 2016: 6 · 2015: 8 · 2014: 7
- FWCI
- 12.68
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Journal of Medical Internet Research (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Health Sciences › Health Professions › General Health Professions › Health Literacy and Information Accessibility
- Social Sciences › Health › Social Media in Health Education
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Keywords
- computer-supported cooperative work, information credibility, accessibility, personalization, social support, chronic disease management, health data sharing, socio-technical design
- MeSH terms
- Adaptation, Psychological, British Columbia, Chronic Disease, Decision Making, Health Services Accessibility, Humans, Social Support, 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.
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