Electronic Informed Consent in Mobile Applications Research
Open accessAbstract
The article covers electronic informed consent (eIC) from different dimensions so that practitioners might understand the history, regulation, and current status of eIC. It covers the transition of informed consent to electronic screens and the implications of that transition in terms of design, costs, and data analysis. The article explores the limits of regulation mandating eIC for mobile application research, and addresses some of the broader social context around eIC.
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At minimum, an informed decision is one in which people are able to reason about the possible consequences based on reliable information about the possible choices.
“At minimum, an informed decision is one in which people are able to reason about the possible consequences based on reliable information about the possible choices [71].”
From Null Compliance: NYC Local Law 144 and the challenges of algorithm accountability (2024) · cites this paper as [71]
Cites
The mPower study, Parkinson disease mobile data collected using ResearchKit
Bot, B. M., Suver, C., Neto, E. C., Kellen, M., Klein, A., Bare, C., Doerr, M., Pratap, A., Wilbanks, J., Dorsey, E. R., et al. (2016) · Scientific Data · doi:10.1038/sdata.2016.11 · Cited by 630 · see citing works
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Null Compliance: NYC Local Law 144 and the challenges of algorithm accountability
Wright, L., Muenster, R. M., Vecchione, B., Qu, T., Cai, P. (., Smith, A., Comm 2450 Student Investigators, Metcalf, J., & Matias, J. N. (2024) · The 2024 ACM Conference on Fairness, Accountability, and Transparency · doi:10.1145/3630106.3658998 · Cited by 43 · see citing works
“Ongoing literature in bioethics, psychology, and design is exploring exactly what it means to make an informed decision [56, 71, 74, 75].”
BackgroundNull Compliance: NYC Local Law 144 and the Challenges of Algorithm Accountability
Wright, L., Muenster, R. M., Vecchione, B., Qu, T., Pika, Cai, Investigators, C. 2. S., Metcalf, J., & Matias, J. N. (2024) · arXiv · doi:10.48550/arxiv.2406.01399 · Cited by 43
- Authors
- Wilbanks, J. T.
- Corresponding author
- Wilbanks, John T.
- ORCID
- Wilbanks, John T.
- Venue
- Journal of Law, Medicine & Ethics
- Publisher
- Cambridge University Press (CUP)
- Published
- 2020
- Volume
- 48
- Issue
- S1
- Pages
- 147-153
- ISSN
- 1073-1105 (ISSN-L)
- 1748-720X
- OpenAlex
- W3021997213
- Cited by
- 14
- References
- 1
- Citations by year
- 2024: 1 · 2023: 2 · 2022: 2 · 2021: 6 · 2020: 3
- FWCI
- 2.43
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- The Journal of Law Medicine & Ethics (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Ethics in Clinical Research
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Ethics and bioethics in healthcare
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Medical and Health Sciences Research
- Keywords
- electronic consent, informed consent, research regulation, research costs, data analysis, history of informed consent
- MeSH terms
- Confidentiality, Humans, Informed Consent, Software, User-Computer Interface, Consent Forms, Mobile Applications
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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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