Evidence map›Paper›PMID 32788153›Full record

ArticleJMIR formative research2020

The Relationship Between Smartphone-Recorded Environmental Audio and Symptomatology of Anxiety and Depression: Exploratory Study.

Daniel Di Matteo, Kathryn Fotinos, Sachinthya Lokuge, Julia Yu, Tia Sternat, Martin A Katzman, Jonathan Rose

Open access · goldAbstract read
In one paragraph

Article in JMIR formative research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 3 pooled it
5.5field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 3 syntheses or guidelines pooled it, 48 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. A Systematic Review of Location Data for Depression Prediction.International journal of environmental research and public health · 2023
    Pooled it
  4. Article
  5. Observational
  6. Review
  7. Mental Health and Mobile Communication Profiles of Crowdsourced Participants.IEEE journal of biomedical and health informatics · 2024
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Observational
  14. Article
  15. Article
  16. Naturalistic computational psychiatry: How to get there?Journal of psychiatry & neuroscience : JPN
    Article
  17. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 1 country.

Daniel Di MatteoThe Centre for Automation of Medicine, The Edward S Rogers Sr Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON, Canada.ORCID https://orcid.org/0000-0001-6082-267X
Kathryn FotinosStress Trauma Anxiety Rehabilitation Treatment Clinic for Mood and Anxiety Disorders, Toronto, ON, Canada.ORCID https://orcid.org/0000-0001-8268-8360
Sachinthya LokugeStress Trauma Anxiety Rehabilitation Treatment Clinic for Mood and Anxiety Disorders, Toronto, ON, Canada.ORCID https://orcid.org/0000-0001-7136-116X
Julia YuStress Trauma Anxiety Rehabilitation Treatment Clinic for Mood and Anxiety Disorders, Toronto, ON, Canada.ORCID https://orcid.org/0000-0001-6479-0484
Tia SternatStress Trauma Anxiety Rehabilitation Treatment Clinic for Mood and Anxiety Disorders, Toronto, ON, Canada.ORCID https://orcid.org/0000-0001-8215-6305
Martin A KatzmanStress Trauma Anxiety Rehabilitation Treatment Clinic for Mood and Anxiety Disorders, Toronto, ON, Canada.ORCID https://orcid.org/0000-0002-6169-2595
Jonathan RoseThe Centre for Automation of Medicine, The Edward S Rogers Sr Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON, Canada.ORCID https://orcid.org/0000-0002-3551-2175
START Clinic · CAProfessional Engineers Ontario · CAUniversity of Toronto · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundObjective and continuous severity measures of anxiety and depression are highly valuable and would have many applications in psychiatry and psychology. A collective source of data for objective measures are the sensors in a person's smartphone, and a particularly rich source is the microphone that can 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.

objectiveThis study aimed to explore the properties of passively recorded environmental audio from a subject's smartphone to find potential correlates of symptom severity of social anxiety disorder, generalized anxiety disorder, depression, and general impairment.

methodsAn 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 during which 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 nonclinical population. High-level features were extracted from the environmental audio of 84 participants with sufficient data, and correlations were measured between the 4 audio features and the 4 self-report measures.

resultsThe regularity in daily patterns of activity and inactivity inferred from the environmental audio volume was correlated with the severity of depression (r=-0.37; P<.001). A measure of sleep disturbance inferred from the environmental audio volume was also correlated with the severity of depression (r=0.23; P=.03). A proxy measure of social interaction based on the detection of speaking voices in the environmental audio was correlated with depression (r=-0.37; P<.001) and functional impairment (r=-0.29; P=.01). None of the 4 environmental audio-based features tested showed significant correlations with the measures of generalized anxiety or social anxiety.

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

Indexed as

acousticsanxietydepressiondigital signal processingecological momentary assessmentmobile appsmobile healthmobile phonespeech recognition software

Identifiers

PMID32788153
PMCPMC7453326
OpenAlexW3049188596

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.