<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Bos FM</submitter><funding>European Research Council</funding><funding>rob giel research center</funding><funding>ZonMw</funding><pagination>12</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC8994809</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>10(1)</volume><pubmed_abstract>&lt;h4>Background&lt;/h4>In bipolar disorder treatment, accurate episode prediction is paramount but remains difficult. A novel idiographic approach to prediction is to monitor generic early warning signals (EWS), which may manifest in symptom dynamics. EWS could thus form personalized alerts in clinical care. The present study investigated whether EWS can anticipate manic and depressive transitions in individual patients with bipolar disorder.&lt;h4>Methods&lt;/h4>Twenty bipolar type I/II patients (with ≥ 2 episodes in the previous year) participated in ecological momentary assessment (EMA), completing five questionnaires a day for four months (Mean = 491 observations per person). Transitions were determined by weekly completed questionnaires on depressive (Quick Inventory for Depressive Symptomatolo</pubmed_abstract><journal>International journal of bipolar disorders</journal><pubmed_title>Anticipating manic and depressive transitions in patients with bipolar disorder using early warning signals.</pubmed_title><pmcid>PMC8994809</pmcid><funding_grant_id>681466</funding_grant_id><funding_grant_id>451001029</funding_grant_id><pubmed_authors>Bos FM</pubmed_authors><pubmed_authors>George SV</pubmed_authors><pubmed_authors>Snippe E</pubmed_authors><pubmed_authors>Schreuder MJ</pubmed_authors><pubmed_authors>Haarman BCM</pubmed_authors><pubmed_authors>Doornbos B</pubmed_authors><pubmed_authors>van der Krieke L</pubmed_authors><pubmed_authors>Wichers M</pubmed_authors><pubmed_authors>Bruggeman R</pubmed_authors></additional><is_claimable>false</is_claimable><name>Anticipating manic and depressive transitions in patients with bipolar disorder using early warning signals.</name><description>&lt;h4>Background&lt;/h4>In bipolar disorder treatment, accurate episode prediction is paramount but remains difficult. A novel idiographic approach to prediction is to monitor generic early warning signals (EWS), which may manifest in symptom dynamics. EWS could thus form personalized alerts in clinical care. The present study investigated whether EWS can anticipate manic and depressive transitions in individual patients with bipolar disorder.&lt;h4>Methods&lt;/h4>Twenty bipolar type I/II patients (with ≥ 2 episodes in the previous year) participated in ecological momentary assessment (EMA), completing five questionnaires a day for four months (Mean = 491 observations per person). Transitions were determined by weekly completed questionnaires on depressive (Quick Inventory for Depressive Symptomatolo</description><dates><release>2022-01-01T00:00:00Z</release><publication>2022 Apr</publication><modification>2025-04-26T18:36:57.793Z</modification><creation>2025-04-06T15:49:08.204Z</creation></dates><accession>S-EPMC8994809</accession><cross_references><pubmed>35397076</pubmed><doi>10.1186/s40345-022-00258-4</doi></cross_references></HashMap>