JMIR Publications

ABSTRACT

Background:

Mental disorders have become a significant cause of disability in developed countries, resulting in substantial economic burdens and straining the public health system. However, self-reported questionnaires used in clinical practice have limitations due to memory bias and subjectivity, leading to potential misdiagnosis and inadequate treatment. To overcome these challenges, incorporating physiological biomarkers using non-invasive sensors can provide a more accurate characterization of the individual’s well-being. Biomarkers such as heart rate variability or those extracted from the electrodermal activity spectral analysis are broadly used to study the stress response and are taken as indices of autonomic nervous system functioning. These biomarkers offer valuable insights, providing objective physiological indicators of stress reactivity and contributing to a better understanding of mental distress and well-being.

Objective:

This study aims to design and validate a remote multiparametric tool, including physiological and cognitive data, to objectively assess mental distress and well-being.

Methods:

This ongoing observational study is aimed to enroll 60 young participants in three groups: (1) high mental well-being; (2) mild to moderate psychological distress; and (3) mental disorder. The assessment will consist of collecting mental health self-reported measures and electrophysiological data during a baseline state, the Stroop test as a stress-inducing stage, and a final recovery period. Several variables related to heart rate variability, pulse arrival time, breathing, electrodermal activity and peripheral temperature will be collected through a medical device and a wearable. A second assessment will be carried out after one month. The assessment tool will be developed using self-reported questionnaires assessing well-being, stress, anxiety and depression as the reference. Principal component analysis and multiple regression models will be performed. Test-retest reliability, known group validity and predictive validity will be assessed.

Results:

Participant recruitment is carried out on a university campus and in mental health services. Different recruitment strategies are implemented: advertising campaigns and invitation letters at the university and recruitment of patients by psychologists. The recruitment period started in October 2022 and is expected to finish by November 2023. As of July 2023, 41 subjects have been recruited. The sample corresponds mainly to the group with mild to moderate psychological distress (N=20), followed by the group with high mental well-being (N=13) and, finally, those diagnosed with an anxiety disorder (N=8).

Conclusions:

This study will establish an initial framework for a comprehensive mental health assessment tool, with the goal of progressing towards a remotely accessible and objectively measured approach that maintains an acceptable level of accuracy in clinical practice and epidemiological studies. Clinical Trial: Registration number (DOI): 10.17605/OSF.IO/N3GCH.