Intraindividual phenotyping of depression in high-risk youth: An application of a multilevel hidden Markov model
Traditionally, depression phenotypes have been defined based on differences that distinguish between subgroups of individuals expressing distinct depressive symptoms often from cross-sectional data. Alternatively, depression phenotypes can be defined based on differences, differentiating between tra...
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Veröffentlicht in: | Development and psychopathology 2023-05, Vol.36 (3), p.1-1271 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Traditionally, depression phenotypes have been defined based on
differences that distinguish between subgroups of individuals expressing distinct depressive symptoms often from cross-sectional data. Alternatively, depression phenotypes can be defined based on
differences, differentiating between transitory states of distinct symptoms profiles that a person transitions into or out of over time. Such within-person phenotypic states are less examined, despite their potential significance for understanding and treating depression.
The current study used intensive longitudinal data of youths (
= 120) at risk for depression. Clinical interviews (at baseline, 4, 10, 16, and 22 months) yielded 90 weekly assessments. We applied a multilevel hidden Markov model to identify intraindividual phenotypes of weekly depressive symptoms for at-risk youth.
Three intraindividual phenotypes emerged: a low-depression state, an elevated-depression state, and a cognitive-physical-symptom state. Youth had a high probability of remaining in the same state over time. Furthermore, probabilities of transitioning from one state to another did not differ by age or ethnoracial minority status; girls were more likely than boys to transition from a low-depression state to either the elevated-depression state or the cognitive-physical symptom state. Finally, these intraindividual phenotypes and their dynamics were associated with comorbid externalizing symptoms.
Identifying these states as well as the transitions between them characterizes how symptoms of depression change over time and provide potential directions for intervention efforts. |
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ISSN: | 0954-5794 1469-2198 1469-2198 |
DOI: | 10.1017/S0954579423000500 |