Multimodal Digital Phenotyping Study in Patients With Major Depressive Episodes and Healthy Controls (Mobile Monitoring of Mood): Observational Longitudinal Study.

Background: Mood disorders are among the most common mental health conditions worldwide. Wearables and consumer-grade personal digital devices create digital traces that can be collected, processed, and analyzed, offering a unique opportunity to quantify and monitor individuals with mental disorders in their natural living environments.

Objective: This study comprised (1) 3 subcohorts of patients with a major depressive episode, either with major depressive disorder, bipolar disorder, or concurrent borderline personality disorder, and (2) a healthy control group.

Sleep During the COVID-19 Pandemic: Longitudinal Observational Study Combining Multisensor Data With Questionnaires.

Background: The COVID-19 pandemic prompted various containment strategies, such as work-from-home policies and reduced social contact, which significantly altered people's sleep routines. While previous studies have highlighted the negative impacts of these restrictions on sleep, they often lack a comprehensive perspective that considers other factors, such as seasonal variations and physical activity (PA), which can also influence sleep.

Objective: This study aims to longitudinally examine the detailed changes in sleep patterns among working adults during the COVID-19 pandemic using a combination of repeated questionnaires and high-resolution passive measurements from wearable sensors.

Examining the Gateway Hypothesis and Mapping Substance Use Pathways on Social Media: Machine Learning Approach.

Background: Substance misuse presents significant global public health challenges. Understanding transitions between substance types and the timing of shifts to polysubstance use is vital to developing effective prevention and recovery strategies. The gateway hypothesis suggests that high-risk substance use is preceded by lower-risk substance use.

The impact of the COVID-19 pandemic on daily rhythms.

Objective: The COVID-19 pandemic has significantly impacted daily activity rhythms and life routines with people adjusting to new work schedules, exercise routines, and other everyday life activities. This study examines temporal changes in daily activity rhythms and routines during the COVID-19 pandemic, emphasizing disproportionate changes among working adult subgroups.

Materials And Methods: In June 2021, we conducted a year-long study to collect high-resolution fitness tracker data and questionnaire responses from 128 working adults.

Using Social Media to Examine Themes Surrounding Fentanyl Misuse and Risk Indicators.

Opioid misuse is a crisis in the United States, and synthetic opioids such as fentanyl pose risks for overdose and mortality. Individuals who misuse substances commonly seek information and support online due to stigma and legal concerns, and this online networking may provide insight for substance misuse prevention and treatment. We aimed to characterize topics in substance-misuse related discourse among members of an online fentanyl community.

Dynamics of the Negative Discourse Toward COVID-19 Vaccines: Topic Modeling Study and an Annotated Data Set of Twitter Posts.

Background: Since the onset of the COVID-19 pandemic, vaccines have been an important topic in public discourse. The discussions around vaccines are polarized, as some see them as an important measure to end the pandemic, and others are hesitant or find them harmful. A substantial portion of these discussions occurs openly on social media platforms.

Relationship between daily rated depression symptom severity and the retrospective self-report on PHQ-9: A prospective ecological momentary assessment study on 80 psychiatric outpatients.

Background: Depression-related negative bias in emotional processing and memory may bias accuracy of recall of temporally distal symptoms. We tested the hypothesis that when responding to the Patient Health Questionnaire (PHQ-9) the responses reflect more accurately temporally proximal than distal mood states.

Methods: Currently, depressed psychiatric outpatients (N = 80) with depression confirmed in semi-structured interviews had the Aware application installed on their smartphones for ecological momentary assessment (EMA).

Alignment Between Heart Rate Variability From Fitness Trackers and Perceived Stress: Perspectives From a Large-Scale In Situ Longitudinal Study of Information Workers.

Background: Stress can have adverse effects on health and well-being. Informed by laboratory findings that heart rate variability (HRV) decreases in response to an induced stress response, recent efforts to monitor perceived stress in the wild have focused on HRV measured using wearable devices. However, it is not clear that the well-established association between perceived stress and HRV replicates in naturalistic settings without explicit stress inductions and research-grade sensors.

Quantifying daily rhythms with non-negative matrix factorization applied to mobile phone data.

Human activities follow daily, weekly, and seasonal rhythms. The emergence of these rhythms is related to physiology and natural cycles as well as social constructs. The human body and its biological functions undergo near 24-h rhythms (circadian rhythms).

Detecting risk level in individuals misusing fentanyl utilizing posts from an online community on Reddit.

Introduction: Opioid misuse is a public health crisis in the US, and misuse of synthetic opioids such as fentanyl have driven the most recent waves of opioid-related deaths. Because those who misuse fentanyl are often a hidden and high-risk group, innovative methods for identifying individuals at risk for fentanyl misuse are needed. Machine learning has been used in the past to investigate discussions surrounding substance use on Reddit, and this study leverages similar techniques to identify risky content from discussions of fentanyl on this platform.

The effects of seasons and weather on sleep patterns measured through longitudinal multimodal sensing.

Previous studies of seasonal effects on sleep have yielded unclear results, likely due to methodological differences and limitations in data size and/or quality. We measured the sleep habits of 216 individuals across the U.S.

Smartphone-Based Tracking of Sleep in Depression, Anxiety, and Psychotic Disorders.

Purpose Of Review: Sleep is an important feature in mental illness. Smartphones can be used to assess and monitor sleep, yet there is little prior application of this approach in depressive, anxiety, or psychotic disorders. We review uses of smartphones and wearable devices for sleep research in patients with these conditions.

Data Collection for Mental Health Studies Through Digital Platforms: Requirements and Design of a Prototype.

Background: Mental and behavioral disorders are the main cause of disability worldwide. However, their diagnosis is challenging due to a lack of reliable biomarkers; current detection is based on structured clinical interviews which can be biased by the patient's recall ability, affective state, changing in temporal frames, etc. While digital platforms have been introduced as a possible solution to this complex problem, there is little evidence on the extent of usability and usefulness of these platforms.

Daily Rhythms in Mobile Telephone Communication.

Circadian rhythms are known to be important drivers of human activity and the recent availability of electronic records of human behaviour has provided fine-grained data of temporal patterns of activity on a large scale. Further, questionnaire studies have identified important individual differences in circadian rhythms, with people broadly categorised into morning-like or evening-like individuals. However, little is known about the social aspects of these circadian rhythms, or how they vary across individuals.