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.

Low hedonic tone and attention-deficit hyperactivity disorder: risk factors for treatment resistance in depressed adults.

BACKGROUND: The burdens imposed by treatment-resistant depression (TRD) necessitate the identification of predictive factors that may improve patient treatment and outcomes. Because depression and attention-deficit hyperactivity disorder (ADHD) are frequently comorbid and share a complex relationship, we hypothesized that ADHD may be a predictive factor for the diagnosis of TRD. This exploratory study aimed to determine the percentage of undetected ADHD in those with TRD and evaluate factors associated with treatment resistance and undetected ADHD in depressed patients. SUBJECTS AND METHODS: Adults referred (n=160) for psychiatric consultation completed a structured interview (MINI Plus, Mini International Neuropsychiatric Interview Plus) to assess the presence of psychiatric disorders. RESULTS: TRD was significantly associated with the number of diagnoses (P<0.001), past (P<0.001) and present medications (P<0.001), chronic anhedonia (P=0.013), and suicide ideation (P=0.008). Undetected ADHD was present in 34% of TRD patients. The number of referral diagnoses (P<0.001), failed medications (P=0.002), and past selective serotonin reuptake inhibitor failures (P=0.035) were predictive of undetected ADHD in TRD. CONCLUSION: Undetected ADHD may be more prevalent among TRD patients than previously thought. In addition, TRD patients are more likely to present with psychiatric comorbidity than non-TRD patients. Screening patients with depression for the presence of ADHD and chronic anhedonia/low hedonic tone may help identify patients with TRD and undetected ADHD and improve treatment outcomes.

Neurobiology of hedonic tone: the relationship between treatment-resistant depression, attention-deficit hyperactivity disorder, and substance abuse.

Anhedonia, defined as the state of reduced ability to experience feelings of pleasure, is one of the hallmarks of depression. Hedonic tone is the trait underlying one's characteristic ability to feel pleasure. Low hedonic tone represents a reduced capacity to experience pleasure, thus increasing the likelihood of experiencing anhedonia. Low hedonic tone has been associated with several psychopathologies, including major depressive disorder (MDD), substance use, and attention-deficit hyperactivity disorder (ADHD). The main neural pathway that modulates emotional affect comprises the limbic-cortical-striatal-pallidal-thalamic circuits. The activity of various components of the limbic-cortical-striatal-pallidal-thalamic pathway is correlated with hedonic tone in healthy individuals and is altered in MDD. Dysfunction of these circuits has also been implicated in the relative ineffectiveness of selective serotonin reuptake inhibitors used to treat anxiety and depression in patients with low hedonic tone. Mood disorders such as MDD, ADHD, and substance abuse share low hedonic tone as well as altered activation of brain regions involved in reward processing and monoamine signaling as their features. Given the common features of these disorders, it is not surprising that they have high levels of comorbidities. The purpose of this article is to review the neurobiology of hedonic tone as it pertains to depression, ADHD, and the potential for substance abuse. We propose that, since low hedonic tone is a shared feature of MDD, ADHD, and substance abuse, evaluation of hedonic tone may become a diagnostic feature used to predict subtypes of MDD, such as treatment-resistant depression, as well as comorbidities of these disorders.

A review of OROS methylphenidate (Concerta(®)) in the treatment of attention-deficit/hyperactivity disorder.

Attention-deficit/hyperactivity disorder (ADHD) is a common neurobehavioural disorder with onset during childhood. It affects a child's development, both at home and at school, and impacts on social, emotional and cognitive functioning, in both the home and the school environment. Untreated ADHD is very often associated with poor academic achievement, low occupational status, increased risk of substance abuse and delinquency. Current practice guidelines recommend a multimodal approach in the treatment of ADHD, which includes educational, behavioural and mental health interventions, and pharmacological management. Stimulant medications, including methylphenidate (MPH) and amphetamine products, are recommended as first-line pharmacotherapy in the treatment of ADHD. The choice of stimulant is influenced by several factors; the most influential factor is the duration of action. Long-acting medication provides benefits long after school and work. It also increases the likelihood of once-daily dosing, thereby eliminating the need for mid-day dosing, making the treatment more private, avoiding stigma and improving adherence to medication. MPH is the most widely used psychotropic medication in child psychiatry. It was first developed for use in children as an oral, immediate-release formulation and more recently as various extended-release formulations. These latter formulations include the 12 h preparation Concerta(®) (osmotic-release oral system [OROS] MPH), which utilizes an osmotic pump system, designed to overcome the difficulties of multiple daily dosing. Since it received approval from the US Food and Drug Administration in August 2000, OROS MPH has been quickly and widely accepted as one of the preferred treatments for ADHD because of its once-daily dosing. This paper reviews the data in support of long-acting OROS MPH in children, adolescents and adults, both in ADHD and in association with its comorbidities.