Integration of Health Questionnaires and Wearable Device Data into Machine Learning Models: A Rapid Literature Review

• Nadiana K. N. Mendes UFC
• Rossana M. C. Andrade UFC
• Pedro A. M. Oliveira IFMA

DOI: https://doi.org/10.5753/sbcas.2026.20388

Abstract

The advancement of wearable devices and machine learning has expanded the integration of passive physiological data and health questionnaires. This rapid review analyzed 13 studies published between 2020 and 2025 on the combined use of these approaches in digital health applications. The findings identified three main strategies: the use of questionnaires as target variables, multimodal integration of self-reports and physiological data, and continuous prediction of clinical scores. Promising potential was observed, particularly in multimodal and temporal models. However, challenges remain, including methodological heterogeneity, small sample sizes, and limited external validation. It is concluded that this convergence represents a consistent trend, but still requires greater standardization and validation for large-scale adoption.

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