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A Modeling and Simulation Method for Preliminary Design of an Electro-Variable Displacement Pump

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Published on: June 1, 2022

Human-centered design methods to achieve preparation phase goals in the multiphase optimization strategy framework.

Karey L O'Hara¹, Lindsey M Knowles^2,3, Kate Guastaferro⁴

¹Arizona State University, Tempe, AZ, USA.

Implementation Research and Practice

|April 24, 2023

Summary

Maximizing public health impact of interventions requires effective development. This study proposes the Discover, Design, Build, and Test (DDBT) framework to enhance the Preparation phase of the Multiphase Optimization Strategy (MOST) for intervention development.

Keywords:

intervention design < intervention interventions < community based mental health intervention multiphase optimization strategy substance abuse prevention

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Area of Science:

Behavioral and biobehavioral intervention science
Public health research
Implementation science

Background:

Effective behavioral interventions for mental health and substance use are crucial for public health.
Optimizing interventions requires balancing effectiveness, affordability, scalability, and efficiency.
Current intervention development methods, particularly in the Preparation phase of MOST, need further refinement.

Purpose of the Study:

To propose the Discover, Design, Build, and Test (DDBT) framework as a structured approach for the Preparation phase of the Multiphase Optimization Strategy (MOST).
To integrate human-centered design and implementation science principles into intervention development.
To provide a roadmap for rigorous and efficient intervention development research.

Main Methods:

The study proposes the DDBT framework, integrating strategies from human-centered design and implementation science.
DDBT provides a theory-driven roadmap for MOST's Preparation phase.
This approach guides specifying conceptual models, identifying/testing intervention components, and defining optimization objectives.

Main Results:

The DDBT framework offers a structured and methods-rich approach to the Preparation phase of MOST.
DDBT capitalizes on human-centered design and implementation science for data collection.
The proposed DDBT/MOST approach integrates DDBT into MOST's Preparation phase for efficient intervention development.

Conclusions:

The synthesized DDBT/MOST approach provides a robust framework for intervention development research.
This integrated model enhances the rigor and efficiency of the Preparation phase of MOST.
The approach aims to improve the public health impact of mental health and substance use interventions through optimized development.