PTP 560 Research Methods Week 4 Thomas Ruediger, PT.
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PTP 560
• Research Methods
• Week 4
Thomas Ruediger, PT
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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
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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
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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
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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
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Single Subject Structure
• How many baseline measure are needed?– AT LEAST 3
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Single Subject Designs
Baseline Characteristics• Stable or variable?– Consistency of the
response
– Left are stable, right are unstable
• Trend– Rate of change or slope
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Single Subject StructureTarget behavior
• Quantifying the measure?
– Frequency• % correct• In an interval
– Duration
– Quantitative Score (Magnitude)
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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
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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
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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
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Week 1 Week 2 Week 3 Week 4
Baseline Intervention
Function
A Baseline
B Intervention
A Baseline
ABA Design
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Week 1 Week 2 Week 3 Week 4
Baseline Intervention
Function
A Baseline
B Intervention
A Baseline
B Intervention
ABAB Design
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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
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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
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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
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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
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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)
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• Autocorrelation: if data are correlated
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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
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Celeration Line
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Celeration Line
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Celeration Line
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Single Subject Designs
Non-ParametricCeleration LineBinomial 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
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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.
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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
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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
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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