Evidence map›Paper›PMID 38236494›Full record

ArticleClinical psychological science : a journal of the Association for Psychological Science2024

The general factor of psychopathology (p): Choosing among competing models and interpreting p.

Avshalom Caspi, Renate M Houts, Helen L Fisher, Andrea Danese, Terrie E Moffitt

Abstract read
In one paragraph

Article in Clinical psychological science : a journal of the Association for Psychological Science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

45 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Avshalom CaspiDepartment of Psychology & Neuroscience, Duke University.
Renate M HoutsDepartment of Psychology & Neuroscience, Duke University.
Helen L FisherSocial, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, & Neuroscience, King's College London, London, UK.
Andrea DaneseSocial, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, & Neuroscience, King's College London, London, UK.
Terrie E MoffittDepartment of Psychology & Neuroscience, Duke University.

Funding

Neuropsychological and genomic signatures of violence exposure in childhoodR01HD077482 · NICHD · DUKE UNIVERSITY · PI CASPI, AVSHALOM · 2013 to 2018
$2.8M
Comprehensive portrait of long-term cannabis users: Are they ready for old age?R01AG069939 · NIA · DUKE UNIVERSITY · PI MOFFITT, TERRIE E · 2021 to 2024
$1.3M
Medical Research Council MR/X010791/1Medical Research Council MR/X021149/1NIA NIH HHS R01 AG069939NICHD NIH HHS R01 HD077482
6 · The paper itself

Abstract

Over the past 10 years, the general factor of psychopathology, p, has attracted interest and scrutiny. We review the history of the idea that all mental disorders share something in common, p; how we arrived at this idea; and how it became conflated with a statistical representation, the Bi-Factor Model. We then leverage the Environmental Risk (E-Risk) longitudinal twin study to examine the properties and nomological network of different statistical representations of p. We find that p performed similarly regardless of how it was modelled, suggesting that if the sample and content are the same the resulting p factor will be similar. We suggest that the meaning of p is not to be found by dueling over statistical models but by conducting well-specified criterion-validation studies and developing new measurement approaches. We outline new directions to refresh research efforts to uncover what all mental disorders have in common.

Identifiers

PMID38236494
PMCPMC10794018

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Registered trials

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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.