. "5 Specifying Questions and Locating Evidence: An Expanded View." Bridging the Evidence Gap in Obesity Prevention: A Framework to Inform Decision Making. Washington, DC: The National Academies Press, 2010.
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Bridging the Evidence Gap in Obesity Prevention: A Framework to Inform Decision Making
hospital discharge records and/or survey data (see the previous discussion of “Why” questions), some of which could be used to examine relationships among relevant variables (e.g., caloric intake, obesity, and diabetes). Some of the evidence could be used in descriptive form. According to Mello (2009), this type of evidence gathering was actually conducted in the New York case.
Questions 6 to 8 in Box 5-2 would allow for a more complete problem assessment to examine potential impacts of candidate interventions. Causal evidence on particular interventions is important to answer “What” questions. Additionally, parallel practice evidence (that is, evidence about the effectiveness of other relevant interventions for other health or social issues) might be useful. Likewise, informed expert opinion could be a useful source of evidence for appraising what is likely to work before population-based investments are made. With limited resources, comparative cost evaluations might also be imperative.
A variety of sources, then, could be used to gather evidence applicable to this case, such as observational research, experimental and quasi-experimental studies, expert knowledge, and parallel evidence on the implementation of interventions. The next section elaborates on these sources.
POTENTIALLY USEFUL SOURCES OF EVIDENCE
Seven categories of study designs and sources of evidence may be useful for addressing the concerns listed in Tables 5-1 to 5-3:
nonexperimental or observational studies,
experimental and quasi-experimental studies,
qualitative research and analysis,
evidence synthesis methods,
parallel evidence, and
It is important to note that quality standards apply to all of these categories, and the relative value of each source depends on the decision-making context (see Chapter 6). Each category is discussed in turn below (see Appendix A for formal definitions and Appendix E for further discussion).
Nonexperimental or Observational Studies
An observational study is one in which the researcher assesses relationships among variables but does not manipulate an intervention or variables associated with potential outcomes. Study designs or methodologies that fall within this category include cross-sectional, longitudinal, or retrospective survey research or opinion polls, trend analysis, some types of market research, secondary analysis of existing databases,