Using smartphones to optimise and scale-up the assessment of model-based planning

Area of Science:

• Cognitive Psychology
• Computational Neuroscience
• Behavioral Science

Background:

• Model-based planning is crucial for flexible behavior, contrasting with habitual responses.
• Reduced model-based planning is linked to compulsivity, but previous measures show small effect sizes.
• Task design may influence the reliability and validity of model-based planning assessments.

Purpose of the Study:

• To develop and validate a smartphone-based tool for measuring model-based planning in a home environment.
• To investigate how game structure affects the reliability and validity of model-based planning measures.
• To optimize the assessment for sensitivity to compulsive symptoms.

Main Methods:

• Developed a diamond-shooting smartphone game to quantify model-based planning.
• Manipulated game structure (e.g., number of trials, transition ratios, reward drift) within and across participants.
• Assessed measurement reliability and validity against established correlates of model-based planning, focusing on compulsivity.

Main Results:

• Model-based planning can be reliably measured at home using a smartphone application.
• Estimating model-based planning required fewer trials than anticipated, with early trials containing the most signal.
• Associations between model-based planning and compulsivity were stronger with less deterministic transition ratios and specific reward drift parameters.

Conclusions:

• A novel smartphone game effectively measures model-based planning in a naturalistic setting.
• Optimized game design, particularly early trials and specific ratio/drift parameters, enhances sensitivity to compulsive traits.
• This approach offers a scalable and sensitive method for studying model-based planning and its relation to compulsivity in the general population.