Personalized Digital Therapeutics for Adaptive SUD Cognitive Training
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Solution Overview
Problem
Current treatments for substance use disorders (SUDs) are ineffective in mitigating relapses due to a lack of personalized interventions that address both cognitive impairment and psychological components, failing to target the underlying neural mechanisms contributing to addictive behaviors and do not translate well to real-world scenarios.
Innovation Solution
A digital therapeutic application that combines multi-component neuromodulatory interventions, including inhibitory control and working memory training, with goal-related context, to enhance plasticity and improve executive control systems, providing personalized interventions tailored to individual needs through adaptive difficulty adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional SUD treatments are provided, then accessibility is improved, but effectiveness in mitigating relapses deteriorates due to lack of personalization and failure to address cognitive impairment
Solution Approach 1:
The treatment system dynamically adapts to individual users by adjusting intervention parameters based on real-time performance data and cognitive assessment results, transforming static conventional treatments into dynamic personalized programs that maintain effectiveness while remaining accessible
Solution Approach 2:
The system targets specific cognitive domains affected by SUD (e.g., inhibitory control, working memory, decision-making) with specialized training modules, providing localized cognitive rehabilitation rather than generic treatments, thereby improving effectiveness without compromising accessibility
2Adaptability or versatility
If in-person behavioral therapies and treatment programs are used, then psychological support is provided, but adherence and motivation deteriorate due to lack of engagement and failure to address cognitive deficits
Solution Approach 1:
The digital therapeutic platform enables users to independently engage with personalized cognitive training modules at their own pace, with the system automatically adjusting difficulty and content based on performance, eliminating the need for constant professional supervision while maintaining psychological support effectiveness
Solution Approach 2:
The system implements real-time feedback mechanisms that track user progress, provide immediate performance information, and adjust treatment parameters dynamically, enhancing user engagement and adherence through visible progress and adaptive challenge levels
3Quantity of substance
If traditional SUD treatments are implemented, then broad coverage is achieved, but translation to real-world scenarios deteriorates due to lack of ecological validity and failure to target neural mechanisms
Solution Approach 1:
The system replaces traditional talk-based psychological interventions with computerized cognitive training protocols that directly target and modify neural circuitry underlying addictive behaviors, substituting indirect psychological support with direct neural mechanism targeting to improve real-world translation
Data Source
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.