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Rates can account for population size and time intervals. To generate a rate, the population from which the counts arose must be defined. Population size is a common choice for a denominator. Many geopolitical regions, such as cities or countries, create estimates of the population during a given year. Cumulative incidence is commonly used when the entire population from which the incident cases arise can be counted and followed to the conclusion of the observation period. Proportional incidence or proportional mortality is sometimes used when an accurate denominator is not available. A more formal statistical test of a difference in two proportions is the chi-squared test; large sample and exact methods are available in virtually any statistical package. To compare the rates of injury in two or more regions, or between time periods, it is sometimes desirable to adjust for other factors, which may confound the comparison.
This chapter orients the injury researcher to important methodologic issues in applying the randomized trial design, and illustrates how the design has been applied in injury research. It provides entry points into the literature on randomized trial methodology. The idea for a randomized trial usually originates from interest in the effects of a particular intervention, which becomes one arm of the trial. Random allocation, the feature that distinguishes a randomized trial from other study designs, is responsible for the substantial advantages of this design. Two issues of randomization are at stake. One is whether the assignment sequence that specifies which subject goes to which intervention arm is truly random. The other is allocation concealment, whether the intervention assignment of a subject is adequately hidden from persons involved in deciding whether and when the subject enters the trial. The data analysis is usually to compare the intervention groups on baseline characteristics.
This chapter considers only observational ecologic studies. Exploratory ecologic studies are a useful source of hypotheses about individual-level associations that can be followed up in studies that use individuals as the units of measurement and analysis. A narrow focus on individual-level associations may miss important spillover effects. Ecologic studies, in contrast, may detect them. Studies of the effectiveness of community-based intervention programs may involve determining whether presence of the law, policy, or program in a population is associated with a lower rate of adverse outcomes in that population. Because primary scientific interest focuses on group-level associations, ecologic studies are well matched to this purpose. The chapter discusses the design considerations in ecologic studies. It also focuses on concerns of special relevance to ecologic studies particularly when they are used for evaluating legal interventions, drawing freely on the Campbell and Stanley formulation.
To study exposures which cannot be randomly assigned, we usually turn to comparative observational study designs: either cohort or case-control studies. The chapter describes the design and analysis of case-control studies. In planning a case-control study, it is helpful to think of the study as being set in a specific population or cohort, even though most members of that population will not participate in the study. In selecting cases, we should consider the step in the causal chain that we wish to study. In principle, controls should be a sample of persons from the same population from which the cases were derived. The chapter also discusses two special case-control designs, proportional mortality studies and case-crossover studies. Matching controls to cases may be justified if it promises to enhance study efficiency or to control for factors that cannot otherwise be measured.
In the twentieth-century, evidence-based injury prevention and control strategies have contributed to a substantial decline in the number of deaths associated with injury. However, researchers in the field of injury prevention have often gathered their study methods from other disciplines; it can be difficult for injury investigators to locate all of the research tools that can be applied to problems related to injury. Injury Control: A Guide to Research and Program Evaluation addresses the growing need for a comprehensive source of knowledge on all research designs available for injury control and research. Included in this accessible guidebook is information about choices in study design, details about study execution and discussion of specific tools such as injury severity scales, programme evaluations and systematic reviews. Epidemiologists, health service investigators, trauma surgeons and emergency medicine physicians will find this a useful source for understanding, reviewing and conducting research related to injuries.
This chapter provides an overview of the major study designs for the injury-related research project, and highlights factors that guide the investigator to an appropriate design choice. It illustrates the application of several commonly used study designs to injury research through examples. The descriptive study design is a narrative account of a specific clinical injury case. Descriptive epidemiologic studies can be a rich source of hypotheses that can be followed up in analytic studies. An analytic study focuses on one or more hypotheses to be tested. Among analytic study designs, a key distinction is between intervention studies and observational studies. An important methodological issue in all observational studies is confounding. A variety of other analytic study designs are available for injury research. Most were developed for specialized research purposes and hence are less commonly used. Finally, the chapter discusses two other analytic study designs, namely case-crossover design and regression-discontinuity design.