Reduction of severe behavior problems in the community using a multicomponent treatment approach

Area of Science:

• Applied Behavior Analysis
• Developmental Disabilities
• Community Psychology

Background:

• Problem behaviors impede community integration for individuals with developmental disabilities.
• Effective interventions are needed to support community participation.
• Hypothesis-driven approaches can guide treatment selection.

Purpose of the Study:

• To evaluate a multicomponent intervention for problem behavior in public community settings.
• To utilize a hypothesis-driven model for selecting treatments.
• To assess intervention effectiveness using novel measurement techniques.

Main Methods:

• A multicomponent intervention including choice-making, functional communication training, and reinforcement delay tolerance.
• Treatments were selected based on functional behavior hypotheses.
• Progress was measured by latency and task completion, not frequency or time sampling.

Main Results:

• Substantial increases in task completion were observed.
• Individuals spent longer durations in community settings without problem behavior.
• Intervention outcomes were socially validated by staff and community members.

Conclusions:

• A hypothesis-driven, multicomponent intervention can effectively remediate problem behavior in community settings.
• Alternative measurement strategies (latency, task completion) are effective for monitoring progress.
• This approach offers solutions for assessing and treating problem behavior in community contexts.