Giving Meaning to the Dark Triad: Comparison of Different Factor Structures of the Dirty Dozen Through Eight Regions of the World

The traits of the dark triad (narcissism, psychopathy, and Machiavellianism) capture the individual differences in the aversive personality. The dark triad has shown significant relations with behaviors that affect people's lives. One of the best-known instruments to assess the dark triad is the Dirty Dozen. However, controversy continues over the use of one general dark triad score or, conversely, three different scores. This study aimed to investigate the factor structure of the Dirty Dozen across eight global regions. There were 11,477 participants in 49 countries grouped into eight regions. Different factor structures were studied using confirmatory factor analyses. Both the three-dimensional models and the bifactor models (symmetrical or traditional and non-symmetrical or bifactor-[S - 1]) showed a good fit to the data. The bifactor-(S - 1) models (with psychopathy or Machiavellianism as the reference factors) show adequate fit to the data, supported by the coherence of the factorial loadings and the bifactor indices. Regarding measurement invariance for both models, configural, metric, and scalar invariance were satisfied. The results indicate that it is not clear whether a psychopathy or Machiavellianism reference factor predominates in the Dirty Dozen. For both models, templates are provided to obtain standardized scores for applied researchers in the eight studied world regions until future studies offer a greater amount of validity evidence for this instrument.

The effects of shared, depression-specific, and anxiety-specific internalizing symptoms on negative and neutral episodic memories following post-learning sleep

Emotional memory bias is a common characteristic of internalizing symptomatology and is enhanced during sleep. The current study employs bifactor S-1 modeling to disentangle depression-specific anhedonia, anxiety-specific anxious arousal, and the common internalizing factor, general distress, and test whether these internalizing symptoms interact with sleep to influence memory for emotional and neutral information. Healthy adults (N = 281) encoded scenes featuring either negative objects (e.g., a vicious looking snake) or neutral objects (e.g., a chipmunk) placed on neutral backgrounds (e.g., an outdoor scene). After a 12-hour period of daytime wakefulness (n = 140) or nocturnal sleep (n = 141), participants judged whether objects and backgrounds were the same, similar, or new compared with what they viewed during encoding. Participants also completed the mini version of the Mood and Anxiety Symptom Questionnaire. Higher anxious arousal predicted worse memory across all stimuli features, but only after a day spent being awake-not following a night of sleep. No significant effects were found for general distress and anhedonia in either the sleep or wake condition. In this study, internalizing symptoms were not associated with enhanced emotional memory. Instead, memory performance specifically in individuals with higher anxious arousal was impaired overall, regardless of emotional valence, but this was only the case when the retention interval spanned wakefulness (i.e., not when it spanned sleep). This suggests that sleep may confer a protective effect on general memory impairments associated with anxiety.

An Evaluation of Item Harmonization Strategies Between Assessment Tools of Psychopathology in Children and Adolescents

Data aggregation in mental health is complicated by using different questionnaires, and little is known about the impact of item harmonization strategies on measurement precision. Therefore, we aimed to assess the impact of various item harmonization strategies for a target and proxy questionnaire using correlated and bifactor models. Data were obtained from the Brazilian High-Risk Study for Mental Conditions (BHRCS) and the Healthy Brain Network (HBN; N = 6,140, ages 5-22 years, 39.6% females). We tested six item-wise harmonization strategies and compared them based on several indices. The one-by-one (1:1) expert-based semantic item harmonization presented the best strategy as it was the only that resulted in scalar-invariant models for both samples and factor models. The between-questionnaires factor correlation, reliability, and factor score difference in using a proxy instead of a target measure improved little when all other harmonization strategies were compared with a completely at-random strategy. However, for bifactor models, between-questionnaire specific factor correlation increased from 0.05-0.19 (random item harmonization) to 0.43-0.60 (expert-based 1:1 semantic harmonization) in BHRCS and HBN samples, respectively. Therefore, item harmonization strategies are relevant for specific factors from bifactor models and had little impact on p-factors and first-order correlated factors when the child behavior checklist (CBCL) and strengths and difficulties questionnaire (SDQ) were harmonized.

The Role of Emotion Dysregulation in Heightened Alcohol Craving Related to Posttraumatic Stress Disorder and Depression Symptoms

Objective: Compared to their male counterparts, women with alcohol use disorders (AUD) alone and those with symptoms of co-occurring emotional disorders (posttraumatic stress disorder, PTSD, and depression) are particularly likely to have increased alcohol craving in response to negative affect and daily stressors. Emotion dysregulation is one transdiagnostic construct that may underlie heightened craving in response to stress within this population. In a secondary data analysis, the current study examined emotion dysregulation as a mediator of the associations of posttraumatic stress symptoms (PTSS) and depression symptoms with heightened stress-induced alcohol craving, as measured in the lab. Given the overlap in symptoms, the relative associations of PTSD and depression symptom clusters with stress-induced craving were explored. Method: 50 women Veterans (84% White, 88% Non-Hispanic, Mage=45.68) attended two in-lab sessions. Self-report measures of emotion dysregulation, PTSD, and depression symptoms were administered at baseline. During session two, participants reported on alcohol craving and negative affect at baseline and again after a personalized stress induction procedure. Results: Emotion dysregulation mediated the association of greater PTSS with heightened stress-induced craving, although emotion dysregulation was not a mediator of the association between depression and stress-induced craving. Greater alcohol craving after the stress induction was positively associated with cognitive-affective symptoms in PTSD and depression (and not with other symptom clusters of these diagnoses, e.g., avoidance, somatic-vegetative symptoms). Conclusions: Emotion dysregulation may be a transdiagnostic factor that helps to explain greater alcohol cravings and drinking in stressful contexts among women Veterans with heightened symptoms of co-occurring emotional disorders.

How personality functioning relates to psychological distress and behavioral attitudes during the Covid-19 pandemic

Functional aspects of personality are crucial for experiencing and handling emotional distress. With the outbreak of the Covid-19 virus and the subsequent installation of mitigation rules of social distancing, severe psycho-social challenges were posed upon people. Research has shown that individuals react differently to these challenges. This study aimed to investigate the role of dimensional aspects of personality during the Covid-19 pandemic. Specifically, we examined how personality functioning, defense mechanisms, and narcissism were related to psychological distress and cognitive and behavioral attitudes towards the rules of social distancing. In a non-clinical sample (N = 254), Level of Personality Functioning Scale, Inventory of Personality Organization, Defense Style Questionnaire, Pathological Narcissism Inventory, and three single questions regarding emotional distress and behavioral attitudes towards the pandemic were used. Structural equation models with reference and residual factors were calculated. Impairments in personality functioning and vulnerable narcissism showed significant positive relationships, adaptive defense mechanisms significant negative relationships with psychological distress during the pandemic. Residual factors for aggression and low moral values showed distinct negative relationships with psychological distress related to social distancing. Among individuals who chose to ignore the rules of social distancing, greater impairment in personality organization was found. Personality functioning may elucidate individual differences in psychological distress and compliance with the mitigation rules during the pandemic. Limitations of measures are carefully considered in all interpretations.

Other-Oriented Empathetic Concern as the Underlying Factor of Extrinsic Emotion Regulation Motives and Its Positive Application for Social Well-Being

Purpose

In recent years, research on interpersonal emotion regulation has garnered increasing attention. Extrinsic emotion regulation (EER) or the regulation of others' emotions is associated with individual personal relationships and mental health outcomes. However, investigations into why people engage in extrinsic emotion regulation are relatively rare. The current study aimed to identify the underlying factor structure of the motives of extrinsic emotion regulation, based on the Extrinsic Emotion Regulation Motives Scale (EERMS), to examine how these factors related to people's moral identity and social relationships during the COVID-19 pandemic.

Participants and Methods

The participants of this study were 464 adults (73.1% females) from China who completed an online survey based on EERMS and other related measures. An exploratory factor analysis (EFA) was utilized to examine the underlying structure of EER motives followed by a bifactor EFA (bi-EFA).

Results

Analyses revealed that the bi-EFA model, with an overarching factor (other-oriented empathetic concern) and three specific factors (self-orientation, reciprocation, and obligation), was best applied to the data. These factors were differently associated with social well-being indicators (moral self-identity, peer relationship quality, and perceived social support).

Conclusion

This preliminary study supports the use of a hierarchical perspective to understand the different dimensions of motives for extrinsic emotion regulation.

Harmonizing bifactor models of psychopathology between distinct assessment instruments: Reliability, measurement invariance, and authenticity

OBJECTIVES

Model configuration is important for mental health data harmonization. We provide a method to investigate the performance of different bifactor model configurations to harmonize different instruments.

METHODS

We used data from six samples from the Reproducible Brain Charts initiative (N = 8,606, ages 5-22 years, 41.0% females). We harmonized items from two psychopathology instruments, Child Behavior Checklist (CBCL) and GOASSESS, based on semantic content. We estimated bifactor models using confirmatory factor analysis, and calculated their model fit, factor reliability, between-instrument invariance, and authenticity (i.e., the correlation and factor score difference between the harmonized and original models).

RESULTS

Five out of 12 model configurations presented acceptable fit and were instrument-invariant. Correlations between the harmonized factor scores and the original full-item models were high for the p-factor (>0.89) and small to moderate (0.12-0.81) for the specific factors. 6.3%-50.9% of participants presented factor score differences between harmonized and original models higher than 0.5 z-score.

CONCLUSIONS

The CBCL-GOASSESS harmonization indicates that few models provide reliable specific factors and are instrument-invariant. Moreover, authenticity was high for the p-factor and moderate for specific factors. Future studies can use this framework to examine the impact of harmonizing instruments in psychiatric research.

Bifactor analysis of the Hospital Anxiety and Depression Scale (HADS) in individuals with traumatic brain injury

Anxiety and depression symptoms are commonly experienced after traumatic brain injury (TBI). However, studies validating measures of anxiety and depression for this population are scarce. Using novel indices derived from symmetrical bifactor modeling, we evaluated whether the Hospital Anxiety and Depression Scale (HADS) reliably differentiated anxiety and depression in 874 adults with moderate-severe TBI. The results showed that there was a dominant general distress factor accounting for 84% of the systematic variance in HADS total scores. The specific anxiety and depression factors accounted for little residual variance in the respective subscale scores (12% and 20%, respectively), and overall, minimal bias was found in using the HADS as a unidimensional measure. Further, in a subsample of 184 participants, the HADS subscales did not clearly discriminate between formal anxiety and depressive disorders diagnosed via clinical interview. Results were consistent when accounting for degree of disability, non-English speaking background, and time post-injury. In conclusion, variance in HADS scores after TBI predominately reflects a single underlying latent variable. Clinicians and researchers should exercise caution in interpreting the individual HADS subscales and instead consider using the total score as a more valid, transdiagnostic measure of general distress in individuals with TBI.

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

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.

Cross-replicating findings on unique motor impairments of children with ASD using confirmatory factor analysis and a novel SPARK study sample

A series of recent reports have shed light on the pervasive nature of motor impairments in children with ASD (Bhat, 2020, 2021, Bhat et al., 2022), underscoring the importance of providing ASD clinicians efficient and accurate tools for motor screening. The Developmental Coordination Disorder-Questionnaire (DCD-Q) is a widely used motor screening tool, yet scant evidence exists regarding its psychometric properties in children with ASD. In a recent Exploratory Factor Analysis (EFA) of the 15-item DCD-Q in a large sample of children with ASD (SPARK study), we found a 5-factor latent structure that identified unique motor impairments in a large sample of children with ASD (Bhat et al., 2022). In the current study, we extend this work by cross-replicating the EFA findings of unique ASD-related motor issues using Confirmatory Factor Analysis (CFA) in a new, more recent wave of children with ASD from the SPARK study (N = 9721). The fits and interpretability of 11 hypothesis-driven CFA models, including 8 correlated-factors, 1 second-order, and 2 bifactor models were compared. Our findings supported the previous 5-factor model with 2 gross motor subdomains, 1 fine motor domain (similar to the original DCD-Q) and 2 general coordination subdomains. This model demonstrated acceptable fit in the new sample as well as superior fit compared to several other parsimonious correlated-factors models. However, the second-order and bifactor models fit slightly better and supported the presence of a general motor skills factor, although 38% of the common variance in the DCD-Q items remained attributable to the 5 subdomains. Using one of the bifactor models, measurement invariance was also supported for DCD-Q across sex, race, and co-occurring conditions of language disorder and intellectual disability. Only partial invariance was supported when testing DCD-Q scores across different age groups. These findings reveal a more complex dimensional picture of the DCD-Q in children with ASD. Results suggest that the DCD-Q can be used in two ways, total scores adequately assess general motor skills for brief screening and subdomain scores offer unique information on the multidimensional motor problems of children with ASD. If subdomain data are of interest, our findings call into question the practice of relying on 3 original subscales of the DCD-Q when screening for ASD-related motor difficulties, whereas 4 out of 5 subscale scores may better highlight domain-specific motor problems. Future studies should continue to further validate DCD-Q's ability to screen for multidimensional motor problems.

Full-information item bifactor model for mathematical ability assessment in Chinese compulsory education quality monitoring

This study focuses on the measurement of mathematical ability in the Chinese Compulsory Education Qualification Monitoring (CCEQM) framework using bifactor theory. First, we propose a full-information item bifactor (FIBF) model for the measurement of mathematical ability. Second, the performance of the FIBF model is empirically studied using a data set from three representative provinces were selected from CCEQM 2015-2017. Finally, Monte Carlo simulations are conducted to demonstrate the accuracy of the model evaluation indices and parameter estimation methods used in the empirical study. The obtained results are as follows: (1) The results for the four used model selection indices (AIC, SABIC, HQ, BIC) consistently showed that the fit of the FIBF model is better than that of the UIRT; (2) All of the estimated general and domain-specific abilities of the FIBF model have reasonable interpretations; (3) The model evaluation indices and parameter estimation methods exhibit excellent accuracy, indicating that the application of the FIBF model is technically feasible in large-scale testing projects.

Zur Messqualität des Beck-Depressionsinventars (BDI-II) in unterschiedlichen klinischen Stichproben

Zusammenfassung. Theoretischer Hintergrund: Das BDI-II ist ein Selbstbeurteilungsinstrument zur Erfassung des Schweregrads einer Depression. Es liegen kaum Analysen mit Modellen aus der Item-Response-Theorie (IRT) vor. Fragestellung: Wie hoch ist die Messgenauigkeit des BDI-II über die unterschiedlichen Ausprägungen des latenten Traits (Depressivität) hinweg und sind die Kategorien der Items jeweils aufsteigend geordnet? Methode: Anhand von sechs großen Datensätzen aus verschiedenen klinischen Bereichen wurden psychometrische Analysen mit dem Graded Response Model durchgeführt. Ergebnisse: In allen Stichproben fand sich eine hohe interne Konsistenz. Die Schwellenwerte waren mit Ausnahme von Item 6 („Bestrafungsgefühle“) geordnet. Gemäß Testinformationsfunktion misst das BDI-II im mittleren bis hohen Depressionsbereich sehr gut (Reliabilität > .90) und im unteren Bereich gut. Schlussfolgerung: Für das BDI-II ergibt sich eine hohe und relativ gleichbleibende Messpräzision über einen weiten Bereich des latenten Traits, weshalb es insbesondere im klinischen, aber auch im nicht klinisch relevanten Wertebereich zur Erhebung des Schweregrades einer Depression gut geeignet ist.

Estructura factorial y datos normativos del Inventario de Depresión de Beck (BDI-II) en población general peruana

El objetivo principal de este estudio fue analizar la dimensionalidad del BDI-II, así como demostrar la invarianza según el sexo y construir datos normativos en población general peruana. Para ello, se contó con la participación de 1665 personas (51.83 % mujeres) procedentes de diferentes regiones del Perú (75.92 % de Cajamarca, 11.05 % de Lima, 6.42 % de La Libertad y 2.62 % de Lambayeque), con un rango de edad de 18 a 54 años (M = 24.99; DE = 8.73), a quienes se les administró el BDI-II. Mediante un análisis factorial confirmatorio se probaron catorce modelos basados en estudios previos. Los resultados indicaron que los modelos bifactor y de segundo orden tenían problemas de convergencia, mientras que los bidimensionales y el unifactorial presentaban adecuados índices de ajuste. Se seleccionó el modelo unidimensional debido a su coherencia teórica, pues los creadores del BDI-II señalan que la prueba se debe interpretar de manera global, sumando los 21 ítems, y desaconsejan la interpretación mediante el cálculo de puntajes separados por dimensiones. Incluso, los antecedentes indican que la varianza explicada del segundo factor es muy baja, por lo cual dicha práctica estaría injustificada. Además, los estudios previos han señalado correlaciones interfactoriales muy altas. Finalmente, se demostró invarianza según el sexo, y los datos normativos, calculados mediante percentiles, mostraron que las puntuaciones superiores a 11 serían clínicamente relevantes. En conclusión, el BDI-II muestra buenas propiedades psicométricas en una estructura unidimensional con 21 ítems, la cual es invariante según el sexo y tiene datos normativos adecuados para población general peruana.

The Berlin Misophonia Questionnaire Revised (BMQ-R): Development and validation of a symptom-oriented diagnostical instrument for the measurement of misophonia

Misophonia is a clinical syndrome which is characterized by intense emotional and physical reactions to idiosyncratic sounds. However, its psychometric measurement is still in the early stages. This study describes the optimization of a self-report instrument, the Berlin Misophonia Questionnaire (BMQ), and addresses its strengths in comparison to existing psychometric measures. This new measure integrates contemporary empirical findings and is based on the latest criteria of misophonia. A cross-sectional online study was conducted using data of 952 affected as well as non-affected individuals. The final BMQ-R consists of 77 items in 21 scales, which were selected using a probabilistic item selection algorithm (Ant Colony Optimization). The results of confirmatory factor analyses, the assessment of reliability, and an extensive construct validation procedure supported the reliability and validity of the developed scales. One outstanding strength of the BMQ-R is its comprehensive measurement of misophonic emotional and physical responses. The instrument further allows for distinguishing between behavioral, cognitive, and emotional dysregulation; the measurement of clinical insight and significance; as well as discerning reactive and anticipating avoidance strategies. Our work offers several improvements to the measurement of misophonia by providing a reliable and valid multidimensional diagnostical instrument. In line with the scientific consensus on defining misophonia, the BMQ-R allows to formally recognize individuals with misophonia and so to compare findings of future studies. Undoubtedly, this measure fills a research gap, which we hope will facilitate the investigation of causes and treatment of misophonia.

General and Specific Dimensions of Mood Symptoms Are Associated With Impairments in Common Executive Function in Adolescence and Young Adulthood

Both unipolar and bipolar depression have been linked with impairments in executive functioning (EF). In particular, mood symptom severity is associated with differences in common EF, a latent measure of general EF abilities. The relationship between mood disorders and EF is particularly salient in adolescence and young adulthood when the ongoing development of EF intersects with a higher risk of mood disorder onset. However, it remains unclear if common EF impairments have associations with specific symptom dimensions of mood pathology such as blunted positive affect, mood instability, or physiological arousal, or if differences in common EF more broadly relate to what is shared across various symptom domains, such as general negative affect or distress. To address this question, bifactor models can be applied to simultaneously examine the shared and unique contributions of particular mood symptom dimensions. However, no studies to our knowledge have examined bifactor models of mood symptoms in relation to measures of common EF. This study examined associations between common EF and general vs. specific symptom dimensions (anhedonia, physiological arousal, and mania) using structural equation modeling in adolescents and young adults with varying severity of mood symptoms (n = 495, ages = 13-25 years, 68.69% female). A General Depression factor capturing shared variance across symptoms statistically predicted lower Common EF. Additionally, a factor specific to physiological arousal was associated with lower Common EF. Anhedonia-specific and Mania-specific factors were not significantly related to Common EF. Altogether, these results indicate that deficits in common EF are driven by, or reflect, general features of mood pathology that are shared across symptom dimensions but are also specifically associated with physiological arousal.

Examining the Relations between Preschooler's Externalizing Behaviors and Academic Performance Using an S-1 Bifactor Model

Externalizing behaviors are associated with poor academic outcomes in community-based samples of children as young as preschool-age. However, there remains debate as to which specific externalizing dimensions link externalizing behaviors to early academic skills. Recently, research has supported the use of S-1 bifactor models to examine the hierarchical structure of externalizing behaviors and the unique relations between externalizing factors and academic impairment in samples of school-age children. The primary goals of this study were to extend the age range at which S-1 bifactor models are applied to externalizing behaviors and to determine if factors derived from an S-1 bifactor model had differing relations to early academic skills. In this study, the early academic skills of 1,356 preschool-age children (mean age = 49.98 months; SD = 8.08) were assessed, and preschool and childcare teachers rated children's externalizing behaviors. Results indicated that an S-1 bifactor model with a Hyperactive-Impulsive reference factor yielded the best-fitting model for preschool-age children's externalizing behaviors. Structural models revealed that both the Hyperactive-Impulsive reference factor and the Inattention factor uniquely predicted preschool children's early academic skills. The degree to which the results applied across the primary groups in the sample (i.e., White versus Black/African American children, girls versus boys) was examined for measurement and structural models.

Internal Structure of Beck Hopelessness Scale: An Analysis of Method Effects Using the CT-C(M-1) Model

ABTRACTThe construct validity in relation to the dimensionality or factor structure of the Beck Hopelessness Scale (BHS) has long been debated in psychometrics. Irrelevant variance due to item wording (method effects) can distort the factor structure, and recent studies have examined the method factor's role in the factor structure of the BHS. However, the models used to control the method effects have severe limitations, and new models are needed. One such model is the correlated trait-correlated method minus one (CT-C(M-1)), which is a powerful approach that gives the trait factor an unambiguous meaning and prevents the anomalous results associated with fully symmetrical bifactor modeling. The present work compares the fit and factor structure of the CT-C(M-1) model to bifactor models proposed in previous literature and evaluates the criterion validity of the CT-C(M-1) model and its discriminatory capacity by taking suicidal ideation as the criterion variable. This study used a large and heterogeneous open mode online sample of Argentinian people (N = 2,164). The results indicated that the CT-C(M-1) model with positive words as referenced items achieves the most adequate factor structure. The factorial scores derived from this model demonstrate good predictive and discriminating capabilities.

Experimental evidence that apologies promote forgiveness by communicating relationship value

Robust evidence supports the importance of apologies for promoting forgiveness. Yet less is known about how apologies exert their effects. Here, we focus on their potential to promote forgiveness by way of increasing perceptions of relationship value. We used a method for directly testing these causal claims by manipulating both the independent variable and the proposed mediator. Namely, we use a 2 (Apology: yes vs. no) × 2 (Value: high vs. low) concurrent double-randomization design to test whether apologies cause forgiveness by affecting the same causal pathway as relationship value. In addition to supporting this causal claim, we also find that apologies had weaker effects on forgiveness when received from high-value transgressors, suggesting that the forgiveness-relevant information provided by apologies is redundant with relationship value. Taken together, these findings from a rigorous methodological paradigm help us parse out how apologies promote relationship repair.

How Multidimensional Is Emotional Intelligence? Bifactor Modeling of Global and Broad Emotional Abilities of the Geneva Emotional Competence Test

Drawing upon multidimensional theories of intelligence, the current paper evaluates if the Geneva Emotional Competence Test (GECo) fits within a higher-order intelligence space and if emotional intelligence (EI) branches predict distinct criteria related to adjustment and motivation. Using a combination of classical and S-1 bifactor models, we find that (a) a first-order oblique and bifactor model provide excellent and comparably fitting representation of an EI structure with self-regulatory skills operating independent of general ability, (b) residualized EI abilities uniquely predict criteria over general cognitive ability as referenced by fluid intelligence, and (c) emotion recognition and regulation incrementally predict grade point average (GPA) and affective engagement in opposing directions, after controlling for fluid general ability and the Big Five personality traits. Results are qualified by psychometric analyses suggesting only emotion regulation has enough determinacy and reliable variance beyond a general ability factor to be treated as a manifest score in analyses and interpretation. Findings call for renewed, albeit tempered, research on EI as a multidimensional intelligence and highlight the need for refined assessment of emotional perception, understanding, and management to allow focused analyses of different EI abilities.

Exploring the Dimensionality of the Social Skills Improvement System Using Exploratory Graph Analysis and Bifactor-(S - 1) Modeling

Since its development over a decade ago, the Social Skills Improvement System (SSIS) has been one of the most widely used measures of social skills in children. However, evidence of its structural validity has been scant. The current study examined the original seven-factor and more recent five-factor structure (SSIS-SEL) of the self-report SSIS in a sample of English elementary school students (N = 3,331) aged 8 to 10 years (M = 8.66, SD = 0.59). A problematic fit was found for both structures with poor discriminant validity. Using exploratory graph analysis and bifactor-(S − 1) modeling, we found support for a four-factor structure, the variation of which was captured by a general factor defined by “empathy and prosocial skills.” Future researchers, particularly those interested in using specific domains of the SSIS, are urged to assess its structure in their studies, if their findings are to be theoretically meaningful.

The Factor Structure of the 4-Item Perceived Stress Scale in English Adolescents

Abstract. This study investigated the factor structure, internal consistency, and known-groups validity of the 4-item Perceived Stress Scale in a large sample of 29,388 English adolescents. Results indicated that the original unidimensional structure was not viable and instead provided support for a two-factor structure. Examination of a bifactor-( S − 1) model indicated that this multidimensionality can be attributed to reverse-worded items; however, beyond method effects, these factors appear to capture distinct, though inter-related, constructs. As this multidimensional structure relies on 2-item factors, we advise use of longer versions of this measure where possible.

Alcohol-Related, Drug-Related, and Non-Substance-Related Aggression: 3 Facets of a Single Construct or 3 Distinct Constructs?

BACKGROUND

Aggression often occurs alongside alcohol and drug misuse. However, it is not clear whether the latent and manifest relations among alcohol-related, drug-related, and non-substance-related aggression are separate manifestations of a single construct or instead are 3 distinct constructs.

METHODS

To examine these associations, we conducted a preregistered analysis of 13,490 participants in the Collaborative Study on the Genetics of Alcoholism. In a structured interview, participants reported their lifetime perpetration of these 3 aggression phenotypes.

RESULTS

The data were better fit by a model that treated these aggression phenotypes as 3 distinct latent factors, as compared to models in which the items all loaded onto 1 ("general") or 2 ("substance-related" and "non-substance-related") aggression factors. This 3-factor model fit better for men than women. Subsequent exploratory analyses then showed that among these 3 factors, alcohol-related aggression explained the variance of overall aggression better than the other 2 factors.

CONCLUSIONS

Our findings suggest that these 3 forms of aggression are distinct phenotypes (especially among men). Yet, people's alcohol-related aggression can accurately characterize their overall aggressive tendencies across these domains. Future research will benefit from articulating the unique and shared pathways and risk factors underlying each of these facets of aggression.

Application of the Bifactor S - 1 Model to Multisource Ratings of ADHD/ODD Symptoms: an Appropriate Bifactor Model for Symptom Ratings

The symmetrical bifactor model is often applied to attention-deficit/hyperactivity disorder (ADHD)-hyperactive/impulsive (HI), ADHD-inattentive (IN), and oppositional defiant disorder (ODD) symptoms, but this model frequently yields anomalous or inadmissible results. An alternative model, the bifactor S - 1 model, is more appropriate for examining the hierarchical structure of ADHD/ODD symptoms. Both models were applied to ADHD-HI, ADHD-IN, and ODD symptom ratings by mothers, fathers, and teachers for 2142 Spanish children (49.49% girls; ages 8-13 years). The symmetrical bifactor model yielded the typical anomalous loadings, with a weakly defined ADHD-HI specific factor and difficult to interpret associations of general and specific factors with correlates. In contrast, the bifactor S - 1 model with ADHD-HI symptoms as general reference factor produced clearly interpretable results. For mothers and fathers, slightly more than 50% of true score variance in ADHD-IN and ODD symptoms represented specific residual variance not shared with the general ADHD-HI reference factor. For teachers, approximately 69% and 39% of true score variance in ADHD-IN and ODD symptoms, respectively, represented specific residual variance not shared with the general ADHD-HI reference factor. The general ADHD-HI reference factor and specific ADHD-IN and ODD residual factors showed convergent and discriminant validity across sources, along with unique associations with peer rejection, social impairment, and academic impairment factors. The bifactor S - 1 model also yielded results consistent with predictions from trait-impulsivity theory of ADHD/ODD development. Researchers should use the bifactor S - 1 model rather than the symmetrical bifactor model if hypotheses involve the latent hierarchical structure of ADHD/ODD symptoms.

Multi-Faceted Constructs in Abnormal Psychology: Implications of the Bifactor S - 1 Model for Individual Clinical Assessment

Burns et al. (this issue) have shown that the application of the symmetrical bifactor model to attention-deficit/hyperactivity disorder (ADHD) and oppositional defiant disorder (ODD) symptoms leads to anomalous and inconsistent results across different rater groups. In contrast to the symmetrical bifactor model, applications of the bifactor S-1 model showed consistent and theoretically well-founded results. The implications of the bifactor S-1 model for individual clinical assessment are discussed. It is shown that individual factor scores of the bifactor S-1 model reveal important information about the profile of individual symptoms that is not captured by factor scores of the multidimensional model with correlated first-order factors. It is argued that for individual clinical assessment factor scores from both types of model (multidimensional model with correlated first-order factors, bifactor S -1 model) should be estimated and compared. Finally, a general strategy for choosing an appropriate model for analyzing multi-faceted constructs is presented that compares areas of applications for (1) the multidimensional model with correlated first-order factors, (2) the bifactor S-1 model with a general reference factor, and (3) the bifactor S - 1 model with a directly assessed general factor.

Appropriate Use of Bifactor Analysis in Psychopathology Research: Appreciating Benefits and Limitations

Co-occurrence of psychiatric disorders is well documented. Recent quantitative efforts have moved toward an understanding of this phenomenon, with the general psychopathology or p-factor model emerging as the most prominent characterization. Over the past decade, bifactor model analysis has become increasingly popular as a statistical approach to describe common/shared and unique elements in psychopathology. However, recent work has highlighted potential problems with common approaches to evaluating and interpreting bifactor models. Here, we argue that bifactor models, when properly applied and interpreted, can be useful for answering some important questions in psychology and psychiatry research. We review problems with evaluating bifactor models based on global model fit statistics. We then describe more valid approaches to evaluating bifactor models and highlight 3 types of research questions for which bifactor models are well suited to answer. We also discuss the utility and limits of bifactor applications in genetic and neurobiological research. We close by comparing advantages and disadvantages of bifactor models with other analytic approaches and note that no statistical model is a panacea to rectify limitations of the research design used to gather data.

Promises and Pitfalls of Latent Variable Approaches to Understanding Psychopathology: Reply to Burke and Johnston, Eid, Junghänel and Colleagues, and Willoughby

The commentaries by Burke and Johnston (this issue), Eid (this issue), Junghänel et al. (this issue), and Willoughby (this issue) on Burns et al. (this issue) provide useful context for comparing three latent variable modeling approaches to understanding psychopathology-the correlated first-order syndrome-specific factors model, the bifactor S - 1 model, and the symmetrical bifactor model. The correlated first-order syndrome-specific factors model has proven useful in constructing explanatory models of psychopathology. The bifactor S - 1 model is also useful for examining the latent structure of psychopathology, especially in contexts with clear theoretical predictions. Joint use of correlated first-order syndrome-specific model and bifactor S - 1 model provides leverage for explaining psychopathology, and both models can also guide individual clinical assessment. In this reply, we further clarify reasons why the symmetrical bifactor model should not be used to study the latent structure of psychopathology and also discuss a restricted bifactor S - 1 model that is equivalent to the first-order syndrome-specific factors model.

Commentary on Application of the Bifactor S-1 Model to Multisource Ratings of ADHD/ODD Symptoms: An Appropriate Bifactor Model for Symptom Ratings

My commentary is organized into four sections. First, I summarize the reasons for the original interest in fitting symmetric bifactor models to ADHD data. Second, I summarize the concerns that Burns and colleagues raised with respect to fitting symmetric bifactor models to ADHD item-level data and describe their recommended alternative approach. Third, I raise two concerns that I had with their manuscript. Fourth, I conclude with a caveat and a general question about the merits of the continued study of the factor structure of ADHD symptoms.

Applying the Bifactor S-1 Model to Ratings of ADHD/ODD Symptoms: A Commentary on Burns et al. (2019) and a Re-Analysis

To examine the construct validity of attention-deficit/hyperactivity disorder (ADHD) and oppositional defiant disorder (ODD), the bifactor S-1 approach has been applied as an alternative to the fully symmetrical bifactor models in order to eliminate anomalous results and to allow for an unambiguous interpretation of g- and s-factors. We compared and contrasted our results with those of Burns et al. (2019) and extended their analyses by taking into account a two- vs. a three-factor structure of ADHD. Data from our previous research were reanalyzed and reinterpreted in accordance with the bifactor S-1 approach, constructing different models with hyperactivity (HY), impulsivity (IM) or hyperactivity/impulsivity (HI) as the general factor. No anomalous results were observed. All factor loadings were significant. Our results were comparable to those reported by Burns et al. (2019), although items from the specific subscales inattention (IN) and ODD accounted for more variance in our sample. Model fit for our HI model was comparable to that in Burns et al. (2019). In our sample, model fit was best when solely HY or IM was chosen as a general reference factor. However, in these cases, the remaining specific factor IM or HY was weakly defined. Overall, we were able to replicate the results found by Burns et al. 2019), although our factor loadings on the g-factor were slightly lower and our specificity regarding IN and ODD was slightly higher. Our results support a two-factor structure of ADHD/ODD in a clinical population.

Factor structure and gender invariance of the Beck Depression Inventory - second edition (BDI-II) in a community-dwelling sample of adults

Objective: The main purpose of this study was to investigate the factor structure of the Beck Depression Inventory – Second Edition (BDI-II) in a sample of adults. Specifically, we evaluated the BDI-II based on confirmatory factor analysis of different measurement models, and compared the optimal factor structure of the BDI-II by gender using measurement invariance analysis.

Method: A cross-sectional survey with 717 community-dwelling adults was conducted. The Brazilian Portuguese version of the BDI-II was administered. Seven different models (one-, two-, three-factor models and their bifactor structures) were tested through CFA. CFA and multigroup analysis were executed with the software MPLUS (Weighted Least Squares Estimator – WLSMV).

Results: Four bifactor models reached acceptable fit indices. A bifactor model with two specific factors (Cognitive–Affective, and Somatic-Affective) provided the best fit to the data. The multigroup analysis of this model demonstrated invariance by gender.

Conclusions: Our findings support the use of the total BDI-II score to identify depressive symptoms, including gender comparisons. Since a bifactor structure fit the data better, the scores of the specific factors should not be used as the first choice, or at least should be used with caution. The analysis of the severity of depression, based on a total score, seems to be the most appropriate option.

How individuals change during internet-based interventions for depression: A randomized controlled trial comparing standardized and individualized feedback

BACKGROUND

Standardized and individualized Internet-based interventions (IBI) for depression yield significant symptom improvements. However, change patterns during standardized or individualized IBI are unknown. Identifying subgroups that experience different symptom courses during IBI and their characteristics is vital for improving response.

METHODS

Mildly to moderately depressed individuals according to self-report (N = 1,089) were randomized to receive module-wise feedback that was either standardized or individualized by a counselor within an otherwise identical cognitive-behavioral IBI for depression (seven modules over six weeks). Depressive symptoms were assessed at baseline and before each module (Patient Health Questionnaire; PHQ-9). Other individual characteristics (self-report) and the presence of an affective disorder (structured clinical interview) were assessed at baseline. Growth mixture modeling was used to identify and compare subgroups with discernable change patterns and associated client variables across conditions.

RESULTS

Model comparisons suggest equal change patterns in both conditions. Across conditions, a group of immediate (62.5%) and a group of delayed improvers (37.5%) were identified. Immediate improvers decreased their PHQ-9 score by 5.5 points from pre to post, with 33% of improvement occurring before treatment commenced. Delayed improvers were characterized by stable symptom severity during the first two modules and smaller overall symptom decrease (3.4 points). Higher treatment expectations, a current major depressive disorder (interview), and lower social support were associated with delayed improvement.

CONCLUSION

Internet-based interventions for depression with individualized and with standardized feedback lead to comparable patterns of change. Expectation management and bolstering of social support are promising strategies for individuals that are at risk for delayed improvement.

Health-related quality-of-life assessment in dementia: Evidence of cross-cultural validity in Latin America

All health-related quality-of-life (HRQL) measures for dementia have been developed in high-income countries and none were validated for cross-cultural use. Yet, the global majority of people living with dementia reside in low- and middle-income countries. We therefore investigated the measurement invariance of a set of self- and informant-report HRQL measures developed in the United Kingdom when used in Latin America. Self-reported HRQL was obtained using (DEMQOL) at a memory assessment service in the United Kingdom (n = 868) and a population cohort study in Latin America (n = 417). Informant reports were collected using DEMQOL-Proxy at both sites (n = 909 and n = 495). Multiple-group confirmatory bifactor models for ordered categorical item responses were estimated to evaluate measurement invariance. Results support configural, metric, and scalar invariance for the concept of general HRQL in DEMQOL and DEMQOL-Proxy. The dominant impact of general HRQL on item responses was evident across U.K. English and Ibero American Spanish versions of DEMQOL (ωh = 0.87-0.90) and DEMQOL-Proxy (ωh = 0.88-0.89). Ratings of "positive emotion" did not show a major impact on general HRQL appraisal, particularly for Latin American respondents. Item information curves show that self- and informant-reports were highly informative about the presence rather than the absence of HRQL impairment. We found no major difference in conceptual meaning, sensitivity, and relevance of DEMQOL and DEMQOL-Proxy for older adults in the United Kingdom and Latin America. Further replication is needed for consensus over which HRQL measures are appropriate for making cross-national comparisons in global dementia research. (PsycINFO Database Record (c) 2019 APA, all rights reserved).