On the Meaning of the “P Factor” in Symmetrical Bifactor Models of Psychopathology: Recommendations for Future Research From the Bifactor-(S−1) Perspective

Assessment ◽  
2021 ◽  
pp. 107319112110602
Author(s):  
Manuel Heinrich ◽  
Christian Geiser ◽  
Pavle Zagorscak ◽  
G. Leonard Burns ◽  
Johannes Bohn ◽  
...  
Keyword(s):  
Mental Disorders ◽  
Future Research ◽  
Specific Factor ◽  
General Factor ◽  
Modeling Framework ◽  
Factor Loadings ◽  
Negative Factor ◽  
Bifactor Models ◽  
Unexpected Findings ◽  
P Factor

Symmetrical bifactor models are frequently applied to diverse symptoms of psychopathology to identify a general P factor. This factor is assumed to mark shared liability across all psychopathology dimensions and mental disorders. Despite their popularity, however, symmetrical bifactor models of P often yield anomalous results, including but not limited to nonsignificant or negative specific factor variances and nonsignificant or negative factor loadings. To date, these anomalies have often been treated as nuisances to be explained away. In this article, we demonstrate why these anomalies alter the substantive meaning of P such that it (a) does not reflect general liability to psychopathology and (b) differs in meaning across studies. We then describe an alternative modeling framework, the bifactor-( S−1) approach. This method avoids anomalous results, provides a framework for explaining unexpected findings in published symmetrical bifactor studies, and yields a well-defined general factor that can be compared across studies when researchers hypothesize what construct they consider “transdiagnostically meaningful” and measure it directly. We present an empirical example to illustrate these points and provide concrete recommendations to help researchers decide for or against specific variants of bifactor structure.

scholarly journals On the Meaning of the General Factor of Psychopathology (“P-Factor”) in Symmetrical Bifactor Models

2020 ◽  
Author(s):  
Manuel Heinrich ◽  
Christian Geiser ◽  
Pavle Zagorscak ◽  
G. Leonard Burns ◽  
Johannes Bohn ◽  
...  
Keyword(s):  
Mental Disorders ◽  
Specific Factor ◽  
General Factor ◽  
Modeling Framework ◽  
Factor Loadings ◽  
Negative Factor ◽  
Bifactor Models ◽  
Unexpected Findings ◽  
P Factor

Symmetrical bifactor models are frequently applied to diverse symptoms of psychopathology to identify a general P factor. This factor is assumed to mark shared liability across psychopathology dimensions and mental disorders. Despite their popularity, however, symmetrical bifactor models often yield anomalous results, including but not limited to non-significant or negative specific factor variances and non-significant or negative factor loadings. To date, these anomalies have often been treated as nuisances to be explained away. In this paper, we demonstrate why these anomalies alter the substantive meaning of P such that it (1) does not reflect general liability to psychopathology and (2) differs in meaning across studies. We then describe an alternative modeling framework, the bifactor-(S − 1) approach. This approach avoids anomalous results, provides a framework for explaining unexpected findings in published symmetrical bifactor studies, and yields a general factor with well-defined meaning across studies. We present an empirical example to illustrate these points and provide concrete recommendations to help researchers decide for or against a specific variant of bifactor structures. In summary, bifactor-(S − 1) models provide an approach to answer questions posed in symmetrical bifactor models in a more comparable and replicable manner.

scholarly journals The p Factor and the n Factor: Associations Between the General Factors of Psychopathology and Neuroticism in Children

2019 ◽  
Author(s):  
Cassandra M Brandes ◽  
Kathrin Herzhoff ◽  
Avante J Smack ◽  
Jennifer L Tackett
Keyword(s):  
Mental Disorders ◽  
Age Groups ◽  
Negative Emotionality ◽  
General Factor ◽  
General Psychopathology ◽  
Bifactor Models ◽  
Specific Factors ◽  
Latent Dimension ◽  
P Factor ◽  
Internalizing And Externalizing

Research across age groups has consistently indicated that psychopathology has a general factor structure, such that there is a broad latent dimension (or p factor) capturing variance common to all mental disorders, as well as specific internalizing and externalizing factors. This research has found that the p factor overlaps substantially with trait negative emotionality (or neuroticism). However, less is known about the psychological substance of the specific factors of the general psychopathology model, or how lower-order facets of neuroticism may relate to each psychopathology factor. We investigated the structure of neuroticism and psychopathology, as well as associations between these domains in a sample of 695 pre-adolescent children using multi-method assessments. We found that both psychopathology and neuroticism may be well-characterized by bifactor models, and that there was substantial overlap between psychopathology (p) and neuroticism (n) general factors, as well as between specific factors (Internalizing with Fear, Externalizing with Irritability).

scholarly journals The p Factor and the n Factor: Associations Between the General Factors of Psychopathology and Neuroticism in Children

2019 ◽  
Vol 7 (6) ◽  
pp. 1266-1284 ◽  
Author(s):  
Cassandra M. Brandes ◽  
Kathrin Herzhoff ◽  
Avanté J. Smack ◽  
Jennifer L. Tackett
Keyword(s):  
Mental Disorders ◽  
Age Groups ◽  
Negative Emotionality ◽  
General Factor ◽  
General Psychopathology ◽  
Bifactor Models ◽  
Specific Factors ◽  
Latent Dimension ◽  
P Factor ◽  
Internalizing And Externalizing

Research across age groups has consistently indicated that psychopathology has a general factor structure such that a broad latent dimension (or p factor) captures variance common to all mental disorders as well as specific internalizing and externalizing factors. This research has found that the p factor overlaps substantially with trait negative emotionality (or neuroticism). However, less is known about the psychological substance of the specific factors of the general psychopathology model or how lower-order facets of neuroticism may relate to each psychopathology factor. We investigated the structure of neuroticism and psychopathology as well as associations between these domains using multimethod assessments in a sample of 695 preadolescent children. We found that both psychopathology and neuroticism may be well characterized by bifactor models and that there was substantial overlap between psychopathology (p) and neuroticism (n) general factors as well as between specific factors (Internalizing with Fear, Externalizing with Irritability).

scholarly journals Riskier Tests of the Validity of Bifactor Models of Psychopathology

2019 ◽  
Author(s):  
Ashley L. Watts ◽  
Holly Poore ◽  
Irwin Waldman
Keyword(s):  
Community Sample ◽  
General Factor ◽  
Symptom Dimensions ◽  
Bifactor Models ◽  
Specific Factors ◽  
Psychopathology Symptom ◽  
Using Data ◽  
P Factor ◽  
Correlated Factors ◽  
Additional Variance

We advanced several “riskier tests” of the validity of bifactor models of psychopathology, which included that the general and specific factors should be reliable and well-represented by their indicators, and that including a general factor should improve the correlated factor model’s external validity. We compared bifactor and correlated factors models using data from a community sample of youth (N=2498) whose parents provided ratings on psychopathology and external criteria (i.e., temperament, aggression, antisociality). Bifactor models tended to yield either general or specific factors that were unstable and difficult to interpret. The general factor appeared to reflect a differentially-weighted amalgam of psychopathology rather than a liability for psychopathology broadly construed. With rare exceptions, bifactor models did not explain additional variance in psychopathology symptom dimensions or external criteria compared with correlated factors models. Together, our findings call into question the validity of bifactor models of psychopathology, and the p-factor more broadly.

Revisiting the Structure of the Short Dark Triad

Assessment ◽  
2017 ◽  
Vol 26 (1) ◽  
pp. 3-16 ◽  
Author(s):  
Björn N. Persson ◽  
Petri J. Kajonius ◽  
Danilo Garcia
Keyword(s):  
Dark Triad ◽  
Specific Factor ◽  
General Factor ◽  
Confirmatory Factor Analyses ◽  
Factor Loadings ◽  
The Past ◽  
S Factor ◽  
Confirmatory Factor ◽  
Best Fitting ◽  
Fitting Model

In the past decade, extensive interest has been directed toward the Dark Triad (i.e., Machiavellianism, narcissism, and psychopathy), popularly assessed by the Short Dark Triad (SD3). Nevertheless, relatively little research has been conducted on the SD3’s factor structure. We investigated the SD3’s psychometric properties in three studies with three independent samples, using exploratory and confirmatory factor analyses ( N1 = 1,487; N2 = 17,740; N3 = 496). In all three studies, Machiavellianism and psychopathy items displayed large general factor loadings, and narcissism larger specific factor loadings. In subsequent studies, two- and three-factor models fitted the data similarly, with the best fitting model being a bifactor model with items from Machiavellianism and psychopathy modelled as one specific factor, and narcissism as a second specific factor. On this basis, we suggest that the SD3 does not seem to capture the different mental processes theorized to underlie the similar behaviors generated by Machiavellianism and psychopathy. Additionally, we recommend the use of a single SD3 composite score, and not subscale scores, as subscales contain small amounts of reliable variance beyond the general factor.

scholarly journals Factorial Invariance in Hierarchical Factor Models of Mental Disorders in African American and European American Youths

2019 ◽  
Author(s):  
Quanfa He ◽  
James Janford Li
Keyword(s):  
Mental Disorders ◽  
Factor Model ◽  
Factorial Invariance ◽  
European American ◽  
General Factor ◽  
Prevalence Rates ◽  
Bifactor Models ◽  
Best Fitting ◽  
Racial Ethnic ◽  
Three Factor

Background: There is converging and compelling evidence that mental disorders are more optimally conceptualized in a hierarchical framework that transcends traditional categorical boundaries. However, the majority of this evidence comes from studies that draw upon predominantly Caucasian populations. Whether the hierarchical conceptualization of mental disorders generalizes across racial-ethnic groups, including for African American (AA) youths, is unclear. This research is especially crucial in light of the observed racial-ethnic differences in the prevalence rates of several mental disorders. Methods: We tested multidimensional and bifactor models of 15 DSM-5 diagnoses and psychiatric traits in two groups, including AA (n=3,088) and European American (EA) (n=5,147) youths aged 8-21 from the Philadelphia Neurodevelopmental Cohort (PNC). We also conducted multigroup confirmatory factor analyses to test for factorial invariance between the best fitting AA and EA multidimensional and bifactor models. Results: In the multidimensional model tests, a three-factor model, specifying internalizing, externalizing, and thought dimensions, emerged as the best fitting model for AAs and EAs. In the bifactor model tests, a three-factor model (i.e., internalizing, externalizing, and thought dimensions) that also specified a general factor emerged as the optimal for both AAs and EAs. The general factor accounted for a significant proportion of the covariation between the secondary factors and the individual disorders and traits. Furthermore, both models were factorially invariant, indicating that there was no significant difference in the factor structure of mental disorders between AAs and EAs in PNC. Conclusions: This study provides evidence that the hierarchical factor structure of mental disorders may be racial-ethnically robust. This finding has implications for etiological and epidemiological studies focused on racial-ethnic subgroup comparisons, particularly with respect to identifying similarities and differences in prevalence rates or sociodemographic risk factors for mental disorders.

Modeling College and Career Readiness for Adolescents With and Without Disabilities: A Bifactor Approach

2017 ◽  
Vol 84 (2) ◽  
pp. 159-176 ◽  
Author(s):  
Allison Lombardi ◽  
Jennifer Freeman ◽  
Graham Rifenbark
Keyword(s):  
Latent Variable ◽  
Measurement Model ◽  
Career Readiness ◽  
Future Research ◽  
Specific Factor ◽  
College And Career Readiness ◽  
General Factor ◽  
College And Career ◽  
Mean Differences ◽  
Mind Set

Nonacademic skills related to college and career readiness (CCR) have become more prevalent in the literature as proposed conceptual models and frameworks, yet little empirical research exists in their support. We employed latent variable modeling to empirically test a previously proposed six-domain framework of CCR for adolescents with and without disabilities. Results support four specific factors of CCR: Academic Engagement, Critical Learning Processes, Mind-Set, and Transition Knowledge. Using a bifactor model, we confirmed one general factor (CCR) and one specific factor (Transition Knowledge), established measurement invariance on the basis of disability, and found latent mean differences between these groups; students without disabilities had greater overall CCR and transition knowledge. Findings support the use of a CCR measurement model with two potential factor scores in future research and practice and may inform efforts to measure CCR nonacademic skills.

scholarly journals Going “Up” to Move Forward: S-1 Bifactor Models and the Study of Neurocognitive Abilities in Psychopathology

2021 ◽  
Vol 18 (14) ◽  
pp. 7413
Author(s):  
Darren Haywood ◽  
Frank D. Baughman ◽  
Barbara A. Mullan ◽  
Karen R. Heslop
Keyword(s):  
Structural Models ◽  
General Factor ◽  
Neurocognitive Performance ◽  
Diagnostic Stability ◽  
Psychopathological Symptoms ◽  
Simulation Techniques ◽  
Wide Range ◽  
Bifactor Models ◽  
Specific Factors ◽  
P Factor

Recently, structural models of psychopathology, that address the diagnostic stability and comorbidity issues of the traditional nosological approach, have dominated much of the psychopathology literature. Structural approaches have given rise to the p-factor, which is claimed to reflect an individual’s propensity toward all common psychopathological symptoms. Neurocognitive abilities are argued to be important to the development and maintenance of a wide range of disorders, and have been suggested as an important driver of the p-factor. However, recent evidence argues against p being an interpretable substantive construct, limiting conclusions that can be drawn from associations between p, the specific factors of a psychopathology model, and neurocognitive abilities. Here, we argue for the use of the S-1 bifactor approach, where the general factor is defined by neurocognitive abilities, to explore the association between neurocognitive performance and a wide range of psychopathological symptoms. We use simulation techniques to give examples of how S-1 bifactor models can be used to examine this relationship, and how the results can be interpreted.

scholarly journals Misbegotten Methodologies and Forgotten Lessons from Tom Swift’s Electric Factor Analysis Machine: A Demonstration with Competing Structural Models of Psychopathology

2021 ◽  
Author(s):  
Ashley Lauren Greene ◽  
Ashley L. Watts ◽  
Miriam K. Forbes ◽  
Roman Kotov ◽  
Robert Krueger ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Model Misspecification ◽  
Theory Development ◽  
Structural Models ◽  
General Factor ◽  
Psychological Constructs ◽  
Methodological Choices ◽  
Bifactor Models ◽  
Specific Factors ◽  
P Factor

Confirmatory factor analysis (CFA) and its bifactor models are popular in empirical investigations of the factor structure of psychological constructs. CFA offers straightforward hypothesis testing but has notable pitfalls, such as the imposition of strict assumptions (i.e., simple structure) that obscure unmodeled complexity. Due to the limitations of bifactor CFAs, they have yielded anomalous results across samples and studies that suggest model misspecification (e.g., evaporating specific factors and unexpected loadings). We propose the use of exploratory factor analysis (EFA) to evaluate the structural validity of CFA solutions—either before or after the estimation of more restrictive CFA models—to (1) identify model misspecifications that may drive anomalous estimates and (2) confirm CFA models by examining whether hypothesized structures emerge with limited researcher input. We evaluated the degree to which predominant factor structures were invariant across contexts along the exploratory-confirmatory continuum and demonstrate how poor methodological choices can distort results and impede theory development. All models fit well, but there were numerous differences in replicability and substantive interpretability. Several similarities emerged between bifactor CFA and EFA models, including evidence of overextraction, the collapse of specific factors onto the general factor, and subsequent shifts in how the general factor was defined. We situate these methodological shortcomings within the broader literature on structural models of psychopathology, articulate implications for theories (such as the p-factor) that are borne out of factor analysis, outline several remedies for problems encountered when performing exploratory bifactor analysis, and propose alternative specifications for confirmatory bifactor models.

Going “Up” to Move Forward: S-1 Bifactor Models and the Study of Neurocognitive Abilities in Psychopathology

2021 ◽  
Author(s):  
Darren Haywood ◽  
Frank Baughman ◽  
Barbara Mullan ◽  
Karen R. Heslop
Keyword(s):  
Structural Models ◽  
General Factor ◽  
Diagnostic Stability ◽  
Psychopathological Symptoms ◽  
Simulation Techniques ◽  
Wide Range ◽  
Bifactor Models ◽  
P Factor ◽  
The Relationship

Recently, structural models of psychopathology, that address the diagnostic stability and comorbidity issues of the nosological approach, have dominated much of the literature. Structural approaches have given rise to the p factor, which is claimed to reflect an individual’s propensity toward all common psychopathological symptoms. Neurocognitive abilities are argued to be important to the development and maintenance of a wide range of disorders, and have between suggested as an important driver of the p factor. However, recent evidence argues against p being an interpretable substantive construct, limiting conclusions that can be drawn from associations between p and neurocognitive abilities. Here, we argue for the use of the S-1 bifactor approach, where the general factor is defined by neurocognitive abilities, to explore the association. We use simulation techniques to give examples of how S-1 bifactor models can be used to examine the relationship, and how the results can be interpreted.

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