Exploratory Modeling Research Articles

Understanding College Students’ Satisfaction With ChatGPT: An Exploratory And Predictive Machine Learning Approach Using Feature Engineering

Artificial Intelligence (AI) technologies are continually improving and becoming more pervasive in many facets of our lives. ChatGPT is one such cutting-edge artificial intelligence application, and it has received a lot of worldwide media attention, specifically from educationists, technologists, and learners. It is imperative to understand and evaluate the impact of ChatGPT on computer science students as it directly and holistically influences them. A quantitative instrumental case study explores ChatGPT’s impact on early adopters in education. A survey of undergraduate computer science students at a state university of Delhi was conducted to get insight into their opinion on adopting this revolutionising technology for their education, career, and overall satisfaction. An end-to-end data science approach is applied to encompass exploratory and predictive modelling with feature engineering solutions. Results reveal the most influential features contributing to students’ satisfaction in adopting ChatGPT for their day-to-day chores concerning their social life, education, and career. The Linear Support Vector classifier, a machine learning algorithm for predicting the satisfaction or dissatisfaction in students’ shows an accuracy score of 72.73% and 97.72%, respectively. The AUC for this multiclass prediction model is convincing and is 0.74, 0.71, and 0.96 for satisfied, neutral, and dissatisfied classes, respectively.

Healing experiences at resort hotels (HERH): Conceptualization and scale development

Anchored in healing experiences literature and therapeutic landscapes theory, this study aims to develop a Healing Experiences at Resort Hotels (HERH) scale. Study 1 comprises an extensive review and culminates in the initial identification of five dimensions. Subsequent intensive interviews with ten interviewees yield 170 statements, which are refined into 26 items spanning five dimensions. In Study 2, through exploratory structural equation modeling using 280 survey responses, results are refined to 22 items across four dimensions: sensory healing, social healing, wellness and cultural healing, and natural healing. With another 574 survey responses, Study 3 then confirms the scale’s reliability, construct and discriminant validity, and criterion-related validity. This four-dimensional 22-item HERH scale constitutes a groundbreaking effort to create a comprehensive scale for healing experiences at resort hotels. As a practical tool, the HERH can be applied by hoteliers to evaluate the quality of healing experiences at resort hotels.

Conceptualization and measurement of foreign language playfulness via exploratory structural equation modeling

The current research sought to conceptualize and measure foreign language playfulness (FLP), a recently developed construct in second language acquisition (SLA), through exploratory structural equation modeling (ESEM), a recently introduced scale measurement approach. Using a sample of 208 Iranian undergraduate language learners, we employed a series of statistical techniques to examine the underlying structure, best fitting model, psychometric properties, measurement invariance, and factor correlation of a new measure of FLP. Findings showed that bifactor EFA, compared with EFA, provided better representation for the underlying structure of the FLPS. Multiple model comparisons indicated that the bifactor ESEM model had a more satisfying representation of the FLPS than the other models (CFA, bifactor CFA, and ESEM). Cronbach's α and omega (ω) demonstrated that the FLPS is a reliable instrument. The bifactor ESEM model of the FLPS was also invariant across genders. Finally, factor correlation in ESEM exhibited a more accurate reflection of the association between the two factors (intellectual playfulness and other-directed playfulness) of the FLPS. The results were discussed by highlighting the importance of using ESEM to validate psychological constructs in SLA.

Navigating Knowledge

In this workshop, we will demonstrate four research tools: 1) card sorting, 2) upward laddering, 3) think-aloud, and 4) a search visualizer. Card sorting can be useful as an exploratory knowledge modelling method to gain insight into people’s understanding of their surrounding world. Derived from Kelly’s Personal Construct Theory (PCT) (Kelly, 1955, Herd, 2001), card sorting can help to explore peoples’ constructs and their perceptions of how the constructs relate to each other; in other words, card sorting can help to elucidate mental frameworks. Although there are many kinds of card sorting, we will guide participants through a hands-on exercise using single-criterion card sorting (using both digital and in person techniques). Participants will learn about text-based, image-based, and object-based options, when to use card sorting, how to collect data, and how to analyse card sorting data through visual-numeric ‘heat maps’ (co-occurrence matrices). The card sorting exercise will lead into upward laddering, a technique that is often used to complement card sorting. While card sorting provides evidence of how constructs are related, upward laddering allows exploration into goals and values (Rugg & Gerrard, 2023). Workshop participants will have an opportunity to access a simple, robust, newly created online tool for upward laddering. Also used alongside card sorting is the think-aloud method which involves both observation to see how people perform a task and think-aloud to hear what people are thinking and noticing while they perform the task. This inexpensive, easy-to-use method allows researchers to tap into reasons and tacit knowledge. The fourth tool we will demonstrate is a newly launched search visualiser (SV). Using keywords, this search tool allows researchers to comb through specific databases and/or to access Google results. Rather than simply return a list of links to articles, the SV returns a visual depiction of the keywords within each text. Each key word is represented as a coloured square. A user can hover their mouse pointer over a given square to see the phrase within which the word appears. Using this tool, researchers can get a better, visual sense of whether the article is likely to offer useful content. There is now a version with audio for visually impaired users as well as a version that can explore synonyms to support textual-literary analysis.

Psychometric Validation of the Gambling Craving Scale in a Treatment-Seeking Sample.

The Gambling Craving Scale (GACS) is a multifaceted measure of gambling craving. Initial validation work by Young and Wohl (2009) in university student samples showed that the GACS had a three-factor structure capturing dimensions of Desire, Anticipation, and Relief. Despite its potential clinical utility as a measure of craving, the GACS has yet to be validated in people seeking treatment for gambling problems. Accordingly, we examined the psychometric properties in a sample of people (N = 209; Mage = 37.66; 62.2% female) participating in a randomized controlled trial testing a novel online treatment for problem gambling. We predicted the GACS would have a three-factor structure. In addition, we also examined measurement invariance across sex and problem gambling risk status. Finally, we assessed concurrent validity of the factors with other measures of problem gambling severity and involvement. Exploratory structural equation modeling findings supported a three-factor structure that was invariant across the groups tested. Each of the Desire, Anticipation, and Relief subscales were significant positive predictors of problem gambling severity and symptoms, and some form of gambling behaviour. Findings show the GACS is a promising scale to assess multidimensional craving experiences among people in treatment for gambling problems.

Measuring emotional contagion as a multidimensional construct: the development and initial validation of the contagion of affective phenomena scales

ABSTRACT We offer an alternative conceptualization of the construct of susceptibility to emotional contagion and four related studies where two separate measures were developed and initially validated. The Contagion of Affective Phenomena Scale-General (CAPS-G) is a 5-item scale that measures the general susceptibility to the contagion of affect, and the Contagion of Affective Phenomena Scale – Emotion (CAPS-E) assesses six distinct emotions. Study 1 generated items with experts. Study 2 explored and confirmed construct validity and the factorial structure of both measures using exploratory structural equation modeling. Study 3 established test–retest reliability, concurrent validity, and discriminant validity. Study 4 found predictive validity with a sample of competitive swimmers. In four separate samples, a 21-item and 6-factor first-order structure of CAPS-E provided the best model fit. We provide initial evidence that supports the use of CAPS-E and CAPS-G as reliable and valid measures of the susceptibility to contagion of affective phenomena.

Validation of the Malay version of the recovery-stress questionnaire for athletes: Application of confirmatory factor analysis and exploratory structural equation modeling

The Recovery-Stress Questionnaire for Athletes (RESTQ-Sport-52) is a tool developed to measure the frequency of stress associated through recovery activities with strong theoretical foundations. The study aims to examine the psychometric properties of the Malay version of RESTQ-Sport-52 using confirmatory factor analysis (CFA) and exploratory structural equation modeling (ESEM). A cross-sectional study with purposive sampling method was employed. There were 617 undergraduate university students in Malaysia participated in the study with mean age of 20 years old (SD = 1.5). The majority of the participants were female (66.1 %), Malay (76 %) and participated in at least one sport or exercise. The RESTQ-Sport-52-M consisted of 52 items with two main sections; (1) general stress and recovery scales and (2) sport-specific stress and recovery scales. Mplus 8.3 was used to perform the CFA and ESEM analysis to examine the construct validity and reliability of RESTQ-Sport-52-M. For measurement model assessment using CFA, the final model of general-stress/recovery and sport-specific stress/recovery indicated a fit based on several fit indices. However, in the measurement model assessment using ESEM, the fit indices for model of general-stress/recovery (CFI = 0.935, SRMR = 0.037, RMSEA = 0.045) and sport-stress/recovery (CFI = 0.923, SRMR = 0.036, RMSEA = 0.044) were generally improved. The construct reliability for measurement models of RESTQ-Sport-52-M ranged from 0.76 to 0.89. The ESEM approach yielded a better fit indices compared to the CFA approach for both scales. The RESTQ-Sport-52-M (50 items) were considered a more valid and reliable questionnaire to measure recovery and stress in sports for Malaysian sample.

Posttraumatic stress disorder symptomology as measured by PCL-5 and its relationships to resilience, hostility and stress among paramedics and social professionals.

This survey study aimed to contribute to the extensive debate on the dimensionality of the Posttraumatic Stress Disorder Checklist for the DSM-5 (PCL-5) questionnaire by examining the psychometric properties and construct validity of its Hungarian version and relying on the inspection of a conceptual network of related variables, that is, perceived stress, hostility, and resilience. Confirmatory factor analysis (CFA), exploratory structural equation modelling (ESEM) and path analysis were applied on data collected from 177 paramedics and 66 professionals from the social field (58.4% male; Mage=43.5±9.96years). Despite the acceptable fit indices gained with CFA when testing the original four-factor DSM-5 model of PCL-5, strong associations (r=0.69-0.90) between subscales were found. Thus, ESEM was applied and as a result a new, three-factor version of the DSM-5 model of PCL-5 was proposed due to significant crossloadings that was theoretically also supported. The Reexperiencing and Avoidance subscales were merged and named Difficulty with Assimilation of Experience (DAE). In the path analysis only two of the tested associations were not significant using the new factor structure, in which stress fully mediated the relationship between resilience and DAE, and resilience and Hyperarousal. Overall, the hypothesised pathways between variables fit the collected data well. (weighted least squares mean-and variance-adjusted χ2=503.750 (df=270), comparative fit index=0.948, Tucker-Lewis index=0.939, root mean square error of approximation (90% confidence interval)=0.064 (0.055-0.073), weighted root mean square residual=1.024). Our analysis of the Hungarian version of PCL-5 contributes to the testing of a DSM-5-based questionnaire measuring posttraumatic stress disorder symptomology.

The Chronic Time Pressure Inventory: further assessment of factorial structure and validity.

Chronic time pressure represents a prevalent concern within modern society, and effective measurement is crucial for research advancement. The Chronic Time Pressure Inventory (CTPI) has thus far demonstrated adequate psychometric properties. However, only two studies have examined the measure and evidence of its validity is limited. Accordingly, the current investigation, via two independent studies, assessed the factorial composition and validity (convergent/discriminant) of the CTPI. Study 1 (N = 398) examined competing factorial models and validity in relation to the Big Five personality traits (Extraversion, Agreeableness, Conscientiousness, Neuroticism, Openness). Study 2 (N = 358) replicated the analysis of factor structure and assessed validity in comparison with five time perspectives (Past Negative, Present Fatalistic, Future, Past Positive, Present Hedonistic). Participants across both studies completed standardized self-report measures capturing the variables. Comparison of confirmatory factor analysis (CFA) and exploratory structural equation modelling (ESEM) factor solutions indicated that an ESEM bifactor model provided the strongest data-model fit. This included a general chronic time pressure component alongside specific subfactors of Feeling Harried and Cognitive Awareness of Time Shortage. All scale items reflected the general factor; however, some items loaded weakly on the intended specific factor. The CTPI is thus a robust indicator of chronic time pressure but needs refinement as a measure of the specific factors. Convergent/discriminant validity analyses inferred that the CTPI captured chronic time pressure as a related, but distinct, construct to perceived stress, and evidenced a relationship with theoretically associated constructs (Big Five personality traits and time perspective). Overall, the CTPI is a sound measure of chronic time pressure and has the potential to further cohesive research efforts on the contribution of this construct to various life domains.

Deterrents to the IoT for smart buildings and infrastructure development: A partial least square modeling approach

Implementing Internet of things (IoT) technology in the context of intelligent buildings and infrastructure development has garnered significant attention within the construction sector. Nonetheless, the implementation of IoT could be improved by assessing various barriers. The purpose of this study was to examine the obstacles related to the adaptation of IoT techniques within the construction sector, as well as the effects on the advancement of intelligent building and infrastructure systems. The study employed a mixed-method approach involving exploratory factor analysis (EFA) and structural equation modeling (SEM) to determine six types of barriers: knowledge, technical, standardization, creativity, complexity, and economics. The study revealed that the implementation of IoT for developing smart construction and infrastructure in the construction sector was significantly influenced by all six constructs. The results of this study offer significant ramifications for the field. The study underscores the necessity for heightened consciousness and instruction regarding the advantages of implementing IoT. The study posits that the technical barriers, including interoperability, modernization of legacy infrastructure, and coordination and collaboration difficulties, require attention from the industry. The study highlights the significance of establishing industry-wide standards and protocols for implementing IoT and regulatory and legal frameworks. Finally, the study underscores the necessity for augmented funding and financing options for IoT endeavors. Subsequent study endeavors may expand upon the present findings by delving into the barriers encountered by alternative sectors and nations and assessing the efficacy of the suggested measures in this investigation.

가상현실내 자기 현존감 척도(Self-Presence Questionnaire) 타당화

Self-presence in virtual reality is the degree to which a user identifies with their avatar, which increases the sense of reality and immersion. This study aims to validate the Self-Presence Questionnaire (SPQ), developed by Ratan and Hasler (2009). The original 23 items of the SPQ scale were translated and back-translated by a counseling expert fluent in both Korean and English and cross-reviewed. Exploratory factor analysis was conducted using data from 575 college students to determine the number of sub-factors, and the construct validity of the model was verified using Exploratory Structural Equation Modeling. As a result, the Korean version of the SPQ compromized three factors: 'Physical', 'Emotional', and 'Identity' self-presence, with a total of 23 items. Criterion, discriminant, and cross-validity of the completed scale were verified with high level of reliability. Finally, the significance of the research results, limitations, and suggestions for future studies were discussed.

A Persian Validation of the Occupational Depression Inventory

Abstract: The present study examined the psychometric and structural properties of the Persian version of the Occupational Depression Inventory (ODI). The ODI focuses on depressive symptoms that employed individuals specifically ascribe to their work. A sample of 355 Iranian schoolteachers was surveyed. Exploratory structural equation modeling (ESEM) bifactor analysis indicated that the ODI meets the requirements for essential unidimensionality. ESEM bifactor analysis and scalability analysis supported the use of the ODI’s total score. The instrument exhibited high reliability. Cross-cultural measurement invariance was supported. As for the concurrent validity of the ODI, occupational depression correlated, in the expected direction, with job satisfaction, life satisfaction, well-being, work engagement, sick leave, and antidepressant intake. No association was observed with sex, age, length of employment, and a history of depressive disorders over the past year. The ODI displayed a balance of convergent and discriminant validity vis-a-vis an attribution-free measure of depressive symptoms. The prevalence of occupational depression was estimated at 2.8% in our sample. Our findings endorse the Persian version of the ODI and confirm the instrument’s overall robustness.

Assessing Water Management Strategies in Data-Scarce Mountain Regions under Uncertain Climate and Socio-Economic Changes

Water management in mountainous regions faces significant challenges due to deep uncertainties arising from data scarcity, knowledge gaps, and the complex interplay of climate and socio-economic changes. While existing approaches focused on uncertainty reduction and water system optimization contribute to managing uncertainties, they often require probability distributions that can be difficult to obtain in data-scarce mountain regions. To address these challenges, we demonstrate the effectiveness of Exploratory Modeling and Analysis (EMA) in assessing water management strategies and identifying operational ranges that avoid future water scarcity. Through a case study in the complex and data-scarce Peruvian Andes, we employed EMA to run 12,000 simulations by 2050, incorporating deep uncertainties from climate and socio-economic scenarios, and hydrological modeling parameters. This analysis identified specific policy combinations demonstrating greater robustness across diverse scenarios and uncertainties. EMA explicitly identifies operational ranges of policies to avoid water scarcity but also highlights the conditions that might trigger policy failure. We also delve into the roles of the different factors used in EMA and their significance in water management applications. Our research illustrates that an exploratory hydrological modeling approach based on robust decision-making can foster a more informed decision-making process for long-term water adaptation in rapidly changing mountain regions under data scarcity and deep uncertainties.

Face as a multidimensional construct: Cross‐cultural validation of the Loss of Face Scale in Taiwan and the United States

AbstractFace culture is a crucial facet of East Asia. The most common self‐report measure for face concern is the unidimensional Loss of Face Scale. In this study, we examined the dimensionality, factor structure, and validity of the Loss of Face Scale in two samples. Sample 1 (N = 602) consisted of 303 Taiwanese mothers and 299 U.S. mothers. Sample 2 (N = 602) was an independent sample from Sample 1, consisting of 294 Taiwanese mothers and 308 U.S. mothers. We proposed a modified 15‐item four‐dimensional factor structure to better capture the complexity of face. Four sub‐domains emerged from the results of exploratory structural equation modelling: Low‐Profile, Over‐Preparation, Harmony Seeking, and Non‐Aggression. Multigroup confirmatory factor analysis indicated configural and metric invariance but failed to establish full scalar invariance across countries. Convergent validity was supported by positive correlations with other Asian cultural values. While all four domains of face showed small to moderate correlations with depression in the U.S., only Low‐Profile was associated with depression in Taiwan, suggesting that not all aspects of face concern are non‐adaptive in East Asian contexts. Future studies should consider the multidimensional nature of face as well as how different dimensions affect mental and social well‐being across cultures.

Assessing the attention-interest-search-action-share (AISAS) model on the traditional textile exhibition visitors

Indonesia, rich in diverse ethnicities, celebrates numerous traditional textile traditions. Traditional textile marketing often finds expression through exhibitions. This study explores the applicability of the AISAS model in the exhibitions of traditional textiles in Jakarta. The research engages 235 participants aged 17 and above, all social media users with prior attendance at such exhibitions. Data analysis uses exploratory and confirmatory factor analyses and structural equation modelling. Hypothesis testing for the linear AISAS model affirms the impact of attention on interest, interest on search, search on action, and action on share, demonstrating positive outcomes. The non-linear AISAS model also confirms the impact of attention on interest and interest on search. However, the impact of interest on action reveals a nuanced result and the effects of search on action face rejection. This study holds significance for MICE (meetings, incentives, conferences, and exhibitions) marketing and textile exhibition strategies, providing valuable insights into consumer behaviour during traditional textile exhibitions.

Power or opportunity? Perceived inequality on life satisfaction explained by reduced trust in South Korea

AbstractThis paper presents new evidence linking different aspects of perceived inequality (education, employment, law enforcement, income and wealth, power, and gender) to life satisfaction. Using large‐scale national survey data, we examined the relationships between the six aspects of perceived inequality, life satisfaction, and generalized trust among South Koreans (N = 17,357). Exploratory structural equation modelling identified a two‐factor structure of perceived inequality: Opportunity Inequality (inequalities in education and employment) and Power Inequality (inequalities in income and wealth, law enforcement, power, and gender). Results from mediation analysis suggested that both aspects of inequality negatively predicted life satisfaction via reduced generalized trust. Those processes were consistent regardless of household income. The study underscores the critical impact that public perceptions of (in)equality in various opportunity and power aspects have on well‐being and trust and emphasizes the urgency of government and policy action to address the growing problem of inequality in South Korean society. The findings highlight the urgent need to address disparities and promote social harmony and well‐being in countries facing similar challenges.

A dynamic exploratory hybrid modelling framework for simulating complex and uncertain system

Complex disaster systems involve various components and mechanisms that could interact in complex ways and change over time, leading to significant deep uncertainty. Due to deep uncertainty, decision-makers have severe inadequacy of knowledge and often encounter unpredictable surprises that may emerge in the future, thus making it difficult to specify appropriate models and parameters to describe the system of interest. In this paper, we propose a dynamic exploratory hybrid modeling framework that fits data, models, and computational experiments together to simulate complex systems with deep uncertainty. In the framework, one needs to develop multiple plausible models from a hybrid modeling perspective and perform enormous computational experiments to explore the diversity of future scenarios. Real-time data is then incorporated into diverse forecasts to dynamically adjust the simulation system. This ultimately enables an ongoing modeling and analysis process in which deep uncertainty would be gradually mitigated. Our approach has been applied to a human-involved car-following system simulation under complex traffic conditions. The results show that the proposed approach can improve the prediction accuracy while enhancing the sensitivity of the simulation system to uncertain changes in the system of interest.

Psychometric properties of the Italian version of the Occupational Fatigue Exhaustion/Recovery (OFER) scale among healthcare professionals

ABSTRACT Objective The purpose of this study was to analyze the psychometric properties of the Italian version of the Occupational Fatigue Exhaustion/Recovery (OFER). Methods A cross-sectional study among 434 healthcare workers was undertaken. The factorial validity of the OFER, was compared using standard confirmatory factor analysis (CFA) with exploratory structural equation modeling (ESEM). Internal consistency, convergent validity, and factorial invariance (across gender) were assessed. Results A three-factor first-order ESEM solution provided the best and most parsimonious representation of the data: χ2(63) = 212.81, p < .001, RMSEA = 0.074 (90% CI 0.063–0.085), CFI = 0.949, TLI = 0.915. The three-factors were chronic fatigue, acute fatigue, and intershift recovery. Chronic and acute factors showed excellent internal consistency (ω > 0.80), however intershift recovery showed less internal consistency (ω < 0.70). OFER scores were found to be positively correlated with FAS scores, supporting its convergent validity. Conclusions The OFER was factorially invariant across gender. Overall, our findings provided evidence for the satisfactory psychometric properties of the OFER among Italian workers, confirming its value for use in both practical occupational and academic research settings.

The factor structure the PHQ-9 in Russian patients recovered from COVID-19

IntroductionThe nine-item Patient Health Questionnaire-9 (PHQ-9) is the first choice for screening for depression in primary care and other medical settings. The PHQ-9 has been shown to be a reliable and valid measure of depression symptoms, but there is disagreement among researchers about the factor structure of this questionnaire. Recent systematic reviews have found four different factor models of the PHQ-9, with one- and two-factor models being the most common. This discrepancy may be due to linguistic, cultural and clinical differences between the populations studied. The factor structure of the Russian version of the PHQ-9 during the COVID-19 pandemic has not been examined in any study to date.ObjectivesThe aim of our study was to determine the factorial structure and internal consistency of the Russian version of the PHQ-9 in COVID-19 survivors.MethodsFourteen thousand 725 (female - 11479 (78.0%), age - 18-79 years (M - 47.09, SD - 12.70) participants completed an online survey including the PHQ-9 and an ad hoc questionnaire focusing on sociodemographic and COVID-related characteristics. McDonald’s omega coefficient was estimated to determine the internal consistency of the questionnaire. Exploratory structural equation modelling (ESEM) with weighted least squares mean and variance adjusted estimator and geomin rotation was performed in Mplus 7.ResultsESEM provided evidence for a three-factor structure of the PHQ-9, representing affective (items 2, 6, 9), anergic (items 1, 3) and somatic (items 3, 5, 7, 8) dimensions of depression. These factors fit the data well (CFI - 0.998; TLI - 0.994; RMSEA (95% CI) - 0.028 (0.024 - 0.032)), better than a single factor (CFI - 0. 955; TLI - 0. 940; RMSEA (95% CI) - 0.089 (0.087 - 0.092)) and two-factor (CFI - 0.985; TLI - 0.971; RMSEA (95% CI) - 0.062 (0.059 - 0.065)). The McDonald’s omega was 0.82.ConclusionsOur study revealed a three-factor structure of the Russian version of the PHQ-9 in COVID-19 survivors. COVID-19. A high internal consistency of the Russian version of the instrument was confirmed.Disclosure of InterestNone Declared

Investigation of the factor structure of GAD-7 in Moscow residents exposed to SARS-CoV2

IntroductionRates of anxiety in the general population increased significantly during the COVID-19 pandemic. Several studies have shown that people exposed to SARS-CoV2 are at increased risk for both exacerbation and de novo development of anxiety disorders. Therefore, screening for anxiety disorders in this at-risk population is essential. In pre-pandemic studies, the 7-item Generalized Anxiety Disorder Questionnaire (GAD-7) was one of the most commonly used self-report instruments. Its validity has been demonstrated in several studies. However, there is no agreement among researchers about its underlying internal structure. Both one-factor and two-factor solutions have been reported. This discrepancy may be due to linguistic, cultural, and clinical differences between the populations studied. To our knowledge, no studies have been conducted to investigate the factor structure of the GAD-7 in the Russian-speaking community sample and the psychometric properties of this questionnaire in SARS-CoV2 exposed individuals.ObjectivesThe aim of the study was to determine the factorial structure and internal consistency of the Russian version of the GAD-7 in a large sample of Moscow residents exposed to SARS-CoV2.MethodsFourteen thousand 725 (male - 11479 (78.0%), age - 18-79 years (M - 47.09, SD - 12.70) Moscow residents exposed to SARS-CoV2 completed an online survey including the GAD-7 and an ad hoc questionnaire focusing on socio-demographic characteristics. McDonald’s Omega was used to assess internal consistency. Exploratory structural equation modelling (ESEM) with weighted least squares means and variance adjusted estimator and geomin rotation was used to assess the factor structure of the Russian version of the GAD-7.ResultsThe McDonald’s Omega of the Russian version of the GAD-7 was 0.85, indicating a good internal consistency of the questionnaire. ESEM provided evidence for a one-factor solution that fits the data well (CFI - 0.996; TLI - 0.995; RMSEA (95% CI) - 0.041 (0.037 - 0.045)).ConclusionsIn Russian people exposed to SARS-CoV2, the GAD-7 showed good internal consistency. Our results are consistent with those of previous studies that reported a single-factor solution for the questionnaire.Disclosure of InterestNone Declared