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Behavior Change Study Design: Single-Subject Jesus Valdez

Study changes in behavior after treatment; line graphs with x/y-axis; detailed data collection; applied in complex group settings; various designs like A-B, Multiple-Baseline. Understand threats and ways to control validity. Importance of replication for external validity demonstrated online.

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Behavior Change Study Design: Single-Subject Jesus Valdez

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  1. Single Subject Jesus Valdez

  2. Purpose To study the changes in behavior of an individual exhibits after exposure to an intervention or treatment of some sort.

  3. Essential characteristics • Line graphs • Dependent outcome is expressed on y-axis • Sequence of time is expressed on x- axis • Involves extensive collection on subject • Can be applied where group designs are difficult

  4. 2 ways it differs from other forms of research • Baseline is followed by the independent variable • Figure caption near the bottom of the graph

  5. What is and why baseline What? Graphic record of measurements taken prior to introducing an intervention in a time-series design Why? It’s the control before the treatment

  6. The 6 Designs • A-B • Reversal (A-B-A) • A-B-A-B • B-A-B • A-B-C-B • Multiple-baseline

  7. A-B Design Design in which measurements are repeatedly made until stability is presumably established (baseline), after which treatment is introduced and an appropriate number or measurements are made

  8. A-B-A Design Same as A-B design, except a second baseline is added

  9. A-B-A-B Design Same as A-B-A design, except a second treatment is added

  10. B-A-B Design Same as A-B-A-B design, except the initial baseline phase is omitted

  11. A-B-C-A Design Same as A-B-A design, except a second baseline phase is replaced by a modified treatment phase

  12. Multiple-Baseline Design Experimental design in which baseline data are collected on several behaviors for on subject, after which the treatment is applied sequentially over a period of time to each behavior

  13. Threats to internal validity • Length of the baseline and conditions • Number of variables changed form condition to condition • Degree and speed of change • Return or not of baseline levels • Number of baselines

  14. Ways to control threat • Subject characteristics, mortality, testing, and history • Less effective with location, date collector characteristics • Weak in instrument decay, data collector bias, attitude

  15. External validity • Are weak when it comes to generalizability • Important to replicate to test generalization

  16. Example of Single Subject Onto the Internet

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