Transcript Application Techniques - University of Michigan–Flint

PTP 560
• Research Methods
• Week 4
Thomas Ruediger, PT
Single Subject Design
• Similar (not identical) to clinical practice
• Independent variable is the intervention
• Dependent variable is the response (outcome)
• Requires strict attention and control
• Allows for flexibility to observe change
– In clinical (real world) setting
Single Subject Designs
• Sample
– Single individual or small group: Assume 1 person for this class
– A community, department or institution
• Advantage
– Small sample: saves time/money; clinically useful
– Appreciates/differentiates unique characteristics
• Methods
– Clinically viable, controlled experimental approach
– Flexible to observe change in ongoing treatments
Single Subject Structure
• Repeated Measures to start - Baseline
– This is where it differs from clinical practice (“the single feature”
– P & W)
– Attempt to reflect ongoing background effects
– How is this different than clinical practice?
• In the clinic we start right away, not wait for a baseline.
• While for SSS we will wait for 3 treatments to begin specific
intervention to test
• Also subjects needs to sign consent form.
• Two caveats on these baseline measures
– Not unethical to withhold treatment when outcome is not
known
– Not all treatment is withheld, just the one of interest
Single Subject Structure
• Baseline Measures (AT LEAST THREE!)
– Stable baseline is most desirable
• Indicates that the behavior is stable
• Increases confidence that changes after the intervention
begins are due to that intervention
– Variable baseline is problematic
• Usually requires continued baseline collection
• Investigate possible causes (Cyclical, time of day/week etc)
• If cannot resolve, at risk for obscuring intervention effect
– Trend or slope of baseline
• Accelerating or decelerating
• May be stable or unstable
Single Subject Structure
• How many baseline measure are needed?
– AT LEAST 3
Single Subject Designs
Baseline Characteristics
• Stable or variable?
– Consistency of the
response
– Left are stable, right
are unstable
• Trend
– Rate of change or slope
Single Subject Structure
Target behavior
• Quantifying the measure?
– Frequency
• % correct
• In an interval
– Duration
– Quantitative Score (Magnitude)
Single Subject Structure
• Intervention Phase
– At least 3 data points
– The minimum number of data points needed in an
A-B study is 6 (3 for phase A and 3 for phase B)
• Reliability usually assessed=assuming no change the measurement is the
same.
– Concurrently with data collection
– Instead of in pilot study
– Inter-rater by percentage agreement
• A(baseline)-B(intervention or independent variable) is the simplest form of
Single Subject Design
– Major limitation is ability to control
– This limitation is a threat to internal validity
Single Subject Designs
Design Phases
• Baseline Phase (Left)
– Information during “no
treatment”
– Serves as a control condition
• Intervention Phase (Right)
– Measures during treatment
– Serves as comparison
Single Subject Structure
• A-B-A design useful to help internal validity
– The Causal Nature, However, behavior must be reversible
• Reversibility just needs to be sig. different, but not back to baseline.
• A-B-A-B
– Strengthens design
– Again behavior must be reversible
• Consider Multiple Baselines (Fig 12.7)
– To avoid being unethical, if withdrawal is unethical
– If behavior is:
• Nonreversible
• Prone to carryover
ABA Design
A
B
A
Baseline
Intervention
Baseline
Function
Week 1
Week 2
Baseline
Intervention
Week 3
Week 4
ABAB Design
A
B
A
B
Baseline
Intervention
Baseline
Intervention
Function
Week 1
Week 2
Baseline
Intervention
Week 3
Week 4
Single Subject Structure
• Multiple Baselines
– Across behaviors
• One subject
• Multiple behaviors (outcomes)
– Across subjects
• Multiple individual subjects
• One target behavior
– Across conditions
• One subject
• One behavior
• Two or more conditions/situations/environments
Single Subject Structure
• Non-concurrent Multiple Baselines (Fig 12.8)
– Multiple individual subjects
– One target behavior
– Intervention begun at randomly assigned intervals
• Alternate Treatments (Fig 12.9)
– Appropriate when response is immediate
– Session by session
– Day by Day
• Multiple Treatment A-B-C-A (Fig 12.10)
– Across conditions
• One subject
• One behavior
• Two or more conditions/situations/environments
Single Subject Structure
• Data analysis
– Comparisons ONLY across adjacent phases
• Only compare letters that are next to each other, so can’t
compare A to C.
– Are the data level?
– Visual
– Mean
– Is there a trend?
– Direction within a phase
– Accelerating/decelerating/constant
– What is the slope?
– Rate of change
Single Subject Structure
• When making comparisons in these scenarios,
what can you compare?
A-B-A
A-B-C-A
A-B-C-D-E-F-G-A
Single Subject Structure
• Data analysis
– The split middle
• Apply the binomial test (Table A.9)
– Two standard deviation method
– Serial dependency
– C statistic
– Statistical Process Control
• Upper and Lower Control Limits
– Based on 3 standard deviations
– Then apply the three rules (p 266)
• Autocorrelation: if data are correlated
Single Subject Designs
• Celeration Line (Split Middle Line)
– Measure of central tendency
– Represents the median point of the data
– Counts data points above or below in a given phase.
– Adjust line up or down to a point where data is equally
divided
– Extend into intervention phase
Celeration Line
Celeration Line
Celeration Line
Single Subject Designs
Non-Parametric
Celeration Line
Binomial Test
1. Extend split middle line of
baseline phase into
intervention phase
2. Count Total points
•
•
Count points above
Count points below
3. Consult Table A.9
This Figure is 12.13 in Ed 3
Single Subject Design
• Generalization is a challenge

Strengthened by:
– Direct replication
– Systematic Replication: with purposeful change in some
parameter
– Clinical Replication: taking it out of realm of research, take
it out to a clinic
– Social Validation: is it okay to use this intervention.
Single Subject Designs
Social Validation
• Importance within specific social context
– Setting Treatment Goals
• Appropriate to functional needs of patient; social importance
– Procedures
• Acceptable treatments/interventions; patient preference, comfort
and safety
– Effects
• Appropriate Magnitude of treatment & treatment effects
Exploratory Research
•
•
•
•
•
•
Prospective: randomized-control study
Retrospective: chart review study
Exploratory: generating questions
Descriptive
For relationship investigation: SSS
For correlation (how much does X vary with Y)
and regression analysis (predicted ability)
• The Case of the “Haves” and the “Have Nots”
Fig 13.2, Fig 13.3 : with an ACL without an ACL have this
risk
Exploratory Research
• Causality can be argued for better with
– 1. Established time sequence
– 2. Strong association
– 3. Biologic credibility
– 4. Consistency with other studies
– 5. Dose-response relationship