An Application of Time Series Analysis to Single-Case Designs in an Intensive Behavioral Intervention for ADHD

Area of Science:

• Behavioral science
• Clinical psychology
• Child psychology

Background:

• Traditional group-based research methods often fail to capture individual behavioral changes during treatment.
• Single case designs and time series analyses are better suited for examining intra-individual variability over time.

Purpose of the Study:

• To apply time series analysis to behavioral data from youth with attention-deficit/hyperactivity disorder (ADHD).
• To characterize intra-individual behavioral changes over time within a behavioral treatment program.

Main Methods:

• Objective behavioral data (desirable and undesirable behaviors) were collected daily for four youth in an afterschool treatment program.
• Moment-by-moment data were summed daily, and trend analyses were applied.

Main Results:

• Linear trends were observed for most behaviors, but variability impacted optimal characterization.
• Seasonal analysis indicated day-of-the-week differences in treatment response.
• Behavioral decreases were noted near the week's primary reinforcer.

Conclusions:

• This study provides proof-of-concept for using time series analysis with moment-by-moment data in clinical research.
• Time series analysis can offer valuable insights into individual treatment responses for conditions like ADHD.