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      Smartphone-Detected Ambient Speech and Self-Reported Measures of Anxiety and Depression: Exploratory Observational Study

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          Abstract

          Background

          The ability to objectively measure the severity of depression and anxiety disorders in a passive manner could have a profound impact on the way in which these disorders are diagnosed, assessed, and treated. Existing studies have demonstrated links between both depression and anxiety and the linguistic properties of words that people use to communicate. Smartphones offer the ability to passively and continuously detect spoken words to monitor and analyze the linguistic properties of speech produced by the speaker and other sources of ambient speech in their environment. The linguistic properties of automatically detected and recognized speech may be used to build objective severity measures of depression and anxiety.

          Objective

          The aim of this study was to determine if the linguistic properties of words passively detected from environmental audio recorded using a participant’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 to collect periodic audiorecordings of participants’ environments and to detect English words using automatic speech recognition. Participants were recruited into a 2-week observational study. The app was installed on the participants’ personal smartphones to record and analyze audio. The participants also completed self-report severity measures of social anxiety disorder, generalized anxiety disorder, depression, and functional impairment. Words detected from audiorecordings were categorized, and correlations were measured between words counts in each category and the 4 self-report measures to determine if any categories could serve as correlates of social anxiety disorder, generalized anxiety disorder, depression, or general impairment.

          Results

          The participants were 112 adults who resided in Canada from a nonclinical population; 86 participants yielded sufficient data for analysis. Correlations between word counts in 67 word categories and each of the 4 self-report measures revealed a strong relationship between the usage rates of death-related words and depressive symptoms ( r=0.41, P<.001). There were also interesting correlations between rates of word usage in the categories of reward-related words with depression ( r=–0.22, P=.04) and generalized anxiety ( r=–0.29, P=.007), and vision-related words with social anxiety ( r=0.31, P=.003).

          Conclusions

          In this study, words automatically recognized from environmental audio were shown to contain a number of potential associations with severity of depression and anxiety. This work suggests that sparsely sampled audio could provide relevant insight into individuals’ mental health.

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          Most cited references38

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          A brief measure for assessing generalized anxiety disorder: the GAD-7.

          Generalized anxiety disorder (GAD) is one of the most common mental disorders; however, there is no brief clinical measure for assessing GAD. The objective of this study was to develop a brief self-report scale to identify probable cases of GAD and evaluate its reliability and validity. A criterion-standard study was performed in 15 primary care clinics in the United States from November 2004 through June 2005. Of a total of 2740 adult patients completing a study questionnaire, 965 patients had a telephone interview with a mental health professional within 1 week. For criterion and construct validity, GAD self-report scale diagnoses were compared with independent diagnoses made by mental health professionals; functional status measures; disability days; and health care use. A 7-item anxiety scale (GAD-7) had good reliability, as well as criterion, construct, factorial, and procedural validity. A cut point was identified that optimized sensitivity (89%) and specificity (82%). Increasing scores on the scale were strongly associated with multiple domains of functional impairment (all 6 Medical Outcomes Study Short-Form General Health Survey scales and disability days). Although GAD and depression symptoms frequently co-occurred, factor analysis confirmed them as distinct dimensions. Moreover, GAD and depression symptoms had differing but independent effects on functional impairment and disability. There was good agreement between self-report and interviewer-administered versions of the scale. The GAD-7 is a valid and efficient tool for screening for GAD and assessing its severity in clinical practice and research.
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            The PHQ-8 as a measure of current depression in the general population.

            The eight-item Patient Health Questionnaire depression scale (PHQ-8) is established as a valid diagnostic and severity measure for depressive disorders in large clinical studies. Our objectives were to assess the PHQ-8 as a depression measure in a large, epidemiological population-based study, and to determine the comparability of depression as defined by the PHQ-8 diagnostic algorithm vs. a PHQ-8 cutpoint > or = 10. Random-digit-dialed telephone survey of 198,678 participants in the 2006 Behavioral Risk Factor Surveillance Survey (BRFSS), a population-based survey in the United States. Current depression as defined by either the DSM-IV based diagnostic algorithm (i.e., major depressive or other depressive disorder) of the PHQ-8 or a PHQ-8 score > or = 10; respondent sociodemographic characteristics; number of days of impairment in the past 30 days in multiple domains of health-related quality of life (HRQoL). The prevalence of current depression was similar whether defined by the diagnostic algorithm or a PHQ-8 score > or = 10 (9.1% vs. 8.6%). Depressed patients had substantially more days of impairment across multiple domains of HRQoL, and the impairment was nearly identical in depressed groups defined by either method. Of the 17,040 respondents with a PHQ-8 score > or = 10, major depressive disorder was present in 49.7%, other depressive disorder in 23.9%, depressed mood or anhedonia in another 22.8%, and no evidence of depressive disorder or depressive symptoms in only 3.5%. The PHQ-8 diagnostic algorithm rather than an independent structured psychiatric interview was used as the criterion standard. The PHQ-8 is a useful depression measure for population-based studies, and either its diagnostic algorithm or a cutpoint > or = 10 can be used for defining current depression.
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              The Psychological Meaning of Words: LIWC and Computerized Text Analysis Methods

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                Author and article information

                Contributors
                Journal
                JMIR Form Res
                JMIR Form Res
                JFR
                JMIR Formative Research
                JMIR Publications (Toronto, Canada )
                2561-326X
                January 2021
                29 January 2021
                : 5
                : 1
                : e22723
                Affiliations
                [1 ] The Centre for Automation of Medicine The Edward S Rogers Sr Department of Electrical and Computer Engineering University of Toronto Toronto, ON Canada
                [2 ] START Clinic for Mood and Anxiety Disorders Toronto, ON Canada
                [3 ] Department of Psychology Adler Graduate Professional School Toronto, ON Canada
                [4 ] Department of Psychology Lakehead University Thunder Bay, ON Canada
                [5 ] The Northern Ontario School of Medicine Thunder Bay, ON Canada
                Author notes
                Corresponding Author: Daniel Di Matteo dandm@ 123456ece.utoronto.ca
                Author information
                https://orcid.org/0000-0001-6082-267X
                https://orcid.org/0000-0001-6710-446X
                https://orcid.org/0000-0001-8268-8360
                https://orcid.org/0000-0001-7136-116X
                https://orcid.org/0000-0001-6479-0484
                https://orcid.org/0000-0001-8215-6305
                https://orcid.org/0000-0002-6169-2595
                https://orcid.org/0000-0002-3551-2175
                Article
                v5i1e22723
                10.2196/22723
                7880807
                33512325
                894e997f-16f1-4050-8c53-9503bcc25572
                ©Daniel Di Matteo, Wendy Wang, Kathryn Fotinos, Sachinthya Lokuge, Julia Yu, Tia Sternat, Martin A Katzman, Jonathan Rose. Originally published in JMIR Formative Research (http://formative.jmir.org), 29.01.2021.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on http://formative.jmir.org, as well as this copyright and license information must be included.

                History
                : 21 July 2020
                : 17 September 2020
                : 13 October 2020
                : 24 December 2020
                Categories
                Original Paper
                Original Paper

                mobile sensing,passive sensing,psychiatric assessment,mood and anxiety disorders,mobile apps,linguistics,speech recognition,speech content,lexical choice

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