The multiphase optimization strategy (MOST) in child maltreatment prevention research

Area of Science:

• Behavioral science
• Intervention science
• Public health

Background:

• Child maltreatment remains a significant public health issue, with rates undiminished despite widespread behavioral interventions.
• Existing interventions often lack the affordability, scalability, and efficiency required to meet demand and reduce prevalence.

Purpose of the Study:

• Introduce the multiphase optimization strategy (MOST) as an innovative framework for child maltreatment prevention.
• Demonstrate MOST's utility in optimizing multicomponent behavioral interventions for effectiveness and efficiency.

Main Methods:

• MOST is an engineering-inspired framework for empirical examination of intervention components.
• Utilized a hypothetical home visiting intervention with artificial data to illustrate optimization of content and engagement strategies.
• Focused on identifying interventions that are effective, efficient, economical, and scalable.

Main Results:

• MOST allows for the systematic evaluation of individual and combined intervention components.
• Optimization through MOST can lead to improved intervention content and engagement strategies.
• Identified potential for optimizing interventions to enhance completion rates and overall impact.

Conclusions:

• MOST provides a robust approach to developing and optimizing behavioral interventions for child maltreatment prevention.
• This strategy can accelerate progress in translational science, leading to more effective and scalable prevention programs.
• Adoption of MOST is recommended to improve the efficiency and impact of interventions aimed at preventing child maltreatment.