ArticleDevelopment and psychopathology2023
Intraindividual phenotyping of depression in high-risk youth: An application of a multilevel hidden Markov model.
Article in Development and psychopathology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
2 citing papers in PubMed, 5 citations in OpenAlex.
- Ambulatory physiological state dynamics predict proximal behavioral markers of affect regulation in everyday life.Journal of psychopathology and clinical science · 2025Article
- Uncovering Social States in Healthy and Clinical Populations Using Digital Phenotyping and Hidden Markov Models: Observational Study.Journal of medical Internet research · 2025Observational
Corrections and comments
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Authors and funding
7 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundTraditionally, depression phenotypes have been defined based on
methodsThe current study used intensive longitudinal data of youths (
resultsThree 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.
conclusionIdentifying 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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.