Automated Screening for Social Anxiety, Generalized Anxiety, and Depression From Objective Smartphone-Collected Data: Cross-sectional Study.

BACKGROUND: The lack of access to mental health care could be addressed, in part, through the development of automated screening technologies for detecting the most common mental health disorders without the direct involvement of clinicians. Objective smartphone-collected data may contain sufficient information about individuals' behaviors to infer their mental states and therefore screen for anxiety disorders and depression. OBJECTIVE: The objective of this study is to compare how a single set of recognized and novel features, extracted from smartphone-collected data, can be used for predicting generalized anxiety disorder (GAD), social anxiety disorder (SAD), and depression. METHODS: An Android app was designed, together with a centralized server system, to collect periodic measurements of objective smartphone data. The types of data included samples of ambient audio, GPS location, screen state, and light sensor data. Subjects were recruited into a 2-week observational study in which the app was run on their personal smartphones. The subjects also completed self-report severity measures of SAD, GAD, and depression. The participants were 112 Canadian adults from a nonclinical population. High-level features were extracted from the data of 84 participants, and predictive models of SAD, GAD, and depression were built and evaluated. RESULTS: Models of SAD and depression achieved a significantly greater screening accuracy than uninformative models (area under the receiver operating characteristic means of 0.64, SD 0.13 and 0.72, SD 0.12, respectively), whereas models of GAD failed to be predictive. Investigation of the model coefficients revealed key features that were predictive of SAD and depression. CONCLUSIONS: We demonstrate the ability of a common set of features to act as predictors in the models of both SAD and depression. This suggests that the types of behaviors that can be inferred from smartphone-collected data are broad indicators of mental health, which can be used to study, assess, and track psychopathology simultaneously across multiple disorders and diagnostic boundaries.

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

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.

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

BACKGROUND: Objective 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. OBJECTIVE: This 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. 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 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. RESULTS: The 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. CONCLUSIONS: In 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.

Effect of Osteopathic Manipulative Therapy on Generalized Anxiety Disorder.

CONTEXT: Traditional management options for generalized anxiety disorder (GAD) have produced low remission rates. As a result, the medical community has turned to complementary and alternative medicine for adjunctive treatment. OBJECTIVE: To investigate the efficacy of adjunctive osteopathic manipulative therapy (OMTh; manipulative care provided by foreign-trained osteopaths) in individuals with GAD. METHODS: This open-label, nonrandomized, black-box study took place at a tertiary care mental health clinic in Toronto, Canada. Adult outpatient participants aged 18 to 65 years with a primary diagnosis of moderate-severe GAD (HAM-A score of ≥20) with or without comorbidities were enrolled in the study between June 2014 and January 2015. Patients who qualified and completed the study received 5 individually tailored OMTh sessions over the course of 8 to 9 weeks. A diagnostic psychiatric assessment (Mini International Neuropsychiatric Interview version 6.0.0) was conducted to confirm diagnoses, along with physician-administered and self-reported measures of anxiety, including the Hamilton Anxiety Scale (HAM-A), the Beck Anxiety Inventory, and the Intolerance for Uncertainty Scale. RESULTS: Significant reductions in total HAM-A scores after OMTh were observed (P<.0001). Significant reductions in total Intolerance for Uncertainty Scale scores were also observed (P<.0001). Beck Anxiety Inventory scores were not found to change significantly with OMTh. Response (defined as 50% reduction of symptoms) and remission (defined as HAM-A score of ≤7) rates were found to be 62% and 26.9%, respectively. CONCLUSION: Osteopathic manipulative therapy may be a valuable adjunct to conventional therapy in patients with GAD, thus warranting further investigation using double-blind procedures.