Post on 17-Dec-2015
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