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Intraindividual phenotyping of depression in high-risk youth: An application of a multilevel hidden Markov model.

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BACKGROUND Traditionally, depression phenotypes have been defined based on interindividual differences that distinguish between subgroups of individuals expressing distinct depressive symptoms often from cross-sectional data. Alternatively, depression phenotypes can be… Click to show full abstract

BACKGROUND Traditionally, depression phenotypes have been defined based on interindividual differences that distinguish between subgroups of individuals expressing distinct depressive symptoms often from cross-sectional data. Alternatively, depression phenotypes can be defined based on intraindividual 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. METHODS The current study used intensive longitudinal data of youths (N = 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. RESULTS 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. CONCLUSION 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.

Keywords: youth; state; hidden markov; markov model; depression; multilevel hidden

Journal Title: Development and psychopathology
Year Published: 2023

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