Literature DB >> 32905495

Digital solutions for shaping mood and behavior among individuals with mood disorders.

Amanda Victory1, Allison Letkiewicz2, Amy L Cochran3.   

Abstract

Mood disorders present on-going challenges to the medical field, with difficulties ranging from establishing effective treatments to understanding complexities of one's mood. One solution is the use of mobile apps and wearables for measuring physiological symptoms and real-time mood in order to shape mood and behavior. Current digital research is focused on increasing engagement in monitoring mood, uncovering mood dynamics, predicting mood, and providing digital microinterventions. This review discusses the importance and risks of user engagement, as well as barriers to improving it. Research on mood dynamics highlights the possibility to reveal data-driven computational phenotypes that could guide treatment. Mobile apps are being used to track voice patterns, GPS, and phone usage for predicting mood and treatment response. Future directions include utilizing mobile apps to deliver and evaluate microinterventions. To continue these advances, standardized reporting and study designs should be considered to improve digital solutions for mood disorders.

Entities:  

Year:  2020        PMID: 32905495      PMCID: PMC7473040          DOI: 10.1016/j.coisb.2020.07.008

Source DB:  PubMed          Journal:  Curr Opin Syst Biol        ISSN: 2452-3100


  36 in total

1.  A comparative study of engagement in mobile and wearable health monitoring for bipolar disorder.

Authors:  Kaela Van Til; Melvin G McInnis; Amy Cochran
Journal:  Bipolar Disord       Date:  2019-10-25       Impact factor: 6.744

2.  Affective dynamics in bipolar spectrum psychopathology: Modeling inertia, reactivity, variability, and instability in daily life.

Authors:  Sarah H Sperry; Thomas R Kwapil
Journal:  J Affect Disord       Date:  2019-03-19       Impact factor: 4.839

Review 3.  Brief psychotherapy for depression: a systematic review and meta-analysis.

Authors:  Jason A Nieuwsma; Ranak B Trivedi; Jennifer McDuffie; Ian Kronish; Dinesh Benjamin; John W Williams
Journal:  Int J Psychiatry Med       Date:  2012       Impact factor: 1.210

4.  Efficacy of Contextually Tailored Suggestions for Physical Activity: A Micro-randomized Optimization Trial of HeartSteps.

Authors:  Predrag Klasnja; Shawna Smith; Nicholas J Seewald; Andy Lee; Kelly Hall; Brook Luers; Eric B Hekler; Susan A Murphy
Journal:  Ann Behav Med       Date:  2019-05-03

5.  The effect of smartphone-based monitoring on illness activity in bipolar disorder: the MONARCA II randomized controlled single-blinded trial.

Authors:  Maria Faurholt-Jepsen; Mads Frost; Ellen Margrethe Christensen; Jakob E Bardram; Maj Vinberg; Lars Vedel Kessing
Journal:  Psychol Med       Date:  2019-04-04       Impact factor: 7.723

6.  Disease management apps and technical assistance systems for bipolar disorder: Investigating the patients´ point of view.

Authors:  Henning Daus; Natalia Kislicyn; Stephan Heuer; Matthias Backenstrass
Journal:  J Affect Disord       Date:  2018-01-02       Impact factor: 4.839

7.  Parsing affective dynamics to identify risk for mood and anxiety disorders.

Authors:  Aaron S Heller; Andrew S Fox; Richard J Davidson
Journal:  Emotion       Date:  2018-06-04

8.  Data-driven classification of bipolar I disorder from longitudinal course of mood.

Authors:  A L Cochran; M G McInnis; D B Forger
Journal:  Transl Psychiatry       Date:  2016-10-11       Impact factor: 6.222

9.  A Dynamical Bifurcation Model of Bipolar Disorder Based on Learned Expectation and Asymmetry in Mood Sensitivity.

Authors:  Shyr-Shea Chang; Tom Chou
Journal:  Comput Psychiatr       Date:  2018-12

10.  Mood Prediction of Patients With Mood Disorders by Machine Learning Using Passive Digital Phenotypes Based on the Circadian Rhythm: Prospective Observational Cohort Study.

Authors:  Chul-Hyun Cho; Taek Lee; Min-Gwan Kim; Hoh Peter In; Leen Kim; Heon-Jeong Lee
Journal:  J Med Internet Res       Date:  2019-04-17       Impact factor: 5.428

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