ReviewBehaviour research and therapy2019
A choose your own adventure story: Conceptualizing depression in children and adolescents from traditional DSM and alternative latent dimensional approaches.
Review in Behaviour research and therapy, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses that pooled it.
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
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Effects of mind-body therapies on depression among adolescents: a systematic review and network meta-analysis.Frontiers in public health · 2024Pooled it
- Depression and episodic memory across the adult lifespan: A meta-analytic review.Psychological bulletin · 2021Pooled it
- Evaluating a hierarchical structural model of psychopathology symptoms across pregnancy and the postpartum period.Journal of psychopathology and clinical science · 2026Article
- The Relationship Between Mental Health Problems and Systemic Family Dynamics Among High School and University Students in Shaanxi Province, China.International journal of public health · 2021Article
- Appropriate Use of Bifactor Analysis in Psychopathology Research: Appreciating Benefits and Limitations.Biological psychiatry · 2020Review
- The breadth and potency of transdiagnostic cognitive risks for psychopathology in youth.Journal of consulting and clinical psychology · 2020Article
- Separating Within-Person from Between-Person Effects in the Longitudinal Co-Occurrence of Depression and Different Anxiety Syndromes in Youth.Journal of research in personality · 2019Article
- Maternal Depressive Symptoms Predict General Liability in Child Psychopathology.Journal of clinical child and adolescent psychology : the official journal for the Society of Clinical Child and Adolescent Psychology, American Psychological Association, Division 53Article
Corrections and comments
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Authors and funding
1 author.
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Abstract
For the past several decades, the phenomenon of depression largely has been defined, classified, and thus assessed and analyzed, according to criteria based on the Diagnostic and Statistical Manual (now DSM5). A substantial body of knowledge on epidemiology, course, risk factors, correlates, consequences, assessment, and intervention for youth depression is based on this classical nosological approach to conceptualizing depression. Yet, recent structural and classification approaches, such as latent dimensional bifactor models (e.g., P factor model; Caspi et al., 2014) and hierarchical organizations (e.g., HiTOP; Kotov, Waszczuk, Krueger, Forbes, & Watson, 2017), have been proposed and supported as alternative options to characterize features of depression. This paper considers conceptualizations of depression among youth with a particular focus on validity: how important clinical outcomes and risks (genetic, neural, temperament, early pubertal timing, stress, and cognitive) relate to depression when ascertained via traditional DSM-defined depression versus more recent latent dimensional model approaches. The construct validity of depression, in terms of associations within respective nomological networks, varies by depression conceptualization. Clinical scientists and applied practitioners need to clearly think through the nature of what depression is and how the latent construct is conceptualized and measured. Conclusions reached for research, teaching, and evidence-based clinical work are affected and may not be the same across different conceptual and nosological organizational schemes.
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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.