The Theory-Based Influence of Map Features on Risk Beliefs: Self-Reports of What Is Seen and Understood for Maps Depicting an Environmental Health Hazard

Abstract

Theory-based research is needed to understand how maps of environmental health risk information influence risk beliefs and protective behavior. Using theoretical concepts from multiple fields of study including visual cognition, semiotics, health behavior, and learning and memory supports a comprehensive assessment of this influence. The authors report results from 13 cognitive interviews that provide theory-based insights into how visual features influenced what participants saw and the meaning of what they saw as they viewed 3 formats of water test results for private wells (choropleth map, dot map, and a table). The unit of perception, color, proximity to hazards, geographic distribution, and visual salience had substantial influences on what participants saw and their resulting risk beliefs. These influences are explained by theoretical factors that shape what is seen, properties of features that shape cognition (preattentive, symbolic, visual salience), information processing (top-down and bottom-up), and the strength of concrete compared with abstract information. Personal relevance guided top-down attention to proximal and larger hazards that shaped stronger risk beliefs. Meaning was more local for small perceptual units and global for large units. Three aspects of color were important: preattentive “incremental risk” meaning of sequential shading, symbolic safety meaning of stoplight colors, and visual salience that drew attention. The lack of imagery, geographic information, and color diminished interest in table information. Numeracy and prior beliefs influenced comprehension for some participants. Results guided the creation of an integrated conceptual framework for application to future studies. Ethics should guide the selection of map features that support appropriate communication goals.

Acknowledgments

This study was supported by a grant from the University of Wisconsin–Madison School of Nursing “Center for Patient Centered Interventions” funded by National Institutes of Health grant P20-NR008987; a grant from the University of Wisconsin–Madison Graduate School; and grant 1UL1RR025011 from the Clinical and Translational Science Award Program of the National Center for Research Resources, National Institutes of Health (for editorial assistance). The authors also thank Nathan Rehberg, a University of Wisconsin–Madison geography student, for assistance with maps and reviewers for helpful comments on the article.

Notes

¹Dot maps depict the distribution of a phenomenon using small symbols. Choropleth maps depict statistical information across areal enumeration units such as a county (Slocum, 2005).

²For example, seeing two marks on a linear scale results in knowledge about the magnitude of their relationship.

³Sometimes proximity is related to weaker perceived risk, perhaps because familiar hazards are perceived as less dangerous or because polluting industries provide economic benefits (Heath, Seshadri, & Lee, 1998).

⁴These dimensions explained beliefs related to contaminated drinking water from a private well (Severtson, Baumann, & Brown, 2008). Beliefs that identified water safety were key influences on protective behavior (Severtson, Baumann, & Brown, 2006).

⁵We also assessed: (a) how map titles supported comprehension, (b) how formats influenced intentions to test water, and (c) participant comments that reflected other common sense model dimensions. For results related to these objectives, visit http://research.son.wisc.edu/wellstudy/JoHC2012.pdf.

⁶A township is a geographic surveyor's unit measuring 6 × 6 square miles. Towns are a local form of government that usually have the same dimensions as does their corresponding township (Wisconsin Towns Association, 2009).

⁷The maximum contaminant level, commonly referred to as a drinking water standard, is the highest permissible level of contaminant in drinking water deemed suitable for human consumption. Maximum contaminant levels are enforced for public water supplies (U.S. Environmental Protection Agency, 2010a) but not for private wells (U.S. Environmental Protection Agency, 2010b).

⁸Brewer (2006) recommended using hatching patterns over color on choropleth maps to designate uncertainty when information is based on a small sample. Our prestudy development of maps found people did not notice hatching, so the background color was removed to make it more conspicuous.

⁹Cognitive think-aloud interviews have a long history as a method to discover cognitive processes as people engage in a task (Ericsson & Simon, 1993). Cognitive interviewing has evolved to include questions about meaning and comprehension (Beatty & Willis, 1997).

¹⁰After the first round, we adjusted (unsuccessfully) the dark red dot to look less brown. After the second round, we deleted the term percent from the township map title to ease comprehension and changed the term drinking water standard to maximum contaminant level (MCL) for all formats. We provided the purple township map (following the red map) to 5 participants from the first and second rounds.

¹¹This information approximates that of arsenic, a drinking water contaminant of groundwater and well water. Participants were asked to pretend rhynium was real.

Note. Numbers in headers (C1-3) pertain to column numbers. Numbers in rows (R1-5) pertain to row numbers.

¹²Numeracy, the ability to understand basic probability and mathematical concepts, influences the comprehension of risk information (Nelson, Reyna, Fagerlin, Lipkus, & Peters, 2008).

¹³ Seeing is tightly integrated with meaning—distinguishing between these remains a challenge to the field of visual cognition (Tversky, 2005). Representing “what is seen” in the model is a reminder that this step occurs, whether or not it is measured.

¹⁴We acknowledge that specific beliefs underlie rather than cause global beliefs. Denoting specific as causing global beliefs supports an analysis of this relationship and the unique role of each belief in mediating the relationship between features and behavior.

¹⁵For examples, see Anselin (2006); Bell, Hoskins, Pickle, and Wartenberg (2006); Brewer (2006); Monmonier and Johnson (1997); Monmonier (1996); and Slocum (2005).