ReviewPsychopathology2020
Moving beyond Ordinary Factor Analysis in Studies of Personality and Personality Disorder: A Computational Modeling Perspective.
Review in Psychopathology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Trait psychoticism is associated with greater intersubject neural dissimilarity during naturalistic social movie viewing.Scientific reports · 2026Article
- Internalizing-externalizing comorbidity and regional brain volumes in the ABCD study.Development and psychopathology · 2021Article
- RDoC and Psychopathology among Youth: Misplaced Assumptions and an Agenda for Future Research.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
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Almost all forms of psychopathology, including personality disorders, are arrived at through complex interactions among neurobiological vulnerabilities and environmental risk factors across development. Yet despite increasing recognition of etiological complexity, psychopathology research is still dominated by searches for large main effects causes. This derives in part from reliance on traditional inferential methods, including ordinary factor analysis, regression, ANCOVA, and other techniques that use statistical partialing to isolate unique effects. In principle, some of these methods can accommodate etiological complexity, yet as typically applied they are insensitive to interactive functional dependencies (modulating effects) among etiological influences. Here, we use our developmental model of antisocial and borderline traits to illustrate challenges faced when modeling complex etiological mechanisms of psychopathology. We then consider how computational models, which are rarely used in the personality disorders literature, remedy some of these challenges when combined with hierarchical Bayesian analysis.
Indexed as
Identifiers
What OpenQuestion holds
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.