ArticleLife sciences, society and policy2018
Is there a duty to participate in digital epidemiology?
Article in Life sciences, society and policy, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed.
- Using Shopping Data to Improve the Diagnosis of Ovarian Cancer: Computational Analysis of a Web-Based Survey.JMIR cancer · 2023Article
- Emerging data inputs for infectious diseases surveillance and decision making.Frontiers in digital health · 2023Review
- Ethical principles for infodemiology and infoveillance studies concerning infodemic management on social media.Frontiers in public health · 2023Article
- Feasibility of mail-based biospecimen collection in an online preconception cohort study.Frontiers in reproductive health · 2022Article
- Toward a Working Definition of eCohort Studies in Health Research: Narrative Literature Review.JMIR public health and surveillance · 2021Review
- Article
- Social Media- and Internet-Based Disease Surveillance for Public Health.Annual review of public health · 2020Review
- Pandemic data challenges.Nature machine intelligence · 2020Article
- Balancing Personal Privacy and Public Safety During COVID-19: The Case of South Korea.IEEE access : practical innovations, open solutions · 2020Article
- Knowledge-for-data trade at the interface between precision medicine and person-centered care.Croatian medical journal · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This paper poses the question of whether people have a duty to participate in digital epidemiology. While an implied duty to participate has been argued for in relation to biomedical research in general, digital epidemiology involves processing of non-medical, granular and proprietary data types that pose different risks to participants. We first describe traditional justifications for epidemiology that imply a duty to participate for the general public, which take account of the immediacy and plausibility of threats, and the identifiability of data. We then consider how these justifications translate to digital epidemiology, understood as an evolution of traditional epidemiology that includes personal and proprietary digital data alongside formal medical datasets. We consider the risks imposed by re-purposing such data for digital epidemiology and propose eight justificatory conditions that should be met in justifying a duty to participate for specific digital epidemiological studies. The conditions are then applied to three hypothetical cases involving usage of social media data for epidemiological purposes. We conclude with a list of questions to be considered in public negotiations of digital epidemiology, including the application of a duty to participate to third-party data controllers, and the important distinction between moral and legal obligations to participate in research.
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.