Quality of Psychiatric Care for Immigrants and People With a Non-English Language Preference: A Systematic Scoping Review.

Objective: Immigrants and persons with a non-English language preference (NELP) face unique challenges in the mental health care system. This systematic scoping review aimed to evaluate the literature for disparities in psychiatric care delivery, beyond access and utilization barriers, experienced by these two populations.

Methods: The authors queried four databases: PubMed, PsycInfo, Web of Science, and CINAHL.

The Trifecta of Industry, Academic, and Health System Partnership to Improve Mental Health Care Through Smartphone-Based Remote Patient Monitoring: Development and Usability Study.

Background: Mental health treatment is hindered by the limited number of mental health care providers and the infrequency of care. Digital mental health technology can help supplement treatment by remotely monitoring patient symptoms and predicting mental health crises in between clinical visits. However, the feasibility of digital mental health technologies has not yet been sufficiently explored.

Machine Learning for Mental Health: Applications, Challenges, and the Clinician's Role.

Purpose Of Review: This review aims to evaluate the current psychiatric applications and limitations of machine learning (ML), defined as techniques used to train algorithms to improve performance at a task based on data. The review emphasizes the clinician's role in ensuring equitable and effective patient care and seeks to inform mental health providers about the importance of clinician involvement in these technologies.

Recent Findings: ML in psychiatry has advanced through electronic health record integration, disease phenotyping, and remote monitoring through mobile applications.