General Factors of Psychopathology,Personality,and Personality Disorder: Across Domain Comparisons

Abstract

Three separate and distinct literatures exist investigating general factors of psychopathology (p factor), personality (general factor of personality, GFP), and personality disorder (g-PD). Surprisingly, there has been little to no investigation regarding the convergence of these three distinct general factors. In the present investigation, two studies were conducted examining the convergence of the p factor, GFP, and g-PD. In Study 1, a combined model extracting all three factors from self-report data simultaneously found high convergence. The findings for the g-PD and GFP were replicated in Study 2 using multimethod data, wherein the GFP and the g-PD were extracted from a community sample of 1,630 older adults and correlated with an index of maladaptivity. The present findings support the position that general factors of psychopathology, personality disorder, and personality are likely to entail a common individual differences continuum, which may impact on how these general factors are to be understood.

Keywords

dimensional vs. categorical individual differences personality personality disorder psychopathology

There has been a recent surge in the study of general factors of psychopathology (Caspi et al., 2014; Lahey et al., 2012; Lahey, Krueger, Rathouz, Waldman, & Zald, 2017), personality (Rushton & Irwing, 2011), and personality disorder (PD) (Jahng et al., 2011; Wright, Hopwood, Skodol, & Morey, 2016) but, to date, no apparent consideration of their potential convergence and the implications of any such convergence. Currently, three largely independent literatures exist.

It is also noteworthy that the interpretations of the general factors are quite different across these three domains of study. Advocates of a substantive understanding of the general factor of personality (GFP) have conceptualized it as a fundamental domain of social effectiveness (Rushton & Irwing, 2011; van der Linden et al., 2017). Musek (2007) provided the initial impetus for the GFP. He interpreted it as a substantive factor representing “positive versus negative aspects of personality . . . emotionality . . . motivation . . . well-being . . . and self-esteem” (p. 1228).

The GFP has been extracted from multiple measures and multiple models of personality (particularly though the five-factor model [FFM]), explaining large amounts of variance in exploratory factor analysis (EFA) and displaying good fit indices in confirmatory factor analysis (CFA) (Loehlin, 2012; Rushton & Irwing, 2011). However, the GFP has also met considerable criticism (Hopwood, Wright, & Donnellan, 2011; Revelle & Wilt, 2013). One particular concern is that the GFP may not in fact have any substantive meaning. Petterssen, Turkheimer, Horn, and Menatti (2012), for example, suggested that the GFP arises from an evaluation bias, comparable to social desirability identified years ago (Edwards, 1953). They point out compellingly that items that have opposite meanings will load quite similarly on the GFP (e.g., the items “sluggish” and “manic” both loaded positively). Because items with opposite meanings should not be endorsed by the same persons, they have suggested that the GFP likely represents a tendency for persons to answer questions with an evaluative bias (e.g., a disposition to answer in a socially desirable or undesirable manner, irrespective of the item’s content).

The literature concerning the general factor of personality disorder (g-PD) is much smaller than that of the GFP and considerably less contentious, albeit perhaps it warrants more skeptical consideration. Jahng et al. (2011) examined a bifactor model of PD criteria and substance abuse. They struggled, though, to understand what the g-PD might be substantively. They acknowledged that it might reflect negative affectivity or level of insight but concluded instead that it represented a level of interpersonal dysfunction. “Although we cannot specify exactly the nature of this general personality disorder factor, one that clearly drives most of the positive association we see between PDs and substance dependence, our results seem most consistent with characterizing this factor as [a level of] interpersonal dysfunction” (Jahng et al., 2011, p. 666).

Sharp and colleagues (2015) also found evidence of a g-PD in an exploratory bifactor analysis (EBFA) of the diagnostic criteria for six PDs. They noted that all the borderline personality disorder (BPD) criteria loaded solely on the g-PD factor and therefore suggested that the g-PD factor was a substantive representation of Criterion A in the Section III Alternative Model of Personality Disorders in the 5th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM–5; American Psychiatric Association, 2013). “Although we do not yet know the exact nature of the general factor, to stimulate further research, we speculate on some intriguing interpretative possibilities. . . . One answer may lie in Criterion A of the new DSM-5-III General Criteria of Personality Disorder” (Sharp et al., 2015, p. 394). Criterion A concerns deficits in the sense of self and interpersonal relatedness that are considered, in theory, to be central to all PD (Bender, Morey, & Skodol, 2011). “BPD is unique in that impairment in the ability to maintain and use benign and coherent internal images of self and others are integrated into one disorder” (Sharp et al., 2015, p. 394).

Wright and colleagues (2016) reached the same conclusion when considering the results of a bifactor analysis of the covariation among the criteria for all 10 PDs. They, too, found that the BPD criteria loaded uniquely on the g-PD factor. Wright et al. (2016) again acknowledged that “the core makeup of the general factor remains . . . ambiguous” (p. 1129), but consistent with Sharp et al. (2015), they suggested that “one possible interpretation is that it reflects borderline personality organization (Kernberg, 1984), with core impairments involving maladaptive self and other representations and identity formation” (p. 1129).

With respect to the general factor of psychopathology, Lahey et al. (2012) again used bifactor analysis. Lahey et al. (2012) emphasized that the p factor had a strong relationship with a variety of negative life outcomes and acknowledged at least four alternative explanations for its existence. They suggested that it might represent an implicit theory of psychopathology held by the participants, but they rejected this because it would seem doubtful that participants would so uniformly align all forms of psychopathology. They also considered that it might be an evaluative bias, as suggested by Pettersson et al. (2012) for the GFP, or simply reflect a common underlying personality disposition, such as neuroticism. However, they largely concluded that it reflected “etiologic factors that are shared by all mental disorders” (Lahey et al., 2012, p. 976).

Caspi and colleagues (2014) similarly examined a bifactor model with a p factor and two specific internalizing and externalizing factors. Caspi and colleagues again reported that the p factor was strongly related to a variety of negative life outcomes. Caspi et al. (2014), though, posed the question “Is p merely a statistical reductio ad absurdum or is it real and meaningful?” (p. 132). They forthrightly acknowledged, “We do not know yet” (p. 132), but were clearly on the side of a substantive meaning. On the other hand, they did not characterize or conceptualize the p factor any more specifically than suggesting that it “summarized individuals’ propensity to develop any and all forms of common psychopathology” (p. 131).

There indeed appears to be strong evidence that variance in personality, personality pathology, and psychopathology can be explained by general factors (referred to here as the GFP, g-PD, and the p factor, respectively). No study, however, has yet explored whether these three general factors are convergent with one another. The current investigation explores this relationship in two studies. The first study extracts and compares the general factors for each of the three domains. The second study seeks to replicate the Study 1 findings in a second sample and extend the literature by using multimethod data and examining associations with external criteria but is confined to markers of the GFP and g-PD only.

Study 1

Method

In the first study, persons who were currently or had been in mental health treatment were recruited for participation from the United States via Mechanical Turk (MTurk). The questionnaire battery was administered online and took 1.5 hr to complete. Participants were compensated $1.50 for their time. Participants were on average 36.3 years old (SD = 11.7 years) and were 65% female. Racial and ethnic backgrounds consisted of 80% White, 9% Black/African American, 6% Hispanic/Latino, 3% Asian, 1% American Indian or Alaskan Native, and 1% other. Thirty-eight percent were currently in mental health treatment, 11% in the past 1 month, 23% in the past 1 year, 13% in the past 5 years, 8% in the past 10 years, and 7% outside the past 10 years. Fifty-three percent were currently taking psychiatric medications. Eighty-five percent had been on psychiatric medications in the past. Thirty-three persons were excluded from the data set because of non–content-based responding (scale described below), for a final sample size of N = 474. The study was approved by the local institutional review board.

Measures

The Supplemental Material available online provides a complete list and further description of all the measures that were administered. Participants completed 16 scales to assess different forms of psychopathology consistent with prior p factor studies, including measures of psychoticism, somatization, depression, hostility, phobia, obsessive-compulsive, anxiety, fear, paranoia, alcohol usage, cannabis usage, drug abuse, antisocial behaviors, nicotine dependence, mania, and delusions. Internal consistency values were above .84 on 15 of the scales.

Participants also completed two alternative measures of the FFM of general personality used in the GFP analyses. For one measure, coefficient α ranged from .84 (Openness) to .92 (Neuroticism), with a median of .89. For the second measure, coefficient α ranged from .82 (Agreeableness) to .87 (Neuroticism).

Participants also completed two alternative measures of maladaptive personality used in the g-PD analyses. For one, coefficient α ranged from .93 (Detachment) to .97 (Eccentricity). For the other, coefficient α ranged from .69 (Antagonism) to .77 (Disinhibition).

Finally, five items were included throughout the questionnaire battery to assess for noncontent responding carelessness (e.g., “I have used a computer in the past two years” [keyed negatively]). Participants with a score of 12+ were eliminated from the data set (n = 33).

Results

Structural equation model analyses were completed in R statistical software (R Core Team, 2013; Rosseel, 2012). Bifactor models were used to maintain consistency with the prior general factor studies, but bifactor models should be applied with caution and have been criticized for “overfitting” data (Bonifay, Lane, & Reise, 2017). Thus, we also calculated the omega hierarchical statistic for the general factors (ω_h; Zinbarg, Revelle, Yovel, & Li, 2005), examined criterion validity (in Study 2), and tested models in which the general factors were extracted using second-order hierarchical and single-factor estimation methods. Absolute measures of model fit—root-mean-square error of approximation (RMSEA) and standardized root-mean-square residual (SRMR)—were given preference over relative indices of model fit—Tucker-Lewis index (TLI) and comparative-fit index (CFI)—because of the large number of indicators in the models (Kenny & McCoach, 2003). Descriptive statistics and intercorrelations for the psychopathology, personality, and PD scales are provided in the Supplemental Material.

Figure 1 displays a full model of three general factors of psychopathology, personality, and PD, with correlations specified between them. The fit indices for the model were less than adequate (Kline, 2015): RMSEA = .090 (90% confidence interval, or CI = [.088, .092]), and SRMR = .135 (CFI = .631), χ²(2,344) = 11,337.201, Akaike information criterion (AIC) = 183,349.588, Bayesian information criterion (BIC) = 184,527.210. They were also less than adequate for second-order hierarchical and single-factor versions of the model, details of which are provided in the Supplemental Material. General factor saturation was higher for the p factor (ω_h = .89) and the g-PD (ω_h = .86) and relatively lower for the GFP (ω_h = .69). The correlation between the p factor and g-PD was r = .92 (SE = .02, p < .001), the correlation between the p factor and the GFP was r = –.70 (SE = .05, p < .001), and the correlation between g-PD and the GFP was r = –.90 (SE = .04, p < .001). The results of this model clearly indicated that the general factors were highly correlated. However, the model fit was less than adequate, and the model was therefore respecified.

Fig. 1.

Study 1 Combined Three-Domain Model of Psychopathology, Personality, and Personality Disorder. A = agreeableness; ALC = Alcohol Use Disorders Identification Test; ANT = antagonism; ANX = Brief Symptom Inventory (BSI) Anxiety; B = Big Five Inventory; C = conscientiousness; DEL = Peters et al. Delusions Inventory; DEP = BSI Depression; DET = detachment; DIS = disinhibition; DRG = Drug Abuse Screening Test; E = extraversion; EXT = externalizing; FD = Five-Factor Form Detachment; FEAR = Fear Questionnaire; FN = Five-Factor Form Neuroticism; FP = Five-Factor Form Openness; FS = Five-Factor Form Disinhibition; FT = Five-Factor Form Antagonism; GFP = general factor of personality; G-PD = general factor of personality disorder; HOS = BSI Hostility; INT = internalizing; MAN = BSI Mania; MAP = Multi-Source Assessment of Personality Pathology Antisocial scale; N = neuroticism; NEG = negative affect; O = openness; OBC = obsessive-compulsive; p = p factor of psychopathology; PAR = BSI Paranoia; PHO = BSI Phobia; PSY = psychoticism; SDS = Severity of Dependence Scale; SMK = Fagerstrom Test for Nicotine Dependence; SOM = BSI Somatization. Double-sided arrows represent a correlation, and single-sided arrows represent regression.

An additional model was constructed to examine a possible better fit. The GFP and the g-PD were combined, consistent with the current understanding of the DSM–5 maladaptive trait model (American Psychological Association, 2013). Because of high overlap, the negative affectivity/neuroticism and internalizing indicators were also combined (i.e., specified to load on the same specific factor). Further, domain-level personality scores were used as indicators to promote model parsimony. This model figure can be seen in the Supplemental Material. The fit indices for the model were RMSEA = .082 (90% CI = [.079, .085]), SRMR = .070 (CFI = .852), χ²(548) = 2,287.044, p < .001, AIC = 106,374.187, BIC = 107,015.013, which met absolute fit index standards for acceptable fit. General factor saturation for the p factor was ω_h =.89 and for the GFP/g-PD factor was ω_h =.70. The correlation between the combined GFP/g-PD factor and the p factor was r = –.90 (SE = .017, p < .001). All but one indicator loaded strongly on the p factor. The GFP/g-PD factor was largely defined by high neuroticism and low agreeableness and conscientiousness. Full loadings for this model are displayed in the Supplemental Material.

Study 2

Method

Participants were a representative sample of 1,630 older adults from the St. Louis Personality and Aging Network (SPAN) longitudinal study of personality and health in later life (Oltmanns, Rodrigues, Weinstein, & Gleason, 2014). Each participant nominated one informant who “knew them best” to complete informant-report questionnaires about him or her (these informants included 50% romantic partners, 27% other family members, 22% friends, and 2% other). Personality data for the present study were collected at a 2.5-year follow-up assessment. Over 1,200 target participants and 1,000 informants completed all measures (numbers vary because of sporadic missing data). Further details are provided in Oltmanns et al. (2014). The study was approved by the local institutional review board.

Measures

Both targets and informants reported on the target’s personality using a well-validated full-length measure of normal personality for the GFP analyses, with coefficient α at the facet level ranging from .58 (Tender-Mindedness) to .84 (Depression) for the self-report and .60 (Actions) to .89 (Self-Discipline) for the informant report.

Targets also completed a structured interview for the assessment of the DSM–IV (American Psychiatric Association, 2000) PDs used in the g-PD analyses. The interviews were administered by trained staff, and case conferences were regularly conducted to discuss ratings. The interrater reliability for a sample of baseline assessment interviews (n = 265) was ICC = .67 (Oltmanns et al., 2014). Internal consistency for the interview criteria used in the present study ranged from α = .52 (Dependent) to α = .83 (Avoidant).

Finally, targets and informants both completed a questionnaire about the target to assess 10 DSM–IV PDs for the g-PD analyses. Internal consistency ranged from .50 (Antisocial) to .80 (Avoidant) for target self-reports and .66 (Schizoid) to .85 (Avoidant) for informant-reports.

A subset of target participant/informant pairs (n = 665) completed seven well-validated measures of self- and informant-rated physical health and self-reported social support, loneliness, insomnia, and life satisfaction. Reliabilities ranged from coefficient α = .66 to α = .94.

See the Supplemental Material for a complete list and further description of all the measures that were administered.

Results

A model was constructed to examine the correlation between the GFP and g-PD. Because of the novelty of the g-PD model, exploratory methods were used to identify specific factors to be extracted. Model construction details and factor loadings are provided in the Supplemental Material. Correlations were specified between latent factors of the same perspective (e.g., self–self and informant–informant) and following associations between personality and PD found in Samuel and Widiger (2008). Fit indices were: RMSEA = .065 (.064, .065), SRMR = .083 (CFI = .722), χ²(3,719) = 19,488.142, p < .001, AIC = 85,078.645, BIC = 87,374.430. The model is depicted in Figure 2. The GFP factor loadings in this model were consistent with previous research—defined by low neuroticism, high extraversion, high agreeableness, and high conscientiousness. The g-PD factor loadings were consistent with what has been found previously, in that the borderline, avoidant, and dependent PD indicators loaded highly on the g-PD (cf, Jahng et al., 2011; Wright et al., 2016). GFP saturation in the combined model was ω_h = .51 and g-PD saturation was ω_h = .48. The correlation between the GFP and g-PD was r = –.82 (SE = .03), p < .001. Fit indices for second-order hierarchical and single-factor estimation of the general factors were less than adequate and can be found in the Supplemental Material. Descriptive statistics and intercorrelations of the scales used in Study 2 are displayed in the Supplemental Material.

Fig. 2.

SPAN Multimethod GFP and g-PD Structural Equation Model. A = agreeableness; AV = avoidant; BD = borderline; C = conscientiousness; DP = dependent; E = extraversion; GFP = general factor of personality; G-PD = general factor of personality disorder; HS = histrionic; I = informant-report; INF = informant-report; MAPP = Multi-Source Assessment of Personality Pathology; N = neuroticism; NA = narcissistic; O = openness; OC = obsessive-compulsive; PA = paranoid; S = self-report; SELF = self-report; SIDP = Structured Interview for DSM�IV Personality; SIDPA = DSM cluster A personality disorders; SIDPB = DSM cluster B personality disorders; ST = schizotypal; SZ = schizoid. Double-sided arrows represent a correlation, and single-sided arrows represent a regression.

A total score of maladaptivity was created by combining measures of physical health, insomnia, social support, satisfaction with life, and loneliness. The GFP correlated with total maladaptivity, r(665) = –.65 (SE = .04), p < .001. The g-PD correlated with total maladaptivity, r(660) = .68 (SE = .04), p < .001.

Discussion

The results of the current study suggest that there may be considerable shared variance among the p factor, the g-PD, and the GFP. Investigators have had trouble arriving at a consensus understanding of the GFP, with many questioning whether it has any real meaning at all. It might be even more difficult to understand a common general factor that is shared by such disparate individual differences as psychopathology, PD, and normal (general) personality. There would appear to be little in common across (for instance) nicotine dependence, mood disorder, antagonism, negative symptoms of schizophrenia, obsessive-compulsive personality, psychosis, narcissism, and low conscientiousness.

The current results might also question some of the existing substantive interpretations of a respective general factor. For example, it did appear to be compelling to suggest that g-PD is largely equivalent to borderline personality organization (Kernberg, 1984) given the prominence of BPD diagnostic criteria within some g-PD studies (Sharp et al., 2015; Wright et al., 2016). However, it would be difficult to suggest that borderline personality organization also largely defines the general factor of psychopathology and general personality. It might seem comparably difficult to suggest that a disposition toward psychopathology (Caspi et al., 2014) provides an apt description of the general factor of personality or conversely that social ineffectiveness (Rushton & Irwing, 2011; van der Linden et al., 2017) provides an apt description of the general factor of psychopathology. Yet the results of the current study suggest that the p factor, GFP, and g-PD may share much in common.

One might then consider the results of the current study to be consistent with the view that the p factor and g-PD are also artifactual products of an evaluative bias, as suggested for the GFP (Pettersson et al., 2012). However, social desirability was largely rejected years ago when it became apparent that much of the variance within measures of social desirability was substantively meaningful individual differences (McCrae & Costa, 1983), consistent with the fact that the p factor and the g-PD are correlated with a substantial amount of real life outcomes (Caspi et al., 2014; Lahey et al., 2012; Patalay et al., 2015; Wright et al., 2016). It is not that persons are attributing to themselves desirable (or undesirable) traits that they do not have; it is that some persons do indeed have many desirable traits, whereas other persons have many undesirable traits.

Nevertheless, it perhaps remains problematic if some of these traits and disorders are themselves inconsistent, if not contradictory (Pettersson et al., 2012). Indeed, what is really shared in common across nicotine dependence, psychosis, disinhibition, fear, mood disorder, schizophrenia, and narcissistic PD? We offer another interpretation of the general factors of personality, psychopathology, and PD that we feel is consistent with both a substantive and an artifactual understanding (Widiger & Oltmanns, 2017). All persons who offer a substantive understanding of the general factor are providing alternative descriptions or bases for the extent of maladaptive dysfunction, whether it reflects interpersonal dysfunction (Jahng et al., 2011), self-other deficits (Sharp et al., 2015; Wright et al., 2016), a general disposition toward psychopathology (Caspi et al., 2014; Lahey et al., 2012), an impulsive responsivity to emotion (Carver, Johnson, & Timpano, 2017), or social ineffectiveness (Rushton & Irwing, 2011). What all of these general factors might have in common, or perhaps how they should be understood, is that they simply reflect extent of impairment or dysfunction within the respective persons’ lives, irrespective of the basis for that dysfunction or impairment, whether it be from the presence of a mood disorder, a psychosis, a PD, or a personality trait. Disparate disorders do not share the same symptoms (Lahey et al., in 2017), but they may share the same impairments and dysfunctions that are secondary to the different symptoms or original fundamental deficits from which the symptoms arise (e.g., both irresponsibly lax and excessively perfectionistic persons will fail to complete tasks on time, yet they will do so for opposite reasons).

Our interpretation is admittedly speculative, but perhaps no more speculative than what has been previously offered. Indeed, most proponents of a substantive interpretation have acknowledged that their proposals were speculative, often with a clear expression of uncertainty as to the precise understanding (e.g., Caspi et al., 2014; Jahng et al., 2011; Sharp et al., 2015; Wright et al., 2016). In addition, in Study 2, both the GFP and g-PD correlated substantially with a diverse, indiscriminate set of indicators of maladaptivity, consistent with our proposed understanding.

Indeed, it is important to recognize that the level of impairment or dysfunction along which the different forms of psychopathology, PD, and personality traits are being organized is largely independent of the basis for that impairment. There is then unlikely to be a common etiological basis for the occurrence or existence of the general factor. In that regard, the dimension is artifactual, as it reflects the associated impairment or dysfunction (e.g., occupational dysfunction) rather than the basis for that impairment (e.g., laxness or perfectionism). It is the level of impairment that determines one’s relative position on the general factor (e.g., the occupational dysfunction), not the presence of a particular disorder or trait (e.g., laxness or perfectionism).

One can normally interpret a factor by the items obtaining the highest scores on that factor. However, in the case of the general factor, the highest loading traits or disorders will simply be the most dysfunctional traits and/or disorders. In the case of the g-PD, this will typically be borderline traits (e.g., Sharp et al., 2015; Wright et al., 2016), whereas in the case of the p factor, it would be the psychotic symptoms and/or disorders (Caspi et al., 2014). p factor researchers have not interpreted this factor as representing level of psychosis on the basis of the psychotic symptoms obtaining the highest loadings, because it is apparent that the other disorders loading on this factor have nothing to do with being psychotic. It would appear then similarly inaccurate to interpret the g-PD as a borderline PD factor because the other PDs loading on this factor have little to do with borderline PD.

Conclusions

No prior study has explicitly concerned the convergence of the p factor, the g-PD, and the GFP. The current investigation demonstrated across two studies that the p factor, g-PD, and GFP are highly convergent, thereby defining a common individual differences continuum. This common variance should have significant implications as to how the general factors across all three domains are to be understood conceptually.

Supplemental Material

OltmannsSupplement_R2 – Supplemental material for General Factors of Psychopathology, Personality, and Personality Disorder: Across Domain Comparisons

Supplemental material, OltmannsSupplement_R2 for General Factors of Psychopathology, Personality, and Personality Disorder: Across Domain Comparisons by Joshua R. Oltmanns, Gregory T. Smith, Thomas F. Oltmanns and Thomas A. Widiger in Clinical Psychological Science

Footnotes

Acknowledgements

We thank the St. Louis Personality & Aging Network (SPAN) Study Lab for data collection, Michael Boudreaux for data management, and David Dueber and Michael Toland for statistical consultation. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Author Contributions

J. R. Oltmanns and T. A. Widiger developed the study concept and study design. Testing and data collection were performed by J. R. Oltmanns, T. F. Oltmanns, and the SPAN lab members. J. R. Oltmanns performed the data analysis and interpretation under the supervision of T. A. Widiger and G. T. Smith. J. R. Oltmanns and T. A. Widiger prepared an initial draft of the manuscript, and subsequent revisions were prepared in collaboration with G. T. Smith and T. F. Oltmanns. All the authors approved the final version of the manuscript for submission.

ORCID ID

Joshua R. Oltmanns

Declaration of Conflicting Interests

The author(s) declared that there were no conflicts of interest with respect to the authorship or the publication of this article.

Funding

This research was supported by National Institute on Aging Grants F31-AG055233 and R01-AG045231 and by National Institute of Mental Health Grant R01-MH077840.

Supplemental Material

Additional supporting information may be found at

References

American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders (4th ed.). Washington, DC: Author.

American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Washington, DC: Author.

Bender

D. S.

Morey

L. C.

Skodol

A. E.

(2011). Toward a model for assessing level of personality functioning in DSM-5, part I: A review of theory and methods. Journal of Personality Assessment, 93, 332–346.

Bonifay

Lane

S. P.

Reise

S. P.

(2017). Three concerns with applying a bifactor model as a structure of psychopathology. Clinical Psychological Science, 5(1), 184–186.

Carver

C. S.

Johnson

S. L.

Timpano

K. R.

(2017). Toward a functional view of the p factor in psychopathology. Clinical Psychological Science, 5, 880–889.

Caspi

Houts

R. M.

Belsky

D. W.

Goldman-Mellor

S. J.

Harrington

Israel

, . . . Moffitt

T. E.

(2014). The p factor: One general psychopathology factor in the structure of psychiatric disorders? Clinical Psychological Science, 2, 119–137.

Edwards

A. L.

(1953). The relationship between the judged desirability of a trait and the probability that the trait will be endorsed. Journal of Applied Psychology, 37, 90–93.

Hopwood

C. J.

Wright

A. G.

Donnellan

M. B.

(2011). Evaluating the evidence for the general factor of personality across multiple inventories. Journal of Research in Personality, 45, 468–478.

Jahng

Trull

T. J.

Wood

P. K.

Tragesser

S. L.

Tomko

Grant

J. D.

, . . . Sher

K. J.

(2011). Distinguishing general and specific personality disorder features and implications for substance dependence comorbidity. Journal of Abnormal Psychology, 120, 656–669.

10.

Kenny

D. A.

McCoach

D. B.

(2003). Effect of the number of variables on measures of fit in structural equation modeling. Structural Equation Modeling, 10, 333–351.

11.

Kernberg

O. F.

(1984). Severe personality disorders: Psychotherapeutic strategies. New Haven, CT: Yale University Press.

12.

Kline

R. B.

(2015). Principles and practice of structural equation modeling. New York, NY: Guilford Press.

13.

Lahey

B. B.

Applegate

Hakes

J. K.

Zald

D. H.

Hariri

A. R.

Rathouz

P. J.

(2012). Is there a general factor of prevalent psychopathology during adulthood? Journal of Abnormal Psychology, 121, 971–977.

14.

Lahey

B. B.

Krueger

R. F.

Rathouz

P. J.

Waldman

I. D.

Zald

D. H.

(2017). A hierarchical causal taxonomy of psychopathology across the life span. Psychological Bulletin, 143, 142–186.

15.

Loehlin

J. C.

(2012). How general across inventories is a general factor of personality? Journal of Research in Personality, 46, 258–263.

16.

McCrae

R. R.

Costa

P. T

. (1983). Social desirability scales: More substance than style. Journal of Consulting and Clinical Psychology, 51, 882–888.

17.

Musek

(2007). A general factor of personality: Evidence for the Big One in the five-factor model. Journal of Research in Personality, 41, 1213–1233.

18.

Oltmanns

T. F.

Rodrigues

M. M.

Weinstein

Gleason

M. E.

(2014). Prevalence of personality disorders at midlife in a community sample: Disorders and symptoms reflected in interview, self, and informant reports. Journal of Psychopathology and Behavioral Assessment, 36, 177–188.

19.

Patalay

Fonagy

Deighton

Belsky

Vostanis

Wolpert

(2015). A general psychopathology factor in early adolescence. British Journal of Psychiatry, 207, 15–22.

20.

Pettersson

Turkheimer

Horn

E. E.

Menatti

A. R.

(2012). The general factor of personality and evaluation. European Journal of Personality, 26, 292–302.

21.

R Core Team. (2013). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing.

22.

Revelle

Wilt

(2013). The general factor of personality: A general critique. Journal of Research in Personality, 47, 493–504.

23.

Rosseel

(2012). lavaan: An R Package for structural equation modeling. Journal of Statistical Software, 48, 1–36. http://www.jstatsoft.org/v48/i02/

24.

Rushton

J. P.

Irwing

(2011). The general factor of personality. In Chamorro-Premuzic

von Stumm

Furnham

(Eds.), The Wiley-Blackwell handbook of individual differences (pp. 132–161). New York, NY: Blackwell Publishing.

25.

Samuel

D. B.

Widiger

T. A.

(2008). A meta-analytic review of the relationships between the five-factor model and DSM-IV-TR personality disorders: A facet level analysis. Clinical Psychology Review, 28, 1326–1342.

26.

Sharp

Wright

A. G.

Fowler

J. C.

Frueh

B. C.

Allen

J. G.

Oldham

Clark

L. A.

(2015). The structure of personality pathology: Both general (‘g’) and specific (‘s’) factors? Journal of Abnormal Psychology, 124, 387–398.

27.

van der Linden

Pekaar

K. A.

Bakker

A. B.

Schermer

J. A.

Vernon

P. A.

Dunkel

C. S.

Petrides

K. V.

(2017). Overlap between the general factor of personality and emotional intelligence: A meta-analysis. Psychological Bulletin, 143, 36–52.

28.

Widiger

T. A.

Oltmanns

J. R.

(2017). The general factor of psychopathology and personality. Clinical Psychological Science, 5, 182–183.

29.

Wright

A. G.

Hopwood

C. J.

Skodol

A. E.

Morey

L. C.

(2016). Longitudinal validation of general and specific structural features of personality pathology. Journal of Abnormal Psychology, 125, 1120–1134.

30.

Zinbarg

R. E.

Revelle

Yovel

(2005). Cronbach’s α, Revelle’s β, and McDonald’s ω_H: Their relations with each other and two alternative conceptualizations of reliability. Psychometrika, 70, 123–133.

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