Perceptions of the Future and Health Behavior in Adulthood.

Engagement in healthier lifestyle behaviors often is motivated by a focus on the future. However, there is limited research on the associations between health behavior and future time perspective, defined as people's tendency to perceive their future as expansive or as limited. Data came from a survey of U.S. adults (N = 805, 49.3% female; M = 50 years, range: 19 to 85 years). Participants completed measures of perceptions of future opportunities and time and health behavior. Opportunities and time factors were uniquely associated with health behavior. While the perceived opportunities factor was strongly associated with better health behavior, the time factor was associated with poorer health behavior. However, this latter association was dependent on individual demographic and health status differences. These findings suggest that perceptions of future opportunities can play an important role in health behavior engagement and thus represent an important target for health promotion.

A longitudinal person-centered investigation of the multidimensional nature of employees' perceptions of challenge and hindrance demands at work.

BACKGROUND AND OBJECTIVES: This research relies on a combination of variable- and person-centered approaches to help improve our understanding of the dimensionality of job demands by jointly considering employees' global levels of job demands, exposure and their specific levels of exposure to challenge and hindrance demands. DESIGN AND METHODS: We relied on a sample of 442 workers who completed a questionnaire twice over three months. Our analyses sought to identify the nature of the job demands profiles experienced by these workers, to document the stability of these profiles over time, and to assess their associations with theoretically-relevant outcomes (i.e., work engagement, job boredom, problem-solving pondering, work-related rumination, proactive health behaviors, and sleep quality and quantity). Furthermore, we examined whether these profiles and associations differed as a function of working remotely or onsite. RESULTS: Five profiles were identified and found to be highly stable over time: Globally Exposed, Not Exposed, Not Exposed but Challenged, Exposed but Not Challenged, and Mixed. These profiles shared clear associations with all outcomes, with the most adaptive outcomes associated with the Exposed but Not Challenged profile, whereas the most detrimental ones were observed in the Mixed profile. However, none of these results differed across employees working onsite and those working remotely. CONCLUSIONS: These findings have theoretical and practical implications regarding the effects of work characteristics on employees' functioning.

Are We Measuring ADHD or Anxiety? Examining the Factor Structure and Discriminant Validity of the Adult ADHD Self-Report Scale in an Adult Anxiety Disorder Population.

Adults with clinical anxiety have significant symptom overlap and above average rates of attention-deficit/hyperactivity disorder (ADHD). Despite this, ADHD remains a vastly under-detected disorder among this population, indicating the need for a screener with well-understood symptom dimensions and good discriminant validity. The current study compared competing models of ADHD as well as discriminant properties of self-reported ADHD symptoms as measured by the Adult ADHD Self-Report Scale (ASRS-v1.1) in 618 adults with clinical anxiety. A three-factor correlated model of Inattention, Impulsivity, and Hyperactivity, with the movement of one item, talks excessively, to a factor of Impulsivity from Hyperactivity fit better than the one-factor, two-factor, and traditional three-factor models of ADHD. Discriminant properties of the screener were fair to good against measures of clinical anxiety and distress; however, some items within the Hyperactivity factor (e.g., difficulty relaxing; feeling driven by a motor) loaded more strongly onto factors of clinical anxiety than ADHD when measures were pooled together. These results suggest that clinicians making differential diagnoses between adult ADHD and anxiety or related disorders should look for evidence of ADHD beyond the overlapping symptoms, particularly for those within the Hyperactivity factor.

A General Theorem and Proof for the Identification of Composed CFA Models.

In this article, we present a general theorem and proof for the global identification of composed CFA models. They consist of identified submodels that are related only through covariances between their respective latent factors. Composed CFA models are frequently used in the analysis of multimethod data, longitudinal data, or multidimensional psychometric data. Firstly, our theorem enables researchers to reduce the problem of identifying the composed model to the problem of identifying the submodels and verifying the conditions given by our theorem. Secondly, we show that composed CFA models are globally identified if the primary models are reduced models such as the CT-C[Formula: see text] model or similar types of models. In contrast, composed CFA models that include non-reduced primary models can be globally underidentified for certain types of cross-model covariance assumptions. We discuss necessary and sufficient conditions for the global identification of arbitrary composed CFA models and provide a Python code to check the identification status for an illustrative example. The code we provide can be easily adapted to more complex models.

What are the consequences of ignoring cross-loadings in bifactor models? A simulation study assessing parameter recovery and sensitivity of goodness-of-fit indices.

Bifactor latent models have gained popularity and are widely used to model construct multidimensionality. When adopting a confirmatory approach, a common practice is to assume that all cross-loadings take zero values. This article presents the results of a simulation study exploring the impact of ignoring non-zero cross-loadings on the performance of confirmatory bifactor analysis. The present work contributes to previous research by including study conditions that had not been examined before. For instance, a wider range of values of the factor loadings both for the group factors and the cross-loadings is considered. Parameter recovery is analyzed, but the focus of the study is on assessing the sensitivity of goodness-of-fit indices to detect the model misspecification that involves ignoring non-zero cross-loadings. Several commonly used SEM fit indices are examined: both biased estimators of the fit index (CFI, GFI, and SRMR) and unbiased estimators (RMSEA and SRMR). Results indicated that parameter recovery worsens when ignoring moderate and large cross-loading values and using small sample sizes, and that commonly used SEM fit indices are not useful to detect such model misspecifications. We recommend the use of the unbiased SRMR index with a cutoff value adjusted by the communality level (R 2), as it is the only fit index sensitive to the model misspecification due to ignoring non-zero cross-loadings in the bifactor model. The results of the present study provide insights into modeling cross-loadings in confirmatory bifactor models but also practical recommendations to researchers.

Direct and Indirect Associations of Widespread Individual Differences in Brain White Matter Microstructure With Executive Functioning and General and Specific Dimensions of Psychopathology in Children.

BACKGROUND: Executive functions (EFs) are important partly because they are associated with risk for psychopathology and substance use problems. Because EFs have been linked to white matter microstructure, we tested the prediction that fractional anisotropy (FA) and mean diffusivity (MD) in white matter tracts are associated with EFs and dimensions of psychopathology in children younger than the age of widespread psychoactive substance use. METHODS: Parent symptom ratings, EF test scores, and diffusion tensor parameters from 8588 9- to 10-year-olds in the ABCD Study (Adolescent Brain Cognitive Development Study) were used. RESULTS: A latent factor derived from EF test scores was significantly associated with specific conduct problems and attention-deficit/hyperactivity disorder problems, with dimensions defined in a bifactor model. Furthermore, EFs were associated with FA and MD in 16 of 17 bilateral white matter tracts (range: ß = .05; SE = .17; through ß = -.31; SE = .06). Neither FA nor MD was directly associated with psychopathology, but there were significant indirect associations via EFs of both FA (range: ß = .01; SE = .01; through ß = -.09; SE = .02) and MD (range: ß = .01; SE = .01; through ß = .09; SE = .02) with both specific conduct problems and attention-deficit/hyperactivity disorder in all tracts except the forceps minor. CONCLUSIONS: EFs in children are inversely associated with diffusion tensor imaging measures in nearly all tracts throughout the brain. Furthermore, variance in diffusion tensor measures that is shared with EFs is indirectly shared with attention-deficit/hyperactivity disorder and conduct problems.

Assessing Language Skills Using Diagnostic Classification Models: An Example Using a Language Instrument.

The primary purpose of the present study is to inform and illustrate, using examples, the use of Diagnostic Classification Models (DCMs) for the assessment of skills and competencies in cognition and academic achievement. A secondary purpose is to compare and contrast traditional and contemporary psychometrics for the measurement of skills and competencies. DCMs are described along the lines of other psychometric models within the Confirmatory Factor Analysis tradition such as the bifactor model and the known mixture models that are utilized to classify individuals into subgroups. The inclusion of interaction terms and constraints along with its confirmatory nature enables DCMs to accurately assess the possession of skills and competencies. The above is illustrated using an empirical dataset from Saudi Arabia (n = 2642), in which language skills are evaluated on how they conform to known levels of competency based on the CEFR (Council of Europe, 2001) using the English Proficiency Test (EPT).

El propósito principal del presente estudio fue informar e ilustrar, mediante ejemplos, el uso de Modelos de Clasificación Diagnóstica (DCM) para la evaluación de habilidades y competencias en cognición y rendimiento académico. Un propósito secundario fue comparar y contrastar la psicometría tradicional y contemporánea para la medición de habilidades y competencias. Los DCM se describen siguiendo las líneas de otros modelos psicométricos dentro de la tradición del Análisis Factorial Confirmatorio, como el modelo bifactor y los conocidos modelos mixtos que se utilizan para clasificar a los individuos en subgrupos. La inclusión de términos y restricciones de interacción junto con su naturaleza confirmatoria permite a los DCM evaluar con precisión la posesión de habilidades y competencias. Lo anterior se ilustra utilizando un conjunto de datos empíricos de Arabia Saudita (n = 2642), que evalúan cómo las habilidades lingüísticas se ajustan a los niveles de competencia conocidos, basados en el MCER (Council of Europe, 2001).

Examining the underlying latent structure of the sports emotion questionnaire: Insights from the bifactor multidimensional item response theory.

Background: Despite the widespread use of the sports emotion questionnaire (SEQ) in several studies, it is surprising that only a few have explicitly tested the validity and utility of the instrument in non-western populations. Besides, the issue of dimensionality and the latent structure of the instrument remain inconclusive given that several authors have revealed different factor structures across diverse populations. The central concern is whether the items on the various dimensions, proposed for the original SEQ, offer adequate information to their respective expected subscale or otherwise. This study assessed the underlying latent structure of the SEQ using confirmatory and bifactor multidimensional item response (MIRT) models. Methods: Through a well-designed validation study 300 athletes from three West African countries, participating in the 2018 West African University Games were surveyed to respond to the SEQ. The data were analyzed using first, a 5-factor confirmatory factor analysis (CFA) via the MIRT model and second, a bifactor MIRT analysis. Results: The results revealed that items on the SEQ were fairly good in measuring the construct under the respective domains of the instrument. However, the outcome of the bifactor model showed that the majority of the items on the SEQ explained common variance in relation to the general factor other than the specific domains (5-dimensions). Conclusion: Findings of the bifactor model question whether the sub-dimensions of the SEQ are needed since most of the items on the SEQ explained larger variances in the general factor than any of the five domains. It is concluded that instruments like SEQ should be scored for a general factor and not as sub-dimensions. Further investigations are encouraged by scholars within the area to probe the dimensionality of the SEQ.

Complementary variable- and person-centered approaches to the dimensionality of burnout among fire station workers.

This research relies on variable- and person-centered approaches to illustrate how each of these approaches may help to improve our understanding of the dimensionality of the burnout construct. Both studies (Study 1: N = 247 administrative and technical employees; Study 2: N = 654 firefighters), showed that employees' burnout ratings simultaneously reflected a global overarching construct co-existing with two specific dimensions (cynicism and emotional exhaustion), with a distinct factor reflecting reduced professional efficacy. In Study 1, perceived supervisor recognition and job satisfaction were associated with lower levels of global burnout levels. In Study 2, we examined the configurations, or profiles, taken by burnout dimensions (global burnout, specific cynicism, specific emotional exhaustion, and reduced professional efficacy), and documented associations between these profiles and four covariates (organizational, supervisor, and colleagues recognition as well as job satisfaction). Five profiles were identified using latent profile analyses: Very Low Burnout Risk, Mentally Distanced, Low Burnout Risk, High Burnout Risk, and Moderately High Burnout Risk. Employees' perceptions of supervisor and colleagues recognition were related to their likelihood of profile membership. Employees' job satisfaction levels also differed as a function of their profile.

Multidimensional structure and measurement invariance of school engagement.

This study examined the multidimensional structure and measurement invariance of a school engagement instrument using confirmatory factor analysis (CFA), exploratory structural equation modeling (ESEM), bifactor CFA (BCFA), and bifactor ESEM (BESEM). Participants consisted of 1731 students in Grades 9 - 11 from the 4-H Study of Positive Youth Development in the United States. The use of the CFA, ESEM, BCFA, and BESEM models was expected to provide more insight into the cross-loading and hierarchical structures of school engagement. We found empirical evidence to support the (a) tripartite factor structure of school engagement, (b) existence of cross-loadings and hierarchical structures, (c) measurement invariance across gender (male vs female) and race (European American vs African American), and (d) expected latent means differences by gender.

Evidence for a Bifactor Structure of the Caregiving Questionnaire with Individuals Involved in Different and Same-Sex Couple Relationships.

Despite the Caregiving Questionnaire (CQ) being a widely used measure for the study of caregiving behavior in the context of romantic relationships, to date, few studies have focused on empirically evaluating its underlying theoretical structure. The aim of this study was to examine the factorial structure and equivalence across sex and sexual orientation of this instrument. A sample of 912 Chilean individuals currently involved in a couple relationship completed the Caregiving Questionnaire and the Experiences in Close Relationship Scale. After comparing various traditional Confirmatory Factor Analysis (CFA)models, the results provide support for a multidimensional and hierarchical nature of a brief 16-items version of the CQ. More specifically, the analyses supported a bifactor-CFA solution composed of two global factors and four specific factors, suggesting that they add information to the caregiving construct in the context of couple relationships. Additionally, the scale showed measurement invariance across sex and sexual orientation. Finally, significant associations were found between CQ scores with measures of romantic attachment in the expected directions. Theoretical implications about the nature of the caregiving system are discussed.

Calibrating the Test of Relational Reasoning: New Information From Oblique Bifactor Models.

Relational reasoning (RR) is believed to be an essential construct for studying higher education learning. Relational reasoning is defined as an ability to discern meaningful patterns within any stream of information. Nonetheless, studies of RR are limited by the psychometric structure of the construct. For many instances, the composite nature of RR has been described as a bifactor structure. Bifactor models limit possibilities for studying the inner structure of composite constructs by demanding orthogonality of latent dimensions. Such assumption severely limits the interpretation of the results when it is applied to psychological constructs. However, over the last 10 years, advances in the fields of Rasch measurement led to the development of the oblique bifactor models, which relax the constraints of the orthogonal bifactor models. We show that the oblique bifactor models exhibit model fit, which is superior compared to the orthogonal bifactor model. Then, we discuss their interpretation and demonstrate the advantages of these models for investigating the inner structure of the test of RR. The data are a nationally representative sample of Russian engineering students (N = 2,036).

The Dimensionality of the 12-Item General Health Questionnaire (GHQ-12): Comparisons of Factor Structures and Invariance Across Samples and Time.

Because of its brevity, the 12-item General Health Questionnaire (GHQ-12) has become one of the most popular and used measure for detecting psychological distress. Originally intended as a unidimensional measure, the majority of subsequent factor-analytic studies have failed to support GHQ-12 as a unitary construct and have instead proposed a plethora of multidimensional structures. In this study, we further examined the factor structure in two different military samples, one consisting of crewmembers from four different frigates deployed in anti-piracy operations and Standing NATO Maritime Group deployments (N = 591) and one consisting of crewmember from three different minehunters/sweepers serving in Standing NATO Mine Counter-Measures Group deployments (N = 196). Results from confirmatory factor analyses (CFA) performed in the first sample supported a bifactor model, consisting of a general factor representing communality among all items and two specific factors reflecting common variance due to wording effects (negatively and positively phrased items). A multi-group CFA further confirmed this structure to be invariant across our second sample. Structural equation modeling also showed that the general factor was strongly associated with symptoms of insomnia and mental health, whereas the specific factors were either non-significantly or considerably weaker associated with the criterion variables. Overall, our results are congruent with the notion that the multidimensionality demonstrated in many previous investigations is most likely an expression of method-specific variance caused by item wording. The explained unique variance associated with these specific factors was further relatively small. Ignoring the multidimensionality and treating GHQ-12 as a unitary construct will therefore most likely introduce minimal bias to most practical applications.

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.

The General Factor of Psychopathology.

An important advance in understanding and defining mental disorders has been the development of empirical approaches to mapping dimensions of dysfunction and their interrelatedness. Such empirical approaches have consistently observed intercorrelations among the many forms of psychopathology, leading to the identification of a general factor of psychopathology (the p factor). In this article, we review empirical support for p, including evidence for the stability and criterion validity of p. Further, we discuss the strong relationship between p and both the general factor of personality and the general factor of personality disorder, substantive interpretations of p, and the potential clinical utility of p. We posit that proposed substantive interpretations of p do not explain the full range of symptomatology typically included in p. The most plausible explanation is that p represents an index of impairment that has the potential to inform the duration and intensity of a client's mental health treatment.

Toward precision therapeutics: general and specific factors differentiate symptom change in depressed adolescents.

BACKGROUND: The longitudinal course of multiple symptom domains in adolescents treated for major depression is not known. Revealing the temporal course of general and specific psychopathology factors, including potential differences between psychotherapies, may aid therapeutic decision-making. METHODS: Participants were adolescents with major depressive disorder (aged 11-17; 75% female; N = 465) who were part of the IMPACT trial, a randomized controlled trial comparing cognitive behavioral therapy, short-term psychoanalytic psychotherapy, and brief psychosocial intervention. Self-reported symptoms at baseline and 6, 12, 36, 52, and 86 weeks postrandomization were analyzed with bifactor modeling. RESULTS: General psychopathology factor scores decreased across treatment and one-year follow-up. Specific melancholic features and depressive cognitions factors decreased from baseline to 6 weeks. Conduct problems decreased across treatment and follow-up. Anxiety increased by 6 weeks and then reverted to baseline levels. Obsessions-compulsions did not change. Changes in general and specific factors were not significantly different between the three psychotherapies during treatment. During follow-up, however, conduct problems decreased more in brief psychosocial intervention versus cognitive behavioral therapy (1.02, 95% Bayes credible interval 0.25, 1.96), but not versus short-term psychoanalytic psychotherapy. CONCLUSIONS: The clinical response signature in this trial is best revealed by rapid reductions in depression symptoms and general psychopathology. Protracted improvements in general psychopathology and conduct problems subsequently occur. Psychosocial treatments for adolescent depression have comparable effects on general and specific psychopathology, although a psychoeducational, goal-focused approach may be indicated for youth with comorbid conduct problems.

Giving G a Meaning: An Application of the Bifactor-(S-1) Approach to Realize a More Symptom-Oriented Modeling of the Beck Depression Inventory-II.

The Beck Depression Inventory-II is one of the most frequently used scales to assess depressive burden. Despite many psychometric evaluations, its factor structure is still a topic of debate. An increasing number of articles using fully symmetrical bifactor models have been published recently. However, they all produce anomalous results, which lead to psychometric and interpretational difficulties. To avoid anomalous results, the bifactor-(S-1) approach has recently been proposed as alternative for fitting bifactor structures. The current article compares the applicability of fully symmetrical bifactor models and symptom-oriented bifactor-(S-1) and first-order confirmatory factor analysis models in a large clinical sample (N = 3,279) of adults. The results suggest that bifactor-(S-1) models are preferable when bifactor structures are of interest, since they reduce problematic results observed in fully symmetrical bifactor models and give the G factor an unambiguous meaning. Otherwise, symptom-oriented first-order confirmatory factor analysis models present a reasonable alternative.

Factor Structure and Measurement Invariance Across Gender of the Beck Depression Inventory-II in Adolescent Psychiatric Patients.

The revised version of the Beck Depression Inventory (BDI-II) is one of the most frequently applied questionnaires not only in adults, but also in adolescents. To date, attempts to identify a replicable factor structure of the BDI-II have mainly been undertaken in adult populations. Moreover, most of the studies which included minors and were split by gender lacked confirmatory factor analyses and were generally conducted in healthy adolescents. The present study therefore aimed to determine the goodness of fit of various factor models proposed in the literature in an adolescent clinical sample, to evaluate alternative solutions for the factor structure and to explore potential gender differences in factor loadings. The focus was on testing bifactor models and subsequently on calculating bifactor statistical indices to help clarify whether a uni- or a multidimensional construct is more appropriate, and on testing the best-fitting factor model for measurement invariance according to gender. The sample comprised 835 adolescent girls and boys aged 13-18 years in out- and inpatient setting. Several factor models proposed in the literature provided a good fit when applied to the adolescent clinical sample, and differences in goodness of fit were small. Exploratory factor analyses were used to develop and test a bifactor model that consisted of a general factor and two specific factors, termed cognitive and somatic. The bifactor model confirmed the existence of a strong general factor on which all items load, and the bifactor statistical indices suggest that the BDI-II should be seen as a unidimensional scale. Concerning measurement invariance across gender, there were differences in loadings on item 21 (Loss of interest in sex) on the general factor and on items 1 (Sadness), 4 (Loss of pleasure), and 9 (Suicidal Thoughts) on the specific factors. Thus, partial measurement invariance can be assumed and differences are negligible. It can be concluded that the total score of the BDI-II can be used to measure depression severity in adolescent clinical samples.

Modeling the Structure of the Triarchic Psychopathy Measure: Conceptual, Empirical, and Analytic Considerations.

This study sought to characterize the factor structure of the Triarchic Psychopathy Measure (TriPM) using data from a sample of 1,082 community-dwelling Italian adults. Exploratory structural equation modeling (ESEM) was used to compare the fit of a bifactor model for each TriPM scale, in which specific-content factors were specified along with a general factor, with the fit of a single, general-factor model. Robust weighted least square (WLSMV) ESEM supported a bifactor latent structure of the TriPM items for all individual scales. When we jointly factor analyzed the 58 TriPM items, a WLSMV ESEM three-factor structure showed adequate fit; the three ESEM factors were akin to TriPM Boldness, Meanness, and Disinhibition theoretical dimensions, respectively, and could be effectively replicated across gender subgroups. Our findings support the three-factor structure of TriPM items, at least in Italian community-dwelling adults, and provide further evidence for the construct validity of the TriPM.