ArticleOnline journal of public health informatics2023
Health Information Seeking Behavior on Social Networking Sites and Self-Treatment: Pilot Survey Study.
Article in Online journal of public health informatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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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
7 citing papers in PubMed.
- Skin Health Information Seeking on Short Video Platforms in Indonesia: Mixed Methods Approach.JMIR dermatology · 2026Article
- Cross-national validation of digital health engagement scales: evidence from 30 countries.Frontiers in public health · 2026Article
- Self-care strategies and interventions to address antimicrobial resistance: evidence review and recommendations for national programs, service providers, caregivers, and self-carers.Frontiers in public health · 2026Review
- BiliBili, Douyin and Xiaohongshu as health information platforms for stroke: evaluating information quality and content.Scientific reports · 2025Article
- Development and Validation of a Large Language Model-Powered Chatbot for Neurosurgery: Mixed Methods Study on Enhancing Perioperative Patient Education.Journal of medical Internet research · 2025Article
- Cyberchondria, somatic symptoms, and internet-based self-diagnosis among the Saudi population.Scientific reports · 2025Article
- Accuracy of online symptom assessment applications, large language models, and laypeople for self-triage decisions.NPJ digital medicine · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Social networking site use and social network-based health information seeking behavior have proliferated to the point that the lines between seeking health information from credible social network-based sources and the decision to seek medical care or attempt to treat oneself have become blurred. Objective: We contribute to emerging research on health information seeking behavior by investigating demographic factors, social media use for health information seeking purposes, and the relationship between health information seeking and occurrences of self-treatment. Methods: Data were collected from an online survey in which participants were asked to describe sociodemographic factors about themselves, social media use patterns, perceptions about their motivations for health information seeking on social media platforms, and whether or not they attempted self-treatment after their social media-related health information seeking. We conducted a binomial logistic regression with self-treatment as a dichotomous categorical dependent variable. Results: Results indicate that significant predictors of self-treatment based on information obtained from social networking sites include race, exercise frequency, and degree of trust in the health-related information received. Conclusions: With an understanding of how sociodemographic factors might influence the decision to self-treat based on information obtained from social networking sites, health care providers can assist patients by educating them on credible social network-based sources of health information and discussing the importance of seeking medical advice from a health care provider.
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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.