2018
DOI: 10.1186/s40345-017-0116-2
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Control charts for monitoring mood stability as a predictor of severe episodes in patients with bipolar disorder

Abstract: BackgroundRecurrent mood episodes and subsyndromal mood instability cause substantial disability in patients with bipolar disorder. Early identification of mood episodes enabling timely mood stabilization is an important clinical goal. This study investigates the ability of control chart methodology to predict manic and/or depressive episodes by applying Shewhart’s control rules to weekly self-reported scores from mania and depression questionnaires.MethodsShewhart’s control rules were applied to weekly self-r… Show more

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Cited by 13 publications
(6 citation statements)
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“…Over time, repeated measures can help in two ways: to understand symptom dynamics in BP and to forecast future moods. [8][9][10][11]54,55 Focusing on the latter, we examined whether personalized models could be built from an individual's past m and d scores in order to predict their future scores.…”
Section: Longitudinal Analysismentioning
confidence: 99%
See 1 more Smart Citation
“…Over time, repeated measures can help in two ways: to understand symptom dynamics in BP and to forecast future moods. [8][9][10][11]54,55 Focusing on the latter, we examined whether personalized models could be built from an individual's past m and d scores in order to predict their future scores.…”
Section: Longitudinal Analysismentioning
confidence: 99%
“…The most obvious are mobile apps to manage mood and deliver treatment for BP. [1][2][3][4][5][6] Other opportunities include the ability to build BP cohorts not limited by geography and to phenotype BP at finer time scales [7][8][9][10][11] with greater, inthe-moment context on an individual's life including their physiology. [12][13][14][15][16][17] To improve the successes of digital research, the community is looking for standardized reporting tools for BP symptoms in a digital setting.…”
mentioning
confidence: 99%
“…In the Cequel trial the time taken to respond to prompts was found to predict improvement in depressive symptoms in advance of any change in mood score 36 . Furthermore, remote self-monitoring methodology is a way to aid individuals to gain greater insight into the dynamic and temporal nature of mood and mood stability in mood disorder in daily life 11,37 .…”
Section: Remotely Collected Mood Data In Mood Disorder Researchmentioning
confidence: 99%
“…The chronic relapsing and remitting nature of psychiatric disorders is such that many researchers have sought to use remote monitoring to predict future mood states with a view to enabling earlier initiation of preventative treatment. A variety of mathematical approaches have been used including relaxation oscillatory models [19], control charts [20] and rough paths theory [21] with varying results. It seems likely that for any model to gain the necessary accuracy upon which to base treatment decisions, predictions would need to be made at in individual rather than group level.…”
Section: Passive Correlates Of Mood Statesmentioning
confidence: 99%