Our daily lives are filled with generalizations. Cook a good steak and decide if it’s done by tasting a small piece—you don’t eat the whole steak. Try out a new therapy with one patient and decide if you will use it again based on its effectiveness—you don’t test it on every patient. Researchers use this same principle in studying interventions, tests, and relationships. They obtain data on a group of subjects to make generalizations about what will happen to others with similar characteristics in a similar situation. To make this process work, we have to develop a plan to select appropriate individuals for a sample in a way that will allow us to extrapolate beyond that group’s performance for the application of research evidence to others.
Whether developing a sampling plan for a research study or determining if published evidence is relevant for clinical practice, we need to understand how study samples are recruited and how these methods impact our ability to generalize findings. The purpose of this chapter is to describe various sampling techniques and how they influence generalizations from representative subjects to make predictions about the larger world.
If we wanted to be truly confident in the effectiveness of an intervention, we would have to test it on every patient in the world for whom that treatment is appropriate. This larger group to which research results will be applied is called the population. It is the aggregate of persons or objects that meet a specified set of criteria and to whom we wish to generalize results of a study. For instance, if we were interested in studying the effects of various treatments for osteoarthritis, the population of interest would be all people in the world who have osteoarthritis.
Of course, it is not practical to test every person who has osteoarthritis, nor could we access them. Working with smaller groups is generally more economical, more time efficient, and potentially more accurate because it affords better control of measurement. Therefore, through a process of sampling, a researcher chooses a subgroup of the population, called a sample. This sample serves as the reference group for estimating characteristics of and drawing conclusions about the population.
Populations are not necessarily restricted to human subjects. Researchers may be interested in studying characteristics of institutions or geographical areas, and these may be the units that define the population. In test–retest reliability studies, the “population” will consist of all possible trials and the “sample” would be the actual measurements taken. Industrial quality control studies use samples of items from the entire inventory of a particular manufacturing lot. Surveys often sample households from a population of housing units. A population can include people, places, organizations, objects, or any other unit of interest.
Target and Accessible Populations