The moderating role of trust in pandemic-relevant institutions on the relation between pandemic fatigue and vaccination intentions.

This research helps to clarify the relation between pandemic fatigue (PF) and vaccination intentions (VI). Theoretically, two patterns seem plausible. First, as with any other health protective measure, PF might reduce the motivation to get vaccinated. Second, PF might increase the motivation to get vaccinated because vaccination reduces the number of (other) health protective measure needed. We tested these two opposing predictions and further explored the moderating role of trust in pandemic-relevant institutions on the link between PF and VI in two large-scale survey studies from Denmark and Germany (collected between 2020 and 2021; total N > 22,000). Data was analyzed using multiple regression models. Analyses reveal a negative link between PF and VI that is less pronounced for people high in trust. Results remain stable when accounting for covariates and quadratic trends. Thus, trust might buffer the negative relation between PF and VI.

semPower: General power analysis for structural equation models.

Structural equation modeling (SEM) is a widespread and commonly used approach to test substantive hypotheses in the social and behavioral sciences. When performing hypothesis tests, it is vital to rely on a sufficiently large sample size to achieve an adequate degree of statistical power to detect the hypothesized effect. However, applications of SEM rarely consider statistical power in informing sample size considerations or determine the statistical power for the focal hypothesis tests performed. One reason is the difficulty in translating substantive hypotheses into specific effect size values required to perform power analyses, as well as the lack of user-friendly software to automate this process. The present paper presents the second version of the R package semPower which includes comprehensive functionality for various types of power analyses in SEM. Specifically, semPower 2 allows one to perform both analytical and simulated a priori, post hoc, and compromise power analysis for structural equation models with or without latent variables, and also supports multigroup settings and provides user-friendly convenience functions for many common model types (e.g., standard confirmatory factor analysis [CFA] models, regression models, autoregressive moving average [ARMA] models, cross-lagged panel models) to simplify power analyses when a model-based definition of the effect in terms of model parameters is desired.

The role of impulse and interference control in aversive personality: A comprehensive assessment.

Ethically and socially aversive behaviors have been attributed to several personality traits, including characteristics collectively referred to under the umbrella term of impulsivity. It is an open question, however, whether such characteristics are an integral part of ethically and socially aversive personality. Relying on three large samples (total N = 9854) and implementing longitudinal assessments, the present study provides a comprehensive investigation of the role of impulse and interference control in aversive personality. Based on contemporary conceptualizations of the impulsivity domain, a total of 17 dimensions spanning both self-reports and behavioral tasks are assessed. To represent aversive personality, we consider the D Factor of Personality (D), i.e., the basic disposition shared by all aversive traits. Results indicate that D co-occurs with a deficit in inhibiting the incorrect action when multiple actions are available, a preference for immediate rewards while failing to consider the consequences of one's actions, and maladaptive behavior directed towards regulating strong affect. However, most associations between D and dimensions of impulsivity were small or non-significant, thereby disconfirming the notion that characteristics related to a lack of impulse control are an integral feature of aversive personality in general.

A tutorial on assessing statistical power and determining sample size for structural equation models.

Structural equation modeling (SEM) is a widespread approach to test substantive hypotheses in psychology and other social sciences. However, most studies involving structural equation models neither report statistical power analysis as a criterion for sample size planning nor evaluate the achieved power of the performed tests. In this tutorial, we provide a step-by-step illustration of how a priori, post hoc, and compromise power analyses can be conducted for a range of different SEM applications. Using illustrative examples and the R package semPower, we demonstrate power analyses for hypotheses regarding overall model fit, global model comparisons, particular individual model parameters, and differences in multigroup contexts (such as in tests of measurement invariance). We encourage researchers to yield reliable-and thus more replicable-results based on thoughtful sample size planning, especially if small or medium-sized effects are expected. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Rethinking aversive personality: Decomposing the Dark Triad traits into their common core and unique flavors.

OBJECTIVE: To explain and predict unethical behavior, much attention has been devoted to the "Dark Triad of Personality", a set of three socially aversive personality traits: Machiavellianism, narcissism, and psychopathy. Despite its popularity, research on the Dark Triad has been beset by recurring concerns surrounding the distinctiveness of its components. Herein, we propose an alternative theoretical view that conceptualizes the Dark Triad traits as specific manifestations of the common core of aversive traits (conceptualized as the Dark Factor of Personality, D) flavored by unique, essentially non-aversive characteristics. METHOD: In two studies (total N > 1000), we test this idea by examining the conceptual and empirical overlap and specificity of the Dark Triad traits vis-à-vis D and each other. RESULTS: Findings support the conceptualization of the Dark Triad traits as flavored manifestations of D and also reveal a marked discrepancy between the current conceptualization of the Dark Triad traits and the empirical structure of its subdimensions. In fact, evidence clearly failed to support the existence of a triad of traits. CONCLUSION: Conceptualizing single aversive traits as a conjunction of core D aspects and essentially non-aversive characteristics (admiration; disinhibition vs. planfulness; vulnerability vs. boldness) holds promise to move the field forward.

Assessing the fitting propensity of factor models.

Model selection is an omnipresent issue in structural equation modeling (SEM). When deciding among competing theories instantiated as formal statistical models, a trade-off is often sought between goodness-of-fit and model parsimony. Whereas traditional fit assessment in SEM quantifies parsimony solely as the number of free parameters, the ability of a model to account for diverse data patterns-known as fitting propensity-also depends on the functional form of a model. The present investigation provides a systematic assessment of the fitting propensity of models typically considered and compared in SEM, namely, exploratory and confirmatory factor analysis models positing a different number of latent factors or a different hierarchical structure (single-factor, correlated factors, higher-order, and bifactor models). Furthermore, the behavior of commonly used fit indices (CFI, SRMR, RMSEA, TLI) and information criteria (AIC, BIC) in accounting for fitting propensity was assessed. Although the results demonstrated varying degrees of fitting propensity for the models under scrutiny, these differences were mostly driven by the number of free parameters. There was little evidence for additional differences in the functional form of the compared models. Fit indices adjusting for the number of free parameters such as the RMSEA and TLI thus adequately accounted for differences in fitting propensity. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Comparative effectiveness of three versions of a stepped care model for insomnia differing in the amount of therapist support in internet-delivered treatment: study protocol for a pragmatic cluster randomised controlled trial (GET Sleep).

INTRODUCTION: It is unclear how internet-delivered cognitive-behavioural therapy for insomnia (CBT-I) can be integrated into healthcare systems, and little is known about the optimal level of therapist guidance. The aim of this study is to investigate three different versions of a stepped care model for insomnia (IG1, IG2, IG3) versus treatment as usual (TAU). IG1, IG2 and IG3 rely on treatment by general practitioners (GPs) in the entry level and differ in the amount of guidance by e-coaches in internet-delivered CBT-I. METHODS AND ANALYSIS: In this randomised controlled trial, 4268 patients meeting International Classification of Diseases, Tenth Revision (ICD-10) criteria for insomnia will be recruited. The study will use cluster randomisation of GPs with an allocation ratio of 3:3:3:1 (IG1, IG2, IG3, TAU). In step 1 of the stepped care model, GPs will deliver psychoeducational treatment; in step 2, an internet-delivered CBT-I programme will be used; in step 3, GPs will refer patients to specialised treatment. Outcomes will be collected at baseline, and 4 weeks, 12 weeks and 6 months after baseline assessment. The primary outcome is insomnia severity at 6 months. An economic evaluation will be conducted and qualitative interviews will be used to explore barriers and facilitators of the stepped care model. ETHICS AND DISSEMINATION: The study protocol was approved by the Ethics Committee of the Medical Centre-University of Freiburg. The results of the study will be published irrespective of the outcome. TRIAL REGISTRATION NUMBER: DRKS00021503.

No probifactor model fit index bias, but a propensity toward selecting the best model.

Based on an extensive Monte Carlo simulation study, Greene et al. (2019) investigated the behavior of various measures of model fit for competing types of confirmatory factor analysis models of psychopathology, the correlated factors model and the bifactor model. Greene et al. (2019) found that fit indices mostly favored a bifactor model over a correlated factors model, which led to the conclusion of a "probifactor fit index bias." Here we show that this conclusion is misleading as far as conditions without complexities in the data-generating model are concerned and in fact incorrect in conditions with complexities (cross-loadings or correlated residuals) in the data-generating model. Specifically, we demonstrate that the very same data Greene et al. (2019) generated from a correlated three-factor model can be likewise obtained from a higher-order or a bifactor model, so that there is no basis for maintaining that the "true" to-be recovered model conformed to a correlated factors structure. Moreover, we show that a standard bifactor model was factually closer aligned with the data generated in conditions with added complexities. As such, fit indices necessarily and correctly favored the bifactor model in most conditions. We explain the observed behavior of several fit indices, thereby showing that the results were not characterized by bias, but were in fact in line with the expected and desired behavior. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Effectiveness and cost-effectiveness of a web-based routine assessment with integrated recommendations for action for depression and anxiety (RehaCAT+): protocol for a cluster randomised controlled trial for patients with elevated depressive symptoms in rehabilitation facilities.

INTRODUCTION: The integration of a web-based computer-adaptive patient-reported outcome test (CAT) platform with persuasive design optimised features including recommendations for action into routine healthcare could provide a promising way to translate reliable diagnostic results into action. This study aims to evaluate the effectiveness and cost-effectiveness of such a platform for depression and anxiety (RehaCAT+) compared with the standard diagnostic system (RehaCAT) in cardiological and orthopaedic health clinics in routine care. METHODS AND ANALYSIS: A two-arm, pragmatic, cluster-randomised controlled trial will be conducted. Twelve participating rehabilitation clinics in Germany will be randomly assigned to a control (RehaCAT) or experimental group (RehaCAT+) in a 1:1 design. A total sample of 1848 participants will be recruited across all clinics. The primary outcome, depression severity at 12 months follow-up (T3), will be assessed using the CAT Patient-Reported Outcome Measurement Information System Emotional Distress-Depression Item set. Secondary outcomes are depression at discharge (T1) and 6 months follow-up (T2) as well as anxiety, satisfaction with participation in social roles and activities, pain impairment, fatigue, sleep, health-related quality of life, self-efficacy, physical functioning, alcohol, personality and health economic-specific general quality of life and socioeconomic cost and benefits at T1-3. User behaviour, acceptance, facilitating and hindering factors will be assessed with semistructured qualitative interviews. Additionally, a smart sensing substudy will be conducted, with daily ecological momentary assessments and passive collection of smartphone usage variables. Data analysis will follow the intention-to-treat principle with additional per-protocol analyses. Cost-effectiveness analyses will be conducted from a societal perspective and the perspective of the statutory pension insurance. ETHICS AND DISSEMINATION: The study will be conducted according to the Declaration of Helsinki. The Ethics Committee of Ulm University, has approved the study (on 24 February 2021 ref. 509/20). Written informed consent will be obtained for all participants. Results will be published via peer-reviewed journals. TRIAL REGISTRATION NUMBER: DRKS00027447.

Measuring the Dark Core of Personality in German: Psychometric Properties, Measurement Invariance, Predictive Validity, and Self-Other Agreement.

The Dark Factor of Personality (D)-the underlying disposition of aversive traits-has been shown to account for various ethically and socially aversive behaviors. Whereas previous findings support the reliability and validity of the original English item sets suggested to measure D, a thorough psychometric examination of their German translation is still pending. Using data from four different samples (total N > 33,000), this study comprehensively evaluates the German version of the D70, D35, and D16 with respect to (a) their factor structure, (b) measurement invariance across gender, (c) measurement equivalence with the original English item sets, (d) predictive validity for relevant outcomes across a six-month period, and (e) self-observer agreement. Results confirm the bifactor structure of the D70 and single-factor models for the D35 and the D16. Measurement invariance testing shows partial strict invariance across gender and language versions. Furthermore, predictive validity and a moderate degree of self-other agreement are supported. The German version of the D70 and its shorter versions thus allow for a psychometrically sound assessment of D.

Disentangling the effects of culture and language on measurement noninvariance in cross-cultural research: The culture, comprehension, and translation bias (CCT) procedure.

Comparability of measurement across different cultural groups is an essential prerequisite for any cross-cultural assessment. However, cross-cultural measurement invariance is rarely achieved and detecting the source of noninvariance is often challenging. In particular, when different language versions of a measure are administered to different cultural groups, noninvariance on certain items may originate either from translation inconsistencies (translation bias) or from actual differences between cultural groups (culture bias). If, on the other hand, a measure is administered in a common language version (e.g., English), item noninvariance may also result from comprehension issues of nonnative speakers (comprehension bias). Here, we outline a procedure suitable for dissociating these sources of item noninvariance, termed the culture, comprehension, and translation bias (CCT) procedure. The CCT procedure is based on a between-subjects design comparing samples from two different cultures who complete a measure in either the same or a different language version. We demonstrate in a simulation study and illustrate in an empirical example with actual cross-cultural data how performing multiple pairwise comparisons across (a) groups differing in culture but not in language, (b) groups differing in language but not in culture, and (c) groups differing in both culture and language allows to pinpoint the source of item noninvariance with high specificity. The CCT procedure thus provides a valuable tool for improving cross-cultural assessment through directing the process of item translation and cultural adaptation. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Themes of the dark core of personality.

Enduring patterns of socially aversive behavior are ascribed to stable personality disorders (such as narcissistic or antisocial tendencies) in clinical psychology or to so called "dark" traits in personality psychology. As recently shown, the substantial overlap among the latter constructs is attributable to a single underlying disposition, called the Dark Factor of Personality (D). Whereas evidence supports the conceptualization of D as the core of aversive traits, the structure of the specific factors of D received less empirical attention so far. To this end, this study further scrutinizes the internal structure of D with items stemming from 12 different aversive traits assessed in three large and heterogeneous samples (total N > 160,000). Specifically, we (a) explored the bifactor structure of D using a modified "bass-ackwards" approach, (b) cross-validated the identified factor solutions via confirmatory factor analyses, and (c) examined the empirical relation of D and the specific factors to five criterion measures. Results indicate that a bifactor structure modeling D along with five specific factors-or themes-labeled Callousness, Deceitfulness, Narcissistic Entitlement, Sadism, and Vindictiveness, best describes the internal structure of D. (PsycInfo Database Record (c) 2021 APA, all rights reserved).