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Introduction

—with K. Douglas Gross

 

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In contrast to experimental trials that test the effectiveness of interventions using variable manipulation and controlled comparisons, observational studies characterize unmodified relationships, analyzing how existing factors or individual characteristics are associated with health outcomes. Observational studies explore the causes, consequences, and predictors of disease or disability. They also characterize the impact of exposure to risk factors on individual or community health. This research approach may be regarded as exploratory since it often probes data about personal, environmental, behavioral, or genetic influences that may explain health outcomes.

The purpose of this chapter is to describe basic approaches to observational research with a focus on cohort and case-control study designs, and to discuss considerations that are relevant to using these designs for evidence-based practice. Analysis procedures for these designs will be covered in Chapter 34.

Exploring Relationships

Observational research may be classified as descriptive or analytic. The purpose of descriptive research is to characterize populations by examining the distribution of health-related variables within them, often with the intention of generating hypotheses about factors that may give rise to observed differences across population groups (see Chapter 20). Analytic research focuses on examining those group differences in order to demonstrate how personal, environmental, behavioral, or genetic exposures help explain why one group’s outcomes differ from another’s. Analytic studies are typically motivated by hypotheses that specify the particular exposures and outcomes to be studied and clarify the interpretations that will be offered for any found associations.

In experimental research, participants are assigned to an intervention or control group for the purpose of demonstrating what outcomes are expected when the trial treatment is provided or withheld. Similarly, observational investigators are interested in comparing the outcomes of subjects who are exposed or unexposed to hypothesized causal agents. However, an observational researcher plays no part in the assignment of subjects to exposed or unexposed conditions. Instead, existing groups of subjects are identified by their shared history or current health status. Although experimental designs offer the best option for demonstrating treatment effectiveness, observational studies are frequently undertaken to derive models that predict the likelihood that a particular treatment will succeed in the presence of one or more prognostic indicators.

image Observational studies are also used to derive clinical prediction rules for prognosis and to identify diagnostic indicators that accurately signal the presence or absence of a target condition. The accuracy of a set of diagnostic indicators may be modeled as a clinical diagnostic rule (see Chapter 33).

Estimating Risk

Perhaps the most common use of an observational design is to draw causal inferences about the effects of a hypothesized risk factor. This is done by comparing outcomes of a group of subjects who have been exposed to a risk factor to ...

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