Tracking Health-Related Quality of Life Dynamics: Advances in Ambulatory Assessment Methods

Abstract

Assessing quality of life in clinical practice and research via patient-reported outcomes is an emerging practice enabling the assessment of individual well-being across different populations and conditions, such as immune-mediated and inflammatory disorders. Standardized questionnaires have traditionally been used for this purpose, but they have several limitations inherent to one-time snapshots from recall-based self-reports. Ambulatory measures may provide an alternative approach to assessing quality of life that allows capturing an individual’s states and behaviours in the context of daily life. In this overview article, we define ambulatory measures, including ecological momentary self-reports, wearable sensors, biochemical sampling, and smartphone sensing, that may be used to estimate quality of life, and present examples of studies that have used these measures. Additionally, we highlight the benefits of integrating multi-method ambulatory measures and overview methods for combining and analyzing them, including data fusion techniques and machine learning. While there are still challenges and limitations to overcome, the integration and application of ambulatory measures in medical research and clinical practice have the potential to provide a more comprehensive and accurate assessment of the quality of (everyday) life.