Article

Implications of Internet availability of genomic information for public health practice.

National Cancer Institute, National Institutes of Health, 6130 Executive Boulevard, Bethesda, MD 20892-7365, USA.
Public Health Genomics (Impact Factor: 2.46). 01/2012; 15(3-4):201-8. DOI: 10.1159/000335892
Source: PubMed

ABSTRACT Tensions in the field have emerged over how best to communicate to the public about genomic discoveries in an era of direct-to-consumer (DTC) DNA testing services available through the Internet. Concerns over what the psychological and behavioral response might be to a nuanced, multiplex risk message have spurred some to offer caution in communicating to the public about personalized risk until the necessary research has been completed on how to communicate effectively. The popularization of DTC testing services, along with a spreading Internet culture on transparency for personal data, may make 'waiting to communicate' a moot point. To steer communication efforts in the midst of increasing access to personal genomic information, a self-regulation framework is presented. The framework emphasizes the importance of presenting a coherent message in all communiqués about public health genomics. Coherence should be based on an evidence-based model of how the public processes information about health conditions and an emphasis on risk-to-action links. Recommendations from the President's Council of Advisors for Science and Technology are reviewed as a way of identifying targets of opportunity for structured communications both within the healthcare system and in the broader external ecosystem of publicly available health information technologies.

Full-text

Available from: Bradford W Hesse, May 30, 2015
0 Followers
 · 
129 Views
  • [Show abstract] [Hide abstract]
    ABSTRACT: Dissemination of genetic testing for disease susceptibility, one application of "personalized medicine", holds the potential to empower patients and providers through informed risk reduction and prevention recommendations. Genetic testing has become a standard practice in cancer prevention for high-risk populations. Heightened consumer awareness of "cancer genes" and genes for other diseases (eg, cardiovascular and Alzheimer's disease), as well as the burgeoning availability of increasingly complex genomic tests (ie, multi-gene, whole-exome and -genome sequencing), has escalated interest in and demand for genetic risk assessment and the specialists who provide it. Increasing demand is expected to surpass access to genetic specialists. Thus, there is urgent need to develop effective and efficient models of delivery of genetic information that comparably balance the risks and benefits to the current standard of in-person communication.
    01/2014; 3(4):e49. DOI:10.2196/resprot.3337
  • [Show abstract] [Hide abstract]
    ABSTRACT: In-person genetic counselling is the model typically used to provide patients with information regarding their genetic testing options. Current and emerging demand for genetic testing may over-burden the health care system and exceed the available numbers of genetic counsellors. Furthermore, genetic counselling is not always available at times and places convenient for patients. There is little evidence that the in-person model alone is always optimal and alternatives to in-person genetic counselling have been studied in genetics and other areas of health care. This paper summarizes the published evidence between 1994 and March 2014 for interactive e-learning and decisional support e-tools that could be used in pre-test genetic counselling. Twenty-one papers from 15 heterogeneous studies of interactive e-learning tools, with or without decision aids, were reviewed. Study populations, designs, and outcomes varied widely but most used an e-tool as an adjunct to conventional genetic counselling. Knowledge acquisition and decisional comfort were achieved and the e-tools were generally well accepted by users. In a time when health care budgets are constrained and availability of genetic counselling is limited, research is needed to determine the specific circumstances in which e-tools might replace or supplement some of the functions of genetic counsellors.
    Clinical Genetics 05/2014; 87(3). DOI:10.1111/cge.12430 · 3.65 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Purpose:Many common health conditions arise due to a combination of genetic factors and lifestyle-related behaviors. People's understanding of the multifactorial nature of health conditions has implications for their receptivity to health messages regarding genomics and medicine, and may be related to their adoption of protective health behaviors. Although past work has investigated aspects of either genetic or behavioral causal beliefs, multifactorial beliefs have not been evaluated systematically.Methods:Utilizing nationally representative cross-sectional data from the Health Information National Trends Survey, we examined the prevalence of multifactorial beliefs regarding the etiology of cancer, obesity, diabetes, heart disease, and hypertension, as well as associations between such beliefs and demographic, health history, and health behavior variables in the US population.Results:Among 3,630 participants, the vast majority (64.2-78.6%) endorsed multifactorial beliefs. The number of statistically significant associations was limited. Trends suggest that endorsement of multifactorial beliefs may differ by demographic and health history characteristics. Beliefs about the multifactorial etiology of cancer were associated with cancer screening behaviors. Multifactorial beliefs about other common health conditions were associated with few health promotion behaviors.Conclusion:These findings and recommendations for future research provide preliminary guidance for developing and targeting genomics-related health messages and communications.Genet Med advance online publication 15 May 2014Genetics in Medicine (2014); doi:10.1038/gim.2014.49.
    Genetics in medicine: official journal of the American College of Medical Genetics 05/2014; DOI:10.1038/gim.2014.49 · 6.44 Impact Factor