Multiple Baseline Designs Chapter 7 Single Subject Research

Multiple Baseline Designs Chapter 7 Single Subject Research and Design

Multiple Baseline • Description – Multiple measures are used to obtain data over two or more baselines – The end result appears visually as a series of A-B designs on top of one another – The DV may consist of 2 or more different behaviors – Versatile and relatively easy to understand – Perhaps the most common design in use today

Multiple Baseline Design • If 3 dependent variables have been chosen, baseline data is obtained for all three dependent variables • The researcher implements the intervention for the first DV while maintaining baseline conditions for the other two • When the criterion is obtained on the first behavior, the intervention may be implemented analyzed as to its effect on the second DV • A follow-up stage is included to ensure that the effects of the IV are maintained

Multiple Baseline Design • MBD are used: – When withdrawal or reversal designs may not be feasible due to ethical concerns of withdrawing treatment – When practical considerations are necessary, such as more than one person needing interventions – In cases where the IV should not be withdrawn or the achieved target behavior cannot be reversed

Prediction Verification and Replication • Verification is evident if the data path changes in a predictable manner through a phase change, as from baseline to intervention • Inferences can be made concerning the complimentary roles of prediction and verification – 1. If potential confounding variables are held constant across all variables and the target behavior remains unchanged from DV 1 to variables 2 and 3, then the prediction is valid – 2. if changes in the IV occur with DV 1, the observed changes in the target behavior are brought about by the IV because only that DV was exposed to the IV

Replication • Replication is achieved when similar results are obtained with each DV following the introduction of the same IV • Replication can provide evidence of a functional relationship between the dependent and independent variables

Covariance Among Dependent Variables • The variables in the treatment may covary, so it is important to select dependent variables that exhibit some degree of independence • Each dependent variable must be measured using the same method of recording behavior

Advantages of Multiple Baseline Designs • The withdrawal of an effective treatment is not required to demonstrate the functional relationship between the IV and DV • The sequential implementation of the IV parallels the practice of teachers • Generalization of behavior change is monitored through the design • The design is easily used and conceptualized

Disadvantages of Multiple Baseline Design • Possibility of covariance • Functional relationships may not be clearly demonstrated • Verification relies on the dependent variable levels not changing until the independent variable is introduced and then changing in a similar manner to any previously treated behaviors • Implementation can be time consuming and may require substantial resources

Multiple Baseline design should not be used: • When selected target behaviors are not functionally similar nor independent of one another • If there is only one subject in one setting and one target behavior • When more than one intervention phase is desirable to demonstrate the functional relationship • When constraints on resources make implementation impossible

Multiple Baseline Across Behavior • Three or more behaviors are identified that are exhibited by the same subject in the same setting and then systematically subjected to the same intervention or independent variable

Critical Issues in Implementing a MB Across Behaviors Design • 1. selection of an individual participant who displays multiple behaviors in a single setting that require intervention • 2. functional similarity and independence of those behaviors as one might be able to determine priority • 3. a reasonable expectation that the same variables will exert equal influence on each of the dependent variables

Critical Issues (continued) • 4. selection of a treatment that can be expected to produce a similar and independent effect on each of the dependent variables • 5. a consistent recording procedure for each of the target behaviors and a criterion level for decision making • 6. confidence that the resources and time needed to record multiple baselines and subsequent intervention will be maintained throughout the study

Multiple Baseline Across Settings • Only one subject is identified but the researcher identifies two or more settings in which the individual emits the same behavior • The same subject is treated for the same behavior in different settings

Issues in the Implementation of the MB Across Settings design • 1. Selection of an individual subject who displays the same target behavior in multiple settings • 2. selection of settings that are functionally similar but also independent of one another as one may best determine priority • 3. a reasonable expectation that the same variables will be exerting the same influence in each of the settings

Issues continued • 4. selection of a treatment that can be expected to produce similar effects in each setting • 5. a consistent recording procedure for each setting and a criterion level for decision making • 6. confidence that resources will be maintained throughout the length of the study

• It is important to note that a major disadvantage of MB across settings design is that extraneous variables that may influence responding in different settings can be difficult to control or predict.

Multiple Baseline Across Subjects • In this design more than one subject participates. • Two or more individuals are identified that emit the same target behavior in the same setting • The subjects should be enough alike that one can expect each subject to respond similarly to the same intervention yet independent enough of one another to avoid covariance

Issues in Implementing a MB across Subjects Design • 1. selection of individual participants who display the same target behavior in the same setting • 2. The subjects should be enough alike that one can expect each subject to respond similarly to the same intervention yet independent enough of one another to avoid covariance • 3. a reasonable expectation that the same variables will exert the same influence on each of the subjects

Issues in Implementing a MB across Subjects Design • 4. selection of an independent variable that is likely to have a similar effect on each subject • 5. a consistent recording procedure for each of the target behaviors and a criterion level for decision making • 6. confidence that the resources and time needed to record multiple baselines and subsequent intervention will be maintained throughout the study

Adaptations of the Multiple Baseline Design • Multiple Probe Design – Data probes are taken during baselines rather than continuous measurement – Used to decrease the collection of data – Researcher makes periodic recordings (probes) of baseline levels to ensure that no significant changes have occurred before the introduction of the intervention – The use of probes reduce the need for resources that may be unavailable to maintain the continuous recording of behavior during baseline phases

• Delayed Multiple Baseline Design – May be employed when a withdrawal design no longer is possible or when other behaviors, settings, or individuals emerge that are in need of intervention – Baselines are not measured at the same time – It allows the use of fewer resources and the researcher may extend the study to new behaviors, settings, and individuals that had not been targeted a priori