Christina H. Drew

Data-gathering strategies for social-behavioural research about participatory geographical information system use

Studies about geographical information systems (GIS) use contribute to geographic information science through critical evaluation of the concepts embedded in GIS tools. Social-behavioural studies about group use of GIS help us to understand the social implications of GIS because groups are fundamental units underlying intra-organizational, organization-wide, and inter-organizational activity in society. When group communication technology is integrated with basic GIS capabilities an enhanced version of GIS called ‘participatory GIS’ (PGIS) is created. Group use of PGIS technology can be studied by sampling social-behavioural events during human-computer-human interaction. Social-behavioural research about PGIS use requires an informed balance among three research domains—substantive, theoretical, and methodological—if we are to make balanced progress in participatory geographical information science associated with the critical evaluation of GIS use. In this paper, we draw from our research on GIS-supported collaborative decision making about land use and resource planning and a conceptual framework called Enhanced Adaptive Structuration Theory. We develop a new framework for understanding choices among data-gathering strategies for social-behavioural studies about PGIS use. The framework for data-gathering strategies is composed of two dimensions. One dimension is the level of induced control in social-behavioural relations during GIS use in a research setting. The other is the amount of pre- or post-structuring of variables embedded in data-collection techniques. Several common datagathering strategies, e.g. laboratory experiment, field experiment, case study, and field survey, are differentiated in terms of those dimensions. Objectives for empirical research are used to compare and contrast the data-gathering strategies. This framework helps researchers understand the trade-offs among various data-gathering strategies as the core of research designs for critical evaluations of PGIS use.

Transparency of environmental decision making: a case study of soil cleanup inside the Hanford 100 area

Environmental decisions in a democracy should be transparent. Transparency allows all those who are interested in a decision to understand what is being decided and why. Transparency is especially critical for decisions that are intended to protect public health and safety, and that have long‐term consequences. Decisions are recorded through publicly available documents (such as Records of Decision), collectively known as the public record. In this paper the transparency of the public record is examined for a specific decision at the US Department of Energy (DOE) Hanford site. To do this, the concept of transparency is unpacked into seven objectives: clarity, accessibility, integration, logic/rationale, truth/accuracy, openness, and accountability; and a framework for measuring decision transparency is developed. Then a Record of Decision is evaluated based on four of the seven objectives. Throughout, the importance of understanding decision processes and expected outcomes, and the broad values underpinning activities and choices are emphasized. It is found that, while many aspects of the process are transparent, it is difficult to discern and connect the values, objectives, subobjectives and criteria used as the basis of the decision. Several information structuring improvements (value trees, decision paths, and simple graphics and tables) that could make the public record more transparent are suggested. Such improvements are necessary for long‐term stewardship because future decision makers are likely to rely on the public record as the primary source of decision information. If information is not transparent, future decisions may be compromised.

Framing scientific analyses for risk management of environmental hazards by communities: case studies with seafood safety issues.

Risk management provides a context for addressing environmental health hazards. Critical to this approach is the identification of key opportunities for participation. We applied a framework based on the National Research Council’s (NRC) analytic–deliberative risk management dialogue model that illustrates two main iterative processes: informing and framing. The informing process involves conveying information from analyses of risk issues, often scientific, to all parties so they can participate in deliberation. In the framing process, ideas and concerns from stakeholder deliberations help determine what and how scientific analyses will be carried out. There are few activities through which affected parties can convey their ideas from deliberative processes for framing scientific analyses. The absence of participation results in one-way communication. The analytic–deliberative dialogue, as envisioned by the NRC and promoted by the National Institute of Environmental Health Sciences (NIEHS), underscores the importance of two-way communication. In this article we present case studies of three groups—an Asian and Pacific Islander community coalition and two Native American Tribes—active in framing scientific analyses of health risks related to contaminated seafood. Contacts with these organizations were established or enhanced through a regional NIEHS town meeting. The reasons for concern, participation, approaches, and funding sources were different for each group. Benefits from their activities include increased community involvement and ownership, better focusing of analytical processes, and improved accuracy and appropriateness of risk management. These examples present a spectrum of options for increasing community involvement in framing analyses and highlight the need for increased support of such activities.

Toward the Assessment of Scientific and Public Health Impacts of the National Institute of Environmental Health Sciences Extramural Asthma Research Program Using Available Data

Background In the past 15 years, asthma prevalence has increased and is disproportionately distributed among children, minorities, and low-income persons. The National Institute of Environmental Health Sciences (NIEHS) Division of Extramural Research and Training developed a framework to measure the scientific and health impacts of its extramural asthma research to improve the scientific basis for reducing the health effects of asthma. Objectives Here we apply the framework to characterize the NIEHS asthma portfolio’s impact in terms of publications, clinical applications of findings, community interventions, and technology developments. Methods A logic model was tailored to inputs, outputs, and outcomes of the NIEHS asthma portfolio. Data from existing National Institutes of Health (NIH) databases are used, along with publicly available bibliometric data and structured elicitation of expert judgment. Results NIEHS is the third largest source of asthma-related research grant funding within the NIH between 1975 and 2005, after the National Heart, Lung, and Blood Institute and the National Institute of Allergy and Infectious Diseases. Much of NIEHS-funded asthma research focuses on basic research, but results are often published in journals focused on clinical investigation, increasing the likelihood that the work is moved into practice along the “bench to bedside” continuum. NIEHS support has led to key breakthroughs in scientific research concerning susceptibility to asthma, environmental conditions that heighten asthma symptoms, and cellular mechanisms that may be involved in treating asthma. Conclusions If gaps and limitations in publicly available data receive adequate attention, further linkages can be demonstrated between research activities and public health improvements. This logic model approach to research impact assessment demonstrates that it is possible to conceptualize program components, mine existing databases, and begin to show longer-term impacts of program results. The next challenges will be to modify current data structures, improve the linkages among relevant databases, incorporate as much electronically available data as possible, and determine how to improve the quality and health impact of the science that we support.

Scientific and public health impacts of the NIEHS Extramural Asthma Research Program: insights from primary data

A conceptual model was developed to guide evaluation of the long-term impacts of research grant programs at the National Institutes of Health, National Institute of Environmental Health Sciences. The model was then applied to the extramural asthma research portfolio in two stages: (1) the first used extant data sources, (2) the second involved primary data collection with asthma researchers and individuals in positions to use asthma research in development of programs, policies, and practices. Reporting on the second stage, this article describes how we sought to broaden the perspectives included in the assessment and obtain a more nuanced picture of research impacts by engaging those involved in conducting or using the research.

Public agencies and environmental risk: Organizing knowledge in a democratic context

Purpose – To derive from the environmental risk and knowledge management literatures a model that integrates organizational form, democratic vision and epistemological needs of public agencies responsible for addressing environmental risks. To analyze the knowledge management practices of the United States Department of Energy (USDOE) that is responsible for cleaning up landscapes contaminated by 50 years of plutonium production.Design/methodology/approach – The model was used as a framework for a case study analysis of the USDOE knowledge management practices.Findings – Conceptual: a vision of democracy and an understanding of the type of knowledge process can facilitate organizational constancy. Organizational forms should be matched to knowledge process and democratic vision. Empirical: USDOE has behaved erratically in addressing environmental risks viewed through this model of knowledge management.Research limitations/implications – The model idealizes democratic visions, epistemological processes and...

Using decision paths to explore three environmental cleanup decisions: a cross-case analysis

Transparent decisions are widely sought by parties interested in and affected by cleanup activities at government-owned facilities. In an approach to transparency, this paper uses decision paths and timelines to compare three decisions at the US Department of Energy Hanford site. A regulatory decision strategy, consisting of seven sequential (linear) steps, is used as the basis for the analysis. We find that the decision path is different for each case, although the timeframe associated with the main steps is similar. Also, although decision steps are evident in each case study, the decision process unfolds in cycles rather than following the linear path typically described to stakeholders. Finally, we observe a stronger emphasis on the information-gathering step than on other steps in the decision process. These findings suggest that new ways of representing decision situations are needed if transparency is to be achieved.

NIEHS extramural global environmental health portfolio: opportunities for collaboration.

Background Global environmental health has emerged as a critical topic for environmental health researchers and practitioners. Estimates of the environmental contribution of total worldwide disease burden range from 25 to 33%. Objective We reviewed grants funded by the National Institute of Environmental Health Sciences (NIEHS) during 2005–2007 to evaluate the costs and scientific composition of the global environmental health portfolio, with the ultimate aim of strengthening global environmental health research partnerships. Methods/Results We examined NIEHS grant research databases to identify the global environmental health portfolio. In the past 3 fiscal years (2005–2007), the NIEHS funded 57 scientific research projects in 37 countries, at an estimated cost of

Measuring partnership activities: partnerships in environmental public health evaluation metrics manual.

30 million. Metals such as arsenic, methylmercury, and lead are the most frequently studied toxic agents, but a wide range of stressors, routes of exposure, and agents are addressed in the portfolio. Conclusions The portfolio analysis indicates that there is a firm foundation of research activities upon which additional global environmental health partnerships could be encouraged. Current data structures could be strengthened to support more automated analysis of grantee information.

The Hanford Openness Workshops: Fostering Open and Transparent Long-Term Decision Making at the Department of Energy

The National Institute of Environmental Health Sciences (NIEHS) has had a long-standing commitment to facilitate and engage community groups in environmental health science research. In 2008, the NIEHS established the Partnerships for Environmental Public Health (PEPH) program to formalize our commitment to outline a coordinated vision for community and academic partnerships. Since then, > 400 grantees have participated in activities designed to foster net-working among grantees within the various NIEHS programs, including webinars and workshops on communicating PEPH findings and translating research to public health policy. A key tenet of the PEPH is community engagement. In response to an NIEHS Request for Information in 2008, the community shared concerns about the lack of evaluation capacity and the need for tools and approaches to develop project specific evaluation metrics for public health–related program areas. In response, the NIEHS developed the PEPH Evaluation Metrics Manual (NIEHS 2012b) with significant input from PEPH grantees, program staff, and experts in the field, including input from > 250 individuals at > 30 professional meetings. Evaluation of PEPH programs provides useful bene-fits to grantees, including the ability to a) identify program successes; b) determine whether a project worked and why (or why not); c) identify areas for program improvement and increased efficiency; d) describe expenditures and justify a need for additional funding; e) recognize and respond to public needs and wants; f ) identify new audiences and applications for projects; and g) prioritize research and plan for the future. Evaluation also may help grantees find allies in other agencies, services, or sectors; publicize achievements in communities; and inform policy and other decision making. Evaluation metrics also provide a means for the NIEHS to evaluate the success of individual projects and the PEPH program as a whole. Typical approaches to evaluating research outcomes involve analyzing publications. However, because many PEPH programs do not publish findings related to their community engagement, we worked with grantees and community members to identify appropriate metrics to measure and demonstrate success in five areas that are common to many PEPH grantees: Partnering (working with other organizations to conduct environmental public health activities) Leveraging (using the resources already available to a project to obtain additional resources) Disseminating findings (providing information about environmental public health issues and results of PEPH research) Training (developing programs that teach researchers, community members, workers, students, and others strategies for reducing hazardous environ-mental exposures) Capacity building (performing activities that improve an organization’s ability to achieve its mission). For each of these five areas, the NIEHS developed an illustrative logic model to demonstrate connections among project activities, outputs, and impacts; > 80 examples of metrics for each activity, output, and impact are provided as examples for grantees developing metrics for evaluating the progress and achievements of their own programs. We present the partnership logic model (Figure 1; NIEHS 2012b) to illustrate how metrics can be developed from a logic model. When developing program logic models, it can be helpful to begin by working with partners to identify and articulate the desired impacts of the program. Once partners agree about “where they want to go” (impacts), discussions of “how to get there” (activities) naturally follow. Then partners can determine “how will we know we are there?” (outputs and metrics). The nouns, adjectives, verbs, and adverbs in the answers to these questions then serve as the basis for metrics. Examples of metrics from grantee programs that address components of the partnership logic model include: Demonstrating success at identifying partners (activity 1), the University of Cincinnati’s anti-idling campaign provided a description of the partners involved and the resources they bring to the project: Cincinnati Public Schools provided access to students and schools; the Cincinnati Health Department provided nursing services; a councilwoman provided credibility and the ability to attract attention to the project; and the Hamilton County Department of Environmental Services provided training and information to Cincinnati Public School staff and students. Demonstrating their success in involving community partners in research, the University of Florida, the Farmworker Association of Florida (FWAF), and Best Start Inc. (a social marketing research firm) described how partners were involved in the Together for Agricultural Safety Project (output 4). Members of the FWAF helped develop and lead focus groups and provided input into the survey development; researchers from the University of Florida and Best Start Inc. collected data; and 382 farm-workers provided data. All three partners also contributed to an article summarizing the process by which the project was implemented (Flocks et al. 2001). The Detroit Community-Academic Urban Research Center is a collaborative partnership that includes the University of Michigan Schools of Public Health, Nursing, and Social Work; the Detroit Department of Health and Wellness Promotion; eight community-based organizations; and the Henry Ford Health System. To demon-strate their success at expanding research collaborations, they provided details of the additional research opportunities that were generated as a result of the partnership (impact 3). These research opportunities included four grants from the NIEHS: