Publications by authors named "D J Kupfer"

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.

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The nature of data obtainable from the commercial smartphone - bolstered by a translational model emphasizing the impact of social and physical zeitgebers on circadian rhythms and mood - offers the possibility of scalable and objective vital signs for major depression. Our objective was to explore associations between passively sensed behavioral smartphone data and repeatedly measured depressive symptoms to suggest which features could eventually lead towards vital signs for depression. We collected continuous behavioral data and bi-weekly depressive symptoms (PHQ-8) from 131 psychiatric outpatients with a lifetime DSM-5 diagnosis of depression and/or anxiety over a 16-week period.

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My long day's journey into sleep began as an adolescent trying to manage my evening chronotype. The relief, I felt when my undergraduate finals were scheduled at night and as a medical student being able to select psychiatry over surgery deepened my interest in sleep and chronobiology. That interest was allowed to flourish at the National Institute of Mental Health and then at Yale Medical School in setting up a sleep laboratory.

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We conducted a 16-week randomized controlled trial in psychiatric outpatients with a lifetime diagnosis of a mood and/or anxiety disorder to measure the impact of a first-of-its-kind precision digital intervention software solution based on social rhythm regulation principles. The full intent-to-treat (ITT) sample consisted of 133 individuals, aged 18-65. An exploratory sub-sample of interest was those individuals who presented with moderately severe to severe depression at study entry (baseline PHQ-8 score ≥15;  = 28).

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