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Applications of time-series analysis to mood fluctuations in bipolar disorder to promote treatment innovation: a case series

Treatment innovation for bipolar disorder has been hampered by a lack of techniques to capture a hallmark symptom: ongoing mood instability. Mood swings persist during remission from acute mood episodes and impair daily functioning. The last significant treatment advance remains Lithium (in the 1970...

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Autores principales: Holmes, E A, Bonsall, M B, Hales, S A, Mitchell, H, Renner, F, Blackwell, S E, Watson, P, Goodwin, G M, Di Simplicio, M
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5068881/
https://www.ncbi.nlm.nih.gov/pubmed/26812041
http://dx.doi.org/10.1038/tp.2015.207
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author Holmes, E A
Bonsall, M B
Hales, S A
Mitchell, H
Renner, F
Blackwell, S E
Watson, P
Goodwin, G M
Di Simplicio, M
author_facet Holmes, E A
Bonsall, M B
Hales, S A
Mitchell, H
Renner, F
Blackwell, S E
Watson, P
Goodwin, G M
Di Simplicio, M
author_sort Holmes, E A
collection PubMed
description Treatment innovation for bipolar disorder has been hampered by a lack of techniques to capture a hallmark symptom: ongoing mood instability. Mood swings persist during remission from acute mood episodes and impair daily functioning. The last significant treatment advance remains Lithium (in the 1970s), which aids only the minority of patients. There is no accepted way to establish proof of concept for a new mood-stabilizing treatment. We suggest that combining insights from mood measurement with applied mathematics may provide a step change: repeated daily mood measurement (depression) over a short time frame (1 month) can create individual bipolar mood instability profiles. A time-series approach allows comparison of mood instability pre- and post-treatment. We test a new imagery-focused cognitive therapy treatment approach (MAPP; Mood Action Psychology Programme) targeting a driver of mood instability, and apply these measurement methods in a non-concurrent multiple baseline design case series of 14 patients with bipolar disorder. Weekly mood monitoring and treatment target data improved for the whole sample combined. Time-series analyses of daily mood data, sampled remotely (mobile phone/Internet) for 28 days pre- and post-treatment, demonstrated improvements in individuals' mood stability for 11 of 14 patients. Thus the findings offer preliminary support for a new imagery-focused treatment approach. They also indicate a step in treatment innovation without the requirement for trials in illness episodes or relapse prevention. Importantly, daily measurement offers a description of mood instability at the individual patient level in a clinically meaningful time frame. This costly, chronic and disabling mental illness demands innovation in both treatment approaches (whether pharmacological or psychological) and measurement tool: this work indicates that daily measurements can be used to detect improvement in individual mood stability for treatment innovation (MAPP).
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spelling pubmed-50688812016-10-20 Applications of time-series analysis to mood fluctuations in bipolar disorder to promote treatment innovation: a case series Holmes, E A Bonsall, M B Hales, S A Mitchell, H Renner, F Blackwell, S E Watson, P Goodwin, G M Di Simplicio, M Transl Psychiatry Original Article Treatment innovation for bipolar disorder has been hampered by a lack of techniques to capture a hallmark symptom: ongoing mood instability. Mood swings persist during remission from acute mood episodes and impair daily functioning. The last significant treatment advance remains Lithium (in the 1970s), which aids only the minority of patients. There is no accepted way to establish proof of concept for a new mood-stabilizing treatment. We suggest that combining insights from mood measurement with applied mathematics may provide a step change: repeated daily mood measurement (depression) over a short time frame (1 month) can create individual bipolar mood instability profiles. A time-series approach allows comparison of mood instability pre- and post-treatment. We test a new imagery-focused cognitive therapy treatment approach (MAPP; Mood Action Psychology Programme) targeting a driver of mood instability, and apply these measurement methods in a non-concurrent multiple baseline design case series of 14 patients with bipolar disorder. Weekly mood monitoring and treatment target data improved for the whole sample combined. Time-series analyses of daily mood data, sampled remotely (mobile phone/Internet) for 28 days pre- and post-treatment, demonstrated improvements in individuals' mood stability for 11 of 14 patients. Thus the findings offer preliminary support for a new imagery-focused treatment approach. They also indicate a step in treatment innovation without the requirement for trials in illness episodes or relapse prevention. Importantly, daily measurement offers a description of mood instability at the individual patient level in a clinically meaningful time frame. This costly, chronic and disabling mental illness demands innovation in both treatment approaches (whether pharmacological or psychological) and measurement tool: this work indicates that daily measurements can be used to detect improvement in individual mood stability for treatment innovation (MAPP). Nature Publishing Group 2016-01 2016-01-26 /pmc/articles/PMC5068881/ /pubmed/26812041 http://dx.doi.org/10.1038/tp.2015.207 Text en Copyright © 2016 Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Original Article
Holmes, E A
Bonsall, M B
Hales, S A
Mitchell, H
Renner, F
Blackwell, S E
Watson, P
Goodwin, G M
Di Simplicio, M
Applications of time-series analysis to mood fluctuations in bipolar disorder to promote treatment innovation: a case series
title Applications of time-series analysis to mood fluctuations in bipolar disorder to promote treatment innovation: a case series
title_full Applications of time-series analysis to mood fluctuations in bipolar disorder to promote treatment innovation: a case series
title_fullStr Applications of time-series analysis to mood fluctuations in bipolar disorder to promote treatment innovation: a case series
title_full_unstemmed Applications of time-series analysis to mood fluctuations in bipolar disorder to promote treatment innovation: a case series
title_short Applications of time-series analysis to mood fluctuations in bipolar disorder to promote treatment innovation: a case series
title_sort applications of time-series analysis to mood fluctuations in bipolar disorder to promote treatment innovation: a case series
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5068881/
https://www.ncbi.nlm.nih.gov/pubmed/26812041
http://dx.doi.org/10.1038/tp.2015.207
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