Abnormal Psychology

Researching Abnormality 159

Random assignment

Assigning participants to each group

in a study using a procedure that relies

on chance.

Sampling bias

The distortion that occurs when the

participants in an experiment have not been

drawn randomly from the relevant population

under investigation.

Population

The complete set of possible relevant

participants.

Sample

The small portion of a population that is

examined in a study.

Internal validity

A characteristic of a study, indicating that

it measures what it purports to measure

because it has controlled for confounds.

External validity

A characteristic of a study, indicating that

the results generalize from the sample to the

population from which it was drawn and from

the conditions used in the study to relevant

conditions outside the study.

inadvertently assign the people who

smile at you to the “non-loss” group.

Whether or not it is conscious (inten-

tional) or unconscious (unintentional),

a tendency or influence that distorts

data—which ends up producing a

confound—is called bias. This is why

researchers place participants in groups

usingrandom assignment, assigning

participants to each group by a proce-

dure that relies on chance.

Even if you randomly assign par-

ticipants to groups or have them take

part in both conditions, other biases

can interfere. Perhaps all your partici-

pants come from the same city, which

recently experienced a devastating hurricane (and so the theme of loss is particu-

larly salient for all participants).Sampling bias occurs when the participants are not

drawn randomly from the relevant population. Sampling bias needs to be avoided if

you want to be able to generalize (i.e., extrapolate) from the people in your study to

the population at large. This brings us to an important distinction: The population

is the complete set of possible participants (e.g., all rats or all people, or in certain

cases all people of a particular age, gender, or race). The sample is the small portion

of the population that is examined in a study.

Many of the same points also apply to the items that are selected to be used as

stimuli in the study. For example, you might select a very powerful “loss” fi lm and a

limp “depressing” fi lm—or vice versa. In this case, an irrelevant characteristic of the

items—how powerful they are—might determine the results. Just as you need to be

careful in sampling and assigning participants to groups, you need to be careful in

selecting the items (such as the specifi c items in a questionnaire), ensuring that they

are in fact representative of the types of items to which you want to generalize.

Internal and External Validity

A study has internal validity if it controls for possible confounding variables. Inter-

nal validity means that variations in the independent variable are in fact responsible

for variations in the dependent variable (or variables, in studies in which more than

one type of measurement is taken) and that the results are not a by-product of other,

extraneous variables.

A study is said to have external validity when the results generalize from the sam-

ple (the particular participants who were tested) to the population from which it was

drawn and from the conditions used in the study (such the particular movies shown,

in the example study) to similar conditions outside the study. If a study does not have

internal validity, it cannot have external validity. In contrast, even if a study has inter-

nal validity (its results have not been confounded), this does not guarantee that it will

have external validity (that its results apply to relevant situations or other people).

Quasi-Experimental Design

Ideally, the participants in a study are randomly assigned to groups. But, in many cases,

random assignment is not ethical, desirable, or possible. For instance, when trying to

test hypotheses about why a disorder develops, researchers cannot “assign” one group

to have a particular set of genes or brain functioning, a particular way of thinking, a

particular type of traumatic experience, or particular friends or families. Therefore, in

trying to understand possible causes of psychopathology, researchers often use quasi-

experimental designs, which rely on groups that already exist. In fact, the “experiment”

that we have been discussing is—like much research on psychopathology—a blend of

experiment (manipulation of independent variable and measurement of dependent vari-

able) and quasi-experiment (the selection of participants from pre-existing groups).

Suppose you want to know what the prevalence

is in the United States of the type of depres-

sion that results from seasonal changes in the

amount of daylight (sometimes referred to as

seasonal affective disorder). You are a researcher

in Portland, Oregon, and are collaborating on

the study with researchers in Boston, New York,

Chicago, and Detroit. Participants in the study

are drawn from those fi ve cities. Do you see the

sampling bias problem? All these cities are in the

northern half of the United States and therefore

have a different number of daylight hours than

does the southern half. Whatever prevalence

rate was calculated would not refl ect the entire

United States.

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