Case Studies

advertisement
Nonexperimental Research
Designs: Case Studies & Single
Variable Research
Chapter 6
James A. Van Slyke
Importance of Case Studies

The Curious Case of Phineas Gage


Before accident
 Intelligent
 capable worker
 excellent manager
 responsible family man
After Accident
 Maintained his general intelligence
 Unreliable and volatile
 Socially Inappropriate
 Lost his family and fortune
R econ stru ction
of th e S k u ll
of P h in eas G age
F rom H ana D am asio et al.,
“T he R eturn of P hineas
G age: C lues about the brain
from the skull of a fam ous
patient” Science. 1994, 264,
1 1 0 2-1105.
Galvanic Skin Response
Iowa Gambling Task
Nonscientific Case Study Method

Case study: An intensive description and analysis
of a single individual.
Data: clinical observations, self-report, archival data
(e.g., medical records)
 Case studies typically report the results of a
treatment.
 Major problem: Lack scientific control
 simultaneous treatments, extraneous variables

Case Study Method (continued)

Advantages of the Case Study Method:
rich source of ideas for developing hypotheses,
 opportunity for clinical innovation,
 method for studying rare events,
 possible challenge to theoretical assumptions,
 tentative support for a psychological theory, and
 complement to the nomothetic study of behavior

Case Study Method (continued)

Disadvantages of the Case Study Method:
difficulty drawing cause-and-effect conclusions
(limited internal validity),
 possible biases when interpreting outcomes due to
observer bias and biases in data collection (e.g., due
to poor memory), and
 problem of generalizing findings from a single
individual (limited external validity)

Case Study Method (continued)




Case studies provide great anecdotal evidence
and “testimonials.”
Case studies that appear in the popular press are
rarely scientific.
People want to believe that the treatment in
these testimonials will work for them, but often
they do not.
It’s better to pay attention to the results of
single-subject experimental designs.
Scientific Case Studies


Single-subject experimental designs have their
roots in B. F. Skinner’s approach called applied
behavioral analysis.
Single-subject designs improve on nonscientific
case studies, because the researcher attempts to
gain more scientific control.
Characteristics of Single-Subject
Experiments

Critical feature of single-subject designs: An
independent variable is examined:
treatment
 no treatment control (baseline stage)


Researchers compare treatment conditions for one
individual whose behavior is continuously
monitored (repeated measures).
Single-Subject Experimental Designs
(continued)
The baseline condition is used to describe behavior before
treatment is provided, and predict what behavior will be
like in the future without treatment.
Single-Subject Experimental Designs
(continued)
Compared to baseline, the
behavior decreases after
treatment is implemented.
Although this pattern of data
suggests the treatment
was effective, some other
factor that occurred at the
same time as the
treatment could have
caused the frequency of
behavior to decrease.
The ABAB Design: Baseline and Treatment
conditions are contrasted in the ABAB Design
Illustration of a Treatment
Effect:
The frequency of the
behavior decreases
during treatment (B),
reverses when treatment
is withdrawn (second A),
and reverses again during
treatment (second B).
This design is also called a
reversal design.
ABAB Design (continued)
Illustration of no reversal:
When the frequency of
behavior does not
reverse when treatment
is withdrawn (second
A), it is very difficult to
determine whether the
treatment was effective.
ABAB Design (continued)

Methodological Issues Associated with ABAB
Designs


If behavior does not reverse back to baseline levels after
treatment is withdrawn, researchers cannot conclude that
treatment caused the initial behavior change.
A variable other than treatment may have caused the
behavior to change.
ABAB Design (continued)

Methodological Issues Associated with ABAB
Designs


Treatment may have promoted change, and then other
variables (e.g., positive attention) may persist to maintain
behavior change.
Some behaviors may not be logically expected to change
once improved (e.g., when new skills are learned).
ABAB Design (continued)

Ethical considerations
Is it ethical to remove a treatment that appears to be
beneficial (i.e., implement the second “A” baseline
stage)?
 Dilemma between goal of understanding and goal of
creating change.

Problems with All Single-Subject Designs

Baseline Records

If baselines demonstrate unstable, increasing, or
decreasing trends in behavior, the effects of
treatment are hard to interpret.
Problems with All Single-Subject Designs

Baseline Records
When baseline behavior shows extreme variability,
it’s difficult to detect a clear discontinuity in
behavior when treatment is implemented.
 Solutions: Look for factors that may contribute to
variability, wait for baseline behavior to stabilize,
average baseline data points across observations.

Problems with Single-Subject Designs
(continued)

Baseline Records, continued
 Whether increasing or decreasing baseline trends
are a problem depends on the desired direction of
behavior change
Problems with Single-Subject Designs
(continued)

Baseline Records, continued
 Suppose the goal is to increase the frequency of a
behavior.
If the baseline shows an increasing frequency of
behavior, determining whether behavior increases
following treatment will be difficult.
 However, if the baseline shows a decreasing trend and
treatment reverses this trend, we can be confident about
the effect of the treatment.

Problems with Single-Subject Designs
(continued)

External Validity
Single-subject designs are frequently criticized
for their limited external validity.
 Will treatment effects observed for one
individual generalize to other individuals?

Problems with Single-Subject Designs
(continued)

External Validity

Reasons why external validity may not be
limited:
 Treatments are usually powerful.
 Multiple-baselines designs can be used to
demonstrate generality of effects.
 Group treatment can be used to demonstrate
effectiveness of treatment.
Download