Back to “the Future”: Evidence of a Bifactor Solution for Scores on the Consideration of Future Consequences Scale

Despite its widespread use, disagreement remains regarding the structure of the Consideration of Future Consequences Scale (CFCS). In particular there is disagreement regarding whether the scale assesses future orientation as a unidimensional or multidimensional (immediate and future) construct. Using 2 samples of high school students in the United Kingdom, 4 models were tested. The totality of results including item loadings, goodness-of-fit indexes, and reliability estimates all supported the bifactor model, suggesting that the 2 hypothesized factors are better understood as grouping or method factors rather than as representative of latent constructs. Accordingly this study supports the unidimensionality of the CFCS and the scoring of all 12 items to produce a global future orientation score. Researchers intending to use the CFCS, and those with existing data, are encouraged to examine a bifactor solution for the scale.     

Present and future temporal profiles and their relationship to health intentions and behaviors: A test on a Norwegian general population sample

We investigated the temporal profiles of a Norwegian general population sample and their relation to health behaviors and intentions. The profiles were based on variables from the present and future dimensions of the Zimbardo Time Perspective Inventory (ZTPI), the Consideration of Future Consequences Scale (CFCS), and the combination of both scales. The analysis revealed that there were only two stable clusters that corresponded to the present and the future profiles. Generally, CFCS‐based present and future profiles were more effective at predicting health behaviors and intentions than ZTPI‐based profiles. Profiles based on the CFCS variables were more predictive of eating behaviors. However, the profiles based on the combination of both CFCS and ZTPI were more predictive of smoking, exercising, and health intentions than the profiles based solely on the CFCS. The variation in walking was explained only by the profiles based on a combination of CFCS and ZTPI.     

Relationships between general self-efficacy,planning for the future,and life satisfaction

In this study we investigated relationships between general self-efficacy, the propensity to plan for the future, the consideration of future consequences, and overall life satisfaction. The sample consisted of 242 university students, with ages ranging from 16 to 31 (M = 18.5, SD = 1.7). Participants completed the New General Self-Efficacy Scale (NGSES), the Continuous Planning Scale (CPS), the Consideration of Future Consequences Scale (CFCS), and the Satisfaction with Life Scale (SWLS). Analyses demonstrated that all variables were significantly intercorrelated, with general self-efficacy being most strongly related to the SWLS, followed by the CFCS and the CPS. Implications are discussed.     

项目表述效应对人格测验信度和效标效度的影响——以核心自我评价量表(CSES)为例

项目表述效应是指由项目表述方式的差异引起的与测量内容无关的系统变异,项目表述效应模型的统计本质是一种双因子模型。本研究以核心自我评价量表(CSES)为例,探讨项目表述效应对人格测验信效度的影响。采用核心自我评价量表、生活满意度量表和积极情感消极情感量表对340名“蚁族”进行测查。结果表明,CSES在核心自我评价特质以外,还存在一个反向题项目表述效应因子;忽视项目表述效应对CSES的同质性信度和效标关联效度有重要影响：高估CSES的同质性信度,低估核心自我评价与生活满意度、积极情感的正相关,高估核心自我评价与消极情感的负相关。     

The Rosenberg Self-Esteem Scale: A Bifactor Answer to a Two-Factor Question?

Despite its long-standing and widespread use, disagreement remains regarding the structure of the Rosenberg Self-Esteem Scale (RSES). In particular, concern remains regarding the degree to which the scale assesses self-esteem as a unidimensional or multidimensional (positive and negative self-esteem) construct. Using a sample of 3,862 high school students in the United Kingdom, 4 models were tested: (a) a unidimensional model, (b) a correlated 2-factor model in which the 2 latent variables are represented by positive and negative self-esteem, (c) a hierarchical model, and (d) a bifactor model. The totality of results including item loadings, goodness-of-fit indexes, reliability estimates, and correlations with self-efficacy measures all supported the bifactor model, suggesting that the 2 hypothesized factors are better understood as “grouping” factors rather than as representative of latent constructs. Accordingly, this study supports the unidimensionality of the RSES and the scoring of all 10 items to produce a global self-esteem score.     

Eat now,exercise later: The relation between consideration of immediate and future consequences and healthy behavior

In light of the current obesity epidemic, individual choices for food and exercise should be understood better. Consideration of the immediate and future consequences of these choices (i.e., time orientation) can be an important predictor of eating and exercising behavior. The objective was to show that behavior-specific time orientation differentially predicts eating and exercising behavior. Two studies were conducted among students (N = 55) and the general public (N = 165). Participants completed two adapted versions (for food and exercise) of the Consideration of Future Consequences Scale (CFC), each consisting of the subscales CFC-future and CFC-immediate. Thereafter they reported their eating and exercising behavior. Study 1 showed that CFC-food, but not CFC-exercise, predicted eating behavior. Similarly, both studies showed that CFC-exercise, but not CFC-food, predicted exercising behavior. Moreover, eating behavior was predicted by CFC-food/immediate, whereas exercising behavior was predicted by CFC-exercise/future. In conclusion, behavior-specific time orientation predicts behavior within a behavioral domain but less well across behavioral domains. Additionally, consideration of immediate and future consequences differentially predict behavior across behavioral domains. In order to predict behavior, time orientation is measured best at a behavior-specific level.     

Bifactor models and rotations: exploring the extent to which multidimensional data yield univocal scale scores

The application of psychological measures often results in item response data that arguably are consistent with both unidimensional (a single common factor) and multidimensional latent structures (typically caused by parcels of items that tap similar content domains). As such, structural ambiguity leads to seemingly endless "confirmatory" factor analytic studies in which the research question is whether scale scores can be interpreted as reflecting variation on a single trait. An alternative to the more commonly observed unidimensional, correlated traits, or second-order representations of a measure's latent structure is a bifactor model. Bifactor structures, however, are not well understood in the personality assessment community and thus rarely are applied. To address this, herein we (a) describe issues that arise in conceptualizing and modeling multidimensionality, (b) describe exploratory (including Schmid-Leiman [Schmid & Leiman, 1957] and target bifactor rotations) and confirmatory bifactor modeling, (c) differentiate between bifactor and second-order models, and (d) suggest contexts where bifactor analysis is particularly valuable (e.g., for evaluating the plausibility of subscales, determining the extent to which scores reflect a single variable even when the data are multidimensional, and evaluating the feasibility of applying a unidimensional item response theory (IRT) measurement model). We emphasize that the determination of dimensionality is a related but distinct question from either determining the extent to which scores reflect a single individual difference variable or determining the effect of multidimensionality on IRT item parameter estimates. Indeed, we suggest that in many contexts, multidimensional data can yield interpretable scale scores and be appropriately fitted to unidimensional IRT models.     

预测视角下双因子模型与高阶因子模型的一般性模拟比较

高阶因子模型本质上是一种特殊的双因子模型, 应用中却常被当做双因子模型的竞争模型。已有研究以满足比例约束的双因子模型(此时等价于一个高阶因子模型)为真实测量模型产生模拟数据, 比较了用双因子模型和高阶因子模型作为测量模型的预测效果。本文使用不满足比例约束的双因子模型(此时不与任何高阶因子模型等价)为真实测量模型产生模拟数据进行比较, 所得结果与满足比例约束的双因子模型的结果有很大差别, 双因子模型结构系数的相对偏差较小、检验力较高, 但第Ⅰ类错误率略高。结论是, 在比例约束条件成立时可以使用高阶因子模型, 否则, 从统计角度看, 一般情况下使用双因子模型进行预测比较好。     

Repetitive Thinking in Social Anxiety Disorder: Are Anticipatory Processing and Post-Event Processing Facets of an Underlying Unidimensional Construct?

Existing literature suggests that anticipatory processing and post-event processing—two repetitive thinking processes linked to social anxiety disorder (SAD)—might be better conceptualized as facets of an underlying unidimensional repetitive thinking construct. The current study tested this by examining potential factor structures underlying anticipatory processing and post-event processing. Baseline data from two randomized controlled trials, consisting of 306 participants with SAD who completed anticipatory processing and post-event processing measures in relation to a speech task, were subjected to confirmatory factor analysis. A bifactor model with a General Repetitive Thinking factor and two group factors corresponding to anticipatory processing and post-event processing best fit with the data. Further analyses indicated an optimal model would include only the General Repetitive Thinking factor (reflecting anticipatory processing and a specific aspect of post-event processing) and Post-event Processing group factor (reflecting another specific aspect of post-event processing that is separable), providing evidence against a unidimensional account of repetitive thinking in SAD. Analyses also indicated that the General Repetitive Thinking factor had moderately large associations with social anxiety and life interference (rs = .43 to .47), suggesting its maladaptive nature. The separable Post-event Processing group factor only had small associations with social anxiety (rs = .16 to .27) and was not related to life interference (r = .11), suggesting it may not, in itself, be a maladaptive process. Future research that further characterises the bifactor model components and tests their utility has the potential to improve the conceptualisation and assessment of repetitive thinking in SAD.     

Time orientation and health-related behaviour: Measurement in general population samples

Research on health behaviour and time orientation has been hindered by a lack of consensus about appropriate measurement. Study 1 assessed the reliability of the Consideration of Future Consequences Scale (CFC) and the Zimbardo Time Perspective Inventory (ZTPI) in a general population sample (n?=?300). Although more reliable, the CFC was less readable. Study 2 assessed the validity of a shortened ZTPI, measuring future and present orientation, and the full CFC. The measures had good discrimination to distinguish interpersonal differences. Construct validity of present, but not future, orientation as measured by the ZTPI, was evidenced by its mediation of the association between socioeconomic status and expectations of participating in diabetes screening. The CFC mediated this relationship more weakly. Further investigation of present orientation in understanding health-related behaviour is warranted.     

The PANAS structure revisited: on the validity of a bifactor model in community and forensic samples

The Positive and Negative Affect Schedule (PANAS) is a widely used inventory for the assessment of affect in psychology and other applied sciences. Despite its popularity, the structure of the PANAS is still under debate. On the one hand, there is evidence of the traditional 2-factor model with Positive Affect (PA) and Negative Affect (NA) as uncorrelated factors. On the other hand, a more complex structure of the PANAS has been discussed. To shed further light on the core dimensions of the PANAS, 2 studies investigated the structure of the PANAS in 2 German samples (N = 354 and N = 364, respectively) by means of confirmatory factor analysis. The factor analysis results of Study 1 for a traitlike time frame instruction suggested a suboptimal model fit for the uncorrelated 2-factor model and the 3-factor model with PA, Afraid, and Upset as factors, whereas a superior model fit occurred for a bifactor model with traitlike PA, NA, and a general 3rd factor named Affective Polarity. In Study 2, the bifactor model was replicated for a statelike PANAS time frame instruction and evidence of criterion validity was provided for PA, NA, and Affective Polarity factors in 2 sex offender subgroups and in a community sample. With Affective Polarity, we introduce an affect dimension that captures additional variance beyond PA and NA. Because of the adjectives with relevant loadings on Affective Polarity, this general factor represents an individual's orientation toward approach and withdrawal, respectively.     

Examining the Factor Structure of the Self-Compassion Scale in Four Distinct Populations: Is the Use of a Total Scale Score Justified?

This study examined the factor structure of the Self-Compassion Scale (SCS) using a bifactor model, a higher order model, a 6-factor correlated model, a 2-factor correlated model, and a 1-factor model in 4 distinct populations: college undergraduates (N = 222), community adults (N = 1,394), individuals practicing Buddhist meditation (N = 215), and a clinical sample of individuals with a history of recurrent depression (N = 390). The 6-factor correlated model demonstrated the best fit across samples, whereas the 1- and 2-factor models had poor fit. The higher order model also showed relatively poor fit across samples, suggesting it is not representative of the relationship between subscale factors and a general self-compassion factor. The bifactor model, however, had acceptable fit in the student, community, and meditator samples. Although fit was suboptimal in the clinical sample, results suggested an overall self-compassion factor could still be interpreted with some confidence. Moreover, estimates suggested a general self-compassion factor accounted for at least 90% of the reliable variance in SCS scores across samples, and item factor loadings and intercepts were equivalent across samples. Results suggest that a total SCS score can be used as an overall mesure of self-compassion.     

Modeling the Balanced Inventory of Desirable Responding: Evidence in Favor of a Revised Model of Socially Desirable Responding

Paulhus (1984) proposed a 2-factor model of socially desirable responding (SDR) and created the Balanced Inventory of Desirable Responding (BIDR) to capture the 2 dimensions: self-deceptive enhancement and impression management. However, the 2-factor model has yet to be supported via confirmatory factor analysis (CFA) of the BIDR. Paulhus and Reid (1991) proposed a revised model of SDR, which bifurcated the self-deceptive enhancement dimension into 2 factors: self-deceptive enhancement (SDE; positively keyed items) and self-deceptive denial (SDD; negatively keyed items). Thus, it was considered useful to test the revised SDR model on the BIDR, as this might have implications for the manner in which the BIDR should be scored. Additionally, as the BIDR subscales might be positively correlated, it was considered useful from a both a theoretical and practical perspective to test the possibility that the BIDR might measure a general SDR process. Based on a sample of 466 adults, Paulhus and Reid's revised model of SDR was largely supported when tested via CFA on a bifactor model, which included a first-order general SDR factor and 2 nested factors. Thus, applied researchers might consider using total BIDR composite scores, a self-deceptive enhancement composite score (positively keyed items), and impression management composite scores. However, ideally, researchers would use a bifactor model to test substantive hypotheses, as the bifactor model partitions true score variance into unique sources, which facilitates less ambiguous interpretations of effects.     

The structure of childhood disruptive behaviors

Attention-deficit/hyperactivity disorder (ADHD) and oppositional defiant disorder (ODD) frequently co-occur. Comorbidity of these 2 childhood disruptive behavior domains has not been satisfactorily explained at either a structural or etiological level. The current study evaluated a bifactor model, which allows for a "g" factor in addition to distinct component factors, in relation to other models to improve understanding of the structural relationship between ADHD and ODD. Participants were 548 children (321 boys, 227 girls) between the ages of 6 years and 18 years who participated in a comprehensive diagnostic assessment incorporating parent and teacher ratings of symptoms. Of these 548 children, 153 children were diagnosed with ADHD (without ODD), 114 children were diagnosed with ADHD + ODD, 26 children were diagnosed with ODD (without ADHD), and 239 children were classified as non-ADHD/ODD comparison children (including subthreshold cases). ADHD symptoms were assessed via parent report on a diagnostic interview and via parent and teacher report on the ADHD Rating Scale. ODD symptoms were assessed via teacher report. A bifactor model of disruptive behavior, comprising a "g" factor and the specific factors of ADHD and ODD, exhibited best fit, compared to 1-factor, 2-factor, 3-factor, and 2nd-order factor models of disruptive behaviors. It is concluded that a bifactor model of childhood disruptive behaviors is superior to existing models and may help explain common patterns of comorbidity between ADHD and ODD.     

Factor validation of the Consideration of Future Consequences Scale: evidence for a short version

The author examined the factor structure of the 12-item Consideration of Future Consequences (CFC) Scale (A. Strathman, F. Gleicher, D. S. Boninger, & S. Edwards, 1994) among 664 undergraduate university students enrolled in human development courses. A principal-components factor analysis with varimax rotation yielded 2 factors. The author used confirmatory factor analysis procedures to examine the fit of 4 models, according to the principal-components factor analysis findings, with the observed covariance. The author used a number of fit indices to compare the 4 models. Both sets of analysis provided the greatest support for an 8-item short version of the CFC Scale. The author discussed findings in regard to the CFC Scale as an instrument to measure future time perspective.     

Evaluation of the Bifactor Structure of the Dispositional Hope Scale

The Dispositional Hope Scale (DHS; Snyder et al., 1991) is composed of items assessing an individual's perception of his or her agency and pathways. This study examined support for the bifactor structure and relation of the factors in this model with depressive symptoms. It also examined cross-gender measurement invariance for the bifactor model. A community sample of 413 women and 257 men completed the DHS. Confirmatory factor analysis indicated more support for the bifactor model than the 1- and 2-factor models. Results also indicated full measurement invariance across gender for the bifactor and the 2-factor models. The general and the specific agency factors, but not the specific pathways factor, correlated with depressive symptoms. The better support for the bifactor model suggests that ideally hope has to be measured and examined by factors reflecting high covariance for agency and pathways, and also factors reflecting unique variances for agency and pathways. The support for full cross-gender measurement invariance indicated that there are no differences in measurement and scaling properties for the DHS across ratings provided by women and men, and therefore the DHS ratings can be scored in the same way for women and men.     

A bifactor model of negative affectivity: fear and distress components among younger and older youth

The Positive and Negative Affect Schedule for Children (PANAS-C) is a 27-item youth-report measure of positive affectivity and negative affectivity. Using 2 large school-age youth samples (clinic-referred sample: N = 662; school-based sample: N = 911), in the present study, we thoroughly examined the structure of the PANAS-C NA and PA scales and fit a bifactor model to the PANAS-C NA items. Our exploratory factor analytic results demonstrated that negative affectivity is comprised of 2 main components-NA: Fear and NA: Distress-specifically among older youth. A bifactor model also evidenced the best model fit relative to a unidimensional and second-order factor structure of the PANAS-C NA items. The NA: Fear group factor evidenced significant correspondence with external criterion measures of anxiety. However, the original PANAS-C NA scale evidenced equal (and in some cases greater) correspondence with criterion measures of anxiety. We thus recommend continued usage and interpretation of the full PANAS-C NA scale despite the identification of the fear and distress group factors underlying general negative affectivity. The identification of these fear and distress group factors nonetheless suggest that negative affectivity may be comprised largely of a fear and distress component among older youth. The implications of these findings are discussed in relation to better understanding the structure of psychopathology across childhood development and informing the development of future treatments of negative emotions.     

Irritability and Emotional Impulsivity as Core Feature of ADHD and ODD in Children

The categorical approach of diagnosing mental disorders entails the problem of frequently occurring comorbidities, suggesting a more parsimonious structure of psychopathology. In this study, we therefore aim to assess how affective dysregulation (AD) is associated with attention-deficit/hyperactivity disorder (ADHD) and oppositional defiant disorder (ODD) in children. To assess AD in children aged 8–12 years (n?=?391), we employed the parent version of a newly constructed parent rating scale. Following item reduction, we conducted exploratory and confirmatory factor analyses to establish a factorial structure of AD. One core dimension was identified, comprising irritability and emotional impulsivity, and two smaller dimensions, comprising positive emotionality and exuberance. Subsequently, we examined five different latent factor models – a unidimensional model, a first-order correlated factor model, a second-order correlated factor model, a traditional bifactor model, and a bifactor S-1 model, in which the first-order factor AD-Irritability/Emotional Impulsivity (II) was modeled as the general reference factor. A bifactor S-1 model with the a priori defined general reference domain AD-II provided the best fit to our data and was straightforward to interpret. This model showed excellent model fit and no anomalous factor loadings. This still held true, when comparing it to bifactor S-1 models with ADHD/ODD-related reference factors. Differential correlations with emotion regulation skills and the established Parent Proxy Anger Scale validate the interpretation of the different dimensions. Our results suggest that irritability/emotional impulsivity might be a common core feature of ADHD and ODD.

     

The challenges of fitting an item response theory model to the Social Anhedonia Scale

This study explored the application of latent variable measurement models to the Social Anhedonia Scale (SAS; Eckblad, Chapman, Chapman, & Mishlove, 1982), a widely used and influential measure in schizophrenia-related research. Specifically, we applied unidimensional and bifactor item response theory (IRT) models to data from a community sample of young adults (n = 2,227). Ordinal factor analyses revealed that identifying a coherent latent structure in the 40-item SAS data was challenging due to (a) the presence of multiple small content clusters (e.g., doublets); (b) modest relations between those clusters, which, in turn, implies a general factor of only modest strength; (c) items that shared little variance with the majority of items; and (d) cross-loadings in bifactor solutions. Consequently, we conclude that SAS responses cannot be modeled accurately by either unidimensional or bifactor IRT models. Although the application of a bifactor model to a reduced 17-item set met with better success, significant psychometric and substantive problems remained. Results highlight the challenges of applying latent variable models to scales that were not originally designed to fit these models.     

Is the Bifactor Model a Better Model or Is It Just Better at Modeling Implausible Responses? Application of Iteratively Reweighted Least Squares to the Rosenberg Self-Esteem Scale

Although the structure of the Rosenberg Self-Esteem Scale (RSES) has been exhaustively evaluated, questions regarding dimensionality and direction of wording effects continue to be debated. To shed new light on these issues, we ask (a) for what percentage of individuals is a unidimensional model adequate, (b) what additional percentage of individuals can be modeled with multidimensional specifications, and (c) what percentage of individuals respond so inconsistently that they cannot be well modeled? To estimate these percentages, we applied iteratively reweighted least squares (IRLS) to examine the structure of the RSES in a large, publicly available data set. A distance measure, d_s, reflecting a distance between a response pattern and an estimated model, was used for case weighting. We found that a bifactor model provided the best overall model fit, with one general factor and two wording-related group factors. However, on the basis of d_r?values, a distance measure based on individual residuals, we concluded that approximately 86% of cases were adequately modeled through a unidimensional structure, and only an additional 3% required a bifactor model. Roughly 11% of cases were judged as “unmodelable” due to their significant residuals in all models considered. Finally, analysis of d_s revealed that some, but not all, of the superior fit of the bifactor model is owed to that model's ability to better accommodate implausible and possibly invalid response patterns, and not necessarily because it better accounts for the effects of direction of wording.