Personalized Digital Therapeutics with Adaptive Cognitive Training
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing treatments for substance use disorders (SUDs) are ineffective due to a lack of integration of cognitive and psychological components, failure to address underlying cognitive impairment, and difficulty in transferring training effects to real-world conditions, leading to high relapse rates.
Innovation Solution
A digital therapeutic application that combines three training activities - inhibitory control, working memory, and goal-related context - to target overlapping neural network substrates, enhancing plasticity and improving executive control systems, with adaptive difficulty adjustments based on user performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional in-person behavioral therapies and treatment programs are used, then treatment coverage is provided, but treatment effectiveness is low due to failure to address cognitive impairment and lack of personalization
Solution Approach 1:
The digital therapeutic application dynamically adapts treatment content and difficulty based on real-time user performance data. The system adjusts training parameters, selects appropriate activities, and modifies intervention strategies according to individual user responses, transforming static treatment protocols into dynamic, personalized therapy sessions that evolve with user progress
Solution Approach 2:
The system continuously collects user performance data during training activities and provides real-time feedback to adjust treatment delivery. Performance metrics inform adaptive algorithms that modify subsequent training content, creating a closed-loop system where user responses directly shape treatment effectiveness and personalization
2Reliability
If cognitive training activities are implemented, then executive control functions are targeted, but transfer to real-world conditions is difficult
Solution Approach 1:
The system prepares users for real-world application by pre-training executive control functions in controlled digital environments before expecting transfer to uncontrolled real-world situations. Training activities are designed to progressively build cognitive skills that can then be applied to substance use challenges in daily life
Solution Approach 2:
Training activities are specifically designed to target local cognitive functions directly relevant to substance use disorders, such as inhibitory control for impulse management and working memory for decision-making. This focused approach enhances transferability by training specific neural circuits involved in substance use behavior rather than general cognitive skills
3Stability of the object's composition
If treatment programs are standardized, then delivery consistency is maintained, but individual cognitive impairments are not addressed
Solution Approach 1:
The system maintains standardized treatment protocols as a foundation while incorporating dynamic adaptation layers that adjust to individual user needs. Core treatment structure remains consistent for reliability, while adaptive algorithms modify content delivery, difficulty levels, and activity selection based on real-time assessment of user cognitive functioning
Data Source
Figure 1
Figure 2A
Figure 2B
AI summary
Provided herein are systems and methods for presenting interventions to address substance use disorders (SUDs) in users. One or more processors may identify for a user with a substance use disorder, a profile including a plurality of substance use words, memory words, and neutral words. The one or more processors may provide a repeated cycle of selection activities and visualization activities. The one or more processors may update the profile of the user using the performance of the user in the activity. The systems and methods provided herein can enhance the efficacy of the medication that the user is taking in concurrence with addressing the SUD.