Digital Technologies Tracking Active and Passive Data Collection in Depressive Disorders: Lessons Learned From a Case Series.

In this case series, we present several examples from participants (2 patients and 1 healthy control) of a 12-week pilot feasibility study to create a digital phenotype of depression (unipolar or bipolar) through active and passive data collection from a smartphone and a wearable device combined with routine clinical care for mood disorders. The selected cases represent real clinical examples that highlight the intrinsic challenges that should be expected when conducting similar studies, including appropriate health data privacy protection, clinical standardization, and interindividual differences in levels of engagement and acceptability of active and passive data collection (ie, self-reported, behavioral, cognitive, and physiological data), particularly with patient-generated data in mobile apps, digital proficiency habituation, and consistent use of wearable devices. In the context of the rapidly growing use of digital technologies in psychiatry, anticipating challenges for the integration of personal mobile devices and smartphone mental health apps as aides to track specific aspects of depressive disorders is critical for a clinically meaningful digital transformation of mood disorders care.

Peripheral Endothelial Dysfunction Is Associated With Incident Major Depressive Disorder.

Background: A subset of individuals with major depressive disorder (MDD) have a high burden of cardiovascular risk factors and cerebral small-vessel disease, implicating vascular disease in the development of depression. Cross-sectional studies demonstrate a link between endothelial dysfunction and MDD, but the prospective association between peripheral endothelial dysfunction (PED) and an incident diagnosis of MDD is unknown.

Methods And Results: Patients undergoing a baseline assessment of cardiovascular risk were evaluated for PED using reactive hyperemia-peripheral arterial tonometry (≤1.

Transitioning Virtual-Only Group Therapy for Substance Use Disorder Patients to a Hybrid Model.

Purpose: Telehealth is associated with a myriad of benefits; however, little is known regarding substance use disorder (SUD) treatment outcomes when participants join group therapy sessions in a combination in-person and virtual setting (hybrid model). We sought to determine if treatment completion rates differed.

Patients And Methods: Policy changes caused by the COVID-19 pandemic created a naturalistic, observational cohort study at seven intensive outpatient (IOP) programs in rural Minnesota.

Digital Phenotyping for Mood Disorders: Methodology-Oriented Pilot Feasibility Study.

Background: In the burgeoning area of clinical digital phenotyping research, there is a dearth of literature that details methodology, including the key challenges and dilemmas in developing and implementing a successful architecture for technological infrastructure, patient engagement, longitudinal study participation, and successful reporting and analysis of diverse passive and active digital data streams.

Objective: This article provides a narrative rationale for our study design in the context of the current evidence base and best practices, with an emphasis on our initial lessons learned from the implementation challenges and successes of this digital phenotyping study.

Methods: We describe the design and implementation approach for a digital phenotyping pilot feasibility study with attention to synthesizing key literature and the reasoning for pragmatic adaptations in implementing a multisite study encompassing distinct geographic and population settings.

Classifying and clustering mood disorder patients using smartphone data from a feasibility study.

Differentiating between bipolar disorder and major depressive disorder can be challenging for clinicians. The diagnostic process might benefit from new ways of monitoring the phenotypes of these disorders. Smartphone data might offer insight in this regard.

Improving Supervisor Confidence in Responding to Distressed Health Care Employees.

Background: Professional distress and burnout are increasingly common among health professionals. This trend prompted stakeholders at a large multicenter health care system to survey supervisors for improvement opportunities. The stakeholders learned that workplace leaders lacked tools and direction for appropriately responding to distressed employees.

A risk identification model for detection of patients at risk of antidepressant discontinuation.

Purpose: Between 30 and 68% of patients prematurely discontinue their antidepressant treatment, posing significant risks to patient safety and healthcare outcomes. Online healthcare forums have the potential to offer a rich and unique source of data, revealing dimensions of antidepressant discontinuation that may not be captured by conventional data sources.

Methods: We analyzed 891 patient narratives from the online healthcare forum, "askapatient.

Systematic review: Wearable remote monitoring to detect nonalcohol/nonnicotine-related substance use disorder symptoms.

Background And Objectives: Substance use disorders (SUDs) are chronic relapsing diseases characterized by significant morbidity and mortality. Phenomenologically, patients with SUDs present with a repeating cycle of intoxication, withdrawal, and craving, significantly impacting their diagnosis and treatment. There is a need for better identification and monitoring of these disease states.

Short Term Second-Generation Antidepressant Monotherapy in Acute Depressive Episodes of Bipolar II Disorder: A Systematic Review and Meta-Analysis.

Purpose: Bipolar II disorder (BD-II) has limited evidence-based treatment guidelines. The aim of this systematic review and meta-analysis was to estimate the efficacy and safety of second-generation antidepressant (SGAD) monotherapy in acute BD-II depression.

Methods: A literature search was conducted from the database inception through March 2021.

Clinician Satisfaction with Rapid Adoption and Implementation of Telehealth Services During the COVID-19 Pandemic.

To examine clinician perspectives on the acceptability, appropriateness/suitability, and feasibility of video telehealth as a way to deliver mental health services during the COVID-19 pandemic. Mental health clinicians were surveyed with 27 Likert questions, using previously validated measures, on satisfaction and implementation experience with video telehealth visits between March and June 2020. A total of 112 of 193 clinicians completed the survey (58.

Substance Use Disorders and Telehealth in the COVID-19 Pandemic Era: A New Outlook.

During the current coronavirus disease 2019 epidemic, many outpatient chemical dependency treatment programs and clinics are decreasing their number of in-person patient contacts. This has widened an already large gap between patients with substance use disorders (SUDs) who need treatment and those who have actually received treatment. For a disorder where group therapy has been the mainstay treatment option for decades, social distancing, shelter in place, and treatment discontinuation have created an urgent need for alternative approaches to addiction treatment.

Implementation of a Centralized Telepsychiatry Consult Service in a Multi-Hospital Metropolitan Health Care System: Challenges and Opportunities.

Background: Providing adequate psychiatry consultation capacity on a 24/7 basis is an intrinsic challenge throughout many multihospital health care systems. At present, implementation research has not adequately defined the effectiveness and feasibility of a centralized telepsychiatry consultation service within a multihospital health care system.

Objective: To demonstrate feasibility of a hub and spoke model for provision of inpatient consult telepsychiatry service from an academic medical center to 2 affiliated regional hospital sites, to reduce patient wait time, and to develop best practice guidelines for telepsychiatry consultations to the acutely medically ill.

Social determinants of health in mental health care and research: a case for greater inclusion.

Social determinants of health (SDOH) are known to influence mental health outcomes, which are independent risk factors for poor health status and physical illness. Currently, however, existing SDOH data collection methods are ad hoc and inadequate, and SDOH data are not systematically included in clinical research or used to inform patient care. Social contextual data are rarely captured prospectively in a structured and comprehensive manner, leaving large knowledge gaps.