Chapter 2

Research in Abnormal Psychology

Slides & Handouts by Karen Clay Rhines, Ph.D.Seton Hall University

Slide 2

Research in Abnormal Psychology

Research is the key to accuracy in all fields

• Particularly important (and challenging) in the field of abnormal psychology

• Theories and treatments that seem reasonable and effective in individual instances may prove disastrous when widely applied

• Only after rigorous testing can a theory or technique be considered valid or effective

Slide 3

Research in Abnormal Psychology

Clinical researchers face certain challenges that make their investigations particularly difficult:• Measuring unconscious motives

• Assessing private thoughts

• Monitoring mood changes

Clinical researchers must consider the cultural backgrounds, races, and genders of those they study

Clinical researchers must follow the code of ethics to ensure that their subjects are not harmed

Slide 4

What Do Clinical Researchers Do?

Clinical researchers try to discover laws and principles of abnormal psychological functioning:

• Generally do not assess, diagnose, or treat individual clients

• Search for nomothetic understanding

• General or universal laws

• Use the scientific method to pinpoint relationships among variables

• Use three methods of investigation…

Slide 5

The Case Study

Provides a detailed description of a person’s life & psychological problems

Is helpful because it can serve as a source of new ideas about behavior• Freud’s theories based entirely on case studies

May offer tentative support for a theory

May challenge a theory’s assumptions

May inspire new therapeutic techniques

May offer opportunities to study unusual problems

Slide 6

The Case Study

Has limitations:

• Observers are biased

• Relies on subjective evidence

• Is low on internal validity

• Provides little basis for generalization

• Is low on external validity

These limitations are addressed by the two other methods of investigation…

Slide 7

The Correlational Method & the Experimental Method

Do not offer richness of detail

Allow researchers to draw broad conclusions

• Typically involve observing many individuals

• Researchers apply procedures uniformly

• Studies can be replicated

• Researchers use statistical tests to analyze results

Slide 8

The Correlational Method

Correlation is the degree to which events or characteristics vary from each other

• Measures the strength of a relationship

• Does not imply cause and effect

The people chosen for a study are its subjects or participants, collectively called a sample

• The sample must be representative

Slide 9

The Correlational Method

Correlational data can be graphed and a “line of best fit” can be drawn

• Positive correlation = variables change in the same direction

Slide 10

Positive Correlation

Slide 11

The Correlational Method

Correlational data can be graphed and a “line of best fit” can be drawn

• Negative correlation = variables change in the opposite direction

Slide 12

Negative Correlation

Slide 13

The Correlational Method

Correlational data can be graphed and a “line of best fit” can be drawn

• Unrelated = no consistent relationship

Slide 14

No Correlation

Slide 15

The Correlational Method

The magnitude (strength) of a correlation is also important

• High magnitude = variables which vary closely together; fall close to the line of best fit

• Low magnitude = variables which do not vary as closely together; loosely scattered around the line of best fit

Slide 16

High (Positive) Correlation

Slide 17

Moderate (Positive) Correlation

Slide 18

The Correlational Method

Direction and magnitude of a correlation are often calculated statistically• Called the “correlation coefficient,” symbolized by the

letter “r”• Sign (+ or -) indicates direction

• Number (from 0.00 to 1.00) indicates magnitude

• 0.00 = no consistent relationship

• +1.00 = perfect positive correlation

• -1.00 = perfect negative correlation

Most correlations found in psychological research fall far short of “perfect”

Slide 19

The Correlational Method

Correlations can be trusted based on statistical probability

• “Statistical significance” means that the finding is unlikely to have occurred by chance

• By convention, if there is less than a 5% probability that findings are due to chance (p < 0.05), results are considered “significant” and thought to reflect the larger population

• Generally, confidence increases with the size of the sample and the magnitude of the correlation

Slide 20

The Correlational Method

Advantages of correlational studies:

• Have high external validity

• Can generalize findings

• Can repeat (replicate) studies on other samples

Difficulties with correlational studies:

• Lack internal validity

• Results describe but do not explain a relationship

Slide 21

Slide 22

The Correlational Method

Two special forms of correlational study:

• Epidemiological studies

• Reveal the incidence and prevalence of a disorder in a particular population

• Incidence = number of new cases in a given time period

• Prevalence = total number of cases in a given time period

• Longitudinal studies

• Observe one sample of participants on many occasions over a long period of time

Slide 23

The Experimental Method

An experiment is a research procedure in which a variable is manipulated and the manipulation’s effect on another variable is observed

• Manipulated variable = independent variable

• Variable being observed = dependent variable

Allows researchers to ask such questions as: Does therapy X reduce symptoms of disorder Y?

• Causal relationships can only be determined through experiments

Slide 24

The Experimental Method

Statistics and research design are very important

• Researchers must eliminate all confounds – those variables other than the independent variable that may also be affecting the dependent variable

• Three features are included in experiments to guard against confounds:

• The control group

• Random assignment

• Blind design

Slide 25

The Experimental Method

A control group is a group of participants who are not exposed to the independent variable, but whose experience is similar to that of the experimental group

• By comparing the groups, researchers can better determine the effect of the independent variable

Rules of statistical significance are applied

Slide 26

The Experimental Method

Researchers must also watch out for preexisting differences between the experimental and control groups

• To do so, researchers use random assignment – any one of a number of selection procedures that ensures that every participant in the experiment is as likely to be placed in one group as another

• Examples: coin flip; drawing names from a hat

Slide 27

The Experimental Method

A final problem with confounds is bias• To avoid bias by the participant, experimenters employ a

“blind design,” in which participants are kept from knowing what condition of the study (experimental or control) they are in

• One strategy for this is providing a placebo – something that looks or tastes like real therapy but has no key ingredient

• To avoid bias by the experimenter, experimenters employ a “double-blind design,” in which both experimenters and participants are kept from knowing what condition of the study participants are in

• Often used in medication trials

Slide 28

Alternative Experimental Designs

It is difficult to devise an experiment that is both well controlled and enlightening

Clinical researchers often must settle for designs that are less than ideal and include:

• Quasi-experimental designs

• Natural experiments

• Analogue experiments

• Single-subject experiments

Slide 29

Alternative Experimental Designs

In quasi-experimental designs, investigators do not randomly assign subjects to groups, but make use of group that already exist

• Example: children with a history of child abuse

To address the problem of confounds, researchers use matched control groups

• These groups are “matched” to the experimental group, based on demographic and other variables

Slide 30

Alternative Experimental Designs

In natural experiments, nature manipulates the independent variable and the experimenter observes the effects

• Example: psychological impact of flooding

• Cannot be replicated at will

• Broad generalizations cannot be made

Slide 31

Alternative Experimental Designs

Analogue experiments allow investigators to freely manipulate independent variables while avoiding ethical and practical limitations

• They induce laboratory subjects to behave in ways that seem to resemble real life

• Example: animal subjects

• Major limitation of all analogue research is that experimenters cannot be certain that the phenomena observed in the lab are the same as the psychological disorders being investigated

Slide 32

Alternative Experimental Designs

In a single-subject (“n of 1”) experiment, a single participant is observed both before and after manipulation of an independent variable

• Experiments rely on baseline data to set a standard for comparison

• Common experimental designs are ABAB and multiple-baseline designs

Slide 33

Alternative Experimental Designs

In ABAB (reversal) designs, a participant’s reactions are measured during a baseline period (A), after the introduction of the independent variable (B), after the removal of the independent variable (A), and after reintroduction of the independent variable (B)

• The subject is, essentially, compared against him or herself rather than against control subjects

Slide 34

Alternative Experimental Designs

Multiple-baseline designs examine two or more dependent variables for change when an independent variable is introduced

Slide 35

Alternative Experimental Designs

Both types of single-subject experiments are similar to individual case studies

• Both focus on one subject only

• Both have low external validity

However, both types of single-subject experiments have higher internal validity than the case study, given the manipulation of an independent variable