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PTP 560

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

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PTP 560

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  1. PTP 560 • Research Methods • Week 4 Thomas Ruediger, PT

  2. 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

  3. 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

  4. 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

  5. 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

  6. Single Subject Structure • How many baseline measure are needed? • AT LEAST 3

  7. Single Subject Designs Baseline Characteristics • Stable or variable? • Consistency of the response • Left are stable, right are unstable • Trend • Rate of change or slope

  8. Single Subject StructureTarget behavior • Quantifying the measure? • Frequency • % correct • In an interval • Duration • Quantitative Score (Magnitude)

  9. 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

  10. 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

  11. 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

  12. ABA Design B Intervention A Baseline A Baseline Function Week 1 Week 2 Week 3 Week 4 Baseline Intervention

  13. ABAB Design B Intervention A Baseline B Intervention A Baseline Function Week 1 Week 2 Week 3 Week 4 Baseline Intervention

  14. 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

  15. 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

  16. 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

  17. 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

  18. 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)

  19. Autocorrelation: if data are correlated

  20. 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

  21. Celeration Line

  22. Celeration Line

  23. Celeration Line

  24. 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

  25. 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.

  26. 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

  27. 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

  28. 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

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