{"paper_id":"44ccdf39-5a2a-490a-b6ea-2181863d7191","body_text":"Evaluating dispositional gratitude among Saudi adults: Reliability, factor structure and measurement invariance of the Gratitude Questionnaire (GQ6) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Evaluating dispositional gratitude among Saudi adults: Reliability, factor structure and measurement invariance of the Gratitude Questionnaire (GQ6) Mohsen M. Alyami, Kateb A. Alshammari, Hassan A. Alzahrani This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7548318/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Empirical evidence underscores gratitude as a protective factor for psychosocial health, highlighting the need for reliable measures. The Gratitude Questionnaire six-item form (GQ6) is widely used to assess dispositional gratitude; its Arabic version is lacking. This study aimed to translate the GQ6 into Arabic and evaluate its psychometric properties, including reliability, factor structure, discriminant validity, and measurement invariance across age and sex groups. Methods A sample of 536 university students ( M age = 23.01, SD = 4.84 years; 50% female) completed an online questionnaire containing the GQ6 and other psychological measures. Exploratory factor analysis (EFA) was conducted on half the sample to identify the underlying factor structure, followed by confirmatory factor analysis (CFA) to validate the model using fit indices including RMSEA, SRMR, CFI, and TLI. Rasch analysis provided detailed item-level insights, and measurement invariance was assessed using multi-group confirmatory factor analysis (MGCFA). Internal consistency was evaluated using Cronbach’s α and McDonald’s ω. Results Initial analyses showed low internal consistency for the Arabic GQ6, leading to the exclusion of two reverse-coded items. Subsequent analyses indicated that a one-factor model with four items (GQ4) exhibited good fit (CFI = 0.96, TLI = 0.89, RMSEA = 0.19, SRMR = 0.03), and good internal consistency (α and ω = 0.85). The GQ4 showed moderate positive correlations with satisfaction with life, self-esteem, and overall well-being ( r = 0.48, 0.42, and 0.43, p < .001 respectively). Regarding measurement invariance, MGCFA supported configural and metric invariance across sex and age groups. Furthermore, Rasch analysis showed that the GQ4 Arabic version demonstrates consistent item performance and minimal variation in response patterns. Conclusion Overall, the GQ4 Arabic version is a reliable and valid measure of dispositional gratitude among Arabic-speaking adults. Psychology Gratitude dispositional gratitude Arabic Gratitude Questionnaire (GQ6) psychometric reliability validity measurement invariance Figures Figure 1 Introduction Gratitude, a complex and multifaceted emotion, has garnered significant scholarly attention, particularly within the field of positive psychology [ 1 , 2 ]. It is conceptualized as both a state and a trait [ 3 , 4 ]. As a state, gratitude is a temporary emotional experience triggered by specific events, marked by feelings of thankfulness and appreciation for the benefits received [ 3 ]. As a trait, gratitude is a stable characteristic or a disposition to notice and appreciate the world in a positive light. This dispositional gratitude has been defined as “ a generalized tendency to recognize and respond with grateful emotion to the roles of other people’s benevolence in the positive experiences and outcomes that one obtains ” (p.112) [ 5 ]. Individuals high in dispositional gratitude tend to feel grateful more frequently and intensely across a wider range of circumstances and maintain a positive outlook on life compared to individuals low in dispositional gratitude [ 6 ]. Gratitude plays a crucial role in enhancing psychosocial well-being, fostering positive relationships, and promoting resilience [ 2 , 4 , 7 ]. A seven year longitudinal study of a nationally representative sample of military veterans found that individuals with high levels of dispositional gratitude were less likely to develop symptoms of depression, anxiety, post-traumatic stress disorder (PTSD), and suicidal behaviours [ 8 ]. Similarly, research involving military soldiers revealed that gratitude not only has direct effects on quality of life but also exerts indirect effects on quality of life via perceived stress [ 9 ]. Analytical reviews have found moderate inverse relationships between gratitude and both post-traumatic stress disorder (PTSD) severity and depression [ 10 , 11 ]. Among student veterans receiving rehabilitation counselling, dispositional gratitude has been linked to a lower intention to drop out, even when controlling for poor academic performance and PTSD symptoms [ 12 ]. Longitudinal studies involving adults with disabilities have shown that higher levels of gratitude enhance flourishing and improve adaptation to disability [ 13 ]. Beyond veterans and clinical samples, gratitude also benefits performance contexts. For example, among athletes gratitude has been found to exhibit a direct negative relationship with burnout and an indirect negative effect through the coach-athlete relationship and hope [ 14 ]. A recent review examining gratitude and life satisfaction (SWL) found strong evidence of a positive correlation between the two [ 15 ].This review encompassed longitudinal cross-lagged studies, all of which supported a causal model suggesting that increased gratitude leads to enhanced SWL [ 15 ]. Gratitude-based interventions have gained significant attention over the last two decades, leading to several reviews on their effects. For instance, recent reviews of expressed gratitude interventions (e.g., writing thank-you notes) found that these interventions significantly improved psychological well-being. Key benefits included enhanced life satisfaction, increased positive affect, and greater happiness [ 15 , 16 ]. Additionally, other reviews have identified modest but significant effect on reducing symptoms of depression and anxiety [ 17 , 18 ] as well as improving sleep quality and prosocial behaviours [ 7 , 19 , 20 ]. Overall, the findings from the observational, longitudinal and intervention studies highlight the importance of gratitude as a potential protective factor for health and well-being, underscoring the need for reliable and valid measures of gratitude. A widely used measure of gratitude as a trait in psychological research is the Gratitude Questionnaire-six item form (GQ6) [ 5 ]. The authors initially developed a 39-item pool aimed at measuring individual differences in people’s disposition or propensity to experience gratitude in everyday life. In study 1, data were collected from a sample of undergraduate psychology students, predominantly young adults [ 5 ]. In addition to the gratitude items, participants also completed various other measures including satisfaction, hope, optimism, happiness, positive and negative affect, empathy, social desirability, and personality traits. Using various statistical techniques, including exploratory factor analysis and structural equation modelling with maximum likelihood estimation, 6 items that loaded strongly on the first factor and uniquely captured different aspects of dispositional gratitude were retained. The authors concluded that the GQ6 has adequate reliability (Cronbach’s α of 0.82), as well as discriminant, convergent and construct validity. In subsequent studies using diverse samples, including older adults, confirmatory factor analysis further validated the one-factor structure of the GQ6 and provided additional evidence for its reliability and validity [ 5 ]. The GQ6 is commonly used in cross-cultural research [ 21 ]. It has been validated in various languages including in Brazil Portuguese [ 22 ], Chinese [ 23 – 25 ], Dutch [ 26 ], German [ 27 ], Hindi [ 28 ], Japanese [ 29 ], Spanish [ 30 , 31 ], Taiwanese [ 32 ], and Turkish [ 33 ]. The GQ6 has also been used in gratitude interventions among various samples, including individuals with PTSD [ 11 ], older adults with chronic pain [ 34 ], adults with depression and anxiety [ 35 ], athletes [ 14 ], and pregnant women [ 36 ]. Despite the GQ6 has shown robust psychometric properties [ 5 , 37 ], concerns persist about its item composition [ 21 ]. Specifically, Item 6: “Long amounts of time can go by before I feel grateful to something or someone” has been identified as problematic. Several adaptations of the GQ6, including Chinese [ 24 ], Dutch [ 26 ], Italian [ 38 ], Japanese [ 29 ], and Portuguese [ 22 ], have retained all six original items. On the other hand, other research has found that Item 6 exhibits low corrected item-total correlation and low factor loading [ 23 , 27 , 28 , 30 – 33 , 39 ]. As a result, these studies developed a five-item version (GQ5) by removing Item 6. These inconsistencies underscore the need to investigate the GQ6’s item composition across different cultural contexts. Despite its extensive use, there is currently no published Arabic version of the GQ6, presenting a significant gap in gratitude research within Arabic-speaking populations. Therefore, the aims of the current study are twofold: (1) to translate the GQ6 into Arabic and evaluate its psychometric properties, including reliability and factor structure; and (2) to evaluate the measurement invariance of the Arabic version of the GQ6 across age and sex groups. Developing a reliable and valid Arabic version of the GQ6 is essential, as it would promote further research into gratitude, potentially leading to valuable insights into its role in psychosocial well-being among Arabic-speaking populations. Methods Study design and participants A cross-sectional design was used, with a convenience sample of undergraduate and postgraduate students recruited from a Saudi university. Recruitment of potential participants involved (1) distributing campus flyers with a QR code linking to the online survey, and (2) in-person invitations by the research team members during lectures. This multi-faceted approach facilitated the recruitment of a diverse sample from different colleges. Eligibility criteria included being 18 years of age or older and fluent in Arabic, the language in which the study was administered. Participants completed a structured anonymous online questionnaire administered between December 2024 to April 2025. The online format offered convenience and accessibility, allowing participants to complete the questionnaire at their own pace while ensuring their anonymity (i.e., no identifying information was collected, such as names, emails, or IP addresses was collected). Participants were provided an information sheet, and their participation was voluntary. Electronic informed consents were obtained electronically. Additionally, no study credits or financial compensation were provided for participation. This research received approval from the Research Ethics Committee at [Information Blinded] University ( Information Blinded ), and all procedures followed were in accordance with the Declaration of Helsinki. Measures Participants provided information on the following demographic variables: age (in years), sex (male, female), marital status (single, married, divorced, widowed), educational level (undergraduate, Master, PhD), and academic field of study (medicine, science, humanities, business, education, etc.). The Gratitude Questionnaire (GQ6) The GQ6 is a self-report measure designed to assess individual differences in people’s disposition or propensity to experience gratitude in everyday life [ 5 ]. It consists of 6 items, each is scored on a 7-point Likert-type scale, ranging from 1 (strongly disagree) to 7 (strongly agree). Two items (Item 3 and Item 6) are reverse-coded. The total score is the sum of individual item scores, with higher scores corresponding to higher levels of trait gratitude. The GQ6 has been shown to have sound psychometric properties across various languages and cultures [ 5 , 21 , 37 ]. The English GQ6 version was translated into Arabic using established guidelines [ 40 – 42 ] to ensure semantic equivalence and cultural appropriateness. First, the English GQ6 was independently translated into Arabic by two bilingual individuals: the first was a professional independent Saudi translator, and the second was a member of the research team. Both individuals completed their translations independently, producing two preliminary versions. Second, another research team member, fluent in both English and Arabic, acted as a moderator by comparing the two preliminary versions. Discrepancies were resolved through iterative discussions with the team, resulting in a single approved Arabic version of the GQ6. Third, an independent bilingual Saudi educational psychologist (unfamiliar with the GQ6 original version) back-translated the Arabic version into English. Following this, the original and back-translated English versions of the GQ6 were compared for equivalence and cultural appropriateness. Finally, the final Arabic version of the GQ6 was piloted with a convenience sample of 23 Saudi university undergraduate university students to assess comprehension. Based on the participants’ responses, no major changes were necessary. Satisfaction With Life Scale (SWLS) Participants’ SWL was assessed using the Satisfaction with Life Scale (SWLS) [ 43 ]. The SWLS is a global measure of one’s overall SWL, consisting of 5 items. Items are scored on a 7-point Likert-type scale, with response ranging from 1 (strongly disagree) to 7 (strongly agree), yielding total scores between 5 and 35. Higher scores indicate greater satisfaction [ 43 ]. Both the English and Arabic versions of the SWLS have demonstrated adequate reliability and validity [ 44 – 46 ]. Rosenberg Self-Esteem Scale (RSES) Participants’ overall sense of self-esteem, encompassing both positive and negative emotions about oneself, was assessed using the Rosenberg Self-Esteem Scale (RSES) [ 47 ]. The RSES consists of 10 items, each scored on a 4-point Likert scale ranging from 1 (strongly disagree) to 4 (strongly agree). Among these items, five are reverse-coded items. Total scores range from 10 to 40, with higher total scores denote higher self-esteem. The RSES is a reliable and valid measure of global self-esteem [ 48 , 49 ], and has been widely used in Arabic-speaking samples [ 50 – 52 ]. World Health Organization Well-Being Index (WHO-5) Subjective well-being was evaluated using the World Health Organization Well-Being Index (WHO-5), a short version of the WHO 10-item scale [ 53 ]. The WHO-5 is a brief and generic measure of subjective well-being over the last two weeks [ 54 ]. Items are scored on a 6-point Likert scale ranging from 0 (at no time) to 5 (all of the time). The total score ranges from 0 to 25, with higher scores indicating best possible well-being. The WHO-5 has been shown to have adequate reliability and validity in various populations [ 54 , 55 ], including among Arabic-speaking healthy and clinical samples [ 56 – 58 ]. Data Analysis Participant characteristics were summarized using absolute and relative frequencies for categorical and median with interquartile range (IQR) for continuous measures. Descriptive statistics and Spearman rank correlations between items were performed. Descriptive statistics were calculated for each item and the total gratitude score. The mean, standard deviation, and skewness of each item were computed to assess central tendency and distribution. Internal consistency was evaluated using Cronbach’s α, McDonald’s omega (ω) coefficients and corrected item-total correlations. A α and ω coefficient of 0.70 or above, along with corrected item-total correlation greater than 0.30, was considered acceptable [ 59 , 60 ]. To assess the underlying factor structure, Exploratory factor analysis (EFA) was conducted on a randomly split 50% subset of the data (n = 268). The Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy (MSA) and Bartlett's test of sphericity were employed to evaluate the suitability of the data for factor analysis. KMO values exceeding 0.6 and a significant Bartlett’s test ( p < 0.05) confirmed adequacy of the data. Maximum likelihood method was used to extract factors, followed by Oblimin rotation. Factor loadings ≥ 0.40 were considered significant for item retention. Confirmatory factor analysis (CFA) was performed on the remaining 50% of the data (n = 268) to validate the factor structure identified in EFA using lavaan package in R with and maximum likelihood estimation. Model fit was assessed using multiple indices, including the chi-square statistic (𝜒 2 ), root mean square error of approximation (RMSEA) with its 95% confidence interval (CI), standardized root mean square residual (SRMR), comparative fit index (CFI), and Tucker-Lewis index (TLI). Cutoff values of RMSEA < 0.06, SRMR < 0.08, and CFI/TLI ≥ 0.95 were considered indicative of good model fit. Additionally, goodness-of-fit index (GFI), adjusted goodness-of-fit index (AGFI), consistent Akaike information criterion (CAIC), and Bayesian information criterion (BIC) were evaluated to further validate model fit [ 61 ]. Concurrent validity was evaluated by examining correlations between the GQ6 and with relevant psychological measures (SWLS, RSES, and WHO-5). Measurement invariance analysis was conducted to examine whether the factor structure held across different demographic groups (sex and age group). Participants were categorized into two distinct age groups: those under 21 years and those aged 21 years and above, based on the median split. We tested for configural, metric, scalar, and strict invariance using the lavaan package in R [ 62 ]. Configural invariance was assessed first to ensure that the same factor structure was valid across groups, followed by tests for metric invariance (equality of factor loadings), scalar invariance (equality of item intercepts) and strict invariance (equality of residuals) [ 63 ]. Model fit was evaluated using the CFI, RMSEA, and SRMR. Based on established guidelines [ 63 – 65 ], invariance was supported if the change in CFI (ΔCFI) was ≤ 0.01, the change in RMSEA (ΔRMSEA) was ≤ 0.015, and the change in SRMR (ΔSRMR) was ≤ 0.030 for metric and ≤ 0.010 for scalar and strict invariance levels. Rasch Rating Scale Model (RSM) was performed using TAM R package to assess the item functioning and fit of the data to the Rasch model. The analysis focused on evaluating the thresholds for each item and determining whether they were consistent with the intended scale. Item fit statistics, such as Infit and Outfit Mean Square, were calculated to evaluate whether each item fit the Rasch model well. Additionally, person reliability was computed to assess the model’s ability to accurately distinguish between different levels of person ability. We also provided a graphical illustration of the estimated item parameters using Item Characteristic Curves (ICCs). All the analyses were performed using R statistical programming (v4.4.1). Results A total of 536 participants had complete data. Participants had a median age of 21 years, with an interquartile range (IQR) of 20 to 25 years and mean age of 23.01 year (SD = 4.84). The sample was evenly distributed by sex (50% female) and predominantly single (86%). Most participants (93%) were undergraduate students with nearly half (48%) enrolled at the College of Education, followed by Computer Science and Engineering (Table 1 ). Table 1 Sociodemographic characteristics of participants (n = 536) Characteristic N (%) Sex Male 268 (50%) Female 268 (50%) Marital status Single 460 (86%) Married 76 (14%) Educational level Bachelor 498 (93%) Master 26 (4.9%) PhD 12 (2.2%) Area of study Applied Medical Sciences 19 (3.5%) Business Administration 36 (6.7%) Computer Science and Engineering 75 (14%) Education 258 (48%) Law 30 (5.6%) Literature and Arts 56 (10%) Nursing 38 (7.1%) Sciences 24 (4.5%) Table 2 presents the descriptive statistics of individual items and total score. The positively worded items (Items 1, 2, 4, and 5) demonstrated high mean scores (range: 6.12–6.38) and negative skewness (-2.30 to -1.65), indicating that most participants responded positively. In contrast, the reverse-coded items (Items 3 and 6) showed substantially lower means (2.75 and 2.33, respectively) with positive skewness (0.91–1.34), indicating that participants generally expressed lower levels of agreement with these negative statements. The total GQ6 score distribution (Mean = 30.07, SD = 3.88; median = 30; range = 18–42) exhibited moderate variability. Histograms displaying the distributions of all items and total scores are available in the supplementary materials. Table 2 Descriptive statistics of the Arabic GQ6 version (n = 536) Item Mean SD Skewness kurtosis SE GQ1 6.36 1.03 -2.30 6.67 0.04 GQ2 6.13 1.22 -1.69 2.89 0.05 GQ3* 2.75 1.84 0.91 -0.22 0.08 GQ4 6.12 1.19 -1.65 3.09 0.05 GQ5 6.38 0.98 -2.26 6.76 0.04 GQ6* 2.33 1.59 1.34 1.17 0.07 GQ6 total score 30.07 3.88 0.37 1.51 0.17 Note : *Negative items; SD, Standard Deviation; SE, Standard Error Reliability Analysis Reliability analysis showed suboptimal internal consistency for the full GQ6 (α = 0.34, ω = 0.40). As shown in Table 3 , removing the reverse-coded items (GQ3 and GQ6) would result in a relatively higher α and ω coefficient values. The scale demonstrated moderate common variance, with a squared multiple correlation of 0.67, indicating that 67% of item variance was explained by the underlying factor. Corrected item-total correlations ranged from 0.34 to 0.60, with the reversed-coded items (GQ3 and GQ6) showing the lowest correlations (0.45 and 0.34), indicating a weaker relationship with the total score. In contrast, GQ2 exhibited the highest item-total correlation (0.60), suggesting it is more consistent with the overall scale. Table 3 Reliability analysis of the Arabic versions of the original GQ6 and modified GQ4 Item α α if deleted SMC if item deleted ω ω if deleted Item-total correlation Original GQ6 GQ1 0.20 0.52 0.19 0.57 GQ2 0.18 0.53 0.17 0.60 GQ3* 0.48 0.71 0.65 0.45 GQ4 0.22 0.57 0.22 0.55 GQ5 0.20 0.55 0.23 0.56 GQ6* 0.47 0.72 0.61 0.34 GQ6 total score 0.34 0.67 0.40 Modified GQ4 GQ1 0.79 0.72 0.79 0.84 GQ2 0.80 0.74 0.80 0.85 GQ4 0.82 0.77 0.82 0.82 GQ5 0.81 0.75 0.81 0.81 GQ4 total score 0.85 0.85 Note : *Negative items; α, Cronbach’s alpha coefficient; ω, McDonald’s omega coefficient; SMC, Squared Multiple Correlation Factor Analysis A random subset comprising 50% of the data (n = 268) was used to conduct the EFA. The data demonstrated adequate factorability, with KMO value of 0.76 and a significant Bartlett's test of sphericity ( p < 0.001). Individual KMO values ranged from 0.55 to 0.85, with GQ4 (0.83) and GQ5 (0.85) showing particularly strong sampling adequacy. Notably, the reverse-coded item (GQ3) had the lowest measure of sampling adequacy (0.55), falling slightly below the conventional 0.60 threshold. As shown in Table 4 , the factor solution revealed clear differentiation between items. Positively worded items (GQ1, GQ2, GQ4 and GQ5) loaded strongly on factor 1 (0.67–0.80), while the reverse-coded items (GQ3 and GQ6) loaded poorly on factor 1 (< 0.40), suggesting they may represent a distinct dimension or contribute to measurement inconsistency. Table 4 EFA factor loadings of Arabic version of the GQ6 (n = 268) Item Factor1 Communality Uniqueness Comprehensiveness GQ1 0.80 0.64 0.36 1 GQ2 0.78 0.60 0.40 1 GQ3* -0.20 0.04 0.96 1 GQ4 0.67 0.45 0.55 1 GQ5 0.67 0.45 0.55 1 GQ6* -0.35 0.12 0.88 1 Note : *Negative item. The two reverse-coded items (GQ3 and GQ6) were removed from further analyses due to their low item-total correlations and factor loadings. Subsequently, a one-factor structure using a modified GQ4 with four items (GQ1, GQ2, GQ4, and GQ5) was tested using CFA on the second random subset of the data (n = 268). Several goodness-of-fit indices were calculated, and the result indicate that the model fit was acceptable (CFI = 0.96, TLI = 0.89, RMSEA = 0.19 (90% CI: 0.12–0.26), SRMR = 0.03, GFI = 0.96, AGFI = 0.83). Most indices were within recommended thresholds, indicating a good model fit. However, the RMSEA value of 0.19 exceeded the commonly accepted threshold of 0.05 for a good fit. Both, the BIC and CAIC were within acceptable limits, with no alternative model exhibiting a significantly lower BIC (ΔBIC ≥ 10). All four items loaded significantly onto their respective factor ( p < 0.001). Standardized factor loadings are shown in Table 5 . The reliability for the newly modified Arabic GQ4 version was very good (α and ω = 0.85). Table 5 CFA standardized factor loadings of the modified Arabic version of the of the GQ4 (n = 268) Factor Items Standardized loading (95%CI) 1 GQ1 0.84 (0.79, 0.89) 1 GQ2 0.78 (0.73, 0.84) 1 GQ4 0.72 (0.65, 0.78) 1 GQ5 0.81 (0.75, 0.86) Concurrent validity The GQ4 demonstrates concurrent validity through significant positive correlations with three established psychological measures including the RSES ( r = 0.419, p < .001), the SWLS ( r = 0.467, p < .001), and the WHO-5 ( r = 0.430, p < .001). Measurement invariance The measurement invariance analyses of the Arabic GQ4 were conducted on the entire sample (n = 536) through sequential model testing. The baseline configural invariance model, which tested the structure’s consistency across sexes demonstrated an acceptable fit: χ²(4) = 48.6, p < .001; CFI = 0.949, TLI = 0.846, RMSEA = 0.204 (95% CI [0.155, 0.257]); SRMR = 0.037. Despite a significant chi-square statistic, the acceptable CFI (> 0.90) and SRMR (< 0.08) values suggest that the basic factorial structure is generally similar across sex groups. However, the RMSEA exceeded the recommended threshold (0.08), indicating potential areas for model improvement. Metric invariance was also tested by constraining factor loadings to be equal across sexes. The model showed acceptable fit: χ²(7) = 57.2, p < .001; CFI = 0.942; TLI = 0.901; RMSEA = 0.164 (95%CI [0.126, 0.204]); SRMR = 0.059. The chi-square difference test compared to the configural model was statistically significant, Δχ²(3) = 8.60, p = 0.035, suggesting that constraining the factor loadings significantly worsened model fit. While the change in CFI was below the recommended threshold (ΔCFI = 0.007), the change in RMSEA exceeded the commonly accepted cutoff (ΔRMSEA = 0.04). Given this mixed pattern of results, strict metric invariance cannot be fully assumed, indicating that some factor loadings may differ across males and females. However, the modification indices for all item loadings were very low (0.021), indicating that the loadings are not causing big misfit across groups. Scalar invariance was tested by constraining both factor loadings and item intercepts to be equal across sexes. The model fit indices were acceptable: χ²(10) = 73.7, p < .001; CFI = 0.927; TLI = 0.912; RMSEA = 0.154 (95%CI [0.122, 0.188]); SRMR = 0.072. The chi-square difference test compared to the metric model was statistically significant, Δχ²(3) = 16.52, p < 0.001, supporting partial scalar invariance. However, the modification indices for intercepts show all the intercepts were equally constrained across sex groups. The strict invariance model also showed poor fit with χ²(14) = 104.3, p < 0.001, CFI = 0.896, TLI = 0.911, and RMSEA = 0.155 (95%CI [0.128, 0.184]), SRMR = 0.071, indicating that it did not provide a better fit compared to the scalar invariance model. The chi-square difference test compared to the metric model was statistically significant, Δχ²(3) = 30.6, p < 0.001, supporting partial strict invariance. The analysis of measurement invariance based on age groups as follows. The baseline configural invariance model testing the consistency across age groups demonstrated an acceptable fit: χ²(4) = 36.4, p < .001; CFI = 0.965, TLI = 0.895, RMSEA = 0.174 (95% CI [0.125, 0.228]); SRMR = 0.026. The acceptable CFI (> 0.90) and SRMR (< 0.08) values suggest that the basic factorial structure is similar across groups. The metric invariance model also showed an acceptable fit: χ²(7) = 38.1, p < .001; CFI = 0.966; TLI = 0.942; RMSEA = 0.129 (95%CI [0.091, 0.170]); SRMR = 0.032. The chi-square difference test compared to the configural model was not statistically significant, Δχ²(3) = 1.70, p = 0.637, suggesting metric invariance holds true across age groups. The scalar invariance model fit indices were also within acceptable thresholds: χ²(10) = 45.1, p < .001; CFI = 0.962; TLI = 0.954; RMSEA = 0.114 (95%CI [0.082, 0.149]); SRMR = 0.039. The chi-square difference test compared to the metric model was not statistically significant, Δχ²(3) = 6.97, p < 0.073, supporting scalar invariance. Finally, the strict invariance model also demonstrated an acceptable fit with χ²(14) = 56.4, p < 0.001, CFI = 0.954, TLI = 0.961, and RMSEA = 0.106 (95%CI [0.078, 0.136]), SRMR = 0.049. The chi-square difference test compared to the metric model was statistically significant, Δχ²(3) = 11.4, p < 0.023, supporting partial strict invariance. In summary, the measurement invariance analyses across sex and age groups indicate a robust factorial structure, with acceptable model fits for both configural and metric invariance. While partial strict invariance was established, some significant differences in fit suggest careful attention to factor loadings and intercepts is warranted. Further information can be found in the supplementary materials. Rasch Analysis A summary of item parameter estimates and infit and outfit statistics for the modified GQ4 Arabic version is presented in the supplementary materials. The item difficulty values range from − 4.07 (GQ5) to -3.49 (GQ4), with lower values suggesting relatively easy items for respondents. All items have similar values for tau categories, indicating consistent performance across all categories. However, GQ1 and GQ4 show more extreme tau values, particularly in tau for Cat1, which may indicate potential issues with discrimination between adjacent response categories. In addition, the infit and outfit values for all the items were between 0.83 and 1.13, indicating that these items had less variation in the observed response pattern than expected by the model. The Item Characteristic Curves (ICCs) for each item illustrate how the probability of selecting different response categories changes with the latent dimension (ability level). Each item shows a consistent pattern where lower categories are more likely at lower ability levels, and higher categories become more probable as ability increases. This consistency across items suggests that they are well-calibrated and fit the Rasch model appropriately, providing reliable measurements of the latent trait (Fig. 1 ). Further details including person-item maps for risk scale are available in the supplementary materials. Discussion This study addresses a gap in the literature regarding the lack of gratitude measurement tools within Arabic-speaking populations, paving the way for further research in this area. Specifically, this research investigated the psychometric properties and measurement invariance of the Arabic version of the GQ6 among a sample of Saudi university students. Initial analyses revealed that the Arabic GQ6 exhibited low internal consistency, prompting the exclusion of two reverse-coded items exhibiting low corrected item-total correlations and factor loadings from further analysis. Subsequent analyses indicated that a one-factor model with four items (GQ4) exhibited good fit across nearly all fit indices, with string standardized factor loadings. The Arabic GQ4 demonstrated good internal consistency and moderate positive correlations with satisfaction with life, self-esteem, and well-being. Regarding measurement invariance, results supported configural and metric invariance across sex and age groups. Furthermore, Rasch analysis showed that the GQ4 Arabic version demonstrates consistent item performance, indicating that the items were relatively easy, while infit and outfit statistics suggest minimal variation in response patterns. The GQ6 includes two reverse-coded items: Item 3 (“When I look at the world, I do not see much to be grateful for”) and Item 6 (“Long amounts of time can go by before I feel grateful to something or someone”). Both items appeared to be problematic in our analysis and thus were excluded from subsequent analyses. Using CFA on a second random subset of the data, the newly modified GQ4 Arabic version exhibited a one-factor structure with good model fit for most indices. The newly modified Arabic GQ4 version also demonstrated good internal consistency. This finding aligns with results from a recent study that validated the GQ6 among a sample of Lebanese adults, which found that the GQ4 (excluding the reverse-coded items) provided the best model fit, demonstrating good internal consistency and an invariant structure across gender at the configural, metric, and scalar levels [ 66 ]. Our findings contribute to the ongoing discussion regarding the appropriate factor structure for the GQ6 across samples and cultural contexts [ 21 ]. Many studies examining the factor structure of the GQ6 in different cultural context have failed to replicate the original 6-item version. For instance, Item 6 “Long amounts of time can go by before I feel grateful to something or someone” have been shown to exhibit low corrected item-total correlation and low factor loading, leading to it exclusion in many validation studies [ 23 , 27 , 28 , 30 – 33 ]. Other research with young adults has found Item 6 to be “difficult to understand” and “very abstract” [ 39 ]. While reverse-coded items are traditionally included to guard against acquiescence bias—the tendency to systematically agree with items regardless of content [ 67 ]—empirical evidence suggests they often fail in practice. Cross-cultural research has demonstrated that such items frequently compromise the psychometric properties of measurement tools (e.g., reliability and factor structure) [ 68 ], measurement model and path coefficients [ 69 ], and can lead to respondent inattention and confusion [ 70 ], and misinterpretation [ 71 ]. These concerns are substantiated by multiple studies. For instance, a large study evaluating an alternative to the traditional mixed-wording approach reformulated negative items into positive equivalents across seven psychological measures administered to 4,192 Emirati university students. Results showed that all-positive versions yielded systematically higher reliability coefficients and cleaner factor structures (e.g., reduced cross-loadings and improved model fit) than mixed-format originals [ 72 ]. Similair findings have been found in studies using the Multidimensional Fatigue Inventory (MFI-20) among patients with inflammatory bowel disease [ 70 ] and Spanish-language scales for personality, emotion regulation and hopelessness across multiple Spanish samples including adolescents, college students, caregivers, adults, and immigrants [ 71 ]. In sum, similar patterns were observed for the two reverse-coded items in the GQ6 Arabic version, and their exclusion yielded a more robust GQ4 version. However, additional research is needed to further confirm the factor structure of the GQ4, investigate whether all-positive wording affects criterion validity. Measurement invariance testing is a fundamental aspect of psychological assessment, yet often overlooked [ 73 ]. As [ 74 ] emphasizes, establishing invariance is prerequisite for meaningful group comparisons as it determines whether observed differences reflect true variations in the latent construct or measurement artifacts. The GQ4 Arabic version demonstrated configural invariance across sex and age groups, confirming that the basic factor structure is generally similar across both groups. Full metric invariance (factor loadings) holds true across age groups, but only partially across sex groups. Scalar and strict invariance are supported across age groups, but only partially across sex groups. These findings are consistent with previous research providing evidence for measurement invariance for the GQ6 and its short forms (e.g., GQ5) in various samples including Western [ 75 ], North American [ 30 ], Asian [ 24 , 76 , 77 ], and South Asian [ 28 ]. The current findings provide evidence for the concurrent validity of the Arabic GQ4 version. Consistent with previous research, the GQ4 demonstrated moderately significant positive correlations with established measures of psychological well-being taken the same time, including satisfaction with life, self-esteem, and subjective well-being. These findings align with previous studies [ 2 , 9 , 15 , 78 ] and support theoretical models positioning gratitude as a fundamental element of flourishing and fulfilling life [ 4 ]. Several limitations should be considered when interpreting these findings. First, the study relied on a convenience sample of university students, which may limit the generalizability of results. Second, the cross-sectional design precludes causal inferences about the relationship between dispositional gratitude and psychological well-being. Third, the original reverse-coded items in the GQ6 were designed to assess the conscious recognition of positive aspects in ones’ life and environment as well as the temporal frequency of grateful affect. While the removal of reverse-coded items improved psychometric properties, this modification may narrow the conceptual breadth of dispositional gratitude as originally conceptualized [ 5 ]. Future research should validate the GQ4 in more diverse samples such as adolescents, older adults, and clinical samples. Additionally, future research should employ a longitudinal design to examine temporal stability and predictive validity of the GQ4. Finally, building on literature discussed [ 70 , 72 ], future research could also test positively reworded versions of the reverse-coded items (e.g., \"I regularly notice things to be grateful for\") to assess whether this approach better preserves the original construct breadth while maintaining the psychometric robustness found in the GQ4 version. Such research could compare the performance of this modified GQ6-positive against both the original GQ6 and the current GQ4 versions. Conclusion The Arabic GQ4 version, a measure of dispositional gratitude, demonstrates robust psychometric properties, including good internal consistency, excellent model fit for a unidimensional structure with high factor loadings, concurrent validity, measurement invariance across demographic groups, consistent item performance, and minimal response pattern variations. This brief and cost-effective measure fills a critical gap by providing researchers and clinicians with a reliable and valid tool to study dispositional gratitude in Arabic-speaking populations. However, while these results are promising, additional validation studies across diverse Arabic-speaking samples and settings are warranted to further confirm the measure’s generalizability and robustness. Abbreviations GQ6 Gratitude Questionnaire 6-item form GQ4 Gratitude Questionnaire 4-item form SWLS Satisfaction With Life Scale RSES Rosenberg Self-Esteem Scale WHO-5 World Health Organization Well-Being Index SWL Satisfaction with life EFA Exploratory factor analysis CFA Confirmatory factor analysis IQR Interquartile range 𝜒2 Chi-square statistic RMSEA Root mean square error of approximation SRMR Standardized root mean square residual CFI Comparative fit index TLI Tucker-Lewis index MGCFA Multi-group confirmatory factor analysis KMO Kaiser-Meyer-Olkin MSA Measure of sampling adequacy CI Confidence interval GFI Goodness-of-fit index AGFI Adjusted goodness-of-fit index CAIC Akaike information criterion BIC Bayesian information criterion RSM Rasch Rating Scale Model ICC Item Characteristic Curve Declarations Ethics approval and consent to participate: The study was conducted in accordance with the Declaration of Helsinki and approved by the Research Ethics Committee at the University of Ha'il (protocol code H-2025-580 and 27 Jan 2025 of approval). All participants involved in this study procided electronic informed consent. Consent for publication: Not applicable. Data Availability Statement: The datasets generated and/or analyzed during this study are not publicly available due to ethical restrictions, but are available from the corresponding author upon reasonable request. Competing interest: The authors declare no conflicts of interest. Funding: This research was funded by Scientific Research Deanship at the University of Ha'il, Saudi Arabia through project number BA-25 001. Author Contributions: Conceptualization, M.M.A. and H.A.A.; methodology, M.M.A., K.A.A.; software, M.M.A.; validation, M.M.A., H.A.A.; and K.A.A.; formal analysis, M.M.A.; investigation, M.M.A., K.A.A.; resources, H.A.A.; and K.A.A.; data curation, M.M.A., H.A.A.; and K.A.A.; writing—original draft preparation, M.M.A.; writing—review and editing, M.M.A., H.A.A.; and K.A.A.; visualization, M.M.A., H.A.A.; and K.A.A.; supervision, M.M.A.; project administration, M.M.A.; funding acquisition, M.M.A. All authors have read and agreed to the published version of the manuscript. Acknowledgments: The authors would like to acknowledge and thank the Scientific Research Deanship for funding this project and all our undergraduate and postgraduate students for participating in this research. References Allen S (2018) The science of gratitude [Internet]. John Templeton Foundation Conshohocken, PA; [cited 2025 Apr 8]. Available from: https://thesnipermind.com/images/Studies-PDF-Format/GGSC-JTF_White_Paper-Gratitude-FINAL.pdf Dalal S, Singh S (2025) Gratitude in action: Effect of gratitude on mental health. J Health Manag 27(1):100–107 Wood AM, Maltby J, Stewart N, Linley PA, Joseph S (2008) A social-cognitive model of trait and state levels of gratitude. Emot Wash DC 8(2):281–290 Wood AM, Froh JJ, Geraghty AWA (2010) Gratitude and well-being: A review and theoretical integration. Clin Psychol Rev 30(7):890–905 McCullough ME, Emmons RA, Tsang JA (2002) The grateful disposition: A conceptual and empirical topography. J Pers Soc Psychol 82(1):112–127 Emmons RA, McCullough ME, Tsang JA (2003) The assessment of gratitude. In: Lopez SJ, Snyder CR (eds) Positive psychological assessment: A handbook of models and measures. American Psychological Association, Washington, DC, US, pp 327–341 Zhu N, Li C, Ye Y, Zhang L, Kong F (2024) Longitudinal effect of gratitude on prosocial behavior among young adults: Evidence from the bi-factor model of gratitude. J Happiness Stud 25(1):3 McGuire AP, Fagan J, Tsai J, Merians AN, Nichter B, Norman S et al (2022) Dispositional gratitude predicts the development of psychopathology and suicidal behaviors: Results from a 7-year population-based study of U.S. military veterans. J Psychiatr Res 149:168–176 Valikhani A, Ahmadnia F, Karimi A, Mills PJ (2019) The relationship between dispositional gratitude and quality of life: The mediating role of perceived stress and mental health. Personal Individ Differ 141:40–46 Iodice JA The association between gratitude and depression: A meta-analysis. Int J Depress Anxiety 2021 June 23;4(1):024 Richardson AL, Gallagher MW (2021) Giving thanks is associated with lower PTSD severity: A meta-analytic review. J Happiness Stud 22(6):2549–2562 Wang A, Reyes A, Urkmez B, McGuire A, Lee B, Umucu E (2024) The association between PTSD, gratitude, academic adjustment, and dropout decisions in veteran students with disabilities: Brief report. J Veterans Stud 10(1):40–47 Phillips BN, Fleming AR, Bean B, Umucu E, Lee B, Roundtree SM et al (2022) Relations among gratitude, adaptation to disability, and flourishing among adults with disabilities: A longitudinal mediation model. Rehabil Psychol 67(4):546–555 Dong L, Zou S, Fan R, Wang B, Ye L (2024) The influence of athletes’ gratitude on burnout: The sequential mediating roles of the coach-athlete relationship and hope. Front Psychol 15:1358799 Kerry N, Chhabra R, Clifton JDW (2023) Being thankful for what you have: A systematic review of evidence for the effect of gratitude on life satisfaction. Psychol Res Behav Manag 16:4799–4816 Kirca A, Malouff M, Meynadier J (2023) The Effect of expressed gratitude interventions on psychological wellbeing: A meta-analysis of randomised controlled studies. Int J Appl Posit Psychol 8(1):63–86 Cregg DR, Cheavens JS (2021) Gratitude interventions: Effective self-help? A meta-analysis of the impact on symptoms of depression and anxiety. J Happiness Stud 22(1):413–445 Diniz G, Korkes L, Tristão LS, Pelegrini R, Bellodi PL, Bernardo WM (2023) The effects of gratitude interventions: A systematic review and meta-analysis. Einstein São Paulo 21:eRW0371 Jans-Beken L, Jacobs N, Janssens M, Peeters S, Reijnders J, Lechner L et al (2020) Gratitude and health: An updated review. J Posit Psychol 15(6):743–782 Ma LK, Tunney RJ, Ferguson E (2017) Does gratitude enhance prosociality? A meta-analytic review. Psychol Bull 143(6):601–635 Cowles B, Medvedev ON (2022) The Gratitude Questionnaire-Six Item Form (GQ-6). In: Medvedev ON, Krägeloh CU, Siegert RJ, Singh NN, editors. Handbook of Assessment in Mindfulness Research [Internet]. Cham: Springer International Publishing; [cited 2025 Feb 1]. pp. 1–15. Available from: https://doi.org/10.1007/978-3-030-77644-2_98-1 Gouveia VV, Ribeiro MGC, De Aquino TAA, Loureto GDL, Nascimento BS, Rezende AT (2021) Gratitude Questionnarie (GQ-6): Evidence of construct validity in Brazil. Curr Psychol 40(5):2481–2489 Fung S fu. Evaluating the psychometric properties of the Gratitude Questionnaire in a Chinese sample: Comparing the 6-Item and 5-Item versions. Mindfulness. 2024 Sept 1;15(9):2321–9 Kong F, You X, Zhao J (2017 Sept) Evaluation of the Gratitude Questionnaire in a Chinese sample of adults: Factorial validity, criterion-related validity, and measurement invariance across sex. Front Psychol 1:8:1498 Zeng Y, Ling Y, Huebner ES, He Y, Lei X (2017) The psychometric properties of the 5-item Gratitude Questionnaire in Chinese adolescents. J Psychiatr Ment Health Nurs 24(4):203–210 Jans-Beken L, Lataster J, Leontjevas R, Jacobs N (2015) Measuring gratitude: A comparative validation of the Dutch Gratitude Questionnaire (GQ6) and Short Gratitude, Resentment, and Appreciation Test (SGRAT). Psychol Belg [Internet]. May 15 [cited 2025 Feb 3];55(1). Available from: https://psychologicabelgica.com/articles/10.5334/pb.bd Hudecek MFC, Blabst N, Morgan B, Lermer E (2020) Measuring gratitude in Germany: Validation study of the German version of the Gratitude Questionnaire-Six Item Form (GQ-6-G) and the Multi-Component Gratitude Measure (MCGM-G). Front Psychol [Internet]. Oct 8 [cited 2025 Feb 6];11. Available from: https://www.frontiersin.org/journals/psychology/articles/ 10.3389/fpsyg.2020.590108/full Dixit SK, Sinha J (2023) Adaptation and validation of the gratitude questionnaire (GQ-6) for the Indian context. Curr Psychol 42(11):8722–8732 Sumi K (2017) Reliability and construct validity of the Gratitude Questionnaire 6 Item Form (GQ 6) in a sample of Japanese college students. J Posit Psychol Wellbeing 1(2):73–84 Langer ÁI, Ulloa VG, Aguilar-Parra JM, Araya-Véliz C, Brito G (2016) Validation of a Spanish translation of the Gratitude Questionnaire (GQ-6) with a Chilean sample of adults and high schoolers. Health Qual Life Outcomes 14(1):53 Magallares A, Recio P, Sanjuán P, Magallares A, Recio P, Sanjuán P (2018) Factor structure of the Gratitude Questionnaire in a Spanish sample. Span J Psychol 21:1–7 Chen LH, Chen MY, Kee YH, Tsai YM (2009) Validation of the Gratitude Questionnaire (GQ) in Taiwanese undergraduate students. J Happiness Stud 10(6):655–664 Yüksel A, Oguz Duran N (2012) Turkish adaptation of the Gratitude Questionnaire. Eurasian J Educ Res. ;(46):199–216 Makhoul M, Bartley EJ (2023) Exploring the relationship between gratitude and depression among older adults with chronic low back pain: A sequential mediation analysis. Front Pain Res 4:1140778 Bohlmeijer ET, Kraiss JT, Watkins P, Schotanus-Dijkstra M (2021) Promoting gratitude as a resource for sustainable mental health: Results of a 3-armed randomized controlled trial up to 6 months follow-up. J Happiness Stud 22(3):1011–1032 Matvienko-Sikar K, Dockray S (2017) Effects of a novel positive psychological intervention on prenatal stress and well-being: A pilot randomised controlled trial. Women Birth 30(2):e111–e118 Bartholomew E, Iqbal N, Medvedev O (2022) Enhancing the assessment of gratitude in mindfulness research: A Rasch Analysis of the 6-Item Gratitude Questionnaire. Mindfulness 13(12):3017–3027 Di Fabio A (2022) Gratitude Questionnaire-6 (GQ-6): Psychometric properties of the Italian version. Counseling 15(2):95–103 Froh JJ, Fan J, Emmons RA, Bono G, Huebner ES, Watkins P (2011) Measuring gratitude in youth: Assessing the psychometric properties of adult gratitude scales in children and adolescents. Psychol Assess 23(2):311–324 Fenn J, Tan CS, George S (2020 Sept) Development, validation and translation of psychological tests. BJPsych Adv 26(5):306–315 Sousa VD, Rojjanasrirat W (2011) Translation, adaptation and validation of instruments or scales for use in cross-cultural health care research: A clear and user-friendly guideline. J Eval Clin Pract 17(2):268–274 Sperber AD (2004) Translation and validation of study instruments for cross-cultural research. Gastroenterology 126(Supp 1):S124–S128 Diener E, Emmons RA, Larsen RJ, Griffin S (1985) The Satisfaction With Life Scale. J Pers Assess 49(1):71–75 Abdallah T (1998) The Satisfaction with Life Scale (SWLS): Psychometric properties in an Arabic-speaking sample. Int J Adolesc Youth 7(2):113–119 Abdel-Khalek AM (2008) Satisfaction with life in Kuwaiti samples. Derasat Nafsiyah Psychol Stud 18:121–135 Pavot W, Diener E (2009) Review of the Satisfaction With Life Scale. In: Diener E, editor. Assessing Well-Being: The Collected Works of Ed Diener [Internet]. Dordrecht: Springer Netherlands; [cited 2020 Oct 25]. pp. 101–17. (Social Indicators Research Series; vol. 39). Available from: https://doi.org/10.1007/978-90-481-2354-4_5 Rosenberg M (1965) Society and the adolescent self-image. Princeton University Press, Princeton, NJ Gray-Little B, Williams VSL, Hancock TD (1997) An item response theory analysis of the Rosenberg Self-Esteem Scale. Pers Soc Psychol Bull 23(5):443–451 Silber E, Tippett JS (1965) Self-Esteem: Clinical assessment and measurement validation. Psychol Rep 16(Suppl 3):1017–1071 Zayed KN, Haddabi BA, Al-Rawahi N, Al-Tauqi M, Thiyabat F, Al-Busafi MS (2016) Gender differences in self-esteem and its relationship with body mass index among Omani adolescents. Can J Clin Nutr 4(1):18–24 Zaidi U, Awad SS, Mortada EM, Qasem HD, Kayal GF (2015) Psychometric evaluation of Arabic version of self-esteem, psychological well-being and Impact of Weight on Quality of Life Questionnaire (IWQOL-Lite) in female student sample of PNU. Eur Med Health Pharm J 8(2):29–33 Abdel-Khalek AM, Korayem AS, El-Nayal MA (2012) Self-esteem among college students from four Arab countries. Psychol Rep 110(1):297–303 Bech P, Gudex C, Johansen KS (1996) The WHO (Ten) Well-Being Index: Validation in diabetes. Psychother Psychosom 65(4):183–190 Topp CW, Østergaard SD, Søndergaard S, Bech P (2015) The WHO-5 Well-Being Index: A systematic review of the literature. Psychother Psychosom 84(3):167–176 Hajos TRS, Pouwer F, Skovlund SE, Oudsten BLD, Geelhoed-Duijvestijn PHLM, Tack CJ et al (2013) Psychometric and screening properties of the WHO-5 well-being index in adult outpatients with Type 1 or Type 2 diabetes mellitus. Diabet Med 30(2):e63–e69 Alshayea AK, Development, and validation of an Arabic version of the World Health Organization Well-Being Index (WHO-5). J Psychopathol Behav Assess [Internet]. 2023 Feb 1 [cited 2023 Feb 2]; Available from: https://doi.org/10.1007/s10862-023-10027-x Fekih-Romdhane F, Cherif W, Alhuwailah A, Fawaz M, Shuwiekh HAM, Helmy M et al (2023) Cross-country validation of the Arabic version of the WHO-5 Well-Being Index in non- clinical young adults from six Arab countries [Internet]. Research Square; [cited 2024 Dec 12]. Available from: https://www.researchsquare.com/article/rs-2988215/v1 Fekih-Romdhane F, Al Mouzakzak F, Abilmona G, Dahdouh O, Hallit S (2024) Validation and optimal cut-off score of the World Health Organization Well-being Index (WHO-5) as a screening tool for depression among patients with schizophrenia. BMC Psychiatry 24:391 Cronbach LJ Coefficient alpha and the internal structure of tests. Psychometrika. 1951 Sept 1;16(3):297–334 McDonald RP (1999) Test theory: A unified treatment. Psychology, New York, p 498 Raftery A Bayesian Model Selection in Structural Equation Models. In 1992 [cited 2025 Mar 10]. Available from: https://www.semanticscholar.org/paper/Bayesian-Model-Selection-in-Structural-Equation-Raftery/187c61f11dd7cd5d2b786f5d085ff0da252fd23f Rosseel Y (2012) lavaan: An R package for structural equation modeling. J Stat Softw 48:1–36 Cheung GW, Rensvold RB (2002) Evaluating goodness-of-fit indexes for testing measurement invariance. Struct Equ Model 9(2):233–255 Chen FF (2007) Sensitivity of goodness of fit indexes to lack of measurement invariance. Struct Equ Model 14(3):464–504 Byrne BM, van De Vijver FJR (2010) Testing for measurement and structural equivalence in large-scale cross-cultural studies: Addressing the issue of nonequivalence. Int J Test 10(2):107–132 Fekih-Romdhane F, Postigo Á, Malaeb D, Sarray El Dine A, Moawad M, Hallit R et al (2025) Validation of the Arabic version of the Gratitude Questionnaire (GQ-4) in a sample of non-clinical adults. BMC Psychol 13:143 Watson D (1992) Correcting for acquiescent response bias in the absence of a balanced scale: An application to class consciousness. Sociol Methods Res 21(1):52–88 Zeng B, Wen H, Zhang J How does the valence of wording affect features of a scale? The method effects in the undergraduate learning burnout scale. Front Psychol [Internet]. 2020 Sept 28 [cited 2025 Apr 19];11. Available from: https://www.frontiersin.orghttps://www.frontiersin.org/journals/psychology/articles/ 10.3389/fpsyg.2020.585179/full Dueber DM, Toland MD, Lingat JE, Love AMA, Qiu C, Wu R et al (2022) To reverse item orientation or not to reverse item orientation, that is the question. Assessment 29(7):1422–1440 van Sonderen E, Sanderman R, Coyne JC (2013 July) Ineffectiveness of reverse wording of questionnaire items: Let’s learn from cows in the rain. PLoS ONE 31(7):e68967 Venta A, Bailey CA, Walker J, Mercado A, Colunga-Rodriguez C, Ángel-González M et al Reverse-coded items do not work in Spanish: Data from four samples using established measures. Front Psychol [Internet]. 2022 June 23 [cited 2025 Apr 19];13. Available from: https://www.frontiersin.orghttps://www.frontiersin.org/journals/psychology/articles/ 10.3389/fpsyg.2022.828037/full Dodeen H The Effects of changing negatively worded items to positively worded items on the reliability and the factor structure of psychological scales. J Psychoeduc Assess. 2023 June 1;41(3):298–310 Maassen E, D’Urso ED, van Assen MALM, Nuijten MB, De Roover K, Wicherts JM (2023) The dire disregard of measurement invariance testing in psychological science. Psychol Methods Karl JA (2023) Multigroup Invariance Testing for Cross-Cultural Research. In: Krägeloh CU, Alyami M, Medvedev ON, editors. International Handbook of Behavioral Health Assessment [Internet]. Cham: Springer International Publishing; [cited 2024 May 24]. pp. 1–17. Available from: https://doi.org/10.1007/978-3-030-89738-3_7-1 Ling Y, Yang Q, Zeng Y, Huebner ES (2021) Assessing the Measurement Invariance of the Gratitude Questionnaire–5 in Chinese and American Adolescents. Span J Psychol 24:e17 Tan Q, Zou J, Kong F (2022) Longitudinal and Gender Measurement Invariance of the Gratitude Questionnaire in Chinese Adolescents. Psychol Rep 125(6):3209–3223 Valdez JPM, Yang W, Datu JAD (2017) Validation of the Gratitude Questionnaire in Filipino Secondary School Students. Span J Psychol 20:E45 Srirangarajan T, Oshio A, Yamaguchi A, Akutsu S Cross-cultural nomological network of gratitude: Findings From Midlife in the United States (MIDUS) and Japan (MIDJA). Front Psychol [Internet]. 2020 May 26 [cited 2025 Apr 23];11. Available from: https://www.frontiersin.orghttps://www.frontiersin.org/journals/psychology/articles/ 10.3389/fpsyg.2020.00571/full Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-7548318\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":true,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":511045018,\"identity\":\"fa9f365e-6d22-404b-a8c4-f0a0d712f5fc\",\"order_by\":0,\"name\":\"Mohsen M. Alyami\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7klEQVRIiWNgGAWjYFACHiAuAGJm5gMMjA1AxgGitBiAtLAlkKqFgceAOC267b0HGH4YHJbXbef5JvFxB4Mc340E5g8/8GgxO3MugbHH4LDhtsO82yRnnmEwlryRwCbZg0/LjRwDoJMOM4K0SPO2MSRuAGoBuxafFsY/Bofttx3meQbSUg/UwvzxDwEtzEBbEoFa2EBaEgxuJDBI47XlzBmDwzIG6cnbDrMZW85skzCceeZhm7QMPi3Hewwfvqmwtt12/vDDGx/bbOT5jicf/vgGjxYQOMDA0AxjSwAxOHYIgjpiFI2CUTAKRsFIBQAzPU/U49iuuwAAAABJRU5ErkJggg==\",\"orcid\":\"https://orcid.org/0000-0001-9278-1841\",\"institution\":\"Department of Psychology, College of Education, University of Ha'il, Ha'il, Saudi Arabia\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Mohsen\",\"middleName\":\"M.\",\"lastName\":\"Alyami\",\"suffix\":\"\"},{\"id\":511045019,\"identity\":\"f7490edb-fe26-4744-b57a-d78e3e1f893a\",\"order_by\":1,\"name\":\"Kateb A. Alshammari\",\"email\":\"\",\"orcid\":\"https://orcid.org/0009-0002-8315-7830\",\"institution\":\"Department of Psychology, College of Education, University of Ha'il, Ha'il, Saudi Arabia\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Kateb\",\"middleName\":\"A.\",\"lastName\":\"Alshammari\",\"suffix\":\"\"},{\"id\":511045020,\"identity\":\"a48ddd22-acb3-4421-8f13-e5af0193a026\",\"order_by\":2,\"name\":\"Hassan A. Alzahrani\",\"email\":\"\",\"orcid\":\"https://orcid.org/0009-0003-8493-4205\",\"institution\":\"Department of Psychology, College of Education, University of Ha'il, Ha'il, Saudi Arabia\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Hassan\",\"middleName\":\"A.\",\"lastName\":\"Alzahrani\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2025-09-06 05:01:43\",\"currentVersionCode\":1,\"declarations\":{\"humanSubjects\":true,\"vertebrateSubjects\":false,\"conflictsOfInterestStatement\":false,\"humanSubjectEthicalGuidelines\":true,\"humanSubjectConsent\":true,\"humanSubjectClinicalTrial\":false,\"humanSubjectCaseReport\":false,\"vertebrateSubjectEthicalGuidelines\":false},\"doi\":\"10.21203/rs.3.rs-7548318/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-7548318/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":90854431,\"identity\":\"c47bc931-a0bb-4ac5-9dae-c5607f90e356\",\"added_by\":\"auto\",\"created_at\":\"2025-09-09 04:09:54\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":85604,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eItem Characteristic Curves (ICC) for each item of the modified Arabic GQ4. The x-axis represents the latent dimension ranging from -4 to 4, and the y-axis represents the probability from 0 to 1. Category 0 to 6 are response options 1 to 7.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7548318/v1/a59b7ad3cf4a5ab4c5eb4f4f.png\"},{\"id\":90854910,\"identity\":\"990670bd-2bbb-42f5-9ba8-5ea8dccf2a32\",\"added_by\":\"auto\",\"created_at\":\"2025-09-09 04:25:55\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":1001353,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7548318/v1/018cdafd-03d1-41a2-8a8d-c49e57dea878.pdf\"}],\"financialInterests\":\"The authors declare no competing interests.\",\"formattedTitle\":\"\\u003cp\\u003e\\u003cstrong\\u003eEvaluating dispositional gratitude among Saudi adults: Reliability, factor structure and measurement invariance of the Gratitude Questionnaire (GQ6)\\u003c/strong\\u003e\\u003c/p\\u003e\",\"fulltext\":[{\"header\":\"Introduction\",\"content\":\"\\u003cp\\u003eGratitude, a complex and multifaceted emotion, has garnered significant scholarly attention, particularly within the field of positive psychology [\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e]. It is conceptualized as both a state and a trait [\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e]. As a state, gratitude is a temporary emotional experience triggered by specific events, marked by feelings of thankfulness and appreciation for the benefits received [\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e]. As a trait, gratitude is a stable characteristic or a disposition to notice and appreciate the world in a positive light. This dispositional gratitude has been defined as \\u0026ldquo;\\u003cem\\u003ea generalized tendency to recognize and respond with grateful emotion to the roles of other people\\u0026rsquo;s benevolence in the positive experiences and outcomes that one obtains\\u003c/em\\u003e\\u0026rdquo; (p.112) [\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e]. Individuals high in dispositional gratitude tend to feel grateful more frequently and intensely across a wider range of circumstances and maintain a positive outlook on life compared to individuals low in dispositional gratitude [\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e].\\u003c/p\\u003e\\u003cp\\u003eGratitude plays a crucial role in enhancing psychosocial well-being, fostering positive relationships, and promoting resilience [\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e]. A seven year longitudinal study of a nationally representative sample of military veterans found that individuals with high levels of dispositional gratitude were less likely to develop symptoms of depression, anxiety, post-traumatic stress disorder (PTSD), and suicidal behaviours [\\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e]. Similarly, research involving military soldiers revealed that gratitude not only has direct effects on quality of life but also exerts indirect effects on quality of life via perceived stress [\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e]. Analytical reviews have found moderate inverse relationships between gratitude and both post-traumatic stress disorder (PTSD) severity and depression [\\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e].\\u003c/p\\u003e\\u003cp\\u003eAmong student veterans receiving rehabilitation counselling, dispositional gratitude has been linked to a lower intention to drop out, even when controlling for poor academic performance and PTSD symptoms [\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e]. Longitudinal studies involving adults with disabilities have shown that higher levels of gratitude enhance flourishing and improve adaptation to disability [\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e]. Beyond veterans and clinical samples, gratitude also benefits performance contexts. For example, among athletes gratitude has been found to exhibit a direct negative relationship with burnout and an indirect negative effect through the coach-athlete relationship and hope [\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e]. A recent review examining gratitude and life satisfaction (SWL) found strong evidence of a positive correlation between the two [\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e].This review encompassed longitudinal cross-lagged studies, all of which supported a causal model suggesting that increased gratitude leads to enhanced SWL [\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e].\\u003c/p\\u003e\\u003cp\\u003eGratitude-based interventions have gained significant attention over the last two decades, leading to several reviews on their effects. For instance, recent reviews of expressed gratitude interventions (e.g., writing thank-you notes) found that these interventions significantly improved psychological well-being. Key benefits included enhanced life satisfaction, increased positive affect, and greater happiness [\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e]. Additionally, other reviews have identified modest but significant effect on reducing symptoms of depression and anxiety [\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e] as well as improving sleep quality and prosocial behaviours [\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e]. Overall, the findings from the observational, longitudinal and intervention studies highlight the importance of gratitude as a potential protective factor for health and well-being, underscoring the need for reliable and valid measures of gratitude.\\u003c/p\\u003e\\u003cp\\u003eA widely used measure of gratitude as a trait in psychological research is the Gratitude Questionnaire-six item form (GQ6) [\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e]. The authors initially developed a 39-item pool aimed at measuring individual differences in people\\u0026rsquo;s disposition or propensity to experience gratitude in everyday life. In study 1, data were collected from a sample of undergraduate psychology students, predominantly young adults [\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e]. In addition to the gratitude items, participants also completed various other measures including satisfaction, hope, optimism, happiness, positive and negative affect, empathy, social desirability, and personality traits. Using various statistical techniques, including exploratory factor analysis and structural equation modelling with maximum likelihood estimation, 6 items that loaded strongly on the first factor and uniquely captured different aspects of dispositional gratitude were retained. The authors concluded that the GQ6 has adequate reliability (Cronbach\\u0026rsquo;s α of 0.82), as well as discriminant, convergent and construct validity. In subsequent studies using diverse samples, including older adults, confirmatory factor analysis further validated the one-factor structure of the GQ6 and provided additional evidence for its reliability and validity [\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e].\\u003c/p\\u003e\\u003cp\\u003eThe GQ6 is commonly used in cross-cultural research [\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e]. It has been validated in various languages including in Brazil Portuguese [\\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e], Chinese [\\u003cspan additionalcitationids=\\\"CR24\\\" citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e], Dutch [\\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e], German [\\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e27\\u003c/span\\u003e], Hindi [\\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e], Japanese [\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e], Spanish [\\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e30\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e], Taiwanese [\\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e32\\u003c/span\\u003e], and Turkish [\\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e33\\u003c/span\\u003e]. The GQ6 has also been used in gratitude interventions among various samples, including individuals with PTSD [\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e], older adults with chronic pain [\\u003cspan citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e34\\u003c/span\\u003e], adults with depression and anxiety [\\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e], athletes [\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e], and pregnant women [\\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e36\\u003c/span\\u003e].\\u003c/p\\u003e\\u003cp\\u003eDespite the GQ6 has shown robust psychometric properties [\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e37\\u003c/span\\u003e], concerns persist about its item composition [\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e]. Specifically, Item 6: \\u0026ldquo;Long amounts of time can go by before I feel grateful to something or someone\\u0026rdquo; has been identified as problematic. Several adaptations of the GQ6, including Chinese [\\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e24\\u003c/span\\u003e], Dutch [\\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e], Italian [\\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e], Japanese [\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e], and Portuguese [\\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e], have retained all six original items. On the other hand, other research has found that Item 6 exhibits low corrected item-total correlation and low factor loading [\\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e27\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e, \\u003cspan additionalcitationids=\\\"CR31 CR32\\\" citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e30\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e33\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e]. As a result, these studies developed a five-item version (GQ5) by removing Item 6. These inconsistencies underscore the need to investigate the GQ6\\u0026rsquo;s item composition across different cultural contexts.\\u003c/p\\u003e\\u003cp\\u003eDespite its extensive use, there is currently no published Arabic version of the GQ6, presenting a significant gap in gratitude research within Arabic-speaking populations. Therefore, the aims of the current study are twofold: (1) to translate the GQ6 into Arabic and evaluate its psychometric properties, including reliability and factor structure; and (2) to evaluate the measurement invariance of the Arabic version of the GQ6 across age and sex groups. Developing a reliable and valid Arabic version of the GQ6 is essential, as it would promote further research into gratitude, potentially leading to valuable insights into its role in psychosocial well-being among Arabic-speaking populations.\\u003c/p\\u003e\"},{\"header\":\"Methods\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eStudy design and participants\\u003c/h2\\u003e\\u003cp\\u003eA cross-sectional design was used, with a convenience sample of undergraduate and postgraduate students recruited from a Saudi university. Recruitment of potential participants involved (1) distributing campus flyers with a QR code linking to the online survey, and (2) in-person invitations by the research team members during lectures. This multi-faceted approach facilitated the recruitment of a diverse sample from different colleges. Eligibility criteria included being 18 years of age or older and fluent in Arabic, the language in which the study was administered.\\u003c/p\\u003e\\u003cp\\u003eParticipants completed a structured anonymous online questionnaire administered between December 2024 to April 2025. The online format offered convenience and accessibility, allowing participants to complete the questionnaire at their own pace while ensuring their anonymity (i.e., no identifying information was collected, such as names, emails, or IP addresses was collected). Participants were provided an information sheet, and their participation was voluntary. Electronic informed consents were obtained electronically. Additionally, no study credits or financial compensation were provided for participation. This research received approval from the Research Ethics Committee at \\u003cem\\u003e[Information Blinded]\\u003c/em\\u003e University (\\u003cem\\u003eInformation Blinded\\u003c/em\\u003e), and all procedures followed were in accordance with the Declaration of Helsinki.\\u003c/p\\u003e\\u003c/div\\u003e\\n\\u003ch3\\u003eMeasures\\u003c/h3\\u003e\\n\\u003cp\\u003eParticipants provided information on the following demographic variables: age (in years), sex (male, female), marital status (single, married, divorced, widowed), educational level (undergraduate, Master, PhD), and academic field of study (medicine, science, humanities, business, education, etc.).\\u003c/p\\u003e\\n\\u003ch3\\u003eThe Gratitude Questionnaire (GQ6)\\u003c/h3\\u003e\\n\\u003cp\\u003eThe GQ6 is a self-report measure designed to assess individual differences in people\\u0026rsquo;s disposition or propensity to experience gratitude in everyday life [\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e]. It consists of 6 items, each is scored on a 7-point Likert-type scale, ranging from 1 (strongly disagree) to 7 (strongly agree). Two items (Item 3 and Item 6) are reverse-coded. The total score is the sum of individual item scores, with higher scores corresponding to higher levels of trait gratitude. The GQ6 has been shown to have sound psychometric properties across various languages and cultures [\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e37\\u003c/span\\u003e].\\u003c/p\\u003e\\u003cp\\u003eThe English GQ6 version was translated into Arabic using established guidelines [\\u003cspan additionalcitationids=\\\"CR41\\\" citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e40\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e42\\u003c/span\\u003e] to ensure semantic equivalence and cultural appropriateness. First, the English GQ6 was independently translated into Arabic by two bilingual individuals: the first was a professional independent Saudi translator, and the second was a member of the research team. Both individuals completed their translations independently, producing two preliminary versions. Second, another research team member, fluent in both English and Arabic, acted as a moderator by comparing the two preliminary versions. Discrepancies were resolved through iterative discussions with the team, resulting in a single approved Arabic version of the GQ6. Third, an independent bilingual Saudi educational psychologist (unfamiliar with the GQ6 original version) back-translated the Arabic version into English. Following this, the original and back-translated English versions of the GQ6 were compared for equivalence and cultural appropriateness. Finally, the final Arabic version of the GQ6 was piloted with a convenience sample of 23 Saudi university undergraduate university students to assess comprehension. Based on the participants\\u0026rsquo; responses, no major changes were necessary.\\u003c/p\\u003e\\n\\u003ch3\\u003eSatisfaction With Life Scale (SWLS)\\u003c/h3\\u003e\\n\\u003cp\\u003eParticipants\\u0026rsquo; SWL was assessed using the Satisfaction with Life Scale (SWLS) [\\u003cspan citationid=\\\"CR43\\\" class=\\\"CitationRef\\\"\\u003e43\\u003c/span\\u003e]. The SWLS is a global measure of one\\u0026rsquo;s overall SWL, consisting of 5 items. Items are scored on a 7-point Likert-type scale, with response ranging from 1 (strongly disagree) to 7 (strongly agree), yielding total scores between 5 and 35. Higher scores indicate greater satisfaction [\\u003cspan citationid=\\\"CR43\\\" class=\\\"CitationRef\\\"\\u003e43\\u003c/span\\u003e]. Both the English and Arabic versions of the SWLS have demonstrated adequate reliability and validity [\\u003cspan additionalcitationids=\\\"CR45\\\" citationid=\\\"CR44\\\" class=\\\"CitationRef\\\"\\u003e44\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR46\\\" class=\\\"CitationRef\\\"\\u003e46\\u003c/span\\u003e].\\u003c/p\\u003e\\n\\u003ch3\\u003eRosenberg Self-Esteem Scale (RSES)\\u003c/h3\\u003e\\n\\u003cp\\u003eParticipants\\u0026rsquo; overall sense of self-esteem, encompassing both positive and negative emotions about oneself, was assessed using the Rosenberg Self-Esteem Scale (RSES) [\\u003cspan citationid=\\\"CR47\\\" class=\\\"CitationRef\\\"\\u003e47\\u003c/span\\u003e]. The RSES consists of 10 items, each scored on a 4-point Likert scale ranging from 1 (strongly disagree) to 4 (strongly agree). Among these items, five are reverse-coded items. Total scores range from 10 to 40, with higher total scores denote higher self-esteem. The RSES is a reliable and valid measure of global self-esteem [\\u003cspan citationid=\\\"CR48\\\" class=\\\"CitationRef\\\"\\u003e48\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR49\\\" class=\\\"CitationRef\\\"\\u003e49\\u003c/span\\u003e], and has been widely used in Arabic-speaking samples [\\u003cspan additionalcitationids=\\\"CR51\\\" citationid=\\\"CR50\\\" class=\\\"CitationRef\\\"\\u003e50\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR52\\\" class=\\\"CitationRef\\\"\\u003e52\\u003c/span\\u003e].\\u003c/p\\u003e\\u003cdiv id=\\\"Sec8\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eWorld Health Organization Well-Being Index (WHO-5)\\u003c/h2\\u003e\\u003cp\\u003eSubjective well-being was evaluated using the World Health Organization Well-Being Index (WHO-5), a short version of the WHO 10-item scale [\\u003cspan citationid=\\\"CR53\\\" class=\\\"CitationRef\\\"\\u003e53\\u003c/span\\u003e]. The WHO-5 is a brief and generic measure of subjective well-being over the last two weeks [\\u003cspan citationid=\\\"CR54\\\" class=\\\"CitationRef\\\"\\u003e54\\u003c/span\\u003e]. Items are scored on a 6-point Likert scale ranging from 0 (at no time) to 5 (all of the time). The total score ranges from 0 to 25, with higher scores indicating best possible well-being. The WHO-5 has been shown to have adequate reliability and validity in various populations [\\u003cspan citationid=\\\"CR54\\\" class=\\\"CitationRef\\\"\\u003e54\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR55\\\" class=\\\"CitationRef\\\"\\u003e55\\u003c/span\\u003e], including among Arabic-speaking healthy and clinical samples [\\u003cspan additionalcitationids=\\\"CR57\\\" citationid=\\\"CR56\\\" class=\\\"CitationRef\\\"\\u003e56\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR58\\\" class=\\\"CitationRef\\\"\\u003e58\\u003c/span\\u003e].\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec9\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eData Analysis\\u003c/h2\\u003e\\u003cp\\u003eParticipant characteristics were summarized using absolute and relative frequencies for categorical and median with interquartile range (IQR) for continuous measures. Descriptive statistics and Spearman rank correlations between items were performed. Descriptive statistics were calculated for each item and the total gratitude score. The mean, standard deviation, and skewness of each item were computed to assess central tendency and distribution.\\u003c/p\\u003e\\u003cp\\u003eInternal consistency was evaluated using Cronbach\\u0026rsquo;s α, McDonald\\u0026rsquo;s omega (ω) coefficients and corrected item-total correlations. A α and ω coefficient of 0.70 or above, along with corrected item-total correlation greater than 0.30, was considered acceptable [\\u003cspan citationid=\\\"CR59\\\" class=\\\"CitationRef\\\"\\u003e59\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR60\\\" class=\\\"CitationRef\\\"\\u003e60\\u003c/span\\u003e]. To assess the underlying factor structure, Exploratory factor analysis (EFA) was conducted on a randomly split 50% subset of the data (n\\u0026thinsp;=\\u0026thinsp;268). The Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy (MSA) and Bartlett's test of sphericity were employed to evaluate the suitability of the data for factor analysis. KMO values exceeding 0.6 and a significant Bartlett\\u0026rsquo;s test (\\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05) confirmed adequacy of the data. Maximum likelihood method was used to extract factors, followed by Oblimin rotation. Factor loadings\\u0026thinsp;\\u0026ge;\\u0026thinsp;0.40 were considered significant for item retention.\\u003c/p\\u003e\\u003cp\\u003eConfirmatory factor analysis (CFA) was performed on the remaining 50% of the data (n\\u0026thinsp;=\\u0026thinsp;268) to validate the factor structure identified in EFA using lavaan package in R with and maximum likelihood estimation. Model fit was assessed using multiple indices, including the chi-square statistic (\\u0026#120594;\\u003csup\\u003e2\\u003c/sup\\u003e), root mean square error of approximation (RMSEA) with its 95% confidence interval (CI), standardized root mean square residual (SRMR), comparative fit index (CFI), and Tucker-Lewis index (TLI). Cutoff values of RMSEA\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.06, SRMR\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.08, and CFI/TLI\\u0026thinsp;\\u0026ge;\\u0026thinsp;0.95 were considered indicative of good model fit. Additionally, goodness-of-fit index (GFI), adjusted goodness-of-fit index (AGFI), consistent Akaike information criterion (CAIC), and Bayesian information criterion (BIC) were evaluated to further validate model fit [\\u003cspan citationid=\\\"CR61\\\" class=\\\"CitationRef\\\"\\u003e61\\u003c/span\\u003e].\\u003c/p\\u003e\\u003cp\\u003eConcurrent validity was evaluated by examining correlations between the GQ6 and with relevant psychological measures (SWLS, RSES, and WHO-5). Measurement invariance analysis was conducted to examine whether the factor structure held across different demographic groups (sex and age group). Participants were categorized into two distinct age groups: those under 21 years and those aged 21 years and above, based on the median split. We tested for configural, metric, scalar, and strict invariance using the lavaan package in R [\\u003cspan citationid=\\\"CR62\\\" class=\\\"CitationRef\\\"\\u003e62\\u003c/span\\u003e]. Configural invariance was assessed first to ensure that the same factor structure was valid across groups, followed by tests for metric invariance (equality of factor loadings), scalar invariance (equality of item intercepts) and strict invariance (equality of residuals) [\\u003cspan citationid=\\\"CR63\\\" class=\\\"CitationRef\\\"\\u003e63\\u003c/span\\u003e]. Model fit was evaluated using the CFI, RMSEA, and SRMR. Based on established guidelines [\\u003cspan additionalcitationids=\\\"CR64\\\" citationid=\\\"CR63\\\" class=\\\"CitationRef\\\"\\u003e63\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR65\\\" class=\\\"CitationRef\\\"\\u003e65\\u003c/span\\u003e], invariance was supported if the change in CFI (ΔCFI) was \\u0026le;\\u0026thinsp;0.01, the change in RMSEA (ΔRMSEA) was \\u0026le;\\u0026thinsp;0.015, and the change in SRMR (ΔSRMR) was \\u0026le;\\u0026thinsp;0.030 for metric and \\u0026le;\\u0026thinsp;0.010 for scalar and strict invariance levels.\\u003c/p\\u003e\\u003cp\\u003eRasch Rating Scale Model (RSM) was performed using TAM R package to assess the item functioning and fit of the data to the Rasch model. The analysis focused on evaluating the thresholds for each item and determining whether they were consistent with the intended scale. Item fit statistics, such as Infit and Outfit Mean Square, were calculated to evaluate whether each item fit the Rasch model well. Additionally, person reliability was computed to assess the model\\u0026rsquo;s ability to accurately distinguish between different levels of person ability. We also provided a graphical illustration of the estimated item parameters using Item Characteristic Curves (ICCs). All the analyses were performed using R statistical programming (v4.4.1).\\u003c/p\\u003e\\u003c/div\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003cp\\u003eA total of 536 participants had complete data. Participants had a median age of 21 years, with an interquartile range (IQR) of 20 to 25 years and mean age of 23.01 year (SD\\u0026thinsp;=\\u0026thinsp;4.84). The sample was evenly distributed by sex (50% female) and predominantly single (86%). Most participants (93%) were undergraduate students with nearly half (48%) enrolled at the College of Education, followed by Computer Science and Engineering (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003e\\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e\\u003ccaption language=\\\"En\\\"\\u003e\\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e\\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\u003cp\\u003eSociodemographic characteristics of participants (n\\u0026thinsp;=\\u0026thinsp;536)\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/caption\\u003e\\u003ccolgroup cols=\\\"2\\\"\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e\\u003cthead\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eCharacteristic\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eN (%)\\u003c/p\\u003e\\u003c/th\\u003e\\u003c/tr\\u003e\\u003c/thead\\u003e\\u003ctbody\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eSex\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eMale\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e268 (50%)\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eFemale\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e268 (50%)\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eMarital status\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eSingle\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e460 (86%)\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eMarried\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e76 (14%)\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eEducational level\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eBachelor\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e498 (93%)\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eMaster\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e26 (4.9%)\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003ePhD\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e12 (2.2%)\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eArea of study\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eApplied Medical Sciences\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e19 (3.5%)\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eBusiness Administration\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e36 (6.7%)\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eComputer Science and Engineering\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e75 (14%)\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eEducation\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e258 (48%)\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eLaw\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e30 (5.6%)\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eLiterature and Arts\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e56 (10%)\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eNursing\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e38 (7.1%)\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eSciences\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e24 (4.5%)\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tbody\\u003e\\u003c/colgroup\\u003e\\u003c/table\\u003e\\u003c/div\\u003e\\u003c/p\\u003e\\u003cp\\u003eTable\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e presents the descriptive statistics of individual items and total score. The positively worded items (Items 1, 2, 4, and 5) demonstrated high mean scores (range: 6.12\\u0026ndash;6.38) and negative skewness (-2.30 to -1.65), indicating that most participants responded positively. In contrast, the reverse-coded items (Items 3 and 6) showed substantially lower means (2.75 and 2.33, respectively) with positive skewness (0.91\\u0026ndash;1.34), indicating that participants generally expressed lower levels of agreement with these negative statements. The total GQ6 score distribution (Mean\\u0026thinsp;=\\u0026thinsp;30.07, SD\\u0026thinsp;=\\u0026thinsp;3.88; median\\u0026thinsp;=\\u0026thinsp;30; range\\u0026thinsp;=\\u0026thinsp;18\\u0026ndash;42) exhibited moderate variability. Histograms displaying the distributions of all items and total scores are available in the supplementary materials.\\u003c/p\\u003e\\u003cp\\u003e\\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab2\\\" border=\\\"1\\\"\\u003e\\u003ccaption language=\\\"En\\\"\\u003e\\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 2\\u003c/div\\u003e\\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\u003cp\\u003eDescriptive statistics of the Arabic GQ6 version (n\\u0026thinsp;=\\u0026thinsp;536)\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/caption\\u003e\\u003ccolgroup cols=\\\"6\\\"\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e\\u003cthead\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eItem\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eMean\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eSD\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eSkewness\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003ekurtosis\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003eSE\\u003c/p\\u003e\\u003c/th\\u003e\\u003c/tr\\u003e\\u003c/thead\\u003e\\u003ctbody\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eGQ1\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e6.36\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e1.03\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e-2.30\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e6.67\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.04\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eGQ2\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e6.13\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e1.22\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e-1.69\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e2.89\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.05\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eGQ3*\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e2.75\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e1.84\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.91\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e-0.22\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.08\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eGQ4\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e6.12\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e1.19\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e-1.65\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e3.09\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.05\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eGQ5\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e6.38\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.98\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e-2.26\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e6.76\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.04\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eGQ6*\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e2.33\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e1.59\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e1.34\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e1.17\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.07\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eGQ6 total score\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e30.07\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e3.88\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.37\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e1.51\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.17\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tbody\\u003e\\u003c/colgroup\\u003e\\u003ctfoot\\u003e\\u003ctr\\u003e\\u003ctd colspan=\\\"6\\\"\\u003e\\u003cem\\u003eNote\\u003c/em\\u003e: *Negative items; SD, Standard Deviation; SE, Standard Error\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tfoot\\u003e\\u003c/table\\u003e\\u003c/div\\u003e\\u003c/p\\u003e\\u003cdiv id=\\\"Sec11\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eReliability Analysis\\u003c/h2\\u003e\\u003cp\\u003eReliability analysis showed suboptimal internal consistency for the full GQ6 (α\\u0026thinsp;=\\u0026thinsp;0.34, ω\\u0026thinsp;=\\u0026thinsp;0.40). As shown in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e, removing the reverse-coded items (GQ3 and GQ6) would result in a relatively higher α and ω coefficient values. The scale demonstrated moderate common variance, with a squared multiple correlation of 0.67, indicating that 67% of item variance was explained by the underlying factor. Corrected item-total correlations ranged from 0.34 to 0.60, with the reversed-coded items (GQ3 and GQ6) showing the lowest correlations (0.45 and 0.34), indicating a weaker relationship with the total score. In contrast, GQ2 exhibited the highest item-total correlation (0.60), suggesting it is more consistent with the overall scale.\\u003c/p\\u003e\\u003cp\\u003e\\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab3\\\" border=\\\"1\\\"\\u003e\\u003ccaption language=\\\"En\\\"\\u003e\\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 3\\u003c/div\\u003e\\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\u003cp\\u003eReliability analysis of the Arabic versions of the original GQ6 and modified GQ4\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/caption\\u003e\\u003ccolgroup cols=\\\"7\\\"\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c7\\\" colnum=\\\"7\\\"\\u003e\\u003c/div\\u003e\\u003cthead\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eItem\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eα\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eα if deleted\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eSMC if item deleted\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003eω\\u003c/p\\u003e \\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003eω if deleted\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003eItem-total correlation\\u003c/p\\u003e\\u003c/th\\u003e\\u003c/tr\\u003e\\u003c/thead\\u003e\\u003ctbody\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eOriginal GQ6\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eGQ1\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.20\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.52\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.19\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e0.57\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eGQ2\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.18\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.53\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.17\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e0.60\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eGQ3*\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.48\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.71\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.65\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e0.45\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eGQ4\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.22\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.57\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.22\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e0.55\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eGQ5\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.20\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.55\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.23\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e0.56\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eGQ6*\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.47\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.72\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.61\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e0.34\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eGQ6 total score\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e0.34\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.67\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e0.40\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eModified GQ4\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eGQ1\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.79\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.72\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.79\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e0.84\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eGQ2\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.80\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.74\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.80\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e0.85\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eGQ4\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.82\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.77\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.82\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e0.82\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eGQ5\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.81\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.75\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.81\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e0.81\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eGQ4 total score\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e0.85\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e0.85\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tbody\\u003e\\u003c/colgroup\\u003e\\u003ctfoot\\u003e\\u003ctr\\u003e\\u003ctd colspan=\\\"7\\\"\\u003e\\u003cem\\u003eNote\\u003c/em\\u003e: *Negative items; α, Cronbach\\u0026rsquo;s alpha coefficient; ω, McDonald\\u0026rsquo;s omega coefficient; SMC, Squared Multiple Correlation\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tfoot\\u003e\\u003c/table\\u003e\\u003c/div\\u003e\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec12\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eFactor Analysis\\u003c/h2\\u003e\\u003cp\\u003eA random subset comprising 50% of the data (n\\u0026thinsp;=\\u0026thinsp;268) was used to conduct the EFA. The data demonstrated adequate factorability, with KMO value of 0.76 and a significant Bartlett's test of sphericity (\\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001). Individual KMO values ranged from 0.55 to 0.85, with GQ4 (0.83) and GQ5 (0.85) showing particularly strong sampling adequacy. Notably, the reverse-coded item (GQ3) had the lowest measure of sampling adequacy (0.55), falling slightly below the conventional 0.60 threshold. As shown in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e, the factor solution revealed clear differentiation between items. Positively worded items (GQ1, GQ2, GQ4 and GQ5) loaded strongly on factor 1 (0.67\\u0026ndash;0.80), while the reverse-coded items (GQ3 and GQ6) loaded poorly on factor 1 (\\u0026lt;\\u0026thinsp;0.40), suggesting they may represent a distinct dimension or contribute to measurement inconsistency.\\u003c/p\\u003e\\u003cp\\u003e\\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab4\\\" border=\\\"1\\\"\\u003e\\u003ccaption language=\\\"En\\\"\\u003e\\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 4\\u003c/div\\u003e\\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\u003cp\\u003eEFA factor loadings of Arabic version of the GQ6 (n\\u0026thinsp;=\\u0026thinsp;268)\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/caption\\u003e\\u003ccolgroup cols=\\\"5\\\"\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e\\u003cthead\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eItem\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eFactor1\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eCommunality\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eUniqueness\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003eComprehensiveness\\u003c/p\\u003e\\u003c/th\\u003e\\u003c/tr\\u003e\\u003c/thead\\u003e\\u003ctbody\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eGQ1\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e0.80\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.64\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.36\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e1\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eGQ2\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e0.78\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.60\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.40\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e1\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eGQ3*\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e-0.20\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.04\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.96\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e1\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eGQ4\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e0.67\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.45\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.55\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e1\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eGQ5\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e0.67\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.45\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.55\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e1\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eGQ6*\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e-0.35\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.12\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.88\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e1\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tbody\\u003e\\u003c/colgroup\\u003e\\u003ctfoot\\u003e\\u003ctr\\u003e\\u003ctd colspan=\\\"5\\\"\\u003e\\u003cem\\u003eNote\\u003c/em\\u003e: *Negative item.\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tfoot\\u003e\\u003c/table\\u003e\\u003c/div\\u003e\\u003c/p\\u003e\\u003cp\\u003eThe two reverse-coded items (GQ3 and GQ6) were removed from further analyses due to their low item-total correlations and factor loadings. Subsequently, a one-factor structure using a modified GQ4 with four items (GQ1, GQ2, GQ4, and GQ5) was tested using CFA on the second random subset of the data (n\\u0026thinsp;=\\u0026thinsp;268). Several goodness-of-fit indices were calculated, and the result indicate that the model fit was acceptable (CFI\\u0026thinsp;=\\u0026thinsp;0.96, TLI\\u0026thinsp;=\\u0026thinsp;0.89, RMSEA\\u0026thinsp;=\\u0026thinsp;0.19 (90% CI: 0.12\\u0026ndash;0.26), SRMR\\u0026thinsp;=\\u0026thinsp;0.03, GFI\\u0026thinsp;=\\u0026thinsp;0.96, AGFI\\u0026thinsp;=\\u0026thinsp;0.83). Most indices were within recommended thresholds, indicating a good model fit. However, the RMSEA value of 0.19 exceeded the commonly accepted threshold of 0.05 for a good fit. Both, the BIC and CAIC were within acceptable limits, with no alternative model exhibiting a significantly lower BIC (ΔBIC\\u0026thinsp;\\u0026ge;\\u0026thinsp;10). All four items loaded significantly onto their respective factor (\\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001). Standardized factor loadings are shown in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003e. The reliability for the newly modified Arabic GQ4 version was very good (α and ω\\u0026thinsp;=\\u0026thinsp;0.85).\\u003c/p\\u003e\\u003cp\\u003e\\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab5\\\" border=\\\"1\\\"\\u003e\\u003ccaption language=\\\"En\\\"\\u003e\\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 5\\u003c/div\\u003e\\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\u003cp\\u003eCFA standardized factor loadings of the modified Arabic version of the of the GQ4 (n\\u0026thinsp;=\\u0026thinsp;268)\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/caption\\u003e\\u003ccolgroup cols=\\\"3\\\"\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e\\u003cthead\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eFactor\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eItems\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eStandardized loading (95%CI)\\u003c/p\\u003e\\u003c/th\\u003e\\u003c/tr\\u003e\\u003c/thead\\u003e\\u003ctbody\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e1\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eGQ1\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.84 (0.79, 0.89)\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e1\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eGQ2\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.78 (0.73, 0.84)\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e1\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eGQ4\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.72 (0.65, 0.78)\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e1\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eGQ5\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.81 (0.75, 0.86)\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tbody\\u003e\\u003c/colgroup\\u003e\\u003c/table\\u003e\\u003c/div\\u003e\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec13\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eConcurrent validity\\u003c/h2\\u003e\\u003cp\\u003eThe GQ4 demonstrates concurrent validity through significant positive correlations with three established psychological measures including the RSES (\\u003cem\\u003er\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.419, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;.001), the SWLS (\\u003cem\\u003er\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.467, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;.001), and the WHO-5 (\\u003cem\\u003er\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.430, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;.001).\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec14\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eMeasurement invariance\\u003c/h2\\u003e\\u003cp\\u003eThe measurement invariance analyses of the Arabic GQ4 were conducted on the entire sample (n\\u0026thinsp;=\\u0026thinsp;536) through sequential model testing. The baseline configural invariance model, which tested the structure\\u0026rsquo;s consistency across sexes demonstrated an acceptable fit: χ\\u0026sup2;(4)\\u0026thinsp;=\\u0026thinsp;48.6, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;.001; CFI\\u0026thinsp;=\\u0026thinsp;0.949, TLI\\u0026thinsp;=\\u0026thinsp;0.846, RMSEA\\u0026thinsp;=\\u0026thinsp;0.204 (95% CI [0.155, 0.257]); SRMR\\u0026thinsp;=\\u0026thinsp;0.037. Despite a significant chi-square statistic, the acceptable CFI (\\u0026gt;\\u0026thinsp;0.90) and SRMR (\\u0026lt;\\u0026thinsp;0.08) values suggest that the basic factorial structure is generally similar across sex groups. However, the RMSEA exceeded the recommended threshold (0.08), indicating potential areas for model improvement.\\u003c/p\\u003e\\u003cp\\u003eMetric invariance was also tested by constraining factor loadings to be equal across sexes. The model showed acceptable fit: χ\\u0026sup2;(7)\\u0026thinsp;=\\u0026thinsp;57.2, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;.001; CFI\\u0026thinsp;=\\u0026thinsp;0.942; TLI\\u0026thinsp;=\\u0026thinsp;0.901; RMSEA\\u0026thinsp;=\\u0026thinsp;0.164 (95%CI [0.126, 0.204]); SRMR\\u0026thinsp;=\\u0026thinsp;0.059. The chi-square difference test compared to the configural model was statistically significant, Δχ\\u0026sup2;(3)\\u0026thinsp;=\\u0026thinsp;8.60, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.035, suggesting that constraining the factor loadings significantly worsened model fit. While the change in CFI was below the recommended threshold (ΔCFI\\u0026thinsp;=\\u0026thinsp;0.007), the change in RMSEA exceeded the commonly accepted cutoff (ΔRMSEA\\u0026thinsp;=\\u0026thinsp;0.04). Given this mixed pattern of results, strict metric invariance cannot be fully assumed, indicating that some factor loadings may differ across males and females. However, the modification indices for all item loadings were very low (0.021), indicating that the loadings are not causing big misfit across groups.\\u003c/p\\u003e\\u003cp\\u003eScalar invariance was tested by constraining both factor loadings and item intercepts to be equal across sexes. The model fit indices were acceptable: χ\\u0026sup2;(10)\\u0026thinsp;=\\u0026thinsp;73.7, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;.001; CFI\\u0026thinsp;=\\u0026thinsp;0.927; TLI\\u0026thinsp;=\\u0026thinsp;0.912; RMSEA\\u0026thinsp;=\\u0026thinsp;0.154 (95%CI [0.122, 0.188]); SRMR\\u0026thinsp;=\\u0026thinsp;0.072. The chi-square difference test compared to the metric model was statistically significant, Δχ\\u0026sup2;(3)\\u0026thinsp;=\\u0026thinsp;16.52, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001, supporting partial scalar invariance. However, the modification indices for intercepts show all the intercepts were equally constrained across sex groups.\\u003c/p\\u003e\\u003cp\\u003eThe strict invariance model also showed poor fit with χ\\u0026sup2;(14)\\u0026thinsp;=\\u0026thinsp;104.3, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001, CFI\\u0026thinsp;=\\u0026thinsp;0.896, TLI\\u0026thinsp;=\\u0026thinsp;0.911, and RMSEA\\u0026thinsp;=\\u0026thinsp;0.155 (95%CI [0.128, 0.184]), SRMR\\u0026thinsp;=\\u0026thinsp;0.071, indicating that it did not provide a better fit compared to the scalar invariance model. The chi-square difference test compared to the metric model was statistically significant, Δχ\\u0026sup2;(3)\\u0026thinsp;=\\u0026thinsp;30.6, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001, supporting partial strict invariance.\\u003c/p\\u003e\\u003cp\\u003eThe analysis of measurement invariance based on age groups as follows. The baseline configural invariance model testing the consistency across age groups demonstrated an acceptable fit: χ\\u0026sup2;(4)\\u0026thinsp;=\\u0026thinsp;36.4, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;.001; CFI\\u0026thinsp;=\\u0026thinsp;0.965, TLI\\u0026thinsp;=\\u0026thinsp;0.895, RMSEA\\u0026thinsp;=\\u0026thinsp;0.174 (95% CI [0.125, 0.228]); SRMR\\u0026thinsp;=\\u0026thinsp;0.026. The acceptable CFI (\\u0026gt;\\u0026thinsp;0.90) and SRMR (\\u0026lt;\\u0026thinsp;0.08) values suggest that the basic factorial structure is similar across groups.\\u003c/p\\u003e\\u003cp\\u003eThe metric invariance model also showed an acceptable fit: χ\\u0026sup2;(7)\\u0026thinsp;=\\u0026thinsp;38.1, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;.001; CFI\\u0026thinsp;=\\u0026thinsp;0.966; TLI\\u0026thinsp;=\\u0026thinsp;0.942; RMSEA\\u0026thinsp;=\\u0026thinsp;0.129 (95%CI [0.091, 0.170]); SRMR\\u0026thinsp;=\\u0026thinsp;0.032. The chi-square difference test compared to the configural model was not statistically significant, Δχ\\u0026sup2;(3)\\u0026thinsp;=\\u0026thinsp;1.70, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.637, suggesting metric invariance holds true across age groups.\\u003c/p\\u003e\\u003cp\\u003eThe scalar invariance model fit indices were also within acceptable thresholds: χ\\u0026sup2;(10)\\u0026thinsp;=\\u0026thinsp;45.1, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;.001; CFI\\u0026thinsp;=\\u0026thinsp;0.962; TLI\\u0026thinsp;=\\u0026thinsp;0.954; RMSEA\\u0026thinsp;=\\u0026thinsp;0.114 (95%CI [0.082, 0.149]); SRMR\\u0026thinsp;=\\u0026thinsp;0.039. The chi-square difference test compared to the metric model was not statistically significant, Δχ\\u0026sup2;(3)\\u0026thinsp;=\\u0026thinsp;6.97, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.073, supporting scalar invariance.\\u003c/p\\u003e\\u003cp\\u003eFinally, the strict invariance model also demonstrated an acceptable fit with χ\\u0026sup2;(14)\\u0026thinsp;=\\u0026thinsp;56.4, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001, CFI\\u0026thinsp;=\\u0026thinsp;0.954, TLI\\u0026thinsp;=\\u0026thinsp;0.961, and RMSEA\\u0026thinsp;=\\u0026thinsp;0.106 (95%CI [0.078, 0.136]), SRMR\\u0026thinsp;=\\u0026thinsp;0.049. The chi-square difference test compared to the metric model was statistically significant, Δχ\\u0026sup2;(3)\\u0026thinsp;=\\u0026thinsp;11.4, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.023, supporting partial strict invariance.\\u003c/p\\u003e\\u003cp\\u003eIn summary, the measurement invariance analyses across sex and age groups indicate a robust factorial structure, with acceptable model fits for both configural and metric invariance. While partial strict invariance was established, some significant differences in fit suggest careful attention to factor loadings and intercepts is warranted. Further information can be found in the supplementary materials.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec15\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eRasch Analysis\\u003c/h2\\u003e\\u003cp\\u003eA summary of item parameter estimates and infit and outfit statistics for the modified GQ4 Arabic version is presented in the supplementary materials. The item difficulty values range from \\u0026minus;\\u0026thinsp;4.07 (GQ5) to -3.49 (GQ4), with lower values suggesting relatively easy items for respondents. All items have similar values for tau categories, indicating consistent performance across all categories. However, GQ1 and GQ4 show more extreme tau values, particularly in tau for Cat1, which may indicate potential issues with discrimination between adjacent response categories. In addition, the infit and outfit values for all the items were between 0.83 and 1.13, indicating that these items had less variation in the observed response pattern than expected by the model. The Item Characteristic Curves (ICCs) for each item illustrate how the probability of selecting different response categories changes with the latent dimension (ability level). Each item shows a consistent pattern where lower categories are more likely at lower ability levels, and higher categories become more probable as ability increases. This consistency across items suggests that they are well-calibrated and fit the Rasch model appropriately, providing reliable measurements of the latent trait (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). Further details including person-item maps for risk scale are available in the supplementary materials.\\u003c/p\\u003e\\u003cp\\u003e\\u003c/p\\u003e\\u003c/div\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eThis study addresses a gap in the literature regarding the lack of gratitude measurement tools within Arabic-speaking populations, paving the way for further research in this area. Specifically, this research investigated the psychometric properties and measurement invariance of the Arabic version of the GQ6 among a sample of Saudi university students. Initial analyses revealed that the Arabic GQ6 exhibited low internal consistency, prompting the exclusion of two reverse-coded items exhibiting low corrected item-total correlations and factor loadings from further analysis. Subsequent analyses indicated that a one-factor model with four items (GQ4) exhibited good fit across nearly all fit indices, with string standardized factor loadings. The Arabic GQ4 demonstrated good internal consistency and moderate positive correlations with satisfaction with life, self-esteem, and well-being. Regarding measurement invariance, results supported configural and metric invariance across sex and age groups. Furthermore, Rasch analysis showed that the GQ4 Arabic version demonstrates consistent item performance, indicating that the items were relatively easy, while infit and outfit statistics suggest minimal variation in response patterns.\\u003c/p\\u003e\\u003cp\\u003eThe GQ6 includes two reverse-coded items: Item 3 (\\u0026ldquo;When I look at the world, I do not see much to be grateful for\\u0026rdquo;) and Item 6 (\\u0026ldquo;Long amounts of time can go by before I feel grateful to something or someone\\u0026rdquo;). Both items appeared to be problematic in our analysis and thus were excluded from subsequent analyses. Using CFA on a second random subset of the data, the newly modified GQ4 Arabic version exhibited a one-factor structure with good model fit for most indices. The newly modified Arabic GQ4 version also demonstrated good internal consistency. This finding aligns with results from a recent study that validated the GQ6 among a sample of Lebanese adults, which found that the GQ4 (excluding the reverse-coded items) provided the best model fit, demonstrating good internal consistency and an invariant structure across gender at the configural, metric, and scalar levels [\\u003cspan citationid=\\\"CR66\\\" class=\\\"CitationRef\\\"\\u003e66\\u003c/span\\u003e].\\u003c/p\\u003e\\u003cp\\u003eOur findings contribute to the ongoing discussion regarding the appropriate factor structure for the GQ6 across samples and cultural contexts [\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e]. Many studies examining the factor structure of the GQ6 in different cultural context have failed to replicate the original 6-item version. For instance, Item 6 \\u0026ldquo;Long amounts of time can go by before I feel grateful to something or someone\\u0026rdquo; have been shown to exhibit low corrected item-total correlation and low factor loading, leading to it exclusion in many validation studies [\\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e27\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e, \\u003cspan additionalcitationids=\\\"CR31 CR32\\\" citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e30\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e33\\u003c/span\\u003e]. Other research with young adults has found Item 6 to be \\u0026ldquo;difficult to understand\\u0026rdquo; and \\u0026ldquo;very abstract\\u0026rdquo; [\\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e].\\u003c/p\\u003e\\u003cp\\u003eWhile reverse-coded items are traditionally included to guard against acquiescence bias\\u0026mdash;the tendency to systematically agree with items regardless of content [\\u003cspan citationid=\\\"CR67\\\" class=\\\"CitationRef\\\"\\u003e67\\u003c/span\\u003e]\\u0026mdash;empirical evidence suggests they often fail in practice. Cross-cultural research has demonstrated that such items frequently compromise the psychometric properties of measurement tools (e.g., reliability and factor structure) [\\u003cspan citationid=\\\"CR68\\\" class=\\\"CitationRef\\\"\\u003e68\\u003c/span\\u003e], measurement model and path coefficients [\\u003cspan citationid=\\\"CR69\\\" class=\\\"CitationRef\\\"\\u003e69\\u003c/span\\u003e], and can lead to respondent inattention and confusion [\\u003cspan citationid=\\\"CR70\\\" class=\\\"CitationRef\\\"\\u003e70\\u003c/span\\u003e], and misinterpretation [\\u003cspan citationid=\\\"CR71\\\" class=\\\"CitationRef\\\"\\u003e71\\u003c/span\\u003e]. These concerns are substantiated by multiple studies. For instance, a large study evaluating an alternative to the traditional mixed-wording approach reformulated negative items into positive equivalents across seven psychological measures administered to 4,192 Emirati university students. Results showed that all-positive versions yielded systematically higher reliability coefficients and cleaner factor structures (e.g., reduced cross-loadings and improved model fit) than mixed-format originals [\\u003cspan citationid=\\\"CR72\\\" class=\\\"CitationRef\\\"\\u003e72\\u003c/span\\u003e]. Similair findings have been found in studies using the Multidimensional Fatigue Inventory (MFI-20) among patients with inflammatory bowel disease [\\u003cspan citationid=\\\"CR70\\\" class=\\\"CitationRef\\\"\\u003e70\\u003c/span\\u003e] and Spanish-language scales for personality, emotion regulation and hopelessness across multiple Spanish samples including adolescents, college students, caregivers, adults, and immigrants [\\u003cspan citationid=\\\"CR71\\\" class=\\\"CitationRef\\\"\\u003e71\\u003c/span\\u003e]. In sum, similar patterns were observed for the two reverse-coded items in the GQ6 Arabic version, and their exclusion yielded a more robust GQ4 version. However, additional research is needed to further confirm the factor structure of the GQ4, investigate whether all-positive wording affects criterion validity.\\u003c/p\\u003e\\u003cp\\u003eMeasurement invariance testing is a fundamental aspect of psychological assessment, yet often overlooked [\\u003cspan citationid=\\\"CR73\\\" class=\\\"CitationRef\\\"\\u003e73\\u003c/span\\u003e]. As [\\u003cspan citationid=\\\"CR74\\\" class=\\\"CitationRef\\\"\\u003e74\\u003c/span\\u003e] emphasizes, establishing invariance is prerequisite for meaningful group comparisons as it determines whether observed differences reflect true variations in the latent construct or measurement artifacts. The GQ4 Arabic version demonstrated configural invariance across sex and age groups, confirming that the basic factor structure is generally similar across both groups. Full metric invariance (factor loadings) holds true across age groups, but only partially across sex groups. Scalar and strict invariance are supported across age groups, but only partially across sex groups. These findings are consistent with previous research providing evidence for measurement invariance for the GQ6 and its short forms (e.g., GQ5) in various samples including Western [\\u003cspan citationid=\\\"CR75\\\" class=\\\"CitationRef\\\"\\u003e75\\u003c/span\\u003e], North American [\\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e30\\u003c/span\\u003e], Asian [\\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e24\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR76\\\" class=\\\"CitationRef\\\"\\u003e76\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR77\\\" class=\\\"CitationRef\\\"\\u003e77\\u003c/span\\u003e], and South Asian [\\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e].\\u003c/p\\u003e\\u003cp\\u003eThe current findings provide evidence for the concurrent validity of the Arabic GQ4 version. Consistent with previous research, the GQ4 demonstrated moderately significant positive correlations with established measures of psychological well-being taken the same time, including satisfaction with life, self-esteem, and subjective well-being. These findings align with previous studies [\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR78\\\" class=\\\"CitationRef\\\"\\u003e78\\u003c/span\\u003e] and support theoretical models positioning gratitude as a fundamental element of flourishing and fulfilling life [\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e].\\u003c/p\\u003e\\u003cp\\u003eSeveral limitations should be considered when interpreting these findings. First, the study relied on a convenience sample of university students, which may limit the generalizability of results. Second, the cross-sectional design precludes causal inferences about the relationship between dispositional gratitude and psychological well-being. Third, the original reverse-coded items in the GQ6 were designed to assess the conscious recognition of positive aspects in ones\\u0026rsquo; life and environment as well as the temporal frequency of grateful affect. While the removal of reverse-coded items improved psychometric properties, this modification may narrow the conceptual breadth of dispositional gratitude as originally conceptualized [\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e].\\u003c/p\\u003e\\u003cp\\u003eFuture research should validate the GQ4 in more diverse samples such as adolescents, older adults, and clinical samples. Additionally, future research should employ a longitudinal design to examine temporal stability and predictive validity of the GQ4. Finally, building on literature discussed [\\u003cspan citationid=\\\"CR70\\\" class=\\\"CitationRef\\\"\\u003e70\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR72\\\" class=\\\"CitationRef\\\"\\u003e72\\u003c/span\\u003e], future research could also test positively reworded versions of the reverse-coded items (e.g., \\\"I regularly notice things to be grateful for\\\") to assess whether this approach better preserves the original construct breadth while maintaining the psychometric robustness found in the GQ4 version. Such research could compare the performance of this modified GQ6-positive against both the original GQ6 and the current GQ4 versions.\\u003c/p\\u003e\"},{\"header\":\"Conclusion\",\"content\":\"\\u003cp\\u003eThe Arabic GQ4 version, a measure of dispositional gratitude, demonstrates robust psychometric properties, including good internal consistency, excellent model fit for a unidimensional structure with high factor loadings, concurrent validity, measurement invariance across demographic groups, consistent item performance, and minimal response pattern variations. This brief and cost-effective measure fills a critical gap by providing researchers and clinicians with a reliable and valid tool to study dispositional gratitude in Arabic-speaking populations. However, while these results are promising, additional validation studies across diverse Arabic-speaking samples and settings are warranted to further confirm the measure\\u0026rsquo;s generalizability and robustness.\\u003c/p\\u003e\"},{\"header\":\"Abbreviations\",\"content\":\"\\u003cdiv class=\\\"DefinitionList\\\"\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eGQ6\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003eGratitude Questionnaire 6-item form\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eGQ4\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003eGratitude Questionnaire 4-item form\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eSWLS\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003eSatisfaction With Life Scale\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eRSES\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003eRosenberg Self-Esteem Scale\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eWHO-5\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003eWorld Health Organization Well-Being Index\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eSWL\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003eSatisfaction with life\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eEFA\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003eExploratory factor analysis\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eCFA\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003eConfirmatory factor analysis\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eIQR\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003eInterquartile range\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003e\\u0026#120594;2\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003eChi-square statistic\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eRMSEA\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003eRoot mean square error of approximation\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eSRMR\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003eStandardized root mean square residual\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eCFI\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003eComparative fit index\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eTLI\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003eTucker-Lewis index\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eMGCFA\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003eMulti-group confirmatory factor analysis\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eKMO\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003eKaiser-Meyer-Olkin\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eMSA\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003eMeasure of sampling adequacy\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eCI\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003eConfidence interval\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eGFI\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003eGoodness-of-fit index\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eAGFI\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003eAdjusted goodness-of-fit index\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eCAIC\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003eAkaike information criterion\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eBIC\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003eBayesian information criterion\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eRSM\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003eRasch Rating Scale Model\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e\\u003cdiv class=\\\"Term\\\"\\u003eICC\\u003c/div\\u003e\\u003cdiv class=\\\"Description\\\"\\u003e\\u003cp\\u003eItem Characteristic Curve\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eEthics approval and consent to participate:\\u0026nbsp;\\u003c/strong\\u003eThe study was conducted in accordance with the Declaration of Helsinki and approved by the Research Ethics Committee at the University of Ha\\u0026apos;il (protocol code H-2025-580 and 27 Jan 2025 of approval). All participants involved in this study procided electronic informed consent.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConsent for publication:\\u0026nbsp;\\u003c/strong\\u003eNot applicable.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eData Availability Statement:\\u0026nbsp;\\u003c/strong\\u003eThe datasets generated and/or analyzed during this study are not publicly available due to ethical restrictions, but are available from the corresponding author upon reasonable request.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCompeting interest:\\u003c/strong\\u003e The authors declare no conflicts of interest.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eFunding:\\u003c/strong\\u003e This research was funded by Scientific Research Deanship at the University of Ha\\u0026apos;il, Saudi Arabia through project number BA-25 001.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAuthor Contributions:\\u003c/strong\\u003e Conceptualization, M.M.A. and H.A.A.; methodology, M.M.A., K.A.A.; software, M.M.A.; validation, M.M.A., H.A.A.; and K.A.A.; formal analysis, M.M.A.; investigation, M.M.A., K.A.A.; resources, H.A.A.; and K.A.A.; data curation, M.M.A., H.A.A.; and K.A.A.; writing\\u0026mdash;original draft preparation, M.M.A.; writing\\u0026mdash;review and editing, M.M.A., H.A.A.; and K.A.A.; visualization, M.M.A., H.A.A.; and K.A.A.; supervision, M.M.A.; project administration, M.M.A.; funding acquisition, M.M.A. All authors have read and agreed to the published version of the manuscript.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAcknowledgments:\\u003c/strong\\u003e The authors would like to acknowledge and thank the Scientific Research Deanship for funding this project and all our undergraduate and postgraduate students for participating in this research.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\u003cli\\u003e\\u003cspan\\u003eAllen S (2018) The science of gratitude [Internet]. John Templeton Foundation Conshohocken, PA; [cited 2025 Apr 8]. Available from: \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://thesnipermind.com/images/Studies-PDF-Format/GGSC-JTF_White_Paper-Gratitude-FINAL.pdf\\u003c/span\\u003e\\u003cspan address=\\\"https://thesnipermind.com/images/Studies-PDF-Format/GGSC-JTF_White_Paper-Gratitude-FINAL.pdf\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eDalal S, Singh S (2025) Gratitude in action: Effect of gratitude on mental health. J Health Manag 27(1):100\\u0026ndash;107\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eWood AM, Maltby J, Stewart N, Linley PA, Joseph S (2008) A social-cognitive model of trait and state levels of gratitude. Emot Wash DC 8(2):281\\u0026ndash;290\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eWood AM, Froh JJ, Geraghty AWA (2010) Gratitude and well-being: A review and theoretical integration. Clin Psychol Rev 30(7):890\\u0026ndash;905\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eMcCullough ME, Emmons RA, Tsang JA (2002) The grateful disposition: A conceptual and empirical topography. J Pers Soc Psychol 82(1):112\\u0026ndash;127\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eEmmons RA, McCullough ME, Tsang JA (2003) The assessment of gratitude. In: Lopez SJ, Snyder CR (eds) Positive psychological assessment: A handbook of models and measures. American Psychological Association, Washington, DC, US, pp 327\\u0026ndash;341\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eZhu N, Li C, Ye Y, Zhang L, Kong F (2024) Longitudinal effect of gratitude on prosocial behavior among young adults: Evidence from the bi-factor model of gratitude. J Happiness Stud 25(1):3\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eMcGuire AP, Fagan J, Tsai J, Merians AN, Nichter B, Norman S et al (2022) Dispositional gratitude predicts the development of psychopathology and suicidal behaviors: Results from a 7-year population-based study of U.S. military veterans. J Psychiatr Res 149:168\\u0026ndash;176\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eValikhani A, Ahmadnia F, Karimi A, Mills PJ (2019) The relationship between dispositional gratitude and quality of life: The mediating role of perceived stress and mental health. Personal Individ Differ 141:40\\u0026ndash;46\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eIodice JA The association between gratitude and depression: A meta-analysis. Int J Depress Anxiety 2021 June 23;4(1):024\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eRichardson AL, Gallagher MW (2021) Giving thanks is associated with lower PTSD severity: A meta-analytic review. J Happiness Stud 22(6):2549\\u0026ndash;2562\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eWang A, Reyes A, Urkmez B, McGuire A, Lee B, Umucu E (2024) The association between PTSD, gratitude, academic adjustment, and dropout decisions in veteran students with disabilities: Brief report. J Veterans Stud 10(1):40\\u0026ndash;47\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003ePhillips BN, Fleming AR, Bean B, Umucu E, Lee B, Roundtree SM et al (2022) Relations among gratitude, adaptation to disability, and flourishing among adults with disabilities: A longitudinal mediation model. Rehabil Psychol 67(4):546\\u0026ndash;555\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eDong L, Zou S, Fan R, Wang B, Ye L (2024) The influence of athletes\\u0026rsquo; gratitude on burnout: The sequential mediating roles of the coach-athlete relationship and hope. Front Psychol 15:1358799\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eKerry N, Chhabra R, Clifton JDW (2023) Being thankful for what you have: A systematic review of evidence for the effect of gratitude on life satisfaction. Psychol Res Behav Manag 16:4799\\u0026ndash;4816\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eKirca A, Malouff M, Meynadier J (2023) The Effect of expressed gratitude interventions on psychological wellbeing: A meta-analysis of randomised controlled studies. Int J Appl Posit Psychol 8(1):63\\u0026ndash;86\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eCregg DR, Cheavens JS (2021) Gratitude interventions: Effective self-help? A meta-analysis of the impact on symptoms of depression and anxiety. J Happiness Stud 22(1):413\\u0026ndash;445\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eDiniz G, Korkes L, Trist\\u0026atilde;o LS, Pelegrini R, Bellodi PL, Bernardo WM (2023) The effects of gratitude interventions: A systematic review and meta-analysis. Einstein S\\u0026atilde;o Paulo 21:eRW0371\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eJans-Beken L, Jacobs N, Janssens M, Peeters S, Reijnders J, Lechner L et al (2020) Gratitude and health: An updated review. J Posit Psychol 15(6):743\\u0026ndash;782\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eMa LK, Tunney RJ, Ferguson E (2017) Does gratitude enhance prosociality? A meta-analytic review. Psychol Bull 143(6):601\\u0026ndash;635\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eCowles B, Medvedev ON (2022) The Gratitude Questionnaire-Six Item Form (GQ-6). In: Medvedev ON, Kr\\u0026auml;geloh CU, Siegert RJ, Singh NN, editors. Handbook of Assessment in Mindfulness Research [Internet]. Cham: Springer International Publishing; [cited 2025 Feb 1]. pp. 1\\u0026ndash;15. Available from: \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1007/978-3-030-77644-2_98-1\\u003c/span\\u003e\\u003cspan address=\\\"10.1007/978-3-030-77644-2_98-1\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eGouveia VV, Ribeiro MGC, De Aquino TAA, Loureto GDL, Nascimento BS, Rezende AT (2021) Gratitude Questionnarie (GQ-6): Evidence of construct validity in Brazil. Curr Psychol 40(5):2481\\u0026ndash;2489\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eFung S fu. Evaluating the psychometric properties of the Gratitude Questionnaire in a Chinese sample: Comparing the 6-Item and 5-Item versions. Mindfulness. 2024 Sept 1;15(9):2321\\u0026ndash;9\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eKong F, You X, Zhao J (2017 Sept) Evaluation of the Gratitude Questionnaire in a Chinese sample of adults: Factorial validity, criterion-related validity, and measurement invariance across sex. Front Psychol 1:8:1498\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eZeng Y, Ling Y, Huebner ES, He Y, Lei X (2017) The psychometric properties of the 5-item Gratitude Questionnaire in Chinese adolescents. J Psychiatr Ment Health Nurs 24(4):203\\u0026ndash;210\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eJans-Beken L, Lataster J, Leontjevas R, Jacobs N (2015) Measuring gratitude: A comparative validation of the Dutch Gratitude Questionnaire (GQ6) and Short Gratitude, Resentment, and Appreciation Test (SGRAT). Psychol Belg [Internet]. May 15 [cited 2025 Feb 3];55(1). Available from: \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://psychologicabelgica.com/articles/10.5334/pb.bd\\u003c/span\\u003e\\u003cspan address=\\\"https://psychologicabelgica.com/articles/10.5334/pb.bd\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eHudecek MFC, Blabst N, Morgan B, Lermer E (2020) Measuring gratitude in Germany: Validation study of the German version of the Gratitude Questionnaire-Six Item Form (GQ-6-G) and the Multi-Component Gratitude Measure (MCGM-G). Front Psychol [Internet]. Oct 8 [cited 2025 Feb 6];11. Available from: \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://www.frontiersin.org/journals/psychology/articles/\\u003c/span\\u003e\\u003cspan address=\\\"https://www.frontiersin.org/journals/psychology/articles/\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.3389/fpsyg.2020.590108/full\\u003c/span\\u003e\\u003cspan address=\\\"10.3389/fpsyg.2020.590108/full\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eDixit SK, Sinha J (2023) Adaptation and validation of the gratitude questionnaire (GQ-6) for the Indian context. Curr Psychol 42(11):8722\\u0026ndash;8732\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eSumi K (2017) Reliability and construct validity of the Gratitude Questionnaire 6 Item Form (GQ 6) in a sample of Japanese college students. J Posit Psychol Wellbeing 1(2):73\\u0026ndash;84\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eLanger \\u0026Aacute;I, Ulloa VG, Aguilar-Parra JM, Araya-V\\u0026eacute;liz C, Brito G (2016) Validation of a Spanish translation of the Gratitude Questionnaire (GQ-6) with a Chilean sample of adults and high schoolers. Health Qual Life Outcomes 14(1):53\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eMagallares A, Recio P, Sanju\\u0026aacute;n P, Magallares A, Recio P, Sanju\\u0026aacute;n P (2018) Factor structure of the Gratitude Questionnaire in a Spanish sample. Span J Psychol 21:1\\u0026ndash;7\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eChen LH, Chen MY, Kee YH, Tsai YM (2009) Validation of the Gratitude Questionnaire (GQ) in Taiwanese undergraduate students. J Happiness Stud 10(6):655\\u0026ndash;664\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eY\\u0026uuml;ksel A, Oguz Duran N (2012) Turkish adaptation of the Gratitude Questionnaire. Eurasian J Educ Res. ;(46):199\\u0026ndash;216\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eMakhoul M, Bartley EJ (2023) Exploring the relationship between gratitude and depression among older adults with chronic low back pain: A sequential mediation analysis. Front Pain Res 4:1140778\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eBohlmeijer ET, Kraiss JT, Watkins P, Schotanus-Dijkstra M (2021) Promoting gratitude as a resource for sustainable mental health: Results of a 3-armed randomized controlled trial up to 6 months follow-up. J Happiness Stud 22(3):1011\\u0026ndash;1032\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eMatvienko-Sikar K, Dockray S (2017) Effects of a novel positive psychological intervention on prenatal stress and well-being: A pilot randomised controlled trial. Women Birth 30(2):e111\\u0026ndash;e118\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eBartholomew E, Iqbal N, Medvedev O (2022) Enhancing the assessment of gratitude in mindfulness research: A Rasch Analysis of the 6-Item Gratitude Questionnaire. Mindfulness 13(12):3017\\u0026ndash;3027\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eDi Fabio A (2022) Gratitude Questionnaire-6 (GQ-6): Psychometric properties of the Italian version. Counseling 15(2):95\\u0026ndash;103\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eFroh JJ, Fan J, Emmons RA, Bono G, Huebner ES, Watkins P (2011) Measuring gratitude in youth: Assessing the psychometric properties of adult gratitude scales in children and adolescents. Psychol Assess 23(2):311\\u0026ndash;324\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eFenn J, Tan CS, George S (2020 Sept) Development, validation and translation of psychological tests. BJPsych Adv 26(5):306\\u0026ndash;315\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eSousa VD, Rojjanasrirat W (2011) Translation, adaptation and validation of instruments or scales for use in cross-cultural health care research: A clear and user-friendly guideline. J Eval Clin Pract 17(2):268\\u0026ndash;274\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eSperber AD (2004) Translation and validation of study instruments for cross-cultural research. Gastroenterology 126(Supp 1):S124\\u0026ndash;S128\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eDiener E, Emmons RA, Larsen RJ, Griffin S (1985) The Satisfaction With Life Scale. J Pers Assess 49(1):71\\u0026ndash;75\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eAbdallah T (1998) The Satisfaction with Life Scale (SWLS): Psychometric properties in an Arabic-speaking sample. Int J Adolesc Youth 7(2):113\\u0026ndash;119\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eAbdel-Khalek AM (2008) Satisfaction with life in Kuwaiti samples. Derasat Nafsiyah Psychol Stud 18:121\\u0026ndash;135\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003ePavot W, Diener E (2009) Review of the Satisfaction With Life Scale. In: Diener E, editor. Assessing Well-Being: The Collected Works of Ed Diener [Internet]. Dordrecht: Springer Netherlands; [cited 2020 Oct 25]. pp. 101\\u0026ndash;17. (Social Indicators Research Series; vol. 39). Available from: \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1007/978-90-481-2354-4_5\\u003c/span\\u003e\\u003cspan address=\\\"10.1007/978-90-481-2354-4_5\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eRosenberg M (1965) Society and the adolescent self-image. Princeton University Press, Princeton, NJ\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eGray-Little B, Williams VSL, Hancock TD (1997) An item response theory analysis of the Rosenberg Self-Esteem Scale. Pers Soc Psychol Bull 23(5):443\\u0026ndash;451\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eSilber E, Tippett JS (1965) Self-Esteem: Clinical assessment and measurement validation. Psychol Rep 16(Suppl 3):1017\\u0026ndash;1071\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eZayed KN, Haddabi BA, Al-Rawahi N, Al-Tauqi M, Thiyabat F, Al-Busafi MS (2016) Gender differences in self-esteem and its relationship with body mass index among Omani adolescents. Can J Clin Nutr 4(1):18\\u0026ndash;24\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eZaidi U, Awad SS, Mortada EM, Qasem HD, Kayal GF (2015) Psychometric evaluation of Arabic version of self-esteem, psychological well-being and Impact of Weight on Quality of Life Questionnaire (IWQOL-Lite) in female student sample of PNU. Eur Med Health Pharm J 8(2):29\\u0026ndash;33\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eAbdel-Khalek AM, Korayem AS, El-Nayal MA (2012) Self-esteem among college students from four Arab countries. Psychol Rep 110(1):297\\u0026ndash;303\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eBech P, Gudex C, Johansen KS (1996) The WHO (Ten) Well-Being Index: Validation in diabetes. Psychother Psychosom 65(4):183\\u0026ndash;190\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eTopp CW, \\u0026Oslash;stergaard SD, S\\u0026oslash;ndergaard S, Bech P (2015) The WHO-5 Well-Being Index: A systematic review of the literature. Psychother Psychosom 84(3):167\\u0026ndash;176\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eHajos TRS, Pouwer F, Skovlund SE, Oudsten BLD, Geelhoed-Duijvestijn PHLM, Tack CJ et al (2013) Psychometric and screening properties of the WHO-5 well-being index in adult outpatients with Type 1 or Type 2 diabetes mellitus. Diabet Med 30(2):e63\\u0026ndash;e69\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eAlshayea AK, Development, and validation of an Arabic version of the World Health Organization Well-Being Index (WHO-5). J Psychopathol Behav Assess [Internet]. 2023 Feb 1 [cited 2023 Feb 2]; Available from: \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1007/s10862-023-10027-x\\u003c/span\\u003e\\u003cspan address=\\\"10.1007/s10862-023-10027-x\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eFekih-Romdhane F, Cherif W, Alhuwailah A, Fawaz M, Shuwiekh HAM, Helmy M et al (2023) Cross-country validation of the Arabic version of the WHO-5 Well-Being Index in non- clinical young adults from six Arab countries [Internet]. Research Square; [cited 2024 Dec 12]. Available from: \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://www.researchsquare.com/article/rs-2988215/v1\\u003c/span\\u003e\\u003cspan address=\\\"https://www.researchsquare.com/article/rs-2988215/v1\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eFekih-Romdhane F, Al Mouzakzak F, Abilmona G, Dahdouh O, Hallit S (2024) Validation and optimal cut-off score of the World Health Organization Well-being Index (WHO-5) as a screening tool for depression among patients with schizophrenia. BMC Psychiatry 24:391\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eCronbach LJ Coefficient alpha and the internal structure of tests. Psychometrika. 1951 Sept 1;16(3):297\\u0026ndash;334\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eMcDonald RP (1999) Test theory: A unified treatment. Psychology, New York, p 498\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eRaftery A Bayesian Model Selection in Structural Equation Models. In 1992 [cited 2025 Mar 10]. Available from: \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://www.semanticscholar.org/paper/Bayesian-Model-Selection-in-Structural-Equation-Raftery/187c61f11dd7cd5d2b786f5d085ff0da252fd23f\\u003c/span\\u003e\\u003cspan address=\\\"https://www.semanticscholar.org/paper/Bayesian-Model-Selection-in-Structural-Equation-Raftery/187c61f11dd7cd5d2b786f5d085ff0da252fd23f\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eRosseel Y (2012) lavaan: An R package for structural equation modeling. J Stat Softw 48:1\\u0026ndash;36\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eCheung GW, Rensvold RB (2002) Evaluating goodness-of-fit indexes for testing measurement invariance. Struct Equ Model 9(2):233\\u0026ndash;255\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eChen FF (2007) Sensitivity of goodness of fit indexes to lack of measurement invariance. Struct Equ Model 14(3):464\\u0026ndash;504\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eByrne BM, van De Vijver FJR (2010) Testing for measurement and structural equivalence in large-scale cross-cultural studies: Addressing the issue of nonequivalence. Int J Test 10(2):107\\u0026ndash;132\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eFekih-Romdhane F, Postigo \\u0026Aacute;, Malaeb D, Sarray El Dine A, Moawad M, Hallit R et al (2025) Validation of the Arabic version of the Gratitude Questionnaire (GQ-4) in a sample of non-clinical adults. BMC Psychol 13:143\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eWatson D (1992) Correcting for acquiescent response bias in the absence of a balanced scale: An application to class consciousness. Sociol Methods Res 21(1):52\\u0026ndash;88\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eZeng B, Wen H, Zhang J How does the valence of wording affect features of a scale? The method effects in the undergraduate learning burnout scale. Front Psychol [Internet]. 2020 Sept 28 [cited 2025 Apr 19];11. Available from: \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://www.frontiersin.orghttps://www.frontiersin.org/journals/psychology/articles/\\u003c/span\\u003e\\u003cspan address=\\\"https://www.frontiersin.orghttps://www.frontiersin.org/journals/psychology/articles/\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.3389/fpsyg.2020.585179/full\\u003c/span\\u003e\\u003cspan address=\\\"10.3389/fpsyg.2020.585179/full\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eDueber DM, Toland MD, Lingat JE, Love AMA, Qiu C, Wu R et al (2022) To reverse item orientation or not to reverse item orientation, that is the question. Assessment 29(7):1422\\u0026ndash;1440\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003evan Sonderen E, Sanderman R, Coyne JC (2013 July) Ineffectiveness of reverse wording of questionnaire items: Let\\u0026rsquo;s learn from cows in the rain. PLoS ONE 31(7):e68967\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eVenta A, Bailey CA, Walker J, Mercado A, Colunga-Rodriguez C, \\u0026Aacute;ngel-Gonz\\u0026aacute;lez M et al Reverse-coded items do not work in Spanish: Data from four samples using established measures. Front Psychol [Internet]. 2022 June 23 [cited 2025 Apr 19];13. Available from: \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://www.frontiersin.orghttps://www.frontiersin.org/journals/psychology/articles/\\u003c/span\\u003e\\u003cspan address=\\\"https://www.frontiersin.orghttps://www.frontiersin.org/journals/psychology/articles/\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.3389/fpsyg.2022.828037/full\\u003c/span\\u003e\\u003cspan address=\\\"10.3389/fpsyg.2022.828037/full\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eDodeen H The Effects of changing negatively worded items to positively worded items on the reliability and the factor structure of psychological scales. J Psychoeduc Assess. 2023 June 1;41(3):298\\u0026ndash;310\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eMaassen E, D\\u0026rsquo;Urso ED, van Assen MALM, Nuijten MB, De Roover K, Wicherts JM (2023) The dire disregard of measurement invariance testing in psychological science. Psychol Methods\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eKarl JA (2023) Multigroup Invariance Testing for Cross-Cultural Research. In: Kr\\u0026auml;geloh CU, Alyami M, Medvedev ON, editors. International Handbook of Behavioral Health Assessment [Internet]. Cham: Springer International Publishing; [cited 2024 May 24]. pp. 1\\u0026ndash;17. Available from: \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1007/978-3-030-89738-3_7-1\\u003c/span\\u003e\\u003cspan address=\\\"10.1007/978-3-030-89738-3_7-1\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eLing Y, Yang Q, Zeng Y, Huebner ES (2021) Assessing the Measurement Invariance of the Gratitude Questionnaire\\u0026ndash;5 in Chinese and American Adolescents. Span J Psychol 24:e17\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eTan Q, Zou J, Kong F (2022) Longitudinal and Gender Measurement Invariance of the Gratitude Questionnaire in Chinese Adolescents. Psychol Rep 125(6):3209\\u0026ndash;3223\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eValdez JPM, Yang W, Datu JAD (2017) Validation of the Gratitude Questionnaire in Filipino Secondary School Students. Span J Psychol 20:E45\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eSrirangarajan T, Oshio A, Yamaguchi A, Akutsu S Cross-cultural nomological network of gratitude: Findings From Midlife in the United States (MIDUS) and Japan (MIDJA). Front Psychol [Internet]. 2020 May 26 [cited 2025 Apr 23];11. Available from: \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://www.frontiersin.orghttps://www.frontiersin.org/journals/psychology/articles/\\u003c/span\\u003e\\u003cspan address=\\\"https://www.frontiersin.orghttps://www.frontiersin.org/journals/psychology/articles/\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.3389/fpsyg.2020.00571/full\\u003c/span\\u003e\\u003cspan address=\\\"10.3389/fpsyg.2020.00571/full\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[{\"identity\":\"7f4d267e-1d29-4641-bbc1-fa0928237fb5\",\"identifier\":\"10.13039/501100008809\",\"name\":\"University of Hail\",\"awardNumber\":\"This research was funded by Scientific Research Deanship at the University of Ha'il, Saudi Arabia through project number BA-25 001.\",\"order_by\":0}],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":true,\"hideJournal\":true,\"highlight\":\"\",\"institution\":\"University of Hail\",\"isAcceptedByJournal\":false,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true},\"keywords\":\"Gratitude, dispositional gratitude, Arabic Gratitude Questionnaire (GQ6), psychometric, reliability, validity, measurement invariance\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-7548318/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-7548318/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003ch2\\u003eBackground\\u003c/h2\\u003e\\u003cp\\u003eEmpirical evidence underscores gratitude as a protective factor for psychosocial health, highlighting the need for reliable measures. The Gratitude Questionnaire six-item form (GQ6) is widely used to assess dispositional gratitude; its Arabic version is lacking. This study aimed to translate the GQ6 into Arabic and evaluate its psychometric properties, including reliability, factor structure, discriminant validity, and measurement invariance across age and sex groups.\\u003c/p\\u003e\\u003ch2\\u003eMethods\\u003c/h2\\u003e\\u003cp\\u003eA sample of 536 university students (\\u003cem\\u003eM\\u003c/em\\u003e\\u003csub\\u003eage\\u003c/sub\\u003e = 23.01, \\u003cem\\u003eSD\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;4.84 years; 50% female) completed an online questionnaire containing the GQ6 and other psychological measures. Exploratory factor analysis (EFA) was conducted on half the sample to identify the underlying factor structure, followed by confirmatory factor analysis (CFA) to validate the model using fit indices including RMSEA, SRMR, CFI, and TLI. Rasch analysis provided detailed item-level insights, and measurement invariance was assessed using multi-group confirmatory factor analysis (MGCFA). Internal consistency was evaluated using Cronbach\\u0026rsquo;s α and McDonald\\u0026rsquo;s ω.\\u003c/p\\u003e\\u003ch2\\u003eResults\\u003c/h2\\u003e\\u003cp\\u003eInitial analyses showed low internal consistency for the Arabic GQ6, leading to the exclusion of two reverse-coded items. Subsequent analyses indicated that a one-factor model with four items (GQ4) exhibited good fit (CFI\\u0026thinsp;=\\u0026thinsp;0.96, TLI\\u0026thinsp;=\\u0026thinsp;0.89, RMSEA\\u0026thinsp;=\\u0026thinsp;0.19, SRMR\\u0026thinsp;=\\u0026thinsp;0.03), and good internal consistency (α and ω\\u0026thinsp;=\\u0026thinsp;0.85). The GQ4 showed moderate positive correlations with satisfaction with life, self-esteem, and overall well-being (\\u003cem\\u003er\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.48, 0.42, and 0.43, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;.001 respectively). Regarding measurement invariance, MGCFA supported configural and metric invariance across sex and age groups. Furthermore, Rasch analysis showed that the GQ4 Arabic version demonstrates consistent item performance and minimal variation in response patterns.\\u003c/p\\u003e\\u003ch2\\u003eConclusion\\u003c/h2\\u003e\\u003cp\\u003eOverall, the GQ4 Arabic version is a reliable and valid measure of dispositional gratitude among Arabic-speaking adults.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Evaluating dispositional gratitude among Saudi adults: Reliability, factor structure and measurement invariance of the Gratitude Questionnaire (GQ6)\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2025-09-09 04:09:50\",\"doi\":\"10.21203/rs.3.rs-7548318/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"b73aaf54-ec09-4136-84c4-b762a4d71026\",\"owner\":[],\"postedDate\":\"September 9th, 2025\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"posted\",\"subjectAreas\":[{\"id\":54288207,\"name\":\"Psychology\"}],\"tags\":[],\"updatedAt\":\"2025-09-09T04:09:50+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2025-09-09 04:09:50\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-7548318\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-7548318\",\"identity\":\"rs-7548318\",\"version\":[\"v1\"]},\"buildId\":\"8U1c8b4HqxoKbykW_rLl7\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}