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A multiple-baseline design across behaviors involves establishing multiple baselines for a single participant across different dependent variables (behaviors), and then introducing the intervention for each behavior at staggered times. By showing that an individual's behavior changes only when the treatment is applied to that specific behavior, researchers can establish causality. For example, if an intervention designed to improve productivity is introduced for an office worker's sales calls first, and later for their report writing, an increase in productivity for each task corresponding only to the staggered introduction time provides clear evidence that the treatment caused the improvement.

Multiple-Baseline Design Across Behaviors

An example of a multiple-baseline design across behaviors involves measuring an office worker's productivity on two different tasks: making sales calls and writing reports. After establishing baselines for both tasks, a goal-setting treatment is introduced for one task first, and later for the second task. If productivity increases on each task only after the treatment is applied to it, the researcher can confidently conclude that the treatment caused the increase.

Multiple-Baseline Design Across Behaviors Example

What is the defining feature of a multiple-baseline design across behaviors?

A clinical psychologist wants to determine whether a reinforcement-based intervention improves a client's self-care habits. She tracks two behaviors — frequency of teeth-brushing and frequency of bed-making — during an initial observation period. She then introduces the reinforcement intervention for both behaviors at the same time and observes that both behaviors increase simultaneously. This procedure allows her to rule out the possibility that an outside event, rather than the intervention, caused the improvements.

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