Suicide Cognitions Scale: Psychometric Support in a Community Sample Using Bifactor Modeling and Altered Item Content

The Suicide Cognitions Scale (SCS) measures suicide-related beliefs proposed by the Fluid Vulnerability Theory. A recent investigation of a revised version of the SCS (i.e., SCS-R) which omits items explicitly referencing suicide has indicated that the measure is highly influenced by a general factor and may be useful for distinguishing severity levels of suicidal thoughts and behaviors; however, limited concurrent validity studies with a range of suicide-related experiences have been conducted. As such, this study replicated and extended previous psychometric research on the SCS-R in an online survey study with a community sample of N = 10,625 U.S. adults. Results confirmed the unidimensional structure of the SCS-R. Logistic regression analyses indicated that the total score of the SCS-R is useful in distinguishing varying levels of suicidal thoughts and behaviors such as past-month planning for suicide without attempt versus past-month suicide attempt. Implications and limitations are discussed.

The centrality of motivation in psychosocial functioning: Network and bifactor analysis of the Quality of Life Scale in first episode psychosis

Psychosocial functioning impairment is prevalent in first episode psychosis and chronic schizophrenia. The Quality of Life Scale (QLS) is a widely-used tool to measure psychosocial functioning; however, given the overlap between negative symptoms and functioning, along with the QLS being conceptualized initially as a measure of the deficit syndrome, it is unclear whether summing QLS items into a total score is an appropriate measure of overall psychosocial functioning. This study aimed to examine the centrality of QLS items and the appropriateness of using a QLS total score. Participants with first episode psychosis (n = 404) completed the QLS. Item centrality was assessed using a network analysis approach, while reliability and dimensionality of the QLS total score and subscales were measured using bifactor modeling and related psychometric indices. Network analysis results showed that an item relating to motivation was the most central item within the scale. Moreover, bifactor modeling results found that motivation and other items relating to negative symptoms may reflect the QLS total score more strongly than other functioning (i.e., Interpersonal, Instrumental) domains. Based on these findings, we urge researchers to use caution when using a QLS total score, as it may unequally confound functional domains and motivation. Moreover, our results continue to underscore the importance of negative symptoms, particularly motivational impairment, in psychosocial functioning. Future studies should aim to examine the centrality of other functioning measures in psychosis and schizophrenia, as our results suggest that psychosocial functioning may be greatly influenced by motivation.

Developmental Histories Facilitating the Emergence of Creative Scientific Expertise: The Role of Developed Cognitive Talents, Education, and Social and Cultural Contexts

Understanding how individual and contextual factors collectively contribute to the developmental histories that facilitate the emergence of creative expertise in science is improved by considering the contribution of the broad structure of developed cognitive abilities to creativity, prospective research on the high achieving or gifted students who may choose careers in and end up as creative scientists later in life, as well as retrospective studies of established creative scientists themselves and what their educational histories reveal. We first review and elaborate on these connections as documented in research which explore the development of talent, including cognitive mechanisms that include math and spatial reasoning and science related educational opportunities. We propose a research thought experiment that utilizes the multi-trait, multi-method matrix, and bifactor modeling to help understand the true overlap between measurement structures of cognitive and creative aptitudes. Then we explore the social and cultural contexts that may facilitate and/or hinder creative solutions in science through the lens of how these ecosystems influence talent development for gifted students and also the production of elite scientists. Based on this review, some policies will be suggested that may enhance the development of scientific creativity and broader societal innovation and expand the pipeline to include and fully develop the talents of disadvantaged students and provide nurturing environments to improve the likelihood of the emergence of scientific creative expertise.

The Exposome and its Associations with Broad Mental and Physical Health Measures in Early Adolescence

Environment is key to human development, yet the complex network structure of exposures (i.e., exposome) makes it challenging to investigate. Here, we analyzed data from the Adolescent Brain and Cognitive Development (ABCD) Study , a large, diverse sample of US adolescents (N=11,235, mean age=10.9, 52% male) with phenotyping at multiple levels of environmental exposure. Applying data-driven iterative factor analyses and bifactor modeling, we reduced dimensionality from hundreds of exposures to six exposome subfactors and a general (adverse) exposome factor. These factors revealed quantitative differences among racial and ethnic groups. Exposome factors increased variance explained in mental health by 10-fold (from <4% to >38%), over and above other commonly used sociodemographic factors. The general exposome factor was associated with psychopathology (Beta=0.27) and key health-related outcomes: obesity (OR=1.4) and advanced pubertal development (OR=1.3). Findings highlight the exposome role in adolescent health and demonstrate the critical need to study environment using the exposome framework.

Internal structure of Beck Hopelessness Scale: An analysis of method effects using the CT-C(M–1) model

The 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 convergent 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.

Examining the Structure of Difficulties in Emotion Regulation Scale with Chinese Population: A Bifactor Approach

The Difficulties in Emotion Regulation Scale (DERS), as one of the most frequently employed measures of emotion regulation (ER), has increasingly been used in numerous researches and applications. However, the structures derived from previous factor-analytic studies have a high degree of inconsistency. In the current study, both the traditional factor analysis method and novel (bifactor) modeling approaches were employed to examine the most optimal measurement structure of the DERS in a sample of 1036 Chinese participants. After a series of comparisons, the findings indicated that the bifactor model, with a general ER factor and four distinct subdimensions, was the most optimal structure for the DERS. Based on the study’s findings, the discussion was focused mainly on the future directions and the implications of this bifactor model. The impact and limitations of the study were also discussed, and several suggestions for future research were provided at the end of the paper.

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.