What question did this study set out to answer?

To assess how platform design features correlate with adolescent mental health outcomes using CDC YRBS data from 2011-2023.

April 22, 2026Open Access

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Platform Design Features Predict Adolescent Mental Health Outcomes: A Non-Circular Feature-Based Analysis Using CDC YRBS Data (2011–2023)

Key Points

To assess how platform design features correlate with adolescent mental health outcomes using CDC YRBS data from 2011-2023.
Conducted feature-based scoring using 13 design features.
Analyzed data from the CDC Youth Risk Behavior Survey (YRBS) covering multiple years.
Evaluated the effectiveness of feature exposure versus social media adoption rates.
Feature exposure significantly predicts adolescent mental health outcomes better than raw adoption rates.
Opacity-type features are the most impactful in influencing mental health outcomes.
A comprehensive feature matrix and analysis code are provided for reproducibility.

Abstract

Feature-based platform scoring using 13 binary/ordinal design features replaces the subjective O/R/α rubric, breaking the circularity in the Void Framework's behavioral scoring system. Population-weighted feature exposure outperforms raw social media adoption rates in predicting five CDC YRBS adolescent mental health outcomes (2011-2023). Opacity-type features dominate, confirming the framework's prediction non-circularly. Includes complete feature matrix, analysis code, and litigation-ready methodology.

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Platform Design Features Predict Adolescent Mental Health Outcomes: A Non-Circular Feature-Based Analysis Using CDC YRBS Data (2011–2023)

Key Points

Abstract

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