ArticleJournal of medical Internet research2015
A Privacy Preservation Model for Health-Related Social Networking Sites.
Article in Journal of medical Internet research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- Addressing online-facilitated stigma: a co-design workshop among patients with lived experiences of dyspareunia.BMJ open · 2025Article
- Current Status of ChatGPT Use in Medical Education: Potentials, Challenges, and Strategies.Journal of medical Internet research · 2024Article
- Privacy Concerns About Sharing General and Specific Health Information on Twitter: Quantitative Study.JMIR formative research · 2024Article
- Effect of SNS addiction on prosocial behavior: mediation effect of fear of missing out.Frontiers in psychology · 2024Article
- Security Implications of AI Chatbots in Health Care.Journal of medical Internet research · 2023Article
- Engaging PatientsFrontiers in pharmacology · 2022Article
- Privacy Protection in Online Health Communities: Natural Experimental Empirical Study.Journal of medical Internet research · 2020Article
- Tracing the Potential Flow of Consumer Data: A Network Analysis of Prominent Health and Fitness Apps.Journal of medical Internet research · 2017Article
- Medical and legal aspects of telemedicine in ophthalmology.Romanian journal of ophthalmologyReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The increasing use of social networking sites (SNS) in health care has resulted in a growing number of individuals posting personal health information online. These sites may disclose users' health information to many different individuals and organizations and mine it for a variety of commercial and research purposes, yet the revelation of personal health information to unauthorized individuals or entities brings a concomitant concern of greater risk for loss of privacy among users. Many users join multiple social networks for different purposes and enter personal and other specific information covering social, professional, and health domains into other websites. Integration of multiple online and real social networks makes the users vulnerable to unintentional and intentional security threats and misuse. This paper analyzes the privacy and security characteristics of leading health-related SNS. It presents a threat model and identifies the most important threats to users and SNS providers. Building on threat analysis and modeling, this paper presents a privacy preservation model that incorporates individual self-protection and privacy-by-design approaches and uses the model to develop principles and countermeasures to protect user privacy. This study paves the way for analysis and design of privacy-preserving mechanisms on health-related SNS.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.