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Updated: Jul 5, 2026
Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
Published on: July 27, 2018
Conceptual model of comprehensive research metrics for improved human health and environment
Jill A Engel-Cox1, Bennett Van Houten, Jerry Phelps
1Battelle Memorial Institute, Arlington, VA 22201, USA. engelcoxj@battelle.org
Objective:
Federal, state, and private research agencies and organizations have faced increasing administrative and public demand for performance measurement. Historically, performance measurement predominantly consisted of near-term outputs measured through bibliometrics. The recent focus is on accountability for investment based on long-term outcomes. Developing measurable outcome-based metrics for research programs has been particularly challenging, because of difficulty linking research results to spatially and temporally distant outcomes. Our objective in this review is to build a logic model and associated metrics through which to measure the contribution of environmental health research programs to improvements in human health, the environment, and the economy.
Data Sources:
We used expert input and literature research on research impact assessment.
Data Extraction:
With these sources, we developed a logic model that defines the components and linkages between extramural environmental health research grant programs and the outputs and outcomes related to health and social welfare, environmental quality and sustainability, economics, and quality of life.
Data Synthesis:
The logic model focuses on the environmental health research portfolio of the National Institute of Environmental Health Sciences (NIEHS) Division of Extramural Research and Training. The model delineates pathways for contributions by five types of institutional partners in the research process: NIEHS, other government (federal, state, and local) agencies, grantee institutions, business and industry, and community partners.
Conclusions:
The model is being applied to specific NIEHS research applications and the broader research community. We briefly discuss two examples and discuss the strengths and limits of outcome-based evaluation of research programs.
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