Stephen F Smagula1. 1. Department of Psychiatry, Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.
Abstract
PURPOSE OF REVIEW: Rest-activity rhythm (RAR) measurements may aid in the detection of depression risk and serve as an important target for depression prevention. This review evaluates the strength of current evidence supporting these potential applications. RECENT FINDINGS: Depression is associated with lower activity levels, that is less regularly patterned, and potentially shifted earlier or later in the day. Specific RAR patterns (combinations of several RAR characteristics) in patients with clinical depression may be unique or partially shared across disorders. Longitudinal research is limited but provides initial evidence that multiple distinct RAR patterns are associated with the risk of developing depression symptoms. SUMMARY: RAR measures provide a comprehensive and objective assessment of depression's behavioral manifestations, and therefore may be useful as monitoring tool, providing additional information to help clinicians tailor behavioral treatments to specific patients. RARs also appear to contribute to depression risk and may be an important target for depression prevention. But research has not established valid predictive metrics using RARs to diagnose depression or detect depression risk. Future research should prioritize establishing the specific RAR patterns related to depression risk in high-risk groups, and should seek to place this risk within the known psychosocial and neurobiological risk architecture of depression.
PURPOSE OF REVIEW: Rest-activity rhythm (RAR) measurements may aid in the detection of depression risk and serve as an important target for depression prevention. This review evaluates the strength of current evidence supporting these potential applications. RECENT FINDINGS:Depression is associated with lower activity levels, that is less regularly patterned, and potentially shifted earlier or later in the day. Specific RAR patterns (combinations of several RAR characteristics) in patients with clinical depression may be unique or partially shared across disorders. Longitudinal research is limited but provides initial evidence that multiple distinct RAR patterns are associated with the risk of developing depression symptoms. SUMMARY: RAR measures provide a comprehensive and objective assessment of depression's behavioral manifestations, and therefore may be useful as monitoring tool, providing additional information to help clinicians tailor behavioral treatments to specific patients. RARs also appear to contribute to depression risk and may be an important target for depression prevention. But research has not established valid predictive metrics using RARs to diagnose depression or detect depression risk. Future research should prioritize establishing the specific RAR patterns related to depression risk in high-risk groups, and should seek to place this risk within the known psychosocial and neurobiological risk architecture of depression.
Authors: E J van Someren; E E Hagebeuk; C Lijzenga; P Scheltens; S E de Rooij; C Jonker; A M Pot; M Mirmiran; D F Swaab Journal: Biol Psychiatry Date: 1996-08-15 Impact factor: 13.382
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Authors: Stephen F Smagula; Robert M Boudreau; Katie Stone; Charles F Reynolds; Joyce T Bromberger; Sonia Ancoli-Israel; Thuy-Tien Dam; Elizabeth Barrett-Connor; Jane A Cauley Journal: Chronobiol Int Date: 2015-11-23 Impact factor: 2.877
Authors: Jeanne E Maglione; Sonia Ancoli-Israel; Katherine W Peters; Misti L Paudel; Kristine Yaffe; Kristine E Ensrud; Greg J Tranah; Katie L Stone Journal: Am J Geriatr Psychiatry Date: 2013-03-26 Impact factor: 4.105
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Authors: Annemarie I Luik; Lisette A Zuurbier; Albert Hofman; Eus J W Van Someren; Henning Tiemeier Journal: Chronobiol Int Date: 2013-08-23 Impact factor: 2.877
Authors: Rébecca Robillard; Sharon L Naismith; Kristie Leigh Smith; Naomi L Rogers; Django White; Zoe Terpening; Tony K C Ip; Daniel F Hermens; Bradley Whitwell; Elizabeth M Scott; Ian B Hickie Journal: PLoS One Date: 2014-02-25 Impact factor: 3.240
Authors: Stephen F Smagula; Robert T Krafty; Julian F Thayer; Daniel J Buysse; Martica H Hall Journal: J Psychiatr Res Date: 2018-04-21 Impact factor: 4.791
Authors: Stephen F Smagula; Caitlin M DuPont; Megan A Miller; Robert T Krafty; Brant P Hasler; Peter L Franzen; Kathryn A Roecklein Journal: Chronobiol Int Date: 2018-07-19 Impact factor: 2.877