BackgroundManic and depressive mood states in bipolar disorder (BD) may emerge from the non-linear relations between constantly changing mood symptoms exhibited as a complex dynamic system. Dynamic... Show moreBackgroundManic and depressive mood states in bipolar disorder (BD) may emerge from the non-linear relations between constantly changing mood symptoms exhibited as a complex dynamic system. Dynamic Time Warp (DTW) is an algorithm that may capture symptom interactions from panel data with sparse observations over time.MethodsThe Young Mania Rating Scale and Quick Inventory of Depressive Symptomatology were repeatedly assessed in 141 individuals with BD, with on average 5.5 assessments per subject every 3–6 months. Dynamic Time Warp calculated the distance between each of the 27 × 27 pairs of standardized symptom scores. The changing profile of standardized symptom scores of BD participants was analyzed in individual subjects, yielding symptom dimensions in aggregated group-level analyses. Using an asymmetric time-window, symptom changes that preceded other symptom changes (i.e., Granger causality) yielded a directed network.ResultsThe mean age of the BD participants was 40.1 (SD 13.5) years old, and 60% were female participants. Idiographic symptom networks were highly variable between subjects. Yet, nomothetic analyses showed five symptom dimensions: core (hypo)mania (6 items), dysphoric mania (5 items), lethargy (7 items), somatic/suicidality (6 items), and sleep (3 items). Symptoms of the “Lethargy” dimension showed the highest out-strength, and its changes preceded those of “somatic/suicidality,” while changes in “core (hypo)mania” preceded those of “dysphoric mania.”ConclusionDynamic Time Warp may help to capture meaningful BD symptom interactions from panel data with sparse observations. It may increase insight into the temporal dynamics of symptoms, as those with high out-strength (rather than high in-strength) could be promising targets for intervention. Show less
Hanssen, I.; Klooster, P. ten; Huijbers, M.; Bennekom, M.L. van; Boere, E.; Filali, E. el; ... ; Regeer, E. 2023
ObjectiveThis article describes the development and psychometric evaluation of the Manic Thought Inventory (MTI), a patient-driven self-report inventory to assess the presence of typical (hypo... Show moreObjectiveThis article describes the development and psychometric evaluation of the Manic Thought Inventory (MTI), a patient-driven self-report inventory to assess the presence of typical (hypo)manic cognitions. MethodsThe initial item pool was generated by patients with bipolar disorder (BD) type I and assessed for suitability by five psychiatrists specialized in treating BD. Study 1 describes the item analysis and exploratory factor structure of the MTI in a sample of 251 patients with BD type I. In study 2, the factor structure was validated with confirmatory factor analysis, and convergent and divergent validity were assessed in an independent sample of 201 patients with BD type I. ResultsStudy 1 resulted in a 50-item version of the MTI measuring one underlying factor. Study 2 confirmed the essentially unidimensional underlying construct in a 47-item version of the MTI. Internal consistency of the 47-item version of the MTI was excellent (alpha = 0.97). The MTI showed moderate to large positive correlations with other measures related to mania. It was not correlated with measures of depression. ConclusionThe MTI showed good psychometric properties and can be useful in research and clinical practice. Patients could use the MTI to select items that they recognize as being characteristic of their (hypo)manic episodes. By monitoring and challenging these items, the MTI could augment current psychological interventions for BD. Show less
Gaspersz, R.; Lamers, F.; Kent, J.; Beekman, A.; Smit, J.; Hemert, A. van; ... ; Penninx, B. 2016
