Of Mice and Mentors

Hesse, Bradford W.

doi:10.1016/j.amepre.2008.05.011

Cited by 17 publications

(4 citation statements)

References 34 publications

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“…Executed correctly, the third way should allow individual scientists to “plug and play” into the broader framework. (Buetow, 2005; B. W. Hesse, 2008)…”

Section: Discussionmentioning

confidence: 99%

“…As the technology matures and the Internet continues to insinuate itself into multiple facets of everyday life, the implications of a new Web-enabled culture will continue to play out in all sectors of society in substantive ways. Global and local commerce will change,(Friedman, 2007) as will health and healthcare,(Eysenbach, 2008) government,(Koh & Prybutok, 2003) science,(B. W. Hesse, 2008) and social discourse.…”

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confidence: 99%

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Realizing the Promise of Web 2.0: Engaging Community Intelligence

Hesse

O’Connell

Augustson

et al. 2011

Journal of Health Communication

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Discussions of “Health 2.0,” first coined in 2005, were guided by three main tenets: (a) health was to become more participatory, as an evolution in the Web encouraged more direct consumer engagement in their own healthcare; (b) data was to become the new “Intel Inside” for systems supporting the “vital decisions” in health; and (c) a sense of “collective intelligence” from the network would supplement traditional sources of knowledge in health decision-making. Interests in understanding the implications of a new paradigm for patient engagement in health and healthcare were kindled by findings from surveys such as the National Cancer Institute’s Health Information National Trends Survey (HINTS), showing that patients were quick to look online for information to help them cope with disease. This paper considers how these three facets of Health 2.0–participation, data, and collective intelligence–can be harnessed to improve the health of the nation according to Healthy People 2020 goals. We begin with an examination of evidence from behavioral science to understand how Web 2.0 participative technologies may influence patient processes and outcomes, better or worse, in an era of changing communication technologies. The paper then focuses specifically on the clinical implications of “Health 2.0” and offers recommendations to ensure that changes in the communication environment do not detract from national (e.g., Health People 2020) health goals. Changes in the clinical environment, as catalyzed by the Health Information Technology for Economic and Clinical Health (HITECH) Act to take advantage of Health 2.0 principles in evidence-based ways, are also considered.

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“…Executed correctly, the third way should allow individual scientists to “plug and play” into the broader framework. (Buetow, 2005; B. W. Hesse, 2008)…”

Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

Realizing the Promise of Web 2.0: Engaging Community Intelligence

Hesse

O’Connell

Augustson

et al. 2011

Journal of Health Communication

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“…12,13 Similarly, Hesse has stressed the urgency of getting not only proteomics and genomics but also populomics —an emerging field focused on the potential role of technology and population health problems—into the cyberinfrastructure for public health. 14–17 Hesse argues that cyberinfrastructure can affect population health in several ways: by expanding the scope of discovery through the use of new spatial pattern detection tools, by adding efficiencies to analysis and research design through visualization, by providing decision support for planning, by connecting many disparate sources of data, and by providing a basis for national and international planning. Eschenbach and Buetow argue that to achieve NCI’s ambitious goal of eliminating suffering and death due to cancer, a new generation of medicines is required, incorporating shared information technologies to connect and coordinate researchers across the cancer enterprise.…”

Section: Discussionmentioning

confidence: 99%

Building a Biomedical Cyberinfrastructure for Collaborative Research

Schád

Mobley

Hamilton

2011

American Journal of Preventive Medicine

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For the potential power of genome-wide association studies (GWAS) and translational medicine to be realized, the biomedical research community must adopt standard measures, vocabularies, and systems to establish an extensible biomedical cyberinfrastructure. Incorporating standard measures will greatly facilitate combining and comparing studies via meta-analysis, which is a means for deriving larger populations, needed for increased statistical power to detect less apparent and more complex associations (gene-environment interactions and polygenic gene-gene interactions). Incorporating consensus-based and well-established measures into various studies should reduce the variability across studies due to attributes of measurement, making findings across studies more comparable. This article describes two consensus-based approaches to establishing standard measures and systems: PhenX (consensus measures for Phenotypes and eXposures), and the Open Geospatial Consortium (OGC). National Institutes of Health support for these efforts has produced the PhenX Toolkit, an assembled catalog of standard measures for use in GWAS and other large-scale genomic research efforts, and the RTI Spatial Impact Factor Database (SIFD), a comprehensive repository of georeferenced variables and extensive metadata that conforms to OGC standards. The need for coordinated development of cyberinfrastructure to support collaboration and data interoperability is clear, and we discuss standard protocols for ensuring data compatibility and interoperability. Adopting a cyberinfrastructure that includes standard measures, vocabularies, and open-source systems architecture will enhance the potential of future biomedical and translational research. Establishing and maintaining the cyberinfrastructure will require a fundamental change in the way researchers think about study design, collaboration, and data storage and analysis.

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“…Termed the “cancer Biomedical Informatics Grid,” or caBIG®, the purpose of this new cyberinfrastructure was to connect the cancer research community in secure, interoperable, standardized, and semantically cohesive ways. 30–31 This new platform for cancer-related research would allow scientists to share protocols, operate in a harmonized way with standard measures, upload and share data, and obtain secure access to a virtual lattice of interconnected data sets. The spirit of the project matches the charge given to the Secretary of the DHHS by the Committee on Vital and Health Statistics in 2001: to “connect the dots” in biomedical and public health research.…”

Section: Open Science In Support Of Nihmentioning

confidence: 99%

Grid-Enabled Measures

Moser

Hesse

Shaikh

et al. 2011

American Journal of Preventive Medicine

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Scientists are taking advantage of the Internet and collaborative web technology to accelerate discovery in a massively connected, participative environment —a phenomenon referred to by some as Science 2.0. As a new way of doing science, this phenomenon has the potential to push science forward in a more efficient manner than was previously possible. The Grid-Enabled Measures (GEM) database has been conceptualized as an instantiation of Science 2.0 principles by the National Cancer Institute with two overarching goals: (1) Promote the use of standardized measures, which are tied to theoretically based constructs; and (2) Facilitate the ability to share harmonized data resulting from the use of standardized measures. This is done by creating an online venue connected to the Cancer Biomedical Informatics Grid (caBIG®) where a virtual community of researchers can collaborate together and come to consensus on measures by rating, commenting and viewing meta-data about the measures and associated constructs. This paper will describe the web 2.0 principles on which the GEM database is based, describe its functionality, and discuss some of the important issues involved with creating the GEM database, such as the role of mutually agreed-on ontologies (i.e., knowledge categories and the relationships among these categories— for data sharing).

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Of Mice and Mentors

Cited by 17 publications

References 34 publications

Realizing the Promise of Web 2.0: Engaging Community Intelligence

Realizing the Promise of Web 2.0: Engaging Community Intelligence

Building a Biomedical Cyberinfrastructure for Collaborative Research

Grid-Enabled Measures

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