1. PowerPoint  Lecture Notes Presentation Chapter 4 Research Methods in the Study of Psychopathology
Abnormal Psychology, Eleventh Edition by Ann M. Kring, Gerald C. Davison, John M. Neale, & Sheri L. Johnson

2. Science and Scientific Methods
The systematic pursuit of knowledge through observation
Scientists gather data to test theories
Theory
Set of propositions developed to explain what is observed
A good theory is falsifiable
Allows for disconfirmation
Hypotheses
Specific predictions about what will occur if a theory is correct.
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3. Table 4.1 Research Methods in Psychopathology
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Case Study
Detailed biographical description of an individual
Family history
Medical status
Educational background
Information about peer and romantic relationships
Personality and adjustment issues
Current difficulties and prior experiences in therapy.
Usefulness
Rich description, especially helpful for rare disorders
Disprove hypothesis
Generate hypotheses
Limitations
Paradigm may influence observations
Cannot rule out alternative explanations
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Correlational Method
Do variable X and variable Y vary together?
Are they related in a systematic way?
Do people who experience more stress have more headaches?
Variables measured but not manipulated
Cannot determine cause or effect
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6. Figure 4.2 Correlational vs. Experimental Studies
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Table 4.2 Data for a Correlational Study with Diagnosis
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8. Table 4.3 Data for Determining a Correlation
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9. Measuring Correlation
Correlation Coefficient
Varies from -1.0 to +1.0
e.g., +.9, -.65, +.32, -.70
Strength
The higher the absolute value, the stronger the relationship
(-.9 > +.6; +.9 > -.8)
Direction
Positive
Higher scores on Var X associated with higher scores on Var Y
Negative
Higher scores on Var X associated with lower scores on Var Y
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10. Figure 4.3 Scatter Diagrams
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Fig 4.2

11. Statistical and Clinical Significance
Statistical significance
Probability ≤ .05
Can be influenced by number of participants
Larger samples increase likelihood of significance
Clinical significance
Is the association meaningful as well as statistically significant?
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Problems of Causality
Correlation does not imply causality
Directionality problem
Var X may cause Var Y
Var Y may cause Var X
Third-variable problem
Var Z causes both Var X and Var Y
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13. Longitudinal vs Cross-sectional designs
Studies participants over time
Examines whether causes are present before disorder develops
High Risk Method
Include only those who are at greatest likelihood of developing a disorder
Reduces the cost of longitudinal research
Cross-sectional
Causes and effects measured at the same time
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14. Epidemiological Research
Epidemiology
Study of the distribution of disorders in a population and possible correlates
Three features of a disorder
Prevalence
Incidence
Risk Factors
The National Comorbidity Survey–Replication
Large-scale national survey
Used structured interviews to collect information on the prevalence of several diagnoses (Kessler et al., 2005).
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15. Table 4.4 Lifetime Prevalence Rates of Selected Disorders
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16. Correlational Research: Behavioral Genetics
Index cases/Probands
Sample of individuals with psychopathology
Concordance
Co-occurrence or similarity of diagnosis
Family studies
First degree relatives (parents, children, siblings)
50% shared genes
Second degree relatives (aunts, uncles, grandparents)
25% shared genes
Twin studies
Monozygotic (MZ) twins
100% shared genes
Dizygotic (DZ) twins
50% shared genes
Equal environment assumption
Adoption studies
Study of adoptees who have biological parents with psychopathology
Cross-fostering
Study of adoptees who have adoptive parents with psychopathology
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17. Correlational Research: Molecular Genetics
Linkage analysis method
Study individual with disorder and family members who also have the disorder
Relies on the study of genetic markers.
Genetic markers are diseases or characteristics with a known chromosomal location of the genes involved.
Association studies
Examine the relationship between a specific allele and a trait or behavior in the population
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The Experiment
Provides information about causal relationships
Involves:
Independent variable
Random assignment
Dependent variable
Can evaluate treatment effectiveness
Experimental Effect
Differences between groups
Figure 4.3 Pennebaker et al., 1988
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Table 4.5 Results of a Hypothetical Study Comparing CBT to No Treatment for Depression
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20. Basic Features of Experimental Design
The investigator manipulates an independent variable
Participants are assigned to the conditions by random assignment.
Researcher measures a dependent variable that is expected to vary with conditions of the independent variable.
Experimental effect
Differences between conditions on the dependent variable
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The Experiment
Internal validity
Extent to which experimental effect is due to independent variable
Control Group
Participants who do not receive treatment
Standard against which treatment effectiveness is judged.
Placebo
Change or improvement due to participants’ expectations
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The Experiment
External validity
Extent to which results generalize beyond the study
Would results apply to others besides the study participants?
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Analogue Experiment
Experiments not always possible in psychopathology
Ethical or practical constraints
Examine related or similar behavior in the lab
Elicit stress or sadness
College students who tend to be anxious
Animal research
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24. Single-Subject Experimental Research
Examine how individual participants respond to changes in the independent variable.
Reversal (ABAB) Design
The reversal technique not always possible
Initial state may not be recoverable.
Chorpita et al. (1977)
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25. Integrating Findings from Multiple Studies
Meta-analysis
Identify relevant studies
Compute effect size
Transforms results to a common scale
Smith et al. (1980)
Meta-analyzed 475 outcome studies
Results: Psychotherapy is effective
Figure 4.5 Steps in Conducting a Meta-Analysis
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Table 4.6 Meta-analysis: One-year prevalence rates for mental illness across 21 European studies
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