Second-order Factor Model Research Articles

Assessing the effectiveness of open innovation implementation strategies in the promotion of ambidextrous innovation in Thai small and medium-sized enterprises

The adoption of open innovation practices is becoming increasingly important for SMEs seeking to remain competitive in today's fast-paced business environment. The aim of this study is to understand the implementation of open innovation processes by SMEs while highlighting two critical processes: open innovation implementation (OII) and open ambidextrous innovation practices (OAIP). The study employes a second-order factor analysis incorporating multigroup structural invariance analysis to explore the differences in ambidextrous innovation practices across SME size categories using a sample of 615 SMEs in Thailand. The primary finding reveals and confirms a statistically significant positive relationship between the implementation of open innovation and the advancement of ambidextrous innovation practices. This relationship underlines the importance of embracing open innovation, as it fosters ambidextrous innovation, thereby enabling fresh perspectives, accelerating creativity, and facilitating knowledge exchange. Three categories of MSMEs—microenterprises, small enterprises, and medium-sized enterprises—are shown to be well positioned for adopting open innovation strategies, each demonstrating a significant ability to foster open innovation practices. In the study, practical and policy recommendations for business practitioners and policy-makers are presented, emphasizing the importance of understanding the organizational, managerial, technological, and contextual factors that underpin successful open innovation implementation. A novel structural second-order factor model that deepens our understanding of the complex relationships between open innovation processes is also introduced, offering valuable insights for academic researchers. In conclusion, this study emphasizes the importance of SMEs embracing open innovation practices and promoting ambidextrous innovation for sustained success and growth, and key strategic takeaways are proposed based on the empirical item-scale results.

Factor structure and psychometric properties of the Chinese version of the Odor Awareness Scale.

The Odor Awareness Scale (OAS) is a questionnaire that assesses individual differences in awareness of odors in the surrounding environment, which has been shown to be associated with affective symptoms in recent researches. To further research, A Chinese version of the OAS needs to be introduced. To investigate the factor structure and validate the psychometric properties of the OAS. A total of 978 participants from college were randomly allocated into two groups for exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), respectively. Additionally, the study entailed item analysis and scrutinized internal consistency reliability, test-retest reliability, and concurrent validity. Test-retest reliability was assessed by having 214 participants complete the OAS twice at a one-week interval. Concurrent validity was measured using the Body Odor Sniffing Questionnaire (BOSQ), the Generalized Anxiety Disorder Scale (GAD-7), and the Toronto Alexithymia Scale (TAS-20). EFA identified three factors that best fit the data: odor sensitivity, odor impact, and odor attention. CFA validated a second-order factor model, yielding good fit indices: / Df = 2.326, RMSEA = 0.052, CFI = 0.911, TLI = 0.900, SRMR = 0.053. The final version of the OAS comprised 27 items and exhibited a commendable internal consistency reliability (Cronbach's α = 0.913), and a good test-retest reliability, as evidenced by the high Pearson correlation coefficient (r = 0.940) and intraclass correlation coefficient (ICC = 0.940). The OAS was significantly correlated with BOSQ (r = 0.416), GAD-7 (r = 0.155), and TAS-20 (r = -0.081). The Chinese version of the OAS demonstrated robust reliability and validity, rendering it a valuable instrument for evaluating odor awareness in the Chinese population.

Validation of the Compassion Fatigue Short Scale among Portuguese firefighters

This study aimed to adapt the Compassion Fatigue-Short Scale to Portugal and examine the reliability and validity of the Portuguese version of the scale (Pt-CF-Short Scale) among Portuguese firefighters. The factor structure of the Pt-CF-Short Scale was compared to the one-factor model fit and a two-factor model and second-order factor model in a sample of 512 firefighters. Confirmatory factor analysis procedures confirmed the good fit of a second-order factor model with two first-order factors (secondary trauma and job burnout). The Pt-CF-Short Scale showed good internal consistency evidence. The Kessler Psychological Distress Scale (K-10), the Brief Symptom Inventory (BSI) and WHOQOOL-Bref were used as convergent measures to assess psychological distress, anxiety, depression, and interpersonal sensitivity and quality of life, respectively. The measure presented a strong correlation with psychological distress and weak and negative association with quality of life. The Pt-CF-Short Scale contributes to understanding compassion fatigue and its correlates within the context of emergency workers. Results indicate that this scale is a valid and reliable assessment tool in evaluating compassion fatigue.

Developing conceptually sound items for a clinical courage questionnaire.

Clinical courage can be described as a rural doctor's adaptability and willingness to undertake clinical work at the limits of their training and experience to meet the needs of their patients. This article describes the in-house development of survey items to include in a quantitative measure of clinical courage. The questionnaire development involved two key concepts: a second-order latent factor model structure and a nominal group technique, used to develop consensus among the research team members. The steps taken to develop a sound clinical courage questionnaire are described in detail. The resulting initial questionnaire is presented, ready for testing with rural clinicians and refinement. This article outlines the psychometric process of questionnaire design and presents the resultant clinical courage questionnaire.

A Note on Comparing the Bifactor and Second-Order Factor Models: Is the Bayesian Information Criterion a Routinely Dependable Index for Model Selection?

This note demonstrates that the widely used Bayesian Information Criterion (BIC) need not be generally viewed as a routinely dependable index for model selection when the bifactor and second-order factor models are examined as rival means for data description and explanation. To this end, we use an empirically relevant setting with multidimensional measuring instrument components, where the bifactor model is found consistently inferior to the second-order model in terms of the BIC even though the data on a large number of replications at different sample sizes were generated following the bifactor model. We therefore caution researchers that routine reliance on the BIC for the purpose of discriminating between these two widely used models may not always lead to correct decisions with respect to model choice.

Development and psychometric properties of the Stressors in Breast Cancer Scale.

A diagnosis of breast cancer generates psychological stress, due not only to treatment and its side effects but also to the impact on different areas of the patient's daily life. Although there are instruments for measuring psychological stress in the cancer context, there is currently no tool for assessing stressors specific to breast cancer. The aim of this study was to develop the Stressors in Breast Cancer Scale (SBCS). A panel of experts evaluated the clarity and relevance of scale items, providing validity evidence based on test content. Psychometric properties of the scale were then analyzed. Validity evidence based on the internal structure of the SBCS was obtained through exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), following a cross-validation strategy. The CFA supported a second-order factor model with five dimensions: physical appearance and sex strains, health and daily difficulties, interpersonal relationship strains, healthcare strains, and worries and concerns about the future. This structure was invariant across two groups distinguished by time from cancer diagnosis (less than 3 and 3 years or more from diagnosis). Reliability, based on McDonald's omega and Cronbach's alpha coefficients, ranged from 0.83 to 0.89 for factor scores, and reached 0.95 for total scores. Validity evidence was also provided by correlations with depression, anxiety, perceived stress, and perceived health and quality of life. The results support the use of the SBCS for measuring stress as a stimulus in the breast cancer context. Implications for clinical practice and research are discussed.

A Second-Order Symmetric Non-Negative Latent Factor Model for Undirected Weighted Network Representation

Precise representation to undirected weighted network (UWN) is the foundation of understanding connection patterns inside a massive node set. It can be addressed via a Symmetric Non-negative Latent Factor (SNLF) model with a non-convex learning objective. However, existing SNLF models commonly adopt a first-order learning algorithm that cannot well handle such a non-convex objective, thereby leading to inaccurate UWN representation. Aiming at addressing this issue, this study incorporates an efficient second-order learning algorithm into an SNLF model, thereby establishing a Second-order Symmetric Non-negative Latent Factor (S <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> NLF) model with two-fold ideas: a) applying the single latent factor-related mapping function to the non-negativity constrained optimization parameters to achieve an unconstrained learning objective, and b) optimizing this learning objective with its optimization parameters through an efficient second-order learning algorithm to achieve accurate representation to the target UWN with affordable computational burden. Empirical studies indicate that owing to its efficient incorporation of the second-order optimization technique, the proposed S <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> NLF model outperforms state-of-the-art SNLF models when they are used to gain highly accurate representation to UWNs emerging from real applications.

Validation of the Japanese version of the revised version of the compound psychological capital scale (CPC-12R).

This study developed a Japanese version of the Revised Version of the Compound Psychological Capital Scale (CPC-12R) and tested its reliability and construct validity. The participants were 1,000 young adults (500 university students and 500 employees) recruited through an internet survey. Confirmatory factor analysis showed that the four first-order factors (hope, optimism, resilience, and self-efficacy) and one second-order factor (PsyCap) model of the previous study is appropriate for the Japanese context. In addition, Cronbach's α and omega-higher-order of CPC-12R were sufficient. The measurement invariance analysis suggested sufficient scalar invariances for the employees and university students and across genders. The Japanese version of the CPC-12R had moderate positive correlations with job satisfaction, work engagement, conscientiousness, and extraversion, as well as a moderate negative correlation with negative emotionality. These findings provide evidence for sufficient reliability and construct validity of the Japanese version of the CPC-12R.

증강현실 기반 가상피팅시스템 사용시 지각된 기술 속성의 다차원성 : 위계적 요인구조모델 분석

The purpose of this study was to identify the underlying dimensions of AR technological attributes (ARTA), and estimate the hierarchical factor models for using a virtual fitting system in fashion retailing. The sample in this study consisted of consumers in their 20s and 30s. A total of 173 usable responses were obtained from volunteers who agreed to participate in the lab experiments and a survey with a questionnaire. The first-order confirmatory factor analysis confirmed that perceived ARTA consisted of five factors: augmentation, vividness, visual comfort, responsiveness, and organized system in using the virtual fitting system. Also, the estimated second-order factor model showed that the five ARTA factors were predicted by higher-order two constructs: the first

Development of the Gender Roles and Male Provision Expectations Scale.

Existing composite measures assess the extent to which women and men support masculinity ideals concerning the expectation that men should provide for their partners and families. In many contexts across sub-Saharan Africa, the male provider role is taken as given. This core masculinity tenet may be associated with related gender role expectations that result in increasing young women's risk of HIV, especially within the context of transactional sex relationships. Extant literature points to five domains potentially associated with male provider role expectations: male authority, men's sexual decision-making control, women's sexual agency, women's economic dependence, and love. The goal of this study was to develop the Gender Roles and Male Provision Expectations (GRMPE) scale toward understanding whether beliefs attached to male provider role expectations increase HIV risk. We developed the GRMPE across three research phases with young women (ages 15-24) in Central Uganda that (1) used qualitative data to refine domains and develop scale items; (2) cognitively tested the refined items; and (3) pilot tested a 26-item scale across five domains with 108 young women. Using confirmatory factor analyses, we retained 15 items across four factors, corresponding to the domains of male authority, sexual decision-making, women's sexual agency, and love; which we then modeled as indicators in a single second-order factor model. The GRMPE demonstrated initial reliability and validity, and tests of criterion validity found significant associations with known HIV risk behaviors. The GRMPE scale shows promise for better examining the determinants of HIV risk and assessing gender norm change interventions.

The Revision and Application of Aurora in China: Based on Successful Intelligence.

Aurora Battery is a corresponding test of successful intelligence. This study aims to examine the factorial structure of the Chinese version of Aurora Battery and to investigate its internal consistency and validity, as well as to discover the developmental features of Chinese students. A total number of 2007 students were recruited from 13 schools across eastern, central, and western China, ranging from 4th to 8th grade (mean age = 12.29 years) and among them, 43.9% are girls. Confirmatory factor analysis (CFA) was used to examine the factorial structure. Among the tested models, a second-order factor model, in which the three ability factors serve as indicators of a general factor, provided an acceptable model fit to the data. Moreover, measurement invariance across gender and grades were supported, which suggests the mean scores of analytical, creative, and practical abilities are comparable in this research. The criterion-related validity analysis suggests that the battery and its three subscales have good criterion validity. The scale reliability analysis shows that the Cronbach's alpha and the McDonald's omega value of the whole test were .84 and .87, respectively, indicating the scale's internal reliability is good. For ability differences among grades, students' analytical and practical abilities increase across all grades, while creativity presents an upward trend from grade 4 to 6, followed by a downward trend from grade 6 to 7, and an increase from grade 7 to 8. Female students outperform male students on both analytical and creative ability, while with no obvious difference on practical abilities.

Classical and Bayesian Uncertainty Intervals for the Reliability of Multidimensional Scales

The reliability of a multidimensional test instrument is commonly estimated using coefficients ωt (total) and ωh (hierarchical). However, point estimates for the coefficients are rarely accompanied by uncertainty estimates. In this study, we compare bootstrap and normal-theory confidence intervals. In addition, we develop Bayesian versions of coefficients ωt and ωh by sampling from a second-order factor model. Results from a comprehensive simulation study show that the studied confidence intervals performed well when the sample size was sufficiently large (). The Bayesian estimates performed well across most studied conditions. When the sample size was small and the reliability low, only the bias-corrected and accelerated bootstrap confidence interval approached a satisfactory coverage among all intervals. This study guides on ωt and ωh confidence intervals and introduces ωt and ωh credible intervals that are easy to use and come with the benefits of Bayesian parameter estimation.

Factor structure of the 10-item CES-D Scale among patients with persistent COVID-19.

The presence of persistent coronavirus disease 2019 (COVID-19) might be associated with significant levels of psychological distress that would meet the threshold for clinical relevance. The Center for Epidemiologic Studies Depression Scale (CES-D) version 10 has been widely used in assessing psychological distress among general and clinical populations from different cultural backgrounds. To our knowledge, however, researchers have not yet validated these findings among patients with persistent COVID-19. A cross-sectional validation study was conducted with 100 patients from the EXER-COVID project (69.8% women; mean(±standard deviation) ages: 47.4 ± 9.5 years). Confirmatory factor analyses (CFAs) were performed on the 10-item CES-D to test four model fits: (a) unidimensional model, (b) two-factor correlated model, (c) three-factor correlated model, and (d) second-order factor model. The diagonal-weighted least-squaresestimator was used, as it is commonly applied to latent variable models with ordered categorical variables. The reliability indices of the 10-itemCES-Din patients with persistent COVID-19 were as follows: depressive affect factor ( ; ), somatic retardation factor ( ; ), and positive affect factor ( ; ). The second-order model fit showed good Omega reliability ( ). Regarding CFAs, the unidimensional-factor model shows poor goodness of fit, especially residuals analysis (root mean square error of approximation[RMSEA] = 0.081[95% confidence interval, CI = 0.040-0.119]; standardized root mean square residual[SRMR] = 0.101). The two-factor correlated model, three-factor correlated model, and second-order factor model showed adequate goodness of fit, and the χ2 difference test ( ) did not show significant differences between the goodness of fit for these models ( ; p = 0.127). Several indices showed a good fit with the three-factor correlated model: goodness-of-fit index = 0.974, comparative fit index = 0.990, relative noncentrality index = 0.990, and incremental fit index = 0.990, which were all above 0.95, the traditional cut-off establishing adequate fit. On the other hand, RMSEA = 0.049 (95%CI = 0.000-0.095), where an RMSEA < 0.06-0.08 indicates an adequate fit. Item loadings on the factors were statistically significant ( ; p's < 0.001), indicating that the items loaded correctly on the corresponding factors and the relationship between factors ( ; p's ≤ 0.001. To our knowledge, this is the first study to provide validity and reliability to 10-itemCES-Din a persistent COVID-19 Spanish patient sample. The validation and reliability of this short screening tool allowus to increase the chance of obtaining complete data in a particular patient profile with increased fatigue and brain fog that limit patients' capacity to complete questionnaires.

Dimensionality Analysis of Entrepreneurial Resilience amid the COVID-19 Pandemic: Comparative Models with Confirmatory Factor Analysis and Structural Equation Modeling

Several previous empirical research studies have defined and operationalized entrepreneurial resilience (ENTR-RISC) as either a construct with multiple dimensions or a construct with a single dimension. While only a few previous research studies have assessed some components of the presumed dimensionality of ENTR-RISC, no research has attempted to assess the dimensional structure of ENTR-RISC amid the COVID-19 pandemic using different alternative competing models. In order to acquire a deeper understanding of the dimensional characteristics of the ENTR-RISC construct, this research assessed its dimensionality by comparing existing models’ goodness of fit (GoF), and the best model that fitted the data was further tested using various confirmatory factor analysis (CFA) models (a second-order factor model, an oblique first-factor model, and a single-factor model) on quantitative data gathered from 590 SME entrepreneurs in Kingdom of Saudi Arabia (KSA). The results of analyzing the tested models via structural equation modeling (SEM) and the AMOS program indicated that the ENTR-RISC construct has a multidimensional three-factor structure. Even though this research helps in the advancement of ENTR-RISC practice and theory, further research is required to test the dimensionality of ENTR-RISC in greater depth. The findings of this study may encourage further research on this topic and stimulate a much-needed discussion on the dimensional structure of the ENTR-RISC concept.

Investigating the validity of the short form Burnout Assessment Tool: A job demands-resources approach

The purpose of this study was to investigate the psychometric properties of the short form Burnout Assessment Tool (BAT-12). As a result of the pandemic, job stress has been compounded and the use of conceptually grounded and accurate measures is needed to identify burnout risks within specific organisations and the overall workforce. The study sample comprised 660 employees from various occupational settings who filled out an online survey. Latent variable methods with ordinal categorical data were implemented to model the data and to test the hypotheses for the study. Results showed that the proposed second-order factor model of the BAT-12 showed a good fit to the data and was invariant across gender and ethnicity. In addition, burnout – as operationalised with the BAT-12 – played the hypothesised mediating role in the Job Demands-Resources model. The BAT-12 also showed convergent validity with the Maslach Burnout Inventory. The authors conclude that BAT-12 is a robust instrument with adequate psychometric properties to measure burnout risk and present a freely available online application for employees to estimate their risk of burnout.

A multifunction approach to assessing Aristotelian phronesis (practical wisdom)

Psychologists have actively studied wisdom for decades, but wisdom models and measures have been developed in an ad hoc manner, without the guidance of a core theory or philosophy. This has led to conceptual confusion and a lack of research cumulativeness. A four-function model of practical wisdom based on Aristotle's theory of phronesis (practical wisdom) has been proposed (Darnell et al., 2019). In this study, these four functions were approximated with existing measures to provide a “proof of concept” investigation. The constitutive function was assessed with virtue identification, selection, and relevance measures. The integrative function was estimated from observed measures of action choices and justifications. The blueprint function was estimated with measures of moral identity. The emotion regulation function was estimated with scales assessing empathy and perspective taking. A second-order factor model fit the hypothesized structure well with independent samples of UK adults and adolescents. This second-order factor was labeled phronesis and it correlated positively with the criterion measure of prosocial behavior. The results suggest the empirical viability of a four-function model of phronesis. Future studies are now indicated for tailoring assessments to measure the Aristotelian theory of phronesis more closely.

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.

Problem-Based mHealth Literacy Scale (PB-mHLS): Development and Validation.

BackgroundMobile devices have greatly facilitated the use of digital health resources, particularly during the COVID-19 pandemic. Mobile health (mHealth) has become a common and important way to monitor and improve health conditions for people from different social classes. The ability to utilize mHealth affects its effectiveness; therefore, the widespread application of mHealth technologies calls for an instrument that can accurately measure health literacy in the era of mobile media.ObjectiveWe aimed to (1) identify the components of mHealth literacy for ordinary users and (2) develop a systematic scale for appropriately measuring individuals’ self-perceived mHealth literacy through a problem-based framework.MethodsWe conducted an exploratory study involving in-depth interviews and observations (15 participants) in January 2020 and used exploratory factor analysis and confirmatory factor analysis to identify the components of mHealth literacy and develop an item pool. In February 2020, we conducted a pilot survey with 148 participants to explore the factor structures of items identified during the exploratory study. Subsequently, 2 surveys were administrated using quota sampling. The first survey (conducted in Guangdong, China) collected 552 responses during March 2020; we assessed composite reliability, convergent validity, and discriminant validity. The second survey (conducted in China nationwide) collected 433 responses during October 2021; we assessed criterion-related validity using structural equation modeling.ResultsWe identified 78 items during the exploratory study. The final scale—the Problem-Based mHealth Literacy Scale—consists of 33 items that reflect 8 domains of mHealth literacy. The first web-based survey suggested that mHealth literacy consists of 8 factors (ie, subscales), namely, mHealth desire, mobile phone operational skills, acquiring mHealth information, acquiring mHealth services, understanding of medical terms, mobile-based patient–doctor communication, evaluating mHealth information, and mHealth decision-making. These factors were found to be reliable (composite reliability >0.7), with good convergent validity (average variance extracted >0.5) and discriminant validity (square root of average variance extracted are greater than the correlation coefficients between factors). The findings also revealed that these 8 factors should be grouped under a second-order factor model (χ2/df=2.701; comparative fit index 0.921; root mean square error of approximation 0.056; target coefficient 0.831). The second survey revealed that mHealth use had a significant impact (β=0.43, P<.001) on mHealth literacy and that mHealth literacy had a significant impact (β=0.23, P<.001) on health prevention behavior.ConclusionsThis study revealed the distinctiveness of mHealth literacy by placing mHealth needs, the ability to understand medical terms, and the skills in patient–doctor interactions in the foreground. The Problem-Based mHealth Literacy Scale is a useful instrument for comprehensively measuring individuals’ mHealth literacy and extends the concept of health literacy to the context of mobile communication.

Attitudes towards refugees: Introducing a short three-dimensional scale.

Many researchers subscribe to the three-component conceptualization of attitudes, the idea that attitudes have cognitive, affective, and behavioural (intentional) components. Yet, these components are rarely considered simultaneously in scales, especially those measuring attitudes towards refugees. Moreover, it is debated how these components relate to one another. We present the development and validation of a six-item short-scale to measure attitudes towards refugees based on three surveys (Study 1: N=330; Study 2a: N=2,083; Study 2b: N=2,174). We assessed the performance of this scale with respect to three rivalling attitude conceptualizations (one-factor, three-factor, and second-order factor model). We found that a three-factor or second-order factor conceptualization fitted best to the data. The scale had excellent psychometric properties. We hope that our work stimulates a wave of relevant research on attitudes towards refugees that applies this scale, and contributes to the debate on the conceptualization of attitudes in general.

Examination of the latent structure of the Ruminative Thoughts Style Questionnaire across countries, gender, and over time

The present work aimed to extend the evidence of the structure validity of the Ruminative Thought Style Questionnaire (RTSQ) 15-item version testing: (1) the structure of two competing models (i.e., four-factor correlated model vs a second-order factor model); (2) the measurement invariance of the final model across four countries (U.S., Spain, Argentina, and the Netherlands) and gender groups (male and female); and (3) the invariance across three assessment waves in a subsample of Spanish youths. Participants were college students (mean age = 20.87, SD = 4.47) from the U.S. (n = 1875; 67.1% of females), Spain (T1, n = 732, 63.9% females; T2, n = 370, 71.6% females: T3, n = 307, 60.6% females), Argentina (n = 368, 65.6% females) and the Netherlands (n = 295, 74.8% females). Confirmatory Factor Analyses supported both correlated factors and second-order factor structure in the whole sample. Due to similar fit indices being observed for both models, and considering the theoretical and practical advantages, we kept the second-order model to examine its invariance across groups and time. Measurement invariance analyses showed that the second-order model was invariant across countries, gender, and over time. Comparisons of the total mean score and the subfacet mean scores (i.e., Repetitive Thoughts, Counterfactual Thoughts, Problem-focused Thoughts, and Anticipatory Thoughts) reveled only small differences across country and gender groups. The present work extends the structural validity evidence of the RTSQ, and provides the first evidence concerning its longitudinal stability across time.