Chapter 2 Research in Abnormal Psychology

Chapter 2 Research in Abnormal Psychology

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 2

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 3

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 4

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 5

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 6

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 7

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 8

Positive Correlation Slide 9

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 10

Negative Correlation Slide 11

The Correlational Method Correlational data can be graphed and a “line of best fit” can be drawn Unrelated no consistent relationship Slide 12

No Correlation Slide 13

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 14

High (Positive) Correlation Slide 15

Moderate (Positive) Correlation Slide 16

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 17

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 18

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 19

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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 21

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 22

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 23

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 24

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 25

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 26

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 27

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 28

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 29

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 30

Alternative Experimental Designs Multiple-baseline designs examine two or more dependent variables for change when an independent variable is introduced Slide 31