Cognify: A Modular Privacy-Conscious AI-Driven Mobile App for Mental Health Based on Cognitive Distortion Detection

Mariam Dawoud, Mohamad Rasmy, Alia El Bolock

2025

Abstract

Cognitive distortions—irrational thought patterns contributing to emotional distress—are central to cognitive behavioral therapy (CBT), but early detection often depends on clinical assessments, limiting opportunities for timely self-reflection. Cognify is a cross-platform mobile application designed to help users detect and understand these distortions by analyzing daily journal entries using a fine-tuned NLP model that classifies entries into 14 cognitive distortion types. The app offers real-time feedback, weekly summaries highlighting recurring patterns, and an intuitive interface that promotes ongoing engagement. This paper presents Cognify’s system architecture, AI model integration, and results from a pilot study, which demonstrated improved user awareness of cognitive patterns, high user satisfaction, and increased journaling consistency over time. The app’s modular design also allows for optional integration of privacy-preserving features, ensuring flexibility to address evolving user needs. By combining AI-driven distortion detection with an adaptable journaling experience, Cognify offers a practical and engaging tool for enhancing cognitive awareness and supporting personal growth.

Paper Citation

in Harvard Style

Dawoud M., Rasmy M. and El Bolock A. (2025). Cognify: A Modular Privacy-Conscious AI-Driven Mobile App for Mental Health Based on Cognitive Distortion Detection. In Proceedings of the 20th International Conference on Software Technologies - Volume 1: ICSOFT; ISBN 978-989-758-757-3, SciTePress, pages 361-368. DOI: 10.5220/0013571400003964

in Bibtex Style

@conference{icsoft25,
author={Mariam Dawoud and Mohamad Rasmy and Alia El Bolock},
title={Cognify: A Modular Privacy-Conscious AI-Driven Mobile App for Mental Health Based on Cognitive Distortion Detection},
booktitle={Proceedings of the 20th International Conference on Software Technologies - Volume 1: ICSOFT},
year={2025},
pages={361-368},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013571400003964},
isbn={978-989-758-757-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 20th International Conference on Software Technologies - Volume 1: ICSOFT
TI - Cognify: A Modular Privacy-Conscious AI-Driven Mobile App for Mental Health Based on Cognitive Distortion Detection
SN - 978-989-758-757-3
AU - Dawoud M.
AU - Rasmy M.
AU - El Bolock A.
PY - 2025
SP - 361
EP - 368
DO - 10.5220/0013571400003964
PB - SciTePress