JMIR Publications

ABSTRACT

Background:

Smartphones and wearable devices are highly accessible technologies that hold promise for tracking treatable psychological symptoms such as depression and anxiety. However, most studies of these devices focus on young and middle-aged adults. The global proportion of older adults aged sixty and above is growing rapidly and will reach more than 20% of the population by 2050, but older adults are significantly underrepresented in studies of passive digital sensing technologies. As mobile application therapies may increasingly use passive sensing to help guide therapeutic approaches, this research gap threatens equitable access to care.

Objective:

In this scoping review, we summarize the state of the evidence for using smartphone and wearable sensors to identify mental states in the older adult population. In particular, we aim to identify approaches for monitoring, sensing and predicting depressive and anxious symptoms in older adults using smartphone or wearable data, and to outline opportunities and challenges in this area of research.

Methods:

Comprehensive searches for studies that associated passive sensor data from smartphones and wearables with depressive or anxiety symptoms in older adults were conducted in Web of Science, PubMed, and Embase database(s) from 2015, until August 2023. Articles were screened at the title and abstract level and at full text review by two reviewers. Studies that did not utilize passive sensing data, did not study older adult populations, or lacked quantitative measurement of depressive or anxiety symptoms, were excluded from the review. Both reviewers extracted data and conducted a descriptive analysis to map the available evidence. Any disagreements were resolved by consensus.

Results:

1245 articles were screened at the title and abstract level, of which 133 were also assessed at full text for eligibility. Out of the 133 articles filtered for full-text review, 41 studies were selected for inclusion in the final analysis. Among these, 36 studies used wearables sensors and only 4 studies employed smartphones for passive sensing. A substantial number of articles indicated an association between sedentary behavior, sleep duration and physical activity level, all measured from smartphone sensors or wearable devices, with severity of depressive or anxious symptoms.

Conclusions:

The present review provides an overview of the literature on the use of wearables and smartphones for studying depressive and anxiety symptoms in older adults and discusses the potential for new technologies to aid in the process. Limitations of the extant data include small sample sizes and under-representation of ethnic and racial minoritized groups. Further research on the role of passive sensor data for identifying and tracking depressive and anxious symptoms in older adults with larger samples is needed.