Digital tools to facilitate the detection and treatment of bipolar disorder - Key developments and future directions

Taiane De Azevedo Cardoso, Shruti Kochhar, John Torous, Emma Morton

Research output: Contribution to journalEditorialOtherpeer-review

6 Citations (Scopus)

Abstract

Bipolar disorder (BD) impacts over 40 million people around the world, often manifesting in early adulthood and substantially impacting the quality of life and functioning of individuals. Although early interventions are associated with a better prognosis, the early detection of BD is challenging given the high degree of similarity with other psychiatric conditions, including major depressive disorder, which corroborates the high rates of misdiagnosis. Further, BD has a chronic, relapsing course, and the majority of patients will go on to experience mood relapses despite pharmacological treatment. Digital technologies present promising results to augment early detection of symptoms and enhance BD treatment. In this editorial, we will discuss current findings on the use of digital technologies in the field of BD, while debating the challenges associated with their implementation in clinical practice and the future directions.

Original languageEnglish
Article numbere58631
Number of pages9
JournalJMIR Mental Health
Volume11
Issue number1
DOIs
Publication statusPublished - Jan 2024

Keywords

  • Apps
  • Bipolar disorder
  • Digital phenotyping
  • Machine learning
  • MHealth
  • Mobile health
  • Mobile health interventions

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