Evidence for Mood Instability in Patients With Bipolar Disorder: Applying Multilevel Hidden Markov Modeling to Intensive Longitudinal Ecological Momentary Assessment Data
Bipolar disorder (BD) is a chronic psychiatric condition characterized by large episodic changes in mood and energy. Recently, BD has been proposed to be conceptualized as chronic cyclical mood instability, as opposed to the traditional view of alternating discrete episodes with stable periods in-be...
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| Veröffentlicht in: | Journal of psychopathology and clinical science 2024-08, Vol.133 (6), p.456-468 |
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| creator | Mildiner Moraga, Sebastian Bos, Fionneke M. Doornbos, Bennard Bruggeman, Richard van der Krieke, Lian Snippe, Evelien Aarts, Emmeke |
| description | Bipolar disorder (BD) is a chronic psychiatric condition characterized by large episodic changes in mood and energy. Recently, BD has been proposed to be conceptualized as chronic cyclical mood instability, as opposed to the traditional view of alternating discrete episodes with stable periods in-between. Recognizing this mood instability may improve care and call for high-frequency measures coupled with advanced statistical models. To uncover empirically derived mood states, a multilevel hidden Markov model (HMM) was applied to 4-month ecological momentary assessment data in 20 patients with BD, yielding ∼9,820 assessments in total. Ecological momentary assessment data comprised self-report questionnaires (5 × daily) measuring manic and depressive constructs. Manic and depressive symptoms were also assessed weekly using the Altman Self-Rating Mania Scale and the Quick Inventory for Depressive Symptomatology Self-Report. Alignment between HMM-uncovered momentary mood states and weekly questionnaires was assessed with a multilevel linear model. HMM uncovered four mood states: neutral, elevated, mixed, and lowered, which aligned with weekly symptom scores. On average, patients remained |
| doi_str_mv | 10.1037/abn0000915 |
| format | Article |
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General Scientific SummaryThe article investigates bipolar disorder with advanced statistical methods and adds evidence challenging the traditional view of alternating discrete mood episodes with stable periods in-between. Instead, it suggests that chronic mood instability may be a significant aspect of bipolar disorder and calls for high-frequency assessments using advanced statistical models to better understand and improve care for individuals with the disorder.</description><identifier>ISSN: 2769-7541</identifier><identifier>ISSN: 2769-755X</identifier><identifier>EISSN: 2769-755X</identifier><identifier>DOI: 10.1037/abn0000915</identifier><identifier>PMID: 38829323</identifier><language>eng</language><publisher>United States: American Psychological Association</publisher><subject>Averages ; Bipolar Disorder ; Ecological momentary assessment ; Emotional Instability ; Emotional States ; Evaluation ; Female ; Human ; Linear analysis ; Male ; Mania ; Markov Models ; Mental depression ; Mixed states ; Questionnaires ; Self report ; Symptoms</subject><ispartof>Journal of psychopathology and clinical science, 2024-08, Vol.133 (6), p.456-468</ispartof><rights>2024 American Psychological Association</rights><rights>2024, American Psychological Association</rights><rights>Copyright American Psychological Association Aug 2024</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><orcidid>0000-0002-3003-7475 ; 0000-0002-3238-8471 ; 0000-0002-2432-7564 ; 0000-0001-6282-7394 ; 0000-0002-9630-0440 ; 0000-0002-5013-3501 ; 0000-0001-6745-5913</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902,30976</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38829323$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Wright, Aidan G. C</contributor><creatorcontrib>Mildiner Moraga, Sebastian</creatorcontrib><creatorcontrib>Bos, Fionneke M.</creatorcontrib><creatorcontrib>Doornbos, Bennard</creatorcontrib><creatorcontrib>Bruggeman, Richard</creatorcontrib><creatorcontrib>van der Krieke, Lian</creatorcontrib><creatorcontrib>Snippe, Evelien</creatorcontrib><creatorcontrib>Aarts, Emmeke</creatorcontrib><title>Evidence for Mood Instability in Patients With Bipolar Disorder: Applying Multilevel Hidden Markov Modeling to Intensive Longitudinal Ecological Momentary Assessment Data</title><title>Journal of psychopathology and clinical science</title><addtitle>J Psychopathol Clin Sci</addtitle><description>Bipolar disorder (BD) is a chronic psychiatric condition characterized by large episodic changes in mood and energy. Recently, BD has been proposed to be conceptualized as chronic cyclical mood instability, as opposed to the traditional view of alternating discrete episodes with stable periods in-between. Recognizing this mood instability may improve care and call for high-frequency measures coupled with advanced statistical models. To uncover empirically derived mood states, a multilevel hidden Markov model (HMM) was applied to 4-month ecological momentary assessment data in 20 patients with BD, yielding ∼9,820 assessments in total. Ecological momentary assessment data comprised self-report questionnaires (5 × daily) measuring manic and depressive constructs. Manic and depressive symptoms were also assessed weekly using the Altman Self-Rating Mania Scale and the Quick Inventory for Depressive Symptomatology Self-Report. Alignment between HMM-uncovered momentary mood states and weekly questionnaires was assessed with a multilevel linear model. HMM uncovered four mood states: neutral, elevated, mixed, and lowered, which aligned with weekly symptom scores. On average, patients remained <25 hr in one state. In almost half of the patients, mood instability was observed. Switching between mood states, three patterns were identified: patients switching predominantly between (a) neutral and lowered states, (b) neutral and elevated states, and (c) mixed, elevated, and lowered states. In all, elevated and lowered mood states were interspersed by mixed states. The results indicate that chronic mood instability is a key feature of BD, even in "relatively" euthymic periods. This should be considered in theoretical and clinical conceptualizations of the disorder.
General Scientific SummaryThe article investigates bipolar disorder with advanced statistical methods and adds evidence challenging the traditional view of alternating discrete mood episodes with stable periods in-between. Instead, it suggests that chronic mood instability may be a significant aspect of bipolar disorder and calls for high-frequency assessments using advanced statistical models to better understand and improve care for individuals with the disorder.</description><subject>Averages</subject><subject>Bipolar Disorder</subject><subject>Ecological momentary assessment</subject><subject>Emotional Instability</subject><subject>Emotional States</subject><subject>Evaluation</subject><subject>Female</subject><subject>Human</subject><subject>Linear analysis</subject><subject>Male</subject><subject>Mania</subject><subject>Markov Models</subject><subject>Mental depression</subject><subject>Mixed states</subject><subject>Questionnaires</subject><subject>Self report</subject><subject>Symptoms</subject><issn>2769-7541</issn><issn>2769-755X</issn><issn>2769-755X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>7QJ</sourceid><recordid>eNp90cuOFCEUBuCK0TiTcTY-gCFxY4ytUFBc3LUzPZekO7rQ6I5QQLWMNJRAddKv5FNKpccxcSEbDsmXHzinaZ4j-BZBzN6pPsC6BOoeNacto2LBuu7b44eaoJPmPOe7alqGCUf8aXOCOW8FbvFp82u1d8YGbcEQE9jEaMBtyEX1zrtyAC6AT6o4G0oGX135Dj64MXqVwKXLMRmb3oPlOPqDC1uwmXxx3u6tBzfO1FCwUelH3NdUY_0sSqzhxYbs9hasY9i6MhkXlAcrHX3cOl3LTdzV61Q6gGXONuf5BC5VUc-aJ4Py2Z7f72fNl6vV54ubxfrj9e3Fcr1QGIuyoNwgaDqB2ID6lguBSEs6wrCGRCPcQ2pUyzSnaugw5arvieCMESgURRRzfNa8OuaOKf6cbC5y57K23qtg45QlhpQgggQnlb78h97FKdUPzUq0BNYX4f8ripmA1VX1-qh0ijknO8gxuV3tg0RQzqOWf0dd8Yv7yKnfWfNA_wy2gjdHoEYlx3zQKhWnvc16Sql2dA6TCGNJJeko_g2e6rOP</recordid><startdate>20240801</startdate><enddate>20240801</enddate><creator>Mildiner Moraga, Sebastian</creator><creator>Bos, Fionneke M.</creator><creator>Doornbos, Bennard</creator><creator>Bruggeman, Richard</creator><creator>van der Krieke, Lian</creator><creator>Snippe, Evelien</creator><creator>Aarts, Emmeke</creator><general>American Psychological Association</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7RZ</scope><scope>PSYQQ</scope><scope>7QJ</scope><scope>K7.</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-3003-7475</orcidid><orcidid>https://orcid.org/0000-0002-3238-8471</orcidid><orcidid>https://orcid.org/0000-0002-2432-7564</orcidid><orcidid>https://orcid.org/0000-0001-6282-7394</orcidid><orcidid>https://orcid.org/0000-0002-9630-0440</orcidid><orcidid>https://orcid.org/0000-0002-5013-3501</orcidid><orcidid>https://orcid.org/0000-0001-6745-5913</orcidid></search><sort><creationdate>20240801</creationdate><title>Evidence for Mood Instability in Patients With Bipolar Disorder: Applying Multilevel Hidden Markov Modeling to Intensive Longitudinal Ecological Momentary Assessment Data</title><author>Mildiner Moraga, Sebastian ; Bos, Fionneke M. ; Doornbos, Bennard ; Bruggeman, Richard ; van der Krieke, Lian ; Snippe, Evelien ; Aarts, Emmeke</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a339t-68d10d5917f1b289914245473c04c13b06da27c86af5368abb49877409a616383</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Averages</topic><topic>Bipolar Disorder</topic><topic>Ecological momentary assessment</topic><topic>Emotional Instability</topic><topic>Emotional States</topic><topic>Evaluation</topic><topic>Female</topic><topic>Human</topic><topic>Linear analysis</topic><topic>Male</topic><topic>Mania</topic><topic>Markov Models</topic><topic>Mental depression</topic><topic>Mixed states</topic><topic>Questionnaires</topic><topic>Self report</topic><topic>Symptoms</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Mildiner Moraga, Sebastian</creatorcontrib><creatorcontrib>Bos, Fionneke M.</creatorcontrib><creatorcontrib>Doornbos, Bennard</creatorcontrib><creatorcontrib>Bruggeman, Richard</creatorcontrib><creatorcontrib>van der Krieke, Lian</creatorcontrib><creatorcontrib>Snippe, Evelien</creatorcontrib><creatorcontrib>Aarts, Emmeke</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>APA PsycArticles®</collection><collection>ProQuest One Psychology</collection><collection>Applied Social Sciences Index & Abstracts (ASSIA)</collection><collection>ProQuest Criminal Justice (Alumni)</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of psychopathology and clinical science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Mildiner Moraga, Sebastian</au><au>Bos, Fionneke M.</au><au>Doornbos, Bennard</au><au>Bruggeman, Richard</au><au>van der Krieke, Lian</au><au>Snippe, Evelien</au><au>Aarts, Emmeke</au><au>Wright, Aidan G. C</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Evidence for Mood Instability in Patients With Bipolar Disorder: Applying Multilevel Hidden Markov Modeling to Intensive Longitudinal Ecological Momentary Assessment Data</atitle><jtitle>Journal of psychopathology and clinical science</jtitle><addtitle>J Psychopathol Clin Sci</addtitle><date>2024-08-01</date><risdate>2024</risdate><volume>133</volume><issue>6</issue><spage>456</spage><epage>468</epage><pages>456-468</pages><issn>2769-7541</issn><issn>2769-755X</issn><eissn>2769-755X</eissn><abstract>Bipolar disorder (BD) is a chronic psychiatric condition characterized by large episodic changes in mood and energy. Recently, BD has been proposed to be conceptualized as chronic cyclical mood instability, as opposed to the traditional view of alternating discrete episodes with stable periods in-between. Recognizing this mood instability may improve care and call for high-frequency measures coupled with advanced statistical models. To uncover empirically derived mood states, a multilevel hidden Markov model (HMM) was applied to 4-month ecological momentary assessment data in 20 patients with BD, yielding ∼9,820 assessments in total. Ecological momentary assessment data comprised self-report questionnaires (5 × daily) measuring manic and depressive constructs. Manic and depressive symptoms were also assessed weekly using the Altman Self-Rating Mania Scale and the Quick Inventory for Depressive Symptomatology Self-Report. Alignment between HMM-uncovered momentary mood states and weekly questionnaires was assessed with a multilevel linear model. HMM uncovered four mood states: neutral, elevated, mixed, and lowered, which aligned with weekly symptom scores. On average, patients remained <25 hr in one state. In almost half of the patients, mood instability was observed. Switching between mood states, three patterns were identified: patients switching predominantly between (a) neutral and lowered states, (b) neutral and elevated states, and (c) mixed, elevated, and lowered states. In all, elevated and lowered mood states were interspersed by mixed states. The results indicate that chronic mood instability is a key feature of BD, even in "relatively" euthymic periods. This should be considered in theoretical and clinical conceptualizations of the disorder.
General Scientific SummaryThe article investigates bipolar disorder with advanced statistical methods and adds evidence challenging the traditional view of alternating discrete mood episodes with stable periods in-between. Instead, it suggests that chronic mood instability may be a significant aspect of bipolar disorder and calls for high-frequency assessments using advanced statistical models to better understand and improve care for individuals with the disorder.</abstract><cop>United States</cop><pub>American Psychological Association</pub><pmid>38829323</pmid><doi>10.1037/abn0000915</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0002-3003-7475</orcidid><orcidid>https://orcid.org/0000-0002-3238-8471</orcidid><orcidid>https://orcid.org/0000-0002-2432-7564</orcidid><orcidid>https://orcid.org/0000-0001-6282-7394</orcidid><orcidid>https://orcid.org/0000-0002-9630-0440</orcidid><orcidid>https://orcid.org/0000-0002-5013-3501</orcidid><orcidid>https://orcid.org/0000-0001-6745-5913</orcidid></addata></record> |
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| ispartof | Journal of psychopathology and clinical science, 2024-08, Vol.133 (6), p.456-468 |
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| subjects | Averages Bipolar Disorder Ecological momentary assessment Emotional Instability Emotional States Evaluation Female Human Linear analysis Male Mania Markov Models Mental depression Mixed states Questionnaires Self report Symptoms |
| title | Evidence for Mood Instability in Patients With Bipolar Disorder: Applying Multilevel Hidden Markov Modeling to Intensive Longitudinal Ecological Momentary Assessment Data |
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