Preferences for opt-in and opt-out enrollment and consent models in biobank research: a national survey of Veterans Administration patients
Open accessAbstract
Purpose In 2006, the Department of Veterans Affairs launched the Genomic Medicine Program with the goal of using genomic information to personalize and improve health care for veterans. A step toward this goal is the Million Veteran Program, which aims to enroll a million veterans in a longitudinal cohort study and establish a database with genomic, lifestyle, military-exposure, and health information. Before the launch of the Million Veteran Program, a survey of Department of Veterans Affairs patients was conducted to measure preferences for opt-in and opt-out models of enrollment and consent.Methods An online survey was conducted with a random sample of 451 veterans. The survey described the proposed Million Veteran Program database and asked respondents about the acceptability of opt-in and opt-out models of enrollment. The study examined differences in responses among demographic groups and relationships between beliefs about each model and willingness to participate.Results Most respondents were willing to participate under both opt-in (80%) and opt-out (69%) models. Nearly 80% said they would be comfortable providing access to residual clinical samples for research. At least half of respondents did not strongly favor one model over the other; of those who expressed a preference, significantly more people said they would participate in a study using opt-in methods. Stronger preferences for the opt-in approach were expressed among younger patients and Hispanic patients.Conclusion Support for the study and willingness to participate were high for both enrollment models. The use of an opt-out model could impede recruitment of certain demographic groups, including Hispanic patients and patients under the age of 55 years.
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Some scholars proposed more lenient forms of informed consent, such as broad consent and blanket consent, to facilitate practical implementation; however, the moral rationality for these informed consents remains controversial.
“Some scholars proposed more lenient forms of informed consent, such as broad consent and blanket consent, to facilitate practical implementation [88, 89]. However, the moral rationality for these informed consents remains controversial.”
From Ethics and governance of trustworthy medical artificial intelligence (2023) · cites this paper as [89]
Cites
Development of a Large-Scale De-Identified DNA Biobank to Enable Personalized Medicine
Roden, D. M., Pulley, J. M., Basford, M., Bernard, G. R., Clayton, E. W., Balser, J., & Masys, D. R. (2008) · Clinical Pharmacology & Therapeutics · doi:10.1038/clpt.2008.89 · Cited by 959 · see citing works
Junghans, C., Feder, G. S., Hemingway, H., Timmis, A., & Jones, M. M. (2005) · BMJ · doi:10.1136/bmj.38583.625613.ae · Cited by 255 · see citing works
McCarty, C. A., Wilke, R. A., Giampietro, P. F., Wesbrook, S. D., & Caldwell, M. D. (2005) · Personalized Medicine · doi:10.1517/17410541.2.1.49 · Cited by 200 · see citing works
One-time general consent for research on biological samples
Wendler, D. S. (2006) · BMJ · doi:10.1136/bmj.332.7540.544 · Cited by 198 · see citing works
Cohort studies and the genetics of complex disease
Manolio, T. A. (2008) · Nature Genetics · doi:10.1038/ng0109-5 · Cited by 136 · see citing works
Willison, D. J., Schwartz, L. J., Abelson, J., Charles, C. A., Swinton, M. E., Northrup, D., & Thabane, L. (2007) · Journal of the American Medical Informatics Association · doi:10.1197/jamia.m2457 · Cited by 87 · see citing works
Merging and emerging cohorts: Necessary but not sufficient
Collins, F. S., & Manolio, T. A. (2007) · Nature · doi:10.1038/445259a · Cited by 71 · see citing works
Veterans' attitudes regarding a database for genomic research
Kaufman, D., Murphy, J., Erby, L. H., Hudson, K., & Scott, J. A. (2009) · Genetics in Medicine · doi:10.1097/gim.0b013e31819994f8 · Cited by 53 · see citing works
Self-citationObtaining ‘fresh’ consent for genetic research with biological samples archived 10 years ago
Vermeulen, E., Schmidt, M. K., Aaronson, N. K., Kuenen, M. A., & van Leeuwen, F. E. (2009) · European Journal of Cancer · doi:10.1016/j.ejca.2008.11.022 · Cited by 30 · see citing works
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Million Veteran Program: A mega-biobank to study genetic influences on health and disease
Gaziano, J. M., Concato, J., Brophy, M., Fiore, L., Pyarajan, S., Breeling, J., Whitbourne, S., Deen, J., Shannon, C., Humphries, D., et al. (2016) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2015.09.016 · Cited by 1,055 · see citing works
Ethics and governance of trustworthy medical artificial intelligence
Zhang, J., & Zhang, Z.-M. (2023) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-023-02103-9 · Cited by 507 · see citing works
Naveed, M., Ayday, E., Clayton, E. W., Fellay, J., Gunter, C. A., Hubaux, J.-P., Malin, B. A., & Wang, X. (2015) · ACM Computing Surveys · doi:10.1145/2767007 · Cited by 261 · see citing works
Disability inclusion in precision medicine research: a first national survey
Sabatello, M., Chen, Y., Zhang, Y., & Appelbaum, P. S. (2019) · Genetics in Medicine · doi:10.1038/s41436-019-0486-1 · Cited by 58 · see citing works
- Authors
- Kaufman, D., Bollinger, J., Dvoskin, R., & Scott, J.
- Affiliations
- Johns Hopkins University (US)
- University of Louisville (US)
- Corresponding author
- Kaufman, David
- Venue
- Genetics in Medicine
- Publisher
- Elsevier BV
- Published
- 2012-09
- Volume
- 14
- Issue
- 9
- Pages
- 787-794
- ISSN
- 1098-3600 (ISSN-L)
- OpenAlex
- W2142764402
- Cited by
- 54
- References
- 9
- Citations by year
- 2026: 1 · 2025: 1 · 2023: 2 · 2022: 1 · 2021: 5 · 2020: 4 · 2019: 1 · 2018: 5 · 2017: 5 · 2016: 7 · 2015: 9 · 2014: 7 · 2013: 6
- FWCI
- 6.71
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Genetics in Medicine (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
- informed consent, biobank research, Million Veteran Program, veterans, Hispanic patients, age differences, genomic medicine
- MeSH terms
- Adolescent, Adult, Aged, Data Collection, Decision Support Techniques, Female, Humans, Informed Consent, Male, Middle Aged, United States, United States Department of Veterans Affairs, Veterans, Cohort Studies, Biological Specimen Banks, Genomics, Ethics, Research, Biomedical Research, Racial Groups
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