Measurement invariance of the DSM–5 Section III pathological personality trait model across sex.

Abstract

The dimensional pathological personality trait model proposed in the Diagnostic and Statistical Manual for Mental Disorders, Fifth Edition (DSM-5), Section III Criterion B, has shown promising results for its validity and utility in conceptualizing personality pathology. However, as its structural equivalence across sex is yet to be tested, the validity for the model across males and females remains uncertain. In the present article, we examined sex measurement invariance of the DSM-5 trait model in a large undergraduate sample using the Personality Inventory for DSM-5. A series of confirmatory and exploratory factor analyses suggested that, although the exact facet-domain relationships as specified in the DSM-5 were not observed, the facets generally organize into a model with five latent factors similar to those listed in the DSM-5 Section III Criterion B. Further, these five factors were fully measurement invariant across sex at the configural, metric, and scalar levels. Examination of the latent trait mean levels suggests that females tend to have higher scores on latent Negative Affectivity, whereas males tend to have higher scores on latent Antagonism, Detachment, Psychoticism, and Disinhibition. These results indicate that the DSM-5 Section III pathological personality trait model is fully structurally equivalent across sex, a property that is lacking in the traditional categorical model in Section II. This further validates the use of the dimensional DSM-5 trait model for personality disorder assessment and conceptualization in both research and clinical settings. (PsycINFO Database Record

A Brief but Comprehensive Review of Research on the Alternative DSM-5 Model for Personality Disorders

“…Finally, maladaptive traits have been found to be associated with a range of other variables, including age [75]; gender [75,217]; general symptom distress [66,77,84,172,[218][219][220]; psychotic disorder [221,222]; dissociative experiences [223]; bipolar disorder [224]; attention-deficit/hyperactivity disorder [225]; problematic alcohol use [66, 226•]; substance use [140,227,228]; self-harm [229]; pathological gambling [230]; internet-gaming disorder [231]; problematic internet use [223]; posttraumatic stress disorder [232, 233•]; physical illness [233•]; disability [57, [234][235][236]; quality of life [149,236]; self-esteem [150]; alexithymia [150]; empathy, self-reflection, and insight [150]; maladaptive schemas [237]; interpersonal problems [150,238,239]; pathological beliefs [240]; defensive styles [241]; emotion dysregulation [150,242]; anxiety mindset [205]; impulsivity [227]; aggression…”

“…Other examples are studies showing that individual differences in trait facets are relatively stable across periods of 2 weeks [57, 235], 4 months [285], and more than 1 year [286]. Further issues that have been addressed include measurement invariance or item bias due to age [287,288], gender [217,289], and clinical status [290]; response styles in PID-5 self-reports [154,155,291,292]; heritability and familial aggregation of maladaptive traits [39,289,[293][294][295]; and perceived likability, impairment, functionality, as well as desire and ability for change of maladaptive traits [68,158,[296][297][298].…”

Measurement Invariance and Sex and Age Differences of the Big Five Inventory–2: Evidence From the Russian Version

“…If MI cannot be established, a between-group observed mean difference cannot be straightforwardly interpreted (Cheung & Rensvold, 2002). This raises difficulties for drawing conclusions about traditional observed mean differences in traits on various aspects including sex and age groups (Church et al, 2011; Suzuki et al, 2019). With respect to the BFI-1, multiple studies explicitly addressed MI across various groups such as sex (Chiorri et al, 2016), survey methods (Lang, John, Lüdtke, Schupp, & Wagner, 2011), age moments (Nye, Allemand, Gosling, Potter, & Roberts, 2016; Specht et al, 2011), data collection methods (Feitosa, Joseph, & Newman, 2015), or geographic regions like countries or urban areas (Gebauer et al, 2014).…”

Psychometric properties of the Chinese version of the Personality Inventory for DSM-5 Brief Form in undergraduate students and clinical patients

“…Although MI of the PID-5 has been examined across cultures, sexes, and across clinical and nonclinical samples [32][33][34], the MI of the PID-5-BF is unknown.…”