JMIR Publications

ABSTRACT

Background:

Objective and continuous severity measures of anxiety and depression are highly valuable and would have many applications in psychiatry and psychology. One source of data for objective measures are the sensors on a person’s smartphone, and a particularly rich source is the microphone that could be used to sample the audio environment. This may give broad insight into activity, sleep, and social interaction, which may be associated with quality of life and severity of anxiety and depression.

Objective:

The aim of this study was to determine if passively recorded environmental audio from a subject’s smartphone can be used to find correlates of symptom severity of social anxiety disorder, generalized anxiety disorder, depression, and general impairment.

Methods:

An Android app was designed, together with a centralized server system, to collect periodic measurements of the volume of sounds in the environment and to detect the presence or absence of English-speaking voices. Subjects were recruited into a 2-week observational study where the app was run on their personal smartphone to collect audio data. Subjects also completed self-report severity measures of social anxiety disorder, generalized anxiety disorder, depression, and functional impairment. Participants were 112 Canadian adults from a non-clinical population. High-level features were extracted from environmental audio of 53 participants with sufficient data, and correlations were measured between four audio features and the four self-report measures.

Results:

The regularity in daily patterns of activity and inactivity inferred from environmental audio volume was correlated with severity of depression (r = -0.32, P = .02). A measure of sleep disturbance inferred from environment audio volume was also correlated with severity of depression (r = 0.32, P = .02) and functional impairment (r = 0.28, P = .04). A proxy measure of social interaction based on the detection of speaking voices in environmental audio was correlated with depression (r = -0.45, P = .001) and functional impairment (r = -0.30, P = .03).

Conclusions:

In this study group, environmental audio was shown to contain signals which were associated with severity of depression and functional impairment due to poor mental health. Associations with severity of social anxiety disorder and generalized anxiety disorder were much weaker by comparison and not statistically significant at a 5% significance level. This work also confirmed prior work showing that the presence of voices is associated with depression. This work suggests that sparsely sampled audio volume could provide potentially relevant insight into subjects’ mental health.