BACKGROUND: Instruments that are intended to measure change over time need to emphasize sensitivity to change as a central property. The aims of this report are to test whether the MOODS-SR, a measure of mood spectrum symptomatology, is sensitive to changes during acute and continuation treatment of depression and whether residual mood spectrum symptoms predict relapse in the subsequent 6 months. METHODS: The study sample includes 316 patients with nonpsychotic depression participating in the protocol 'Depression: the search for treatment-relevant phenotypes'. Patients were initially randomized to selective serotonin reuptake inhibitors or interpersonal psychotherapy and then treated for 9 months using an algorithm-based protocol. Measures of mood symptomatology included the self-report version of the structured clinical interview for mood spectrum (MOODS-SR), the Quick Inventory for Depressive Symptomatology and the Hamilton Rating Scale for Depression. RESULTS: Repeated-measures ANOVA indicates that during the acute phase MOODS scores decrease significantly from baseline to weeks 6 and 12. This decrease was significantly different (p < 0.001) between those who remitted and those who did not remit on the depressive, the rhythmicity component and the total score. Nonrelapsing subjects had stable scores across the continuation phase, while among relapsing subjects, a significant increase was found in the depressive component (p < 0.001), the rhythmicity component (p = 0.024) and the total score (p < 0.001), at 2 months, followed by a decrease from 2 to 6 months. Scores on the depressive component at the entry into continuation predicted relapse in the subsequent 6 months. CONCLUSIONS: Our findings suggest that the MOODS-SR is sensitive to change in depression status and may help the clinician to detect symptoms and signs not considered by established symptom severity scales.
Miniati, M., Rucci, P., Frank, E., Oppo, A., Kupfer, D.J., Fagiolini, A., et al. (2009). Sensitivity to Change and Predictive Validity of the MOODS-SR Questionnaire, Last-month Version. PSYCHOTHERAPY AND PSYCHOSOMATICS, 78(2), 116-124 [10.1159/000201937].
Sensitivity to Change and Predictive Validity of the MOODS-SR Questionnaire, Last-month Version
FAGIOLINI, A.;
2009-01-01
Abstract
BACKGROUND: Instruments that are intended to measure change over time need to emphasize sensitivity to change as a central property. The aims of this report are to test whether the MOODS-SR, a measure of mood spectrum symptomatology, is sensitive to changes during acute and continuation treatment of depression and whether residual mood spectrum symptoms predict relapse in the subsequent 6 months. METHODS: The study sample includes 316 patients with nonpsychotic depression participating in the protocol 'Depression: the search for treatment-relevant phenotypes'. Patients were initially randomized to selective serotonin reuptake inhibitors or interpersonal psychotherapy and then treated for 9 months using an algorithm-based protocol. Measures of mood symptomatology included the self-report version of the structured clinical interview for mood spectrum (MOODS-SR), the Quick Inventory for Depressive Symptomatology and the Hamilton Rating Scale for Depression. RESULTS: Repeated-measures ANOVA indicates that during the acute phase MOODS scores decrease significantly from baseline to weeks 6 and 12. This decrease was significantly different (p < 0.001) between those who remitted and those who did not remit on the depressive, the rhythmicity component and the total score. Nonrelapsing subjects had stable scores across the continuation phase, while among relapsing subjects, a significant increase was found in the depressive component (p < 0.001), the rhythmicity component (p = 0.024) and the total score (p < 0.001), at 2 months, followed by a decrease from 2 to 6 months. Scores on the depressive component at the entry into continuation predicted relapse in the subsequent 6 months. CONCLUSIONS: Our findings suggest that the MOODS-SR is sensitive to change in depression status and may help the clinician to detect symptoms and signs not considered by established symptom severity scales.File | Dimensione | Formato | |
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https://hdl.handle.net/11365/26838
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