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A multiple-baseline design across participants involves establishing a baseline for several different individuals and then introducing the treatment to each person at a different, staggered time. Because each participant essentially undergoes an AB design, the staggered introduction is crucial for establishing internal validity. If the dependent variable changes for each individual specifically after the intervention is applied to them, it is highly unlikely to be a result of coincidence or a shared external event, demonstrating that the treatment is the cause.

Multiple-Baseline Design Across Participants

In 2009, Scott Ross and Robert Horner conducted a study illustrating the multiple-baseline design across participants by evaluating a school-wide bullying prevention program. They observed the aggressive behaviors of specific problem students across three different schools to establish a baseline. They then implemented the prevention program at the first school, waited two weeks to implement it at the second school, and waited another two weeks for the third school. Because the aggressive behaviors of the students dropped shortly after the program was implemented at their respective schools, the staggered introduction made it highly unlikely that the changes were due to external coincidences, demonstrating the internal validity of the design.

Ross and Horner Bullying Prevention Study

A study by Ross and Horner (2009) illustrates the multiple-baseline design across participants. They evaluated a bullying prevention program across three different schools. Baselines of aggressive behavior were established at all three schools. The program (treatment) was then introduced at each school at staggered intervals (separated by 2 weeks). Aggressive behavior dropped at each school only after the program was implemented there, demonstrating the program's effect while ruling out coincidental factors.

Multiple-Baseline Design Across Participants Example

In a multiple-baseline design across participants, what is the crucial procedural feature that helps establish internal validity?

A researcher wants to evaluate a new note-taking intervention using three participants. She records each participant's exam scores during a baseline phase and then begins the intervention with all three participants during the same week. Because she measured baselines for multiple individuals, this design effectively rules out the possibility that an outside event—rather than the intervention—caused any observed improvement in exam scores.

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