Validation of an Italian Version of the Savoring Beliefs Inventory

Validation of an Italian Version of the Savoring Beliefs Inventory | 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 Validation of an Italian Version of the Savoring Beliefs Inventory Elisa Pancini, Daniela Villani, Stefania Balzarotti, Fred B. Bryant This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8871514/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 Savoring (i.e., the process of noticing, attending to, and appreciating positive experience) is a critical determinant of positive emotion, and the ability to savor is an important aspect of well-being. The present study reports the development and validation of an Italian-language version of Bryant’s ( 2003 ) Savoring Beliefs Inventory (SBI), which measures individual differences in savoring ability. A large sample of Italian young adults ( N = 553; age range = 17–31) completed the adapted SBI along with measures of life satisfaction, flourishing, happiness, mindfulness, and positive and negative affect. Confirmatory factor analyses were used to develop a four-factor measurement model consisting of separate intercorrelated factors reflecting the ability to savor future positive experiences through Anticipation, present positive experiences through Savoring the Moment, and past positive experiences through Reminiscence (along with a negative method factor on which negatively-worded items loaded). Analyses supported the reliability, convergent and discriminant validity, and gender invariance of the three SBI subscales. These results provide evidence that the Italian SBI is a valid and reliable measure of individuals’ beliefs about their ability to savor positive experience. Savoring savoring beliefs well-being positive psychology Italian adults Introduction How happy people feel in their daily lives depends not only on how often good things happen to them, but also on how they process these positive experiences. As de La Rochefoucauld ( 1796 ) observed, “happiness does not consist in things themselves but in the relish we have of them” (p. 51). This critical process of cultivating and relishing positive feelings has been termed savoring , or “the capacity to attend to, appreciate, and enhance the positive experiences in one’s life” (Bryant & Veroff, 2007 , p. xi). Confirming de la Rochefoucauld’s perceptive insight, daily diary research has found that the peak benefit of positive events is gained only through the act of savoring them (Jose, Lim, & Bryant, 2012 ). Savoring encompasses three interrelated temporal orientations—savoring future positive experiences before they occur (anticipation), savoring present positive experiences as they unfold (savoring the moment), and savoring past positive experiences after they end (reminiscence)—through which people create or regulate positive feelings in the here-and-now (Bryant, 1989 , 2003 ). To assess individual differences in the ability to savor positive experience, Bryant ( 2003 ) developed the Savoring Beliefs Inventory (SBI) using samples of young adults in the United States. As cross-cultural work on savoring has progressed, the original English SBI has been modified for use in numerous countries, including China, Egypt, France, Greece, Hungary, India, Iran, Japan, Korea, Mexico, Romania, Russia, Spain, Thailand, and Turkey (Bryant, 2021 ). The present study was designed to adapt the SBI for use in Italy. Savoring and Well-Being Extensive research supports the conclusion that savoring is a fundamental component of well-being. A higher capacity for savoring is linked to higher levels of well-being, including not only greater happiness, life satisfaction, and positive affect (Smith & Bryant, 2017 ), but also lower levels of depressive symptoms and negative affect (Ford et al., 2017 ). Moreover, applied studies have identified savoring as a mechanism that fosters resilience in the face of hardship (Sytine et al., 2019) and mitigates the detrimental effects of stress (Boelen, 2024 ). Experimental interventions that promote savoring skills enhancing psychological health (Smith & Hanni, 2019 ). Large-scale prospective studies have found that savoring ability reduces age-related declines in well-being (Stephens et al., 2025 ), and experience-sampling data confirms the beneficial effects of savoring throughout adulthood (Growney et al., 2025 ). Supplementing self-report measures, neuropsychological research has confirmed that the ability to savor helps people regulate their positive emotional experiences. For example, participants instructed to savor positive pictures exhibit stronger and more sustained picture-elicited neural responses, compared to those instructed simply to passively view the same pictures (Wilson & MacNamara, 2021 ). Furthermore, individuals with a greater ability to savor positive experiences show more stable neural responses to rewards over time, while those with a lower capacity experience a greater decrease in neural activity (Irvin et al., 2022). This evidence aligns with findings suggesting that difficulties savoring mental imagery may contribute to the development and maintenance of depression (Jackson et al., 2024 ). Measurement Models Underlying Prior Cross-Cultural Adaptations of the SBI The SBI was originally developed to assess individual differences in savoring ability based on a measurement model consisting of three forms of savoring (Anticipation, Savoring the Moment, and Reminiscence), along with two method factors reflecting positively- and negatively-worded items, respectively (Bryant, 2003 ). The SBI consists of 24 statements (8 for each temporal form of savoring), half reflecting an ability to savor, and half an inability to savor, and respondents use a seven-point scale to rate how true each statement is for them. Over time, researchers have used confirmatory factor analysis (CFA) to develop a variety of different measurement models in adapting the SBI for use in other cultures. Several of these cross-cultural adaptations have produced measurement models that are simpler than the original five-factor model and lack method factors. For example, in developing a Turkish SBI, Metin-Orta ( 2018 ) formulated a one-factor model; and in developing a German SBI, Limpächer and Hoyer ( 2026 ) constructed a tripartite model composed of the three temporal savoring factors. The measurement models developed for several other cross-cultural adaptations of the SBI have incorporated method factors in various forms to control for variation in responses due to item wording. For example, in creating a Japanese SBI, Kawakubo et al. ( 2019 ) replicated Bryant’s original (2003) five-factor model containing three temporal savoring factors and separate positive and negative method factors. In developing a Persian SBI, Aghaie et al. (2016) formulated an alternative five-factor structure consisting of a Savoring the Moment factor and four factors reflecting positively- or negatively-worded items assessing anticipation or reminiscence, respectively. In developing a Russian SBI, Titova et al. ( 2022 ) established a four-factor model consisting of the three temporal savoring dimensions (with one item cross-loading) and a negatively-worded method factor. Building on the work of these previous cross-cultural adaptations, the purpose of the present study was to create an Italian SBI, develop a measurement model for it (using CFA to test the unidimensional, three-, four-, and five-factor models used in previous studies), and assess the construct validity of the final model. Research Hypotheses Based on theory and research on the multidimensionality of savoring (Bryant, 2021 ), we hypothesized that a multi-factor measurement model would provide a better representation of responses to the Italian SBI than would a unidimensional model. Grounded in an underlying tripartite model, the number of factors was expected to range from three to five, based on the potential need to incorporate either one or two method factors in the model. Based on prior research, we also expected the savoring factors to be moderately intercorrelated (Bryant, 2021 ). Regarding the construct validity of the temporal savoring factors, based on prior theory and research on the centrality of momentary savoring (Bryant, 2021 ; Titova et al., 2022 ), we hypothesized that the ability to savor the moment would show stronger associations with criterion measures of well-being (satisfaction with life, flourishing, happiness), dispositional mindfulness, and dispositional emotion (positive and negative affect), compared to the ability to savor through anticipation or reminiscence. Finally, based on prior research on differences in levels of savoring ability across temporal forms of savoring (Bryant, 2003 ), and between males and females (Bryant, 2003 ; Bryant & Veroff, 2007 ), we hypothesized that composite subscale scores would be highest on the Reminiscence factor and that females would score higher than males on all three forms of savoring. Method Power Analysis We conducted prospective power and sensitivity analyses for each of the inferential statistical tests we used, including CFAs to establish a formal measurement model for the Italian SBI, and Pearson correlations as well as independent-samples and pairwise t -tests to assess the model’s construct validity. In determining target sample size for CFA, if none of our a priori models provided acceptable goodness-of-fit to the data, we also sought to obtain a final sample that would be large enough to support data-driven model modifications in which we would randomly split the full sample in half, using one subsample to search for theoretically relevant model respecifications that improved model fit, and the other subsample to assess the cross-sample generalizability of the modified model. Given practical limitations, we aimed for a sample size of ≥ 500, that would, if necessary, provide random subsamples of 250 for model development and model confirmation, respectively. Following MacCallum, Browne, and Sugawara’s ( 1996 ) procedure for determining power to detect model misfit in covariance structure analysis, sample sizes of 500 and 250 both provide > 99% power to detect RMSEA > .08 versus a close-fit model for our largest hypothesized CFA model (with df = 224). Our final sample consisted of 558 participants, 553 of whom had complete data for the 24 SBI items. We used Power Analysis and Sample Size (PASS; Hintze, 2023 ) software to conduct sensitivity power analyses for inferential tests of the SBI’s convergent and discriminant validity. To assess patterns of relationship between composite SBI subscales and criterion measures, we administered different sets of criterion measures along with the SBI to different subgroups of these participants ( N s ranging from 78 to 413). The minimum detectable correlation at two-tailed p < .05 with 80% power is: (a) .31 with N = 78, and (b) .14 with N = 413. To assess the ability of the SBI to discriminate males ( N = 166) and females ( N = 382) based on SBI subscale and total scores, we used independent-samples t tests, which provided 80% power to detect a minimum effect size of d = 0.34 at two-tailed p < .05. To assess differences in levels of savoring beliefs across the three SBI subscales within participants, we used pairwise t -tests, which provided 80% power to detect a minimum effect size of d = 0.12 at two-tailed p < .05. Participants The final sample consisted of 553 participants (166 males, 382 females, and 5 who did not report gender) with a mean age of 23.58 years ( SD = 2.90; range = 17–31). The observed gender imbalance is consistent with previous SBI validation studies conducted in other languages, which also employed convenience and snowball sampling methods (e.g., Aghaie et al., 2017 ; Golay et al., 2018 ; Metin-Orta, 2018 ). The educational level of the sample varied widely, with 42% having completed their education in secondary or high school, 34% having a bachelor’s degree, and 22% having a master’s or doctoral degree (2% did not report their education). Concerning marital status, 45% were single, 45% were in a relationship with a partner, and 10% were either married or cohabiting with a partner. Concerning employment status, 33% were students, 33% were employed, 12% were students who were also employed, 4% were unemployed, and 4% described their employment as “other.” Procedure This study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki (Goodyear et al., 2007 ) and approved by the Ethics Committee for Research in Psychology of the Department of Psychology of xxx (protocol number: 119_24). All participants signed an informed consent form prior to participation. Participants responded voluntarily and anonymously, and no financial or other compensation was provided. Participants were recruited using a snowball sampling procedure. The study invitation was initially distributed to undergraduate students, in line with previous validation studies of the SBI (Aghaie et al., 2017 ; Golay et al., 2018 ; Metin-Orta, 2018 ), who were invited to complete the survey and to further share the invitation within their personal networks. Data were collected via online questionnaires administered using Qualtrics. After completing the SBI, Qualtrics was used to randomly assign participants to different subsets of criterion measures. As a result, not all participants completed all criterion measures. This random assignment procedure was implemented to minimize selection bias while allowing the assessment of multiple aspects of construct validity without overburdening participants. Consequently, different subgroups of participants completed different combinations of criterion measures, depending on the random allocation. The present study was conducted within the context of a broader research project aimed at investigating psychological well-being in young adults. Measures Savoring Beliefs Inventory (SBI). The SBI is a self-report instrument developed by Bryant ( 2003 ) to assess individuals’ beliefs about savoring. It consists of 24 items rated on a 7-point Likert scale, ranging from 1 (“strongly disagree”) to 7 (“strongly agree”). The SBI comprises three subscales whose scores can also be summed to obtain a total score: (1) the Anticipation subscale, which measures perceived ability to savor experiences through anticipation; (2) the Present Moment subscale, which assesses perceived ability to savor experiences as they occur; and (3) the Reminiscing subscale, which evaluates perceived ability to savor past experiences. The original English version of the SBI was independently translated into Italian by three bilingual authors, SB, DV, and EP, and the translations were compared and discussed until full agreement was reached. In the present study, the final versions of the Italian SBI Anticipation, Present Moment, and Reminiscence subscales showed acceptable to strong internal consistency reliability coefficients (Cronbach’s α = .72, .88, and .77, respectively), as did the SBI Total score (Cronbach’s α = .87). Satisfaction with Life (SWLS). This scale was developed by Diener and colleagues ( 1985 ; Italian version: Di Fabio & Busoni, 2009 ) to assess life satisfaction. It consists of five items rated on a 7-point Likert scale, ranging from 1 (“strongly disagree”) to 7 (“strongly agree”). Higher scores indicate greater satisfaction with life. Evidence supports the construct validity of the Italian version of the SWLS as a measure of life satisfaction (Di Fabio & Busoni, 2009 ; Di Fabio & Gori, 2020 ). In the present study, the Italian SWLS showed good internal consistency reliability (Cronbach’s α = .85). Flourishing Scale (FS). This scale, developed by Diener (2009; Italian version: Di Fabio, 2016 ), aims to assess components of psychological well-being, including relationships, self-esteem, life purpose, and optimism. It consists of eight positively-worded items, with responses rated on a 7-point Likert scale ranging from 1 (“strongly disagree”) to 7 (“strongly agree”). Higher scores indicate greater flourishing. The Italian FS shows evidence of construct validity as a measure of flourishing (Di Fabio, 2016 ; Giuntoli et al., 2017 ). In the present study, the Italian FS showed good internal consistency reliability (Cronbach’s α = .85). Subjective Happiness Scale (SHS). This instrument was developed by Lyubomirsky and Lepper ( 1999 ; Italian validation: Iani et al., 2014 ) to assess global subjective happiness through statements that ask participants to evaluate themselves or compare themselves to others. It consists of four items, rated on a 7-point Likert scale ranging from 1 (“not at all”) to 7 (“very much”). The total score is calculated as the mean of the four items (with the fourth item reverse-scored), resulting in possible scores ranging from 1 to 7, where higher scores indicate greater happiness. Iani et al. ( 2014 ) presented evidence supporting the construct validity of the Italian SHS as a measure of happiness. In the present study, the Italian SHS showed good internal consistency reliability (Cronbach’s α = .84). Mindful Attention Awareness Scale (MAAS). This instrument is designed to assess individual differences in present-moment awareness during which one consciously attends to what is happening (Brown & Ryan, 2003 ; Italian version: Veneziani & Voci, 2015 ). The scale consists of 15 items, rated on a 7-point Likert scale ranging from 1 (“almost always”) to 7 (“almost never”). Veneziani and Voci ( 2015 ) presented evidence supporting the structural and construct validity of the Italian MAAS as a measure of mindfulness. In the present study, the Italian MAAS showed good internal consistency reliability (Cronbach’s α = .84). Positive and Negative Affect Scale (PANAS). This scale was developed by Watson, Clark, and Tellegen ( 1988 ; Italian validation: Terracciano, McCrae, & Costa, 2003) to assess individual differences in positive and negative affect. The scale consists of 20 items, 10 assessing positive affect and 10 assessing negative affect, rated on a 5-point Likert scale ranging from 1 (“very slightly or not at all”) to 5 (“extremely”). Scores for each subscale are calculated by summing the corresponding items, with higher scores indicating greater levels of positive or negative affect, respectively. Terracciano et al. (2003) presented evidence supporting the structural and construct validity of the Italian PANAS as a measure of state positive and negative affect. In the present study, the Italian PANAS showed strong internal consistency reliability for both its positive and negative scales (Cronbach’s α = .87 and .89, respectively). Demographic Questions. These questions were designed to collect demographic information about the sample, including gender, age, educational level, marital status, and employment status. Results Overview Data analyses unfolded in three stages. First, we computed descriptive statistics to examine the distributional properties of the Italian SBI items and the validational criterion measures. Second, we used CFA to assess the goodness-of-fit of alternative models for the Italian SBI data and develop a formal measurement model for the instrument. Third, to assess construct validity, we constructed composite measures for the SBI subscales and criterion variables and used: (a) correlation and regression analyses to test hypotheses about the convergent and discriminant validity of SBI subscales in relation to the criterion measures; (b) pairwise t -tests to test hypotheses about within-person differences in levels of savoring beliefs across subscales; and (c) independent samples t -tests to test hypotheses about gender differences in levels of savoring ability across subscales. Descriptive Statistics Examining scores for the 24 SBI items, participants scored much higher on positively -worded items (mean = 4.82) than on negatively -worded items (mean = 3.18), pairwise t (552) = 27.18, p < .0001, Cohen’s d = 1.16, indicating participants endorsed items reflecting the presence of savoring ability more strongly than they endorsed items reflecting the absence of savoring ability. In addition, participants scored slightly higher on positively -worded items (mean = 4.96) than on reverse-scored negatively -worded items (mean = 4.82), pairwise t (552) = 4.23, p < .0001, Cohen’s d = 0.19, indicating a small but significant tendency for respondents to endorse positively-worded items more strongly than they rejected negatively-worded items. Positively -worded SBI items had small negative skewness (mean = -0.57), while negatively -worded items had small positive skewness (mean = 0.50), reflecting more frequent higher and lower responses, respectively. All SBI items had slight negative kurtosis (mean = -0.22), suggesting flatter, somewhat platykurtic distributions. Based on Lei and Lomax ( 2005 ), absolute skewness and kurtosis values below 1.0 indicate slight nonnormality. Developing a Measurement Model for the Italian SBI Model Estimation Based on prior theory and research, we used maximum-likelihood CFA via LISREL 8.80 (Jöreskog & Sörbom, 2006 ) to assess the goodness-of-fit of four different a priori measurement models for the Italian SBI: (a) a unidimensional one-factor model (Bryant, 2003 ) consisting of a single underlying general factor (Model 1); (b) a three-factor model consisting of temporal factors reflecting Anticipation, Savoring the Moment, and Reminiscence (Model 2); (c) a five-factor model (Bryant, 2003 ) consisting of the three temporal factors and two method factors (Positively-worded items and Negatively-worded items) (Model 3); and (d) a four-factor model (Titova et al, 2022 ) consisting of the three temporal factors and one method factor (Negatively-worded items) (Model 4). We included this last model based on the possibility that the five-factor model might well produce an ill-conditioned CFA solution, as often arises with multiple method factors in the same model (Garrido et al., 2025 ; Marsh, 1989 ). Model 2 ( three factors) constrained each item to load only on the savoring factor it was intended to reflect. Model 3 ( five factors) specified that each item loaded on the savoring factor it was intended to reflect and freed cross-loadings both for positively-worded items on a positive method and for negatively-worded items on a negative method factor. Model 4 ( four factors) specified that each item loaded on the savoring factor it was intended to reflect and freed cross-loadings only for negatively-worded items on a negative method factor. In all CFA models, we fixed the variance of each factor to 1.0, to define the units of variance for the latent variables, and estimated the unique error variance of each of item without correlated measurement errors. In all multi-factor CFA models, the three savoring factors were allowed to intercorrelate. In the five-factor model, the positive and negative method factors were allowed to intercorrelate, but were constrained to be uncorrelated with the three savoring factors. In the four-factor model, the negative method factor was constrained to be uncorrelated with the three savoring factors. To evaluate model goodness-of-fit, we used two measures of absolute fit—the root mean square error of approximation (RMSEA) and standardized root mean square residual (SRMR)—and two measures of relative fit—the comparative fit index (CFI) and the non-normed fit index (NNFI). Better model fit is indicated by lower values of absolute fit measures and higher values of relative fit measures. In assessing goodness-of-fit, we considered RMSEA < .08 (Browne & Cudeck, 1993 ), SRMR .90 and NNFI > .90 (Bentler & Bonett, 1990) as representing acceptable model fit. To make the loadings of negatively-worded items more apparent in the factor solutions, we did not reverse-score the 12 negatively-anchored SBI items before conducting CFA (although we reverse-scored negatively-worded SBI items in computing unit-weighted composite measures to assess construct validity). We also used the Akaike information criterion (AIC; Akaike, 1973 ) to compare the goodness-of-fit of CFA models. AIC balances model fit with model complexity, by adding a penalty for the number of estimated parameters to help guard against overfitting. Lower AIC scores reflect models that fit the data better without being overly complex. Table 2 presents goodness-of-fit statistics for the four a priori CFA models of the Italian SBI. As found in previous studies in the U.S. (Bryant, 2003 ), France (Golay et al., 2018 ), Japan (Kawakubo et al., 2019 , and Russia (Titova et al., 2022 ), the one-factor model (Model 1) fit the Italian SBI data poorly (RMSEA and SRMR > .10, fit indices < .81). Further supporting the multidimensionality of Italian savoring beliefs, the three-factor model (Model 2) provided a significant improvement in fit relative to the one-factor model, Δχ 2 (3) = 809.83, p < .0001, Cohen’s w = 1.21. However, also replicating prior cross-cultural adaptations of the SBI (Bryant, 2003 ; Kawakubo et al., 2019 ; Titova et al., 2022 ), the three-factor model left room for improvement in its goodness-of-fit (RMSEA and SRMR > .08, fit indices < .90). As seen in Table 2 , the five-factor model (Model 3) provided a reasonable fit to the SBI data (RMSEA and SRMR .93). However, inspection of the CFA solution revealed that having both positive and negative method factors in the model produced anomalous parameter estimates—specifically, the Anticipation factor had nonsignificant correlations with both Savoring the Moment ( r = 0.0) and Reminiscence ( r = .04). The absence of significant correlations among the Savoring factors in this model is particularly problematic, given that Anticipation correlates .45 with Savoring the Moment and .61 with Reminiscence in the three-factor model (Model 2). Evidently, the method factors have absorbed substantive variance from the savoring factors (see Garrido et al., 2025 ). As noted earlier, such discrepancies indicate an ill-conditioned solution that can result when specifying multiple method factors. Accordingly, we assessed the goodness-of-fit of a more parsimonious (four factor) version of the five-factor model (Model 4) that omitted the Positive method factor and used only the Negative method factor, as previously developed by Titova et al. ( 2022 ) in adapting the Russian SBI. Along these lines, simulation research indicates that in most cases, modeling a single “negative wording” factor is sufficient to achieve the best recovery of underlying factor structure (Garrido et al., 2025 ). As hypothesized, this four-factor model fit the data significantly better than the three-factor model, Δχ 2 (15) = 367.57, p < .0001, w = 0.82. Moreover, unlike the five-factor model, the correlations among the SBI factors in the four-factor model (i.e., Anticipation and Savoring the Moment, r = .46; Anticipation and Reminiscence, r = .60; Savoring the Moment and Reminiscence, r = .49) were highly consistent with those found in the three-factor model. Nevertheless, as was the case for the three-factor model, the four-factor model’s RMSEA value (i.e., .082) exceeded .08, making it an unacceptable measurement model (see Table 2 ). Model Respecification Following Titova et al. ( 2022 ), we sought to improve the goodness-of-fit of the four-factor model (Model 4) by adding a single cross-loading to the a priori model. Before proceeding, we took steps to avoid capitalizing on chance, given that adding estimated parameters based on post hoc inspection of results is prone to capitalize on chance (MacCallum et al., 1992 ). Although it would be ideal to have an independent sample for cross-validation, we adopted a commonly-used alternative method to increase the expected cross-sample generalizability of model modifications by randomly splitting our sample in half and using (a) one subsample (i.e., the Development sample N = 276) to explore ways to improve model fit a posteriori and (b) the other subsample (i.e., the Confirmation sample; N = 277) to test the replicability of respecified models a priori (see Brockway et al., 2002 ). We began the specification search by re-estimating the four-factor model using the data of the Development Sample and examining the modification index (MI), also known as the Lagrange multiplier, for each parameter that was fixed to zero in the model. Each MI estimates the reduction in the model’s goodness-of-fit χ 2 value (with df = 1) that would be expected if a particular fixed parameter were to be freely estimated in the model (MI values > 3.84 represent p < .05). The largest MI in the four-factor model (MI = 47.17) was the cross-loading of SBI item 12—a negatively-worded item intended to reflect Reminiscence (i.e., “When I reminisce about pleasant memories, I often start to feel sad or disappointed”)—on the Savoring the Moment factor. We thus freed the cross-loading of SBI item 12 on the Savoring the Moment factor, so item 12 loaded on both Reminiscence and Savoring the Moment, and estimated this respecified model (Model 5). As expected, this cross-loading was statistically significant in the modified four-factor model (completely standardized loading = − .50; 25% variance explained in the item, p < .0001). As seen in Table 2 , the modified four-factor model fit the SBI data significantly better than the original four-factor model, Δχ 2 (1) = 57.94, p < .0001, w = 0.21, and provided a reasonable measurement model for the Italian SBI (RMSEA and SRMR .92). However, inspection of the CFA solution for Model 5 revealed that when allowing SBI item 12 to cross-load on the Savoring the Moment factor, the completely standardized loading of this item on the Reminiscence factor was dramatically reduced from − .35 in Model 4 (i.e., 12% variance explained), z = 5.81, p < .0001, to a nonsignificant value of − .08 in Model 5 (i.e., < 1% variance explained), z = 1.34, p = .18. Clearly, scoring low on negatively-worded item 12 (i.e., rejecting the notion that one often gets sad or disappointed when reminiscing about pleasant memories) is more diagnostic of the ability to savor the moment than of the ability to savor past positive memories in the Italian data. Based on the fact that the loading of SBI item 12 on its intended Reminiscence factor disappeared when allowing item 12 also to load on the Savoring the Moment factor in Model 5, we decided to estimate a final version of the four-factor model that constrained SBI item 12 to load only on the Savoring the Moment factor (Model 6). As seen in Table 2 , the resulting CFA model demonstrated comparable fit to Model 5, Δχ 2 (1, N = 276) = 1.69, p = .19, w = 0.08 (RMSEA = .078, SRMR = .076, CFI = .92, NNFI = .91), but offered a more parsimonious structure and a lower AIC.(Model 6 also avoids inflating the correlation between the Savoring the Moment and Reminiscence composite subscales as a result of the item cross-loading.) The standardized loading of SBI item 12 on Savoring the Moment was − .54, z = 9.44, p < .0001. Thus, when forcing item 12 to load on only one or the other factor, more than twice as much of its variance reflects present -focused savoring ability (29% in Model 6), as opposed to past -focused savoring ability (12% in Model 4). Confirming the cross-sample generalizability of Model 6, imposing the final four-factor model on the data of the Confirmation sample ( N = 277) produced goodness-of-fit statistics that were comparable to those of the Development sample. As a final step in measurement modeling, imposing this final four-factor model on the data of the full sample ( N = 553) likewise produced acceptable model fit (see Table 2 ). Note that the final four-factor model (Model 6) has the same df as the initial four-factor model (Model 4), but provides a superior goodness-of-fit in terms of a lower χ 2 (951.51 vs. 1047.39), lower RMSEA (.076 vs. .082), lower SRMR (.073 vs. .077), higher CFI (.93 vs. .92), higher NNFI (.92 vs. .91), and lower AIC (1119.30 vs. 1245.32). Thus, we have chosen the final four-factor model as the measurement model for the Italian SBI. Analysis of Estimated Parameters in the Final Four-Factor Model Table 3 displays the completely standardized factor loadings (i.e., when standardizing factors as well as items), squared multiple correlations for items (i.e., the proportion of variance that the model explains in each item), and factor intercorrelations from the final four-factor CFA model for the Italian SBI. Standardized absolute values of factor loadings of the SBI items on their intended savoring factors were moderate overall ( M = .57, Mdn = .55, range = .23–.80) and were somewhat larger on the Savoring the Moment factor ( M = .65, 95% CI [.56, .75], range = .44–.80) than on the Anticipation ( M = .49, 95% CI [.34, .64], range = .23–.75) and Reminiscence ( M = .57, 95% CI [.44, .70], range = .39–.73) factors. On average, the final four-factor CFA model explained 40% of the variance in each SBI item ( R 2 range = .07–.68). Squaring the standardized loadings on the savoring factors, R 2 values were appreciably larger for items reflecting the Savoring the Moment factor ( M = .52, 95% CI [.38, .66]), compared to items reflecting the Anticipation ( M = .32, 95% CI [.18-.46]) or Reminiscence ( M = .37, 95% CI [.27, .46]) factors. Following Worthington and Whittaker’s ( 2006 ) guidelines for scale development, three of the 24 SBI items (i.e., 1, 2, and 22)—each designed to tap Anticipation—had factor loadings < |.40, suggesting some limitations in their ability to adequately reflect future-focused savoring beliefs within the Italian sample. Consistent with the notion that negatively-anchored items are potentially confusing to respondents (Garrido et al., 2025 ; Weijters & Baumgartner, 2012 ), negatively -worded items had somewhat lower absolute standardized loadings ( M = − .52, 95% CI [-.42, − .62], mean R 2 = .27) on their respective savoring factors, compared to positively -worded items ( M = .63, 95% CI [.54, .72], mean R 2 = .40), even after controlling for the effects of the negative method factor. Standardized loadings of the negatively-worded items on the negative method factor were moderate in size ( M = − .34, Mdn = .36, range = − .13 – − .46), indicating that on average roughly 12% of the variance in responses to the negatively-worded items was method-specific (i.e., mean squared standardized loading on method factor = .12). As hypothesized, the three savoring factors were moderately intercorrelated ( r s = .42–.59; see Table 3 ). Anticipation and Savoring the Moment shared 20% of their variance (i.e., .45 2 ); Anticipation and Reminiscence shared 35% of their variance (i.e., .59 2 ); and Reminiscence and Savoring the Moment shared 18% of their variance (i.e., .42 2 ). Thus, 65–82% of the variance in each factor is independent of the variance of the other two savoring factors, supporting the distinctiveness of the three temporal forms of savoring ability as separate constructs. Assessing the Construct Validity of the Italian SBI In the final stage of the data analysis, we tested a priori hypotheses designed to evaluate the convergent and discriminant validity of the three savoring factors in the Italian SBI. First, we used correlational analyses to: (a) assess the convergent and discriminant validity of SBI total score and subscale scores in relation to the six criterion measures; and (b) test the hypothesis that the Savoring the Moment subscale would correlate more strongly than the Anticipation and Reminiscence subscales with the six criterion measures. Second, we used multiple regression analyses to test the hypotheses that: (a) Savoring the Moment would show stronger unique relationships with the criterion measures than the Anticipation and Reminiscence subscales when controlling for the effects of the other two subscales; and (b) each SBI subscale would show a different pattern of relationships with the three savoring factors, when predicting scores on individual criterion measures. Finally, we tested for hypothesized differences in levels of savoring ability across the three SBI subscales within individuals and between men and women. Constructing Composite Measures. In assessing the convergent and discriminant validity of the Italian SBI, we first reverse-scored the negatively-worded SBI items and then computed mean scores for unit-weighted composite measures of: (a) the Anticipation, Savoring the Moment, and Reminiscence subscales, and SBI Total score; and (b) the criterion measures of life satisfaction, flourishing, happiness, mindfulness, positive affect, and negative affect. We constructed two versions of the Savoring the Moment and Reminiscence subscales: an 8-item original version based on Bryant ( 2003 ), and an Italian version (9 items for Savoring the Moment, 7 for Reminiscence) based on the final four-factor CFA model. The correlation between the original and Italian versions was .99 for Savoring the Moment (94% shared variance) and .97 (98% shared variance) for Reminiscing. We used only the Italian versions of the SBI subscales in our validity analyses. Table 1 displays descriptive statistics (means and standard deviations), internal consistency reliability coefficients (Cronbach’s αs), intercorrelations, and pairwise sample sizes, for these composite measures. As seen in Table 1 , internal consistency reliabilities ranged from acceptable (for Anticipation, α = .72; for Reminiscence, α = .77) to good (for Savoring the Moment, α = .87; for Total score, α = .87); reliabilities for the criterion measures were good and ranged from .84 for happiness and mindfulness to .89 for negative affect. Thus, following Aghaie et al. (2016), all Cronbach’s alphas were in the discrete-good range. Correlational Analyses . We first examined correlations to evaluate the convergent and discriminant validity of the three SBI subscales. Supporting convergent validity, all three SBI subscales correlated positively with life satisfaction, flourishing, happiness, and mindfulness. In addition, the Anticipation and Savoring the Moment subscales correlated positively with positive affect; and the Savoring the Moment subscale correlated negatively with negative affect. We assessed the discriminant validity of the Savoring the Moment subscale, relative to the Anticipation and Reminiscence subscales, by testing the hypothesis that the Savoring the Moment subscale would correlate more strongly than the other two SBI subscales with all six criterion measures. To do this, we first computed a 95% confidence interval (CI) for the correlation between each SBI subscale and each criterion measure (see rows 1–3 of Table 1 ). For each criterion measure, we then determined whether or not (a) the 95% CI of its correlation with the Savoring the Moment subscale overlapped with (b) the 95% CIs of its correlations with each of the other two SBI subscales. Correlations with nonoverlapping 95% CIs were significantly different at p < .05 (see Tryon, 2001 ). Supporting discriminant validity, the Savoring the Moment subscale correlated more strongly with life satisfaction, flourishing, happiness, and mindfulness than did the Anticipation or Reminiscence subscales ( p s < .05). Contrary to our hypothesis, the 95% CIs of the correlations of all three SBI subscales with positive affect had overlapping 95% CIs, as did the correlations of all three SBI subscales with negative affect, indicating a lack of discriminant validity for the SBI subscales. (We note that the correlations with positive and negative affect had much smaller sample sizes, compared to correlations with other criterion measures, making their 95% CIs much wider and reducing power to detect nonoverlapping CIs.) Multiple Regression Analyses. In a second set of validity analyses, we used multiple regression to examine the independent relationships of each SBI subscale with each criterion measure when controlling for the associations of the other two SBI subscales (see Table 4 ). To assess multicollinearity in these analyses, we examined each predictor’s variance inflation factor (VIF). Following Neter, Wasserman, and Kutner ( 1990 ), multicollinearity was not as issue, given that the VIFs for all predictors in each analysis were well below 10 (range = 1.20–1.36). As hypothesized, when controlling for the effects of the other two subscales, the Savoring the Moment subscale showed the strongest and most consistent unique relationships with the six criterion measures, compared to the Anticipation and Reminiscence subscales. Further supporting the discriminant validity of the three SBI subscales, each subscale showed a different pattern of relationships with the six criterion measures when controlling for the other two subscales (see Table 4 ). Specifically, Savoring the Moment uniquely predicted all six criterion measures, Anticipation uniquely predicted only Flourishing, and Reminiscence had no unique relationships with the criterion measures. The absence of unique associations for Reminiscence suggests that it does not provide predictive information over and above the other SBI subscales for this set of validational measures. Analyses of Within-Person Differences in Savoring Ability across Subscales. As an additional test of the discriminant validity of the Italian SBI, we examined hypothesized differences in levels of savoring beliefs within individuals. In assessing the discriminant validity of the original SBI factors, Bryant ( 2003 ) found that scores on the Reminiscing subscale were significantly higher than on the other two temporal subscales, and scores on the Savoring the Moment subscale were significantly higher than were scores on the Anticipating subscale. Confirming hypotheses, pairwise t -tests using the present data revealed that subscale scores on Reminiscence were higher than on both Savoring the Moment, t (552) = 13.12, p < .0001, d = .56, and Anticipation, t (552) = 7.25, p < .0001, d = .31, subscales. Contrary to expectation, however, scores on the Savoring the Moment subscale were lower than on the Anticipation subscale, t (552) = 7.59, p < .0001, d = .32. Thus, whereas the original American sample felt more capable of savoring the moment than savoring through anticipation, the opposite was true for the Italian sample. Nevertheless, these within-person differences in levels of savoring ability across the three temporal forms of savoring support the discriminant validity of the Italian SBI. Assessing Gender Invariance of the Final-Four Factor Model The issue of measurement invariance concerns whether an instrument, such as the SBI, functions comparably across different groups of people. Although composite scores are often used to compare levels of responses across different groups, these analyses of mean differences assume that the scores being contrasted are in fact comparable across groups. Three types of measurement invariance are relevant and can be assessed using nested multigroup CFA in a series of progressively more restrictive hypotheses about group equality in the pattern (configural invariance) and magnitude (metric invariance) of factor loadings, and in the magnitude of item intercepts (scalar invariance) (see Vandenberg & Lance, 2000 ). Configural invariance exists if the same model provides an acceptable fit to the data of different groups. Assuming that configural invariance holds, then metric invariance exists if constraining each item’s factor loading to be equal across groups does not worsen model fit, compared to separately estimating loadings for each group. A lack of metric invariance would indicate that one or more factors have a different meaning across groups, preventing valid between-group comparisons of subscale scores for these noninvariant factors. Assuming that metric invariance holds, then scalar invariance exists if constraining each item’s intercept to be equal across groups (when fixing factor means to zero) does not worsen model fit, compared to estimating intercepts separately for each group. Differences in item intercepts when fixing factor means to zero in each group would reflect instances of differential item functioning (McDonald, 1999 ) that indicate these items produce different mean responses for members of different groups who have the same value on the underlying factor. In this case, group differences in observed subscale scores would reflect not only true differences in the underlying latent factor but also group-specific biases in how people use the measurement scale. Because we wanted to examine potential gender differences in levels of savoring ability using the Italian SBI, we evaluated the gender invariance of loadings on the three savoring factors (but not loadings on the negative method factor). In testing metric and scalar invariance, we assessed the size of the difference in CFI values across nested models, with difference in the CFIs (ΔCFI) ≤ .01 considered evidence of measurement invariance (Cheung & Rensvold, 1999 ). Separate single-group CFAs demonstrated that the final four-factor model provided an acceptable goodness-of-fit for both the male and female data (configural invariance). In addition, multigroup CFA tests of gender invariance revealed that males and females had comparable loadings on all three savoring factors, ΔCFI = .0005, and comparable intercepts for all 24 items, ΔCFI = .0065 (i.e., changes in model CFI across nested models fell below the .01 threshold for inferring noninvariance). These results indicate that the items in the final four-factor model function comparably for men and women, thus enabling meaningful comparisons of subscale scores between groups. Assessing Gender Differences in Savoring Beliefs Both the original SBI (Bryant, 2003 ) as well as cross-cultural adaptations of the SBI in Hungary (Nagy et al, 2022 ), Japan (Kawakubo et al., 2019 ), and Korea (Kim & Bryant, 2017 ) produced subscales or global scales on which females reported higher mean scores than males. Based on these findings and on the notion that women are typically more expressive of their feelings and tend to have a richer inner life than men (Bryant & Veroff, 2007 ), we hypothesized than females would score higher than males on the Italian SBI subscales and total score. Partially supporting our hypothesis, females had higher scores than males on: (a) the Anticipation subscale (females: M = 5.00, SD = 0.86; males: M = 4.79, SD = 0.88), t (546) = 2.64, p < .01, d = 0.25; (b) the Reminiscence subscale (females: M = 5.37, SD = 0.83; males: M = 4.94, SD = 0.98), t (547) = 5.28, p < .0001, d = 0.49; and (c) SBI total score , (females: M = 4.95, SD = 0.75; males: M = 4.76, SD = 0.77), t (546) = 2.70, p < .01, d = 0.25. But there was no gender difference on the Savoring the Moment subscale (females: M = 4.95, SD = 0.75; males: M = 4.76, SD = 0.77), t (546) = 0.15, p = .88, d = 0.01. This pattern of results provides further support for the discriminant validity of the Italian SBI. Discussion The present study adds to existing literature on positive emotion regulation by developing an Italian version of the Savoring Beliefs Inventory (SBI) and examining its psychometric properties in a sample of Italian young adults. Savoring has been defined as the ability to attend to, appreciate, and increase the positive experiences that occur in one’s life (Bryant & Veroff, 2007 ) and several studies have provided evidence that this capacity represents a critical factor for the individual’s well-being (e.g., Boelen, 2024 ; Ford et al., 2017 ; Growney et al., 2025 ; Smith & Bryant, 2017 ). While the SBI was originally developed in the United States as an instrument to measure individual differences in the (self-reported) ability to savor positive experiences (Bryant, 2003 ), a growing body of research has recently developed cross-cultural adaptations of the original English scale in numerous languages, including for instance French (Golay et al., 2018 ), Japanese (Kawakubo et al., 2019 ), and Russian (Titova et al., 2022 ). To the best of our knowledge, however, there is no evidence of the validity and reliability of the SBI in the Italian context. To achieve our research goals, we first used confirmatory factor analysis (CFA) to assess the goodness-of-fit of four alternative, a priori measurement models for the Italian SBI data. According to the theoretical conceptualization of savoring (Bryant, 2003 ), the construct is multidimensional in its nature, comprising three interrelated temporal orientations (i.e., anticipation, savoring the moment, and reminiscence) through which people regulate their positive emotions in a given moment. Consistent with theory and with most studies that have tested the factorial structure of the SBI (Aghaie et al., 2016; Golay et al., 2018 ; Kawakubo et al., 2019 ; Limpächer & Hoyer, 2026 ; Titova et al., 2022 ; for an exception see Metin-Orta, 2018 ), our results revealed that the three-factor measurement model provided a better representation of responses to the Italian SBI than a unidimensional model. These results suggest that Italian respondents make separate self-evaluations of their ability to savor positive experience concerning the three assumed temporal orientations. Nonetheless, as found in previous studies (Bryant, 2003 ; Kawakubo et al., 2019 ; Limpächer & Hoyer, 2026 ), we also observed that the five-factor solution provided a better fit to the Italian data than the three-factor one, supporting the need to include separate method factors in the measurement model that reflect the variation in responses due to either positive or negative item wording. In this regard, several studies using different instruments have repeatedly shown that using both positively- and negatively-worded items in a questionnaire can introduce significant method effects and that this source of variance has to be accounted for to avoid inaccurate conclusions about the validity and reliability of a scale (e.g., Garrido et al., 2025 ; Lindwall et al., 2012 ; Zeng et al., 2020 ). Because the inspection of the five-factor solution (i.e., Anticipation, Savoring the Moment, and Reminiscence, plus a Positive and Negative Method factor) revealed anomalous parameter estimates (i.e., null correlations among the theoretical factors), in subsequent steps of analysis, we tested a more parsimonious, four-factor model that included the Negative Method factor only (Titova et al., 2022 ). The results showed that this model provided better fit compared to the others, suggesting stronger support for the method effect of negatively-worded items compared to the effect associated with positively-worded items. In other words, participants exhibited a systematic response style in which they differentiated less among temporal orientations when answering negatively-worded items, producing more uniform responses across the three temporal dimensions of savoring for these items. Although some research has shown that negatively-worded items often create stronger method effects than positively-worded items (DiStefano & Motl, 2006 ), it is generally agreed that the direction in which valence of wording impacts the strengths of method effects can depend on a number of variables, such as the specific scale, population, and cultural context (Lindwall et al., 2012 ; Zeng et al., 2020 ). Of note, however, in our results, standardized factor loadings on the Negative Method factor were overall moderate in size and a small proportion (around 12%) of the variance in responses to the negatively-worded items was method-specific. Although the four-factor solution appeared to provide the best fit to the Italian data, we observed that SBI item 12 ( feeling disappointed when reminiscing ) cross loaded on the Savoring the Moment factor. Adequate fit was achieved after the model was respecified and item 12 was allowed to load on Savoring the Moment rather than on its intended Reminiscence factor. Thus, it seems that in the Italian sample, experiencing negative emotions such as sadness and disappointment when reminiscing about pleasant memories is more indicative of a low capacity for present -focused savoring than an inability to engage in past -focused savoring. Although recalling pleasant autobiographical memories is a well-established method for boosting positive affect (Bryant et al., 2005 ; Joseph et al., 2020 ), recent research has shown that reminiscing about good times that are gone and cannot be repeated may lead to the experience of mixed emotions such as happiness and sadness because of a sense of “no-longer-having” those good times in the present (Larsen et al., 2021 ). Likewise, it has been suggested that making unfavorable comparisons between past happy memories and current life circumstances may decrease rather than enhance positive affect (Nelis et al., 2015 ). Along this line of reasoning, SBI item 12 may reflect a form of nostalgic rumination that can hinder the ability to savor the present moment. Specifically, an excessive focus on pleasant past positive events (i.e., “how great things were”) can induce disappointment or a sense of loss, causing an individual to overlook and undervalue current positive experiences. Of note, other validation studies have found low (<. |40|) factor loadings for this item: − .35 (Bryant, 2003 ), − .38 (Golay et al., 2018 ), − .26 (Titova et al., 2022 ). The finding that not feeling sad or disappointed when reminiscing has more to do with present -focused savoring ability than past -focused savoring ability is consistent with the notion that enjoying the process of sharing pleasant memories with others is closely related to savoring the moment in Italian culture. Along these lines, Italian culture has traditionally emphasized strong social connections and shared celebration, with Italian society “characterized by a deep sense of community and interconnectedness” (Lo Bianco & Schatman, 2023 , p. 2939). In this regard, Italians have a long-standing oral tradition of sharing stories and reminiscing about past events with loved ones during social gatherings as a way to strengthen bonds, enhance the present moment, and foster a sense of belonging (Timpanelli, 1998 ). Viewed from this perspective, it makes sense that disavowing negative feelings associated with reminiscing is a sign of being fully able to appreciate present positive experiences for Italians. But why does SBI item 12 reflect Savoring the Moment more strongly than the other measured indicators of Reminiscence? We note that the other Reminiscence items predominantly focus on solitary, intrapersonal experiences in which one generates positive feelings by thinking about pleasant memories by oneself. This focus is evident in both positively-worded items (item 3: “I enjoy looking back on…my past”; item 9: “I can make myself feel good by remembering…my past; item 15: “I like to store memories…so I can recall them later”; item 21: “It’s easy for me to rekindle the joy from pleasant memories”), as well as negatively -worded items (item 6: “I don’t like to look back on good times from the past…”; item 18: “Thinking about...the past is basically a waste of time”). As opposed to items that emphasize thinking about or remembering positive memories, SBI item 12 is the only Reminiscence indicator that focuses on how respondents feel when they “reminisce,” which we argue encompasses the interpersonal behavior of sharing memories with others during social occasions. Standardized absolute values of factor loadings of the SBI items on their intended savoring factors were moderate and – although some items of the Anticipation subscale (i.e., items 1, 4, and 22) showed weak factor loadings – overall they were comparable with prior research. Since other studies have observed low values in standardized factor loadings of some items (e.g., items 1, 7, 12, 22; Aghaie et al., 2017 ; Bryant, 2003 ; Kawakubo et al., 2019 ; Titova et al., 2022 ), we retained all items to facilitate cross-cultural comparisons. We believe that future studies with more representative samples are needed to replicate these findings and to evaluate whether these items should be modified or replaced by new items that are more reliable indicators of future-focused savoring beliefs in Italian samples. Finally, consistent with prior research and hypotheses, the three savoring factors were moderately intercorrelated (e.g., Bryant, 2003 ; Titova et al., 2020), thus supporting the distinctiveness of the three temporal forms of savoring ability as conceptually related but separate constructs. The results also revealed that the three temporal subscales of the Italian adaptation of the SBI (as well as SBI Total score) have acceptable levels of reliability in terms of internal consistency, as Cronbach’s α coefficients were in the discrete-good range (Aghaie et al., 2016). Although the SBI is best conceptualized as a multidimensional measure reflecting distinct temporal facets of savoring, concerns may arise regarding the use of a Total score when a one-factor model does not optimally represent the data. Nevertheless, as noted by Limpächer and Hoyer ( 2026 ), the use of a composite score may still be justified for pragmatic reasons—such as comparability with prior research and applicability in clinical contexts—while acknowledging that the subscales provide more differentiated information and remain preferable for theory-driven analyses. Concerning convergent validity of the Italian SBI, all three SBI subscales were significantly and positively associated with criterion measures of well-being, such as life satisfaction (Aghaie et al., 2016; Limpächer & Hoyer, 2026 ; Titova et al., 2022 ), happiness (Bryant, 2003 ; Kawakubo et al., 2019 ; Titova et al., 2022 ), and flourishing, as well as with dispositional mindfulness (Cheung & Ng, 2020 ; Kiken et al., 2017 ). The ability to savor the moment was also associated with higher positive affect and lower negative affect (Titova et al., 2022 ); in contrast, anticipation correlated with greater positive affect only, while reminiscence was uncorrelated with dispositional emotion. Likewise, the results concerning the 95% confidence intervals ( CI s) for the correlations and the regression analyses overall confirmed our hypothesis regarding the discriminant validity of the temporal savoring factors: The ability to savor the moment predicted higher life satisfaction, happiness, positive affect, dispositional mindfulness, and lower negative affect above and beyond reminiscence and anticipation facets of savoring (Bryant, 2003 , 2021 ; Kawakubo et al., 2019 ; Titova et al., 2022 ). The ability to anticipate positive experiences that may happen in the future contributed (together with savoring the moment) to higher levels flourishing, whereas the ability to savor through reminiscence did not show any differential association with these measures. In contrast, after partialing out the variance in reminiscence scores that is shared with the other two SBI facets, the remaining variance in Reminiscence was associated (though not significantly) with lower levels of happiness and positive affect. Adding evidence in support of the discriminant validity of the Italian SBI, our results revealed within-person differences in levels of savoring ability across the three temporal forms of savoring. In particular, when asked to rate their savoring capacities, Italian respondents reported being most capable of savoring through reminiscence, moderately capable of savoring through anticipation, and least capable of savoring the moment. This pattern of results is roughly consistent with those found in the original construction of the scale (Bryant, 2003 ). Finally, we examined gender differences in levels of savoring ability across subscales. The results of separate single-group and multi-group CFA provided evidence of measurement invariance across gender, thus enabling meaningful comparisons of subscale scores between the male and female groups. Consistent with previous research (Bryant, 2003 ; Kawakubo et al., 2019 ; Titova et al., 2022 ), we found that Italian females reported higher scores than males on the ability to savor through reminiscence and anticipation; however, no significant difference emerged in the ability to savor the moment. Although most studies conducted so far have consistently found that females tend to report higher levels of savoring abilities than males across all three savoring facets, other studies conducted in the European context have failed to observe gender differences (Golay et al., 2018 ; Limpächer & Hoyer, 2026 ). Overall, these findings support the construct validity of the Italian SBI as a measure of savoring beliefs about anticipating, savoring the moment, and reminiscing among Italian adults. Our study provides evidence that the Italian SBI can become a reliable and useful instrument with sound psychometric properties for basic and applied research. In this regard, the developed Italian adaptation of the SBI could be helpful to expand existing studies in the Italian context to deepen our understanding of the role of savoring capacities for enhancing or maintaining individuals’ well-being (Colombo et al., 2021 ) and in developing interventions to improve people’s capacity to value positive events (Villani et al., 2023 ). Limitations and Future Directions Several limitations are worth considering and could be the focus of future studies. First, a potential source of bias is the non-representative nature of our sample, which was predominantly female and limited to young adults. Although other studies examining the psychometric properties of the SBI have focused on the young population (e.g., Aghaie et al., 2016; Bryant, 2003 Studies 1–5; Golay et al., 2018 ; Mertin-Orta, 2018), future research involving a more representative sample of the Italian-Speaking population is needed to establish the generalizability of our results with respect to reliability, factor structure, and construct validity. Further research on the psychometric properties of this measure could also include clinical groups, such as people diagnosed with depression (Limpächer & Hoyer, 2026 ). Another limitation of the present study concerns the use of nonindependent samples to develop and confirm the final measurement model of the Italian SBI, which limits its cross-sample generalizability. As we noted above commenting on the items that showed weak standardized factor loadings, future work is needed to collect data with independent samples to replicate the final four-factor model. Additionally, to further validate the Italian version of the SBI, test-retest reliability should be assessed to provide information about the temporal stability of the measurement of the construct. Last, we used self-report measures only as criteria in evaluating the construct validity of the Italian SBI, which is also a self-report measure. Future studies should thus possibly include a wider array of validational criterion measures, such as behavioral and neuropsychological criterion measures, to move beyond self-report measures. Declarations Author Contribution All authors contributed to the study conception and design. Material preparation and data collection were performed by EP, DV, SB. Data analysis were performed by SB, FBB. The first draft of the manuscript was written by FBB and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. 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The method effects in the Undergraduate Learning Burnout Scale. Frontiers in Psychology , 11 , 585179. Tables Table 1. Descriptive statistics, internal consistency reliability coefficients, and correlations among composite measures Study Measures M SD N α SBI MOM SBI REM SBI TOT SAT FLOUR HAPP MIND PA NA SBI Anticipation 4.93 0.87 553 .72 .40 *** (553) .44 *** (553) .75 *** (553) .29 *** [.19, .38] (351) .35 *** [.26, .43] (412) .31 *** [.19, .41] (260) .14 * [.01, .26] (226) .27 * [.06, .47] (79) -.09 ns [-.31, .13] (78) SBI Momentary (SBI MOM) 4.57 1.14 553 .88 -- .36 *** (553) .84 *** (553) .55 *** [.48, .62] (351) .58 *** [.51, .64] (412) .73 *** [.66, .78] (260 .44 *** [.33, .54] (226) .30 ** [.08, .49] (79) -.38 ** [-.55, -.17] (78) SBI Reminiscence (SBI REM) 5.22 0.90 553 .77 -- .71 *** (553) .20 *** [.10, .30] (351) .31 *** [.22, .39] (413) .21 *** [.09, .32] (261) .18 ** [.05, .30] (226) -.01 ns [-.22, .21] (79) -.01 ns [-.21, .23] (78) SBI Total score (SBI TOT) 4.88 0.76 553 .87 -- .50 *** (351) .57 *** (412) .59 *** (260) .37 *** (226) .27 * (79) -.23 * (78) Satisfaction with Life (SAT) 4.36 1.19 352 .86 -- .68 *** (299) .68 *** (145) .27 *** (142) .46 *** (79) -.33 ** (78) Flourishing (FLOURISH) 5.36 0.85 416 .85 -- .61 *** (262) .26 ** (142) .50 *** (79) -.22 ns (78) Subjective Happiness (HAPP) 4.62 1.29 263 .84 -- .28 *** (141) -- (0) -- (0) Mindfulness (MIND) 4.14 0.97 226 .84 -- -- (0) -- (0) Positive Affect (PA) 3.71 0.65 79 .87 -- -.11 ns (78) Negative Affect (NA) 2.50 0.79 78 .89 -- ns p > .05. * p < .05. ** p < .01. *** p < .001. Note . M = mean. SD = standard deviation. N = sample size. α = Cronbach’s alpha. SBI Anticipation = SBI Anticipation subscale. SBI MOM = SBI Savoring the Moment subscale. SBI REM = SBI Reminiscence subscale. SBI TOT = SBI Total score. SAT = Satisfaction with Life Scale. FLOURISH = Flourishing Scale. HAPP = Subjective Happiness Scale. MIND = Mindful Attention Awareness Scale. PA = PANAS Positive Affect subscale; NA = PANAS Negative Affect subscale. The 95% confidence interval is tabled in brackets for the correlation between each SBI subscale and each criterion measure. Pairwise sample size is tabled in parentheses for each correlation. All participants completed the SBI, and different subsets of participants completed different sets of criterion measures. None of the participants who completed the Positive and Negative Affect subscales also completed the Happiness or Mindfulness measures. Table 2. Goodness-of-fit statistics from confirmatory factor analysis models for the Italian Savoring Beliefs Inventory CFA Model Sample χ 2 df RMSEA SRMR CFI NNFI AIC Model 1: One factor (Global savoring) Pooled ( N = 553) 2224.89 252 .146 .108 .81 .79 3329.57 Model 2: Three savoring factors (Anticipation, Savoring the Moment, and Reminiscence) Pooled ( N = 553) 1414.96 249 .102 .089 .89 .87 1776.12 Model 3: Five factors (three savoring factors and Positive and Negative method factors) a Pooled (N = 553) 745.05 224 .066 .054 .95 .94 905.89 Model 4: Four factors (three savoring factors and a Negative Method factor) b Pooled (N = 553) 1047.39 237 .082 .077 .92 .91 1245.32 Development c (N = 276) 635.28 237 .081 .080 .93 .92 789.15 Model 5: Four factors (three savoring factors and a Negative Method factor) adding a cross-loading for SBI item 12 on the Savoring the Moment factor d Development (N = 276) 577.34 236 .073 .079 .94 .93 710.02 Model 6: Four factors (three savoring factors and a Negative Method factor) with SBI item 12 loading on the Savoring the Moment factor instead of on the Reminiscence factor Development (N = 276) 579.03 237 .073 .078 .94 .93 709.64 Confirmation (N = 276) 618.64 237 .078 .076 .92 .91 764.57 Pooled (N = 553) 951.51 237 .076 .073 .93 .92 1119.30 a Although the five-factor model with three savoring factor and separate positive and negative method factors (Model 3) provided an acceptable goodness-of-fit, it produced nonsignificant correlations among the three temporal SBI factors, in contrast to all other multifactor models in which the SBI factors were moderately intercorrelated. These anomalous parameter estimates suggest that the method factors contain variance associated with the savoring factors themselves, and are a sign of an ill-conditioned CFA solution (see Garrido et al., 2025; Marsh, 1989). For this reason, we rejected the five-factor model as a measurement model for responses to the Italian SBI. b Although the four-factor model with three temporal savoring factors and a single negative method factor (Model 4) produced the hypothesized significant correlations among the three temporal savoring factors, its RMSEA value exceeded the .08 threshold for acceptable fit, paralleling the misfit of this model for the Russian SBI (Titova et al, 2022). c To conduct a specification search for a better-fitting measurement model, we randomly split the full sample in half and estimated Model 4 using the data of the first random-half (i.e., the Development sample; N = 276) and using the data of the second random-half (i.e., the Confirmation sample; N = 277) to assess the cross-sample generalizability of the final model. We freed the fixed parameter in Model 4 that had the largest model modification index (i.e., the cross-loading of SBI Reminiscence item 12 on the Savoring the Moment factor to create Model 5. d Inspection of the CFA solution for Model 5 revealed that when SBI item 12 was allowed to cross-load on the Savoring the Moment factor, the Reminiscence factor explained only 1% of the variance in SBI item 12 and the loading of item 12 on the Reminiscence factor was nonsignificant. Thus, we fixed the loading of SBI item 12 on the Reminiscence factor to 0.0 to create Model 6, which we then confirmed using the data of the Confirmation sample, as well as the data of the Pooled sample. Model 6 represent the formal measurement model for the Italian SBI. Note . In all CFA models, we fixed the variance of each factor to 1.0, to define the units of variance for the latent variables. In all multi-factor CFA models, the three savoring factors were allowed to intercorrelate. In the five-factor model, the positive and negative method factors were allowed to intercorrelate, but were constrained to be uncorrelated with the three savoring factors. In the four-factor models, the negative method factor was constrained to be uncorrelated with the three savoring factors. Table 3. Completely standardized factor loadings, squared multiple correlations for items, and factor loadings from the final four-factor CFA model for the Italian Savoring Beliefs Inventory (N = 553) SBI Items (item numbers) Savoring Factors Negative Method Factor R 2 ANT MOM REM Get pleasure from looking forward (SBI 1) .33 -- -- -- .11 Don’t like to look forward too much (SBI 4) -.23 -- -- .13 .07 Can feel the joy of anticipation (SBI 7) .75 -- -- -- .56 Anticipating is a waste of time (SBI 10) -.45 -- -- .39 .35 Can enjoy events before they occur (SBI 13) .69 -- -- -- .48 Hard to get excited beforehand (SBI 16) -.57 -- -- .32 .43 Can feel good by imagining outcome (SBI 19) .53 -- -- -- .28 Feel uncomfortable when anticipate (SBI 22) -.38 -- -- .46 .36 Know how to make the most of good time (SBI 5) -- .74 -- -- .55 Find it hard to hang onto a good feeling (SBI 2) -- -.71 -- .30 .59 Can prolong enjoyment by own effort (SBI 11) -- .80 -- -- .64 Am own “worst enemy” in enjoying (SBI 8) -- -.53 -- .39 .43 Feel fully able to appreciate good things (SBI 17) -- . 66 -- -- .44 Can’t capture the joy of happy moments (SBI 14) -- -.74 -- .34 .67 Find it easy to enjoy self when want to (SBI 23) -- .44 -- -- .19 Don’t enjoy things as much as should (SBI 20) -- -.73 -- .34 .65 Feel disappointed when reminisce (SBI 12) -- -.52 -- .42 .44 Enjoy looking back on happy times (SBI 3) -- -- .71 -- .50 Don’t like to look back afterwards (SBI 6) -- -- -.41 .29 .25 Can feel good by remembering past (SBI 9) -- -- .73 -- .53 Like to store memories for later recall (SBI 15) -- -- .67 -- .45 Reminiscing is a waste of time (SBI 18) -- -- -.53 .39 .44 Easy to rekindle joy of happy memories (SBI 21) -- -- .53 -- .28 Best not to recall past fun times (SBI 24) -- -- -.39 .37 .29 Factor Correlations ANT MOM Savoring the Moment .45 -- Reminiscence .59 .42 Note . ANT = Anticipation. MOM = Savoring the Moment. REM = Reminiscence. R 2 = proportion of variance that the model explains in each item. Items have been paraphrased and re-ordered to streamline presentation. Blank loadings were fixed at zero in the CFA model. The negative method factor was constrained to be uncorrelated with the three Savoring factors. All model parameter estimates were statistically significant at p < .0001. Table 4 . Results of multiple regression analyses using the three SBI subscales to predict criterion measures: Standardized coefficients SBI Subscales Criterion Measures N F df R 2 ANT MOM REM Satisfaction with Life 351 52.52 *** 3, 347 .31 .08 ns .52 *** -.01 ns Flourishing 412 75.20 *** 3, 408 .36 .12 ** .50 *** .07 ns Subjective Happiness 260 99.49 *** 3, 256 .54 .04 ns .76 *** -.13 ns Mindfulness 226 17.25 *** 3, 222 .19 -.01 ns .43 *** .01 ns Positive Affect 79 4.20 ** 3, 75 .14 .23 ns .26 ** -.19 ns Negative Affect 78 4.99 ** 3, 74 .17 .06 ns -.46 *** .15 ns ns p > .05. * p < .05. ** p < .01. *** p < .001. Note . ANT = Anticipation. MOM = Savoring the Moment. REM = Reminiscenc Additional Declarations No competing interests reported. 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Bryant","email":"","orcid":"","institution":"Loyola University Chicago","correspondingAuthor":false,"prefix":"","firstName":"Fred","middleName":"B.","lastName":"Bryant","suffix":""}],"badges":[],"createdAt":"2026-02-13 11:53:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8871514/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8871514/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106724841,"identity":"702bbe63-8551-4d39-92bb-d9360934dfed","added_by":"auto","created_at":"2026-04-12 18:30:02","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1510355,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8871514/v1/8fbb9ab6-c943-4a1d-bc36-ee82b53e6599.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Validation of an Italian Version of the Savoring Beliefs Inventory","fulltext":[{"header":"Introduction","content":"\u003cp\u003eHow happy people feel in their daily lives depends not only on how often good things happen to them, but also on how they process these positive experiences. As de La Rochefoucauld (\u003cspan class=\"CitationRef\"\u003e1796\u003c/span\u003e) observed, \u0026ldquo;happiness does not consist in things themselves but in the relish we have of them\u0026rdquo; (p. 51). This critical process of cultivating and relishing positive feelings has been termed \u003cem\u003esavoring\u003c/em\u003e, or \u0026ldquo;the capacity to attend to, appreciate, and enhance the positive experiences in one\u0026rsquo;s life\u0026rdquo; (Bryant \u0026amp; Veroff, \u003cspan class=\"CitationRef\"\u003e2007\u003c/span\u003e, p. xi). Confirming de la Rochefoucauld\u0026rsquo;s perceptive insight, daily diary research has found that the peak benefit of positive events is gained only through the act of savoring them (Jose, Lim, \u0026amp; Bryant, \u003cspan class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eSavoring encompasses three interrelated temporal orientations\u0026mdash;savoring \u003cem\u003efuture\u003c/em\u003e positive experiences before they occur (anticipation), savoring \u003cem\u003epresent\u003c/em\u003e positive experiences as they unfold (savoring the moment), and savoring \u003cem\u003epast\u003c/em\u003e positive experiences after they end (reminiscence)\u0026mdash;through which people create or regulate positive feelings in the here-and-now (Bryant, \u003cspan class=\"CitationRef\"\u003e1989\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e2003\u003c/span\u003e). To assess individual differences in the ability to savor positive experience, Bryant (\u003cspan class=\"CitationRef\"\u003e2003\u003c/span\u003e) developed the Savoring Beliefs Inventory (SBI) using samples of young adults in the United States. As cross-cultural work on savoring has progressed, the original English SBI has been modified for use in numerous countries, including China, Egypt, France, Greece, Hungary, India, Iran, Japan, Korea, Mexico, Romania, Russia, Spain, Thailand, and Turkey (Bryant, \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). The present study was designed to adapt the SBI for use in Italy.\u003c/p\u003e\n\u003ch3\u003eSavoring and Well-Being\u003c/h3\u003e\n\u003cp\u003eExtensive research supports the conclusion that savoring is a fundamental component of well-being. A higher capacity for savoring is linked to higher levels of well-being, including not only greater happiness, life satisfaction, and positive affect (Smith \u0026amp; Bryant, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), but also lower levels of depressive symptoms and negative affect (Ford et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Moreover, applied studies have identified savoring as a mechanism that fosters resilience in the face of hardship (Sytine et al., 2019) and mitigates the detrimental effects of stress (Boelen, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Experimental interventions that promote savoring skills enhancing psychological health (Smith \u0026amp; Hanni, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Large-scale prospective studies have found that savoring ability reduces age-related declines in well-being (Stephens et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), and experience-sampling data confirms the beneficial effects of savoring throughout adulthood (Growney et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSupplementing self-report measures, neuropsychological research has confirmed that the ability to savor helps people regulate their positive emotional experiences. For example, participants instructed to savor positive pictures exhibit stronger and more sustained picture-elicited neural responses, compared to those instructed simply to passively view the same pictures (Wilson \u0026amp; MacNamara, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Furthermore, individuals with a greater ability to savor positive experiences show more stable neural responses to rewards over time, while those with a lower capacity experience a greater decrease in neural activity (Irvin et al., 2022). This evidence aligns with findings suggesting that difficulties savoring mental imagery may contribute to the development and maintenance of depression (Jackson et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eMeasurement Models Underlying Prior Cross-Cultural Adaptations of the SBI\u003c/h3\u003e\n\u003cp\u003eThe SBI was originally developed to assess individual differences in savoring ability based on a measurement model consisting of three forms of savoring (Anticipation, Savoring the Moment, and Reminiscence), along with two method factors reflecting positively- and negatively-worded items, respectively (Bryant, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). The SBI consists of 24 statements (8 for each temporal form of savoring), half reflecting an ability to savor, and half an inability to savor, and respondents use a seven-point scale to rate how true each statement is for them.\u003c/p\u003e \u003cp\u003eOver time, researchers have used confirmatory factor analysis (CFA) to develop a variety of different measurement models in adapting the SBI for use in other cultures. Several of these cross-cultural adaptations have produced measurement models that are simpler than the original five-factor model and lack method factors. For example, in developing a Turkish SBI, Metin-Orta (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) formulated a one-factor model; and in developing a German SBI, Limp\u0026auml;cher and Hoyer (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2026\u003c/span\u003e) constructed a tripartite model composed of the three temporal savoring factors.\u003c/p\u003e \u003cp\u003eThe measurement models developed for several other cross-cultural adaptations of the SBI have incorporated method factors in various forms to control for variation in responses due to item wording. For example, in creating a Japanese SBI, Kawakubo et al. (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) replicated Bryant\u0026rsquo;s original (2003) five-factor model containing three temporal savoring factors and separate positive and negative method factors. In developing a Persian SBI, Aghaie et al. (2016) formulated an alternative five-factor structure consisting of a Savoring the Moment factor and four factors reflecting positively- or negatively-worded items assessing anticipation or reminiscence, respectively. In developing a Russian SBI, Titova et al. (\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) established a four-factor model consisting of the three temporal savoring dimensions (with one item cross-loading) and a negatively-worded method factor. Building on the work of these previous cross-cultural adaptations, the purpose of the present study was to create an Italian SBI, develop a measurement model for it (using CFA to test the unidimensional, three-, four-, and five-factor models used in previous studies), and assess the construct validity of the final model.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eResearch Hypotheses\u003c/h2\u003e \u003cp\u003eBased on theory and research on the multidimensionality of savoring (Bryant, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), we hypothesized that a multi-factor measurement model would provide a better representation of responses to the Italian SBI than would a unidimensional model. Grounded in an underlying tripartite model, the number of factors was expected to range from three to five, based on the potential need to incorporate either one or two method factors in the model. Based on prior research, we also expected the savoring factors to be moderately intercorrelated (Bryant, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRegarding the construct validity of the temporal savoring factors, based on prior theory and research on the centrality of momentary savoring (Bryant, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Titova et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), we hypothesized that the ability to savor the moment would show stronger associations with criterion measures of well-being (satisfaction with life, flourishing, happiness), dispositional mindfulness, and dispositional emotion (positive and negative affect), compared to the ability to savor through anticipation or reminiscence. Finally, based on prior research on differences in levels of savoring ability across temporal forms of savoring (Bryant, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2003\u003c/span\u003e), and between males and females (Bryant, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Bryant \u0026amp; Veroff, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), we hypothesized that composite subscale scores would be highest on the Reminiscence factor and that females would score higher than males on all three forms of savoring.\u003c/p\u003e \u003c/div\u003e"},{"header":"Method","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003ePower Analysis\u003c/h2\u003e \u003cp\u003eWe conducted prospective power and sensitivity analyses for each of the inferential statistical tests we used, including CFAs to establish a formal measurement model for the Italian SBI, and Pearson correlations as well as independent-samples and pairwise \u003cem\u003et\u003c/em\u003e-tests to assess the model\u0026rsquo;s construct validity. In determining target sample size for CFA, if none of our \u003cem\u003ea priori\u003c/em\u003e models provided acceptable goodness-of-fit to the data, we also sought to obtain a final sample that would be large enough to support data-driven model modifications in which we would randomly split the full sample in half, using one subsample to search for theoretically relevant model respecifications that improved model fit, and the other subsample to assess the cross-sample generalizability of the modified model. Given practical limitations, we aimed for a sample size of \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e\u0026thinsp;500, that would, if necessary, provide random subsamples of 250 for model development and model confirmation, respectively. Following MacCallum, Browne, and Sugawara\u0026rsquo;s (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e1996\u003c/span\u003e) procedure for determining power to detect model misfit in covariance structure analysis, sample sizes of 500 and 250 both provide\u0026thinsp;\u0026gt;\u0026thinsp;99% power to detect RMSEA \u0026gt; .08 versus a close-fit model for our largest hypothesized CFA model (with \u003cem\u003edf\u003c/em\u003e\u0026thinsp;=\u0026thinsp;224).\u003c/p\u003e \u003cp\u003eOur final sample consisted of 558 participants, 553 of whom had complete data for the 24 SBI items. We used Power Analysis and Sample Size (PASS; Hintze, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) software to conduct sensitivity power analyses for inferential tests of the SBI\u0026rsquo;s convergent and discriminant validity. To assess patterns of relationship between composite SBI subscales and criterion measures, we administered different sets of criterion measures along with the SBI to different subgroups of these participants (\u003cem\u003eN\u003c/em\u003es ranging from 78 to 413). The minimum detectable correlation at two-tailed \u003cem\u003ep\u003c/em\u003e \u0026lt; .05 with 80% power is: (a) .31 with \u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;78, and (b) .14 with \u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;413.\u003c/p\u003e \u003cp\u003eTo assess the ability of the SBI to discriminate males (\u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;166) and females (\u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;382) based on SBI subscale and total scores, we used independent-samples \u003cem\u003et\u003c/em\u003e tests, which provided 80% power to detect a minimum effect size of \u003cem\u003ed\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.34 at two-tailed \u003cem\u003ep\u003c/em\u003e \u0026lt; .05. To assess differences in levels of savoring beliefs across the three SBI subscales within participants, we used pairwise \u003cem\u003et\u003c/em\u003e-tests, which provided 80% power to detect a minimum effect size of \u003cem\u003ed\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.12 at two-tailed \u003cem\u003ep\u003c/em\u003e \u0026lt; .05.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eParticipants\u003c/h3\u003e\n\u003cp\u003eThe final sample consisted of 553 participants (166 males, 382 females, and 5 who did not report gender) with a mean age of 23.58 years (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.90; range\u0026thinsp;=\u0026thinsp;17\u0026ndash;31). The observed gender imbalance is consistent with previous SBI validation studies conducted in other languages, which also employed convenience and snowball sampling methods (e.g., Aghaie et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Golay et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Metin-Orta, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The educational level of the sample varied widely, with 42% having completed their education in secondary or high school, 34% having a bachelor\u0026rsquo;s degree, and 22% having a master\u0026rsquo;s or doctoral degree (2% did not report their education). Concerning marital status, 45% were single, 45% were in a relationship with a partner, and 10% were either married or cohabiting with a partner. Concerning employment status, 33% were students, 33% were employed, 12% were students who were also employed, 4% were unemployed, and 4% described their employment as \u0026ldquo;other.\u0026rdquo;\u003c/p\u003e\n\u003ch3\u003eProcedure\u003c/h3\u003e\n\u003cp\u003eThis study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki (Goodyear et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) and approved by the Ethics Committee for Research in Psychology of the Department of Psychology of xxx (protocol number: 119_24). All participants signed an informed consent form prior to participation. Participants responded voluntarily and anonymously, and no financial or other compensation was provided. Participants were recruited using a snowball sampling procedure. The study invitation was initially distributed to undergraduate students, in line with previous validation studies of the SBI (Aghaie et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Golay et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Metin-Orta, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), who were invited to complete the survey and to further share the invitation within their personal networks. Data were collected via online questionnaires administered using Qualtrics. After completing the SBI, Qualtrics was used to randomly assign participants to different subsets of criterion measures. As a result, not all participants completed all criterion measures. This random assignment procedure was implemented to minimize selection bias while allowing the assessment of multiple aspects of construct validity without overburdening participants. Consequently, different subgroups of participants completed different combinations of criterion measures, depending on the random allocation. The present study was conducted within the context of a broader research project aimed at investigating psychological well-being in young adults.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eMeasures\u003c/h2\u003e \u003cp\u003e \u003cb\u003eSavoring Beliefs Inventory (SBI).\u003c/b\u003e The SBI is a self-report instrument developed by Bryant (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) to assess individuals\u0026rsquo; beliefs about savoring. It consists of 24 items rated on a 7-point Likert scale, ranging from 1 (\u0026ldquo;strongly disagree\u0026rdquo;) to 7 (\u0026ldquo;strongly agree\u0026rdquo;). The SBI comprises three subscales whose scores can also be summed to obtain a total score: (1) the \u003cem\u003eAnticipation\u003c/em\u003e subscale, which measures perceived ability to savor experiences through anticipation; (2) the \u003cem\u003ePresent Moment\u003c/em\u003e subscale, which assesses perceived ability to savor experiences as they occur; and (3) the Reminiscing subscale, which evaluates perceived ability to savor past experiences. The original English version of the SBI was independently translated into Italian by three bilingual authors, SB, DV, and EP, and the translations were compared and discussed until full agreement was reached. In the present study, the final versions of the Italian SBI Anticipation, Present Moment, and Reminiscence subscales showed acceptable to strong internal consistency reliability coefficients (Cronbach\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;.72, .88, and .77, respectively), as did the SBI Total score (Cronbach\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;.87).\u003c/p\u003e \u003cp\u003e \u003cb\u003eSatisfaction with Life (SWLS).\u003c/b\u003e This scale was developed by Diener and colleagues (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1985\u003c/span\u003e; Italian version: Di Fabio \u0026amp; Busoni, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) to assess life satisfaction. It consists of five items rated on a 7-point Likert scale, ranging from 1 (\u0026ldquo;strongly disagree\u0026rdquo;) to 7 (\u0026ldquo;strongly agree\u0026rdquo;). Higher scores indicate greater satisfaction with life. Evidence supports the construct validity of the Italian version of the SWLS as a measure of life satisfaction (Di Fabio \u0026amp; Busoni, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Di Fabio \u0026amp; Gori, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In the present study, the Italian SWLS showed good internal consistency reliability (Cronbach\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;.85).\u003c/p\u003e \u003cp\u003e \u003cb\u003eFlourishing Scale (FS).\u003c/b\u003e This scale, developed by Diener (2009; Italian version: Di Fabio, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), aims to assess components of psychological well-being, including relationships, self-esteem, life purpose, and optimism. It consists of eight positively-worded items, with responses rated on a 7-point Likert scale ranging from 1 (\u0026ldquo;strongly disagree\u0026rdquo;) to 7 (\u0026ldquo;strongly agree\u0026rdquo;). Higher scores indicate greater flourishing. The Italian FS shows evidence of construct validity as a measure of flourishing (Di Fabio, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Giuntoli et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In the present study, the Italian FS showed good internal consistency reliability (Cronbach\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;.85).\u003c/p\u003e \u003cp\u003e \u003cb\u003eSubjective Happiness Scale (SHS).\u003c/b\u003e This instrument was developed by Lyubomirsky and Lepper (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Italian validation: Iani et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) to assess global subjective happiness through statements that ask participants to evaluate themselves or compare themselves to others. It consists of four items, rated on a 7-point Likert scale ranging from 1 (\u0026ldquo;not at all\u0026rdquo;) to 7 (\u0026ldquo;very much\u0026rdquo;). The total score is calculated as the mean of the four items (with the fourth item reverse-scored), resulting in possible scores ranging from 1 to 7, where higher scores indicate greater happiness. Iani et al. (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) presented evidence supporting the construct validity of the Italian SHS as a measure of happiness. In the present study, the Italian SHS showed good internal consistency reliability (Cronbach\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;.84).\u003c/p\u003e \u003cp\u003e \u003cb\u003eMindful Attention Awareness Scale (MAAS).\u003c/b\u003e This instrument is designed to assess individual differences in present-moment awareness during which one consciously attends to what is happening (Brown \u0026amp; Ryan, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Italian version: Veneziani \u0026amp; Voci, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The scale consists of 15 items, rated on a 7-point Likert scale ranging from 1 (\u0026ldquo;almost always\u0026rdquo;) to 7 (\u0026ldquo;almost never\u0026rdquo;). Veneziani and Voci (\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) presented evidence supporting the structural and construct validity of the Italian MAAS as a measure of mindfulness. In the present study, the Italian MAAS showed good internal consistency reliability (Cronbach\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;.84).\u003c/p\u003e \u003cp\u003e \u003cb\u003ePositive and Negative Affect Scale (PANAS).\u003c/b\u003e This scale was developed by Watson, Clark, and Tellegen (\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e1988\u003c/span\u003e; Italian validation: Terracciano, McCrae, \u0026amp; Costa, 2003) to assess individual differences in positive and negative affect. The scale consists of 20 items, 10 assessing positive affect and 10 assessing negative affect, rated on a 5-point Likert scale ranging from 1 (\u0026ldquo;very slightly or not at all\u0026rdquo;) to 5 (\u0026ldquo;extremely\u0026rdquo;). Scores for each subscale are calculated by summing the corresponding items, with higher scores indicating greater levels of positive or negative affect, respectively. Terracciano et al. (2003) presented evidence supporting the structural and construct validity of the Italian PANAS as a measure of state positive and negative affect. In the present study, the Italian PANAS showed strong internal consistency reliability for both its positive and negative scales (Cronbach\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;.87 and .89, respectively).\u003c/p\u003e \u003cp\u003e \u003cb\u003eDemographic Questions.\u003c/b\u003e These questions were designed to collect demographic information about the sample, including gender, age, educational level, marital status, and employment status.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n\u003ch2\u003eOverview\u003c/h2\u003e\n\u003cp\u003eData analyses unfolded in three stages. First, we computed descriptive statistics to examine the distributional properties of the Italian SBI items and the validational criterion measures. Second, we used CFA to assess the goodness-of-fit of alternative models for the Italian SBI data and develop a formal measurement model for the instrument. Third, to assess construct validity, we constructed composite measures for the SBI subscales and criterion variables and used: (a) correlation and regression analyses to test hypotheses about the convergent and discriminant validity of SBI subscales in relation to the criterion measures; (b) pairwise \u003cem\u003et\u003c/em\u003e-tests to test hypotheses about within-person differences in levels of savoring beliefs across subscales; and (c) independent samples \u003cem\u003et\u003c/em\u003e-tests to test hypotheses about gender differences in levels of savoring ability across subscales.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n\u003ch2\u003eDescriptive Statistics\u003c/h2\u003e\n\u003cp\u003eExamining scores for the 24 SBI items, participants scored much higher on \u003cem\u003epositively\u003c/em\u003e-worded items (mean\u0026thinsp;=\u0026thinsp;4.82) than on \u003cem\u003enegatively\u003c/em\u003e-worded items (mean\u0026thinsp;=\u0026thinsp;3.18), pairwise \u003cem\u003et\u003c/em\u003e(552)\u0026thinsp;=\u0026thinsp;27.18, \u003cem\u003ep\u003c/em\u003e \u0026lt; .0001, Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.16, indicating participants endorsed items reflecting the \u003cem\u003epresence\u003c/em\u003e of savoring ability more strongly than they endorsed items reflecting the \u003cem\u003eabsence\u003c/em\u003e of savoring ability. In addition, participants scored slightly higher on \u003cem\u003epositively\u003c/em\u003e-worded items (mean\u0026thinsp;=\u0026thinsp;4.96) than on reverse-scored \u003cem\u003enegatively\u003c/em\u003e-worded items (mean\u0026thinsp;=\u0026thinsp;4.82), pairwise \u003cem\u003et\u003c/em\u003e(552)\u0026thinsp;=\u0026thinsp;4.23, \u003cem\u003ep\u003c/em\u003e \u0026lt; .0001, Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.19, indicating a small but significant tendency for respondents to endorse positively-worded items more strongly than they rejected negatively-worded items.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePositively\u003c/em\u003e-worded SBI items had small negative skewness (mean = -0.57), while \u003cem\u003enegatively\u003c/em\u003e-worded items had small positive skewness (mean\u0026thinsp;=\u0026thinsp;0.50), reflecting more frequent higher and lower responses, respectively. All SBI items had slight negative kurtosis (mean = -0.22), suggesting flatter, somewhat platykurtic distributions. Based on Lei and Lomax (\u003cspan class=\"CitationRef\"\u003e2005\u003c/span\u003e), absolute skewness and kurtosis values below 1.0 indicate slight nonnormality.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n\u003ch2\u003eDeveloping a Measurement Model for the Italian SBI\u003c/h2\u003e\n\u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\n\u003ch2\u003eModel Estimation\u003c/h2\u003e\n\u003cp\u003eBased on prior theory and research, we used maximum-likelihood CFA via LISREL 8.80 (J\u0026ouml;reskog \u0026amp; S\u0026ouml;rbom, \u003cspan class=\"CitationRef\"\u003e2006\u003c/span\u003e) to assess the goodness-of-fit of four different \u003cem\u003ea priori\u003c/em\u003e measurement models for the Italian SBI: (a) a unidimensional one-factor model (Bryant, \u003cspan class=\"CitationRef\"\u003e2003\u003c/span\u003e) consisting of a single underlying general factor (Model 1); (b) a three-factor model consisting of temporal factors reflecting Anticipation, Savoring the Moment, and Reminiscence (Model 2); (c) a five-factor model (Bryant, \u003cspan class=\"CitationRef\"\u003e2003\u003c/span\u003e) consisting of the three temporal factors and two method factors (Positively-worded items and Negatively-worded items) (Model 3); and (d) a four-factor model (Titova et al, \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e) consisting of the three temporal factors and one method factor (Negatively-worded items) (Model 4). We included this last model based on the possibility that the five-factor model might well produce an ill-conditioned CFA solution, as often arises with multiple method factors in the same model (Garrido et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e; Marsh, \u003cspan class=\"CitationRef\"\u003e1989\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eModel 2 (\u003cem\u003ethree\u003c/em\u003e factors) constrained each item to load only on the savoring factor it was intended to reflect. Model 3 (\u003cem\u003efive\u003c/em\u003e factors) specified that each item loaded on the savoring factor it was intended to reflect and freed cross-loadings both for positively-worded items on a positive method and for negatively-worded items on a negative method factor. Model 4 (\u003cem\u003efour\u003c/em\u003e factors) specified that each item loaded on the savoring factor it was intended to reflect and freed cross-loadings only for negatively-worded items on a negative method factor.\u003c/p\u003e\n\u003cp\u003eIn all CFA models, we fixed the variance of each factor to 1.0, to define the units of variance for the latent variables, and estimated the unique error variance of each of item without correlated measurement errors. In all multi-factor CFA models, the three savoring factors were allowed to intercorrelate. In the five-factor model, the positive and negative method factors were allowed to intercorrelate, but were constrained to be uncorrelated with the three savoring factors. In the four-factor model, the negative method factor was constrained to be uncorrelated with the three savoring factors.\u003c/p\u003e\n\u003cp\u003eTo evaluate model goodness-of-fit, we used two measures of \u003cem\u003eabsolute\u003c/em\u003e fit\u0026mdash;the root mean square error of approximation (RMSEA) and standardized root mean square residual (SRMR)\u0026mdash;and two measures of \u003cem\u003erelative\u003c/em\u003e fit\u0026mdash;the comparative fit index (CFI) and the non-normed fit index (NNFI). Better model fit is indicated by lower values of absolute fit measures and higher values of relative fit measures. In assessing goodness-of-fit, we considered RMSEA \u0026lt; .08 (Browne \u0026amp; Cudeck, \u003cspan class=\"CitationRef\"\u003e1993\u003c/span\u003e), SRMR \u0026lt; .08 (Hu \u0026amp; Bentler, \u003cspan class=\"CitationRef\"\u003e1998\u003c/span\u003e), CFI \u0026gt; .90 and NNFI \u0026gt; .90 (Bentler \u0026amp; Bonett, 1990) as representing acceptable model fit. To make the loadings of negatively-worded items more apparent in the factor solutions, we did not reverse-score the 12 negatively-anchored SBI items before conducting CFA (although we reverse-scored negatively-worded SBI items in computing unit-weighted composite measures to assess construct validity). We also used the Akaike information criterion (AIC; Akaike, \u003cspan class=\"CitationRef\"\u003e1973\u003c/span\u003e) to compare the goodness-of-fit of CFA models. AIC balances model fit with model complexity, by adding a penalty for the number of estimated parameters to help guard against overfitting. Lower AIC scores reflect models that fit the data better without being overly complex.\u003c/p\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e presents goodness-of-fit statistics for the four \u003cem\u003ea priori\u003c/em\u003e CFA models of the Italian SBI. As found in previous studies in the U.S. (Bryant, \u003cspan class=\"CitationRef\"\u003e2003\u003c/span\u003e), France (Golay et al., \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e), Japan (Kawakubo et al., \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e, and Russia (Titova et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e), the \u003cem\u003eone-factor\u003c/em\u003e model (Model 1) fit the Italian SBI data poorly (RMSEA and SRMR \u0026gt; .10, fit indices \u0026lt; .81). Further supporting the multidimensionality of Italian savoring beliefs, the \u003cem\u003ethree-factor\u003c/em\u003e model (Model 2) provided a significant improvement in fit relative to the one-factor model, \u0026Delta;\u0026chi;\u003csup\u003e2\u003c/sup\u003e(3)\u0026thinsp;=\u0026thinsp;809.83, \u003cem\u003ep\u003c/em\u003e \u0026lt; .0001, Cohen\u0026rsquo;s \u003cem\u003ew\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.21. However, also replicating prior cross-cultural adaptations of the SBI (Bryant, \u003cspan class=\"CitationRef\"\u003e2003\u003c/span\u003e; Kawakubo et al., \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e; Titova et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e), the three-factor model left room for improvement in its goodness-of-fit (RMSEA and SRMR \u0026gt; .08, fit indices \u0026lt; .90).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAs seen in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, the \u003cem\u003efive-factor\u003c/em\u003e model (Model 3) provided a reasonable fit to the SBI data (RMSEA and SRMR \u0026lt; .07, fit indices \u0026gt; .93). However, inspection of the CFA solution revealed that having both positive and negative method factors in the model produced anomalous parameter estimates\u0026mdash;specifically, the Anticipation factor had nonsignificant correlations with both Savoring the Moment (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0) and Reminiscence (\u003cem\u003er\u003c/em\u003e = .04). The absence of significant correlations among the Savoring factors in this model is particularly problematic, given that Anticipation correlates .45 with Savoring the Moment and .61 with Reminiscence in the three-factor model (Model 2). Evidently, the method factors have absorbed substantive variance from the savoring factors (see Garrido et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e). As noted earlier, such discrepancies indicate an ill-conditioned solution that can result when specifying multiple method factors.\u003c/p\u003e\n\u003cp\u003eAccordingly, we assessed the goodness-of-fit of a more parsimonious (four factor) version of the five-factor model (Model 4) that omitted the Positive method factor and used only the Negative method factor, as previously developed by Titova et al. (\u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e) in adapting the Russian SBI. Along these lines, simulation research indicates that in most cases, modeling a single \u0026ldquo;negative wording\u0026rdquo; factor is sufficient to achieve the best recovery of underlying factor structure (Garrido et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eAs hypothesized, this four-factor model fit the data significantly better than the three-factor model, \u0026Delta;\u0026chi;\u003csup\u003e2\u003c/sup\u003e(15)\u0026thinsp;=\u0026thinsp;367.57, \u003cem\u003ep\u003c/em\u003e \u0026lt; .0001, \u003cem\u003ew\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.82. Moreover, unlike the five-factor model, the correlations among the SBI factors in the four-factor model (i.e., Anticipation and Savoring the Moment, \u003cem\u003er\u003c/em\u003e = .46; Anticipation and Reminiscence, \u003cem\u003er\u003c/em\u003e =\u0026thinsp;.60; Savoring the Moment and Reminiscence, \u003cem\u003er\u003c/em\u003e =\u0026thinsp;.49) were highly consistent with those found in the three-factor model. Nevertheless, as was the case for the three-factor model, the four-factor model\u0026rsquo;s RMSEA value (i.e., .082) exceeded .08, making it an unacceptable measurement model (see Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n\u003ch2\u003eModel Respecification\u003c/h2\u003e\n\u003cp\u003eFollowing Titova et al. (\u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e), we sought to improve the goodness-of-fit of the four-factor model (Model 4) by adding a single cross-loading to the \u003cem\u003ea priori\u003c/em\u003e model. Before proceeding, we took steps to avoid capitalizing on chance, given that adding estimated parameters based on \u003cem\u003epost hoc\u003c/em\u003e inspection of results is prone to capitalize on chance (MacCallum et al., \u003cspan class=\"CitationRef\"\u003e1992\u003c/span\u003e). Although it would be ideal to have an independent sample for cross-validation, we adopted a commonly-used alternative method to increase the expected cross-sample generalizability of model modifications by randomly splitting our sample in half and using (a) one subsample (i.e., the \u003cem\u003eDevelopment\u003c/em\u003e sample \u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;276) to explore ways to improve model fit \u003cem\u003ea posteriori\u003c/em\u003e and (b) the other subsample (i.e., the \u003cem\u003eConfirmation\u003c/em\u003e sample; \u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;277) to test the replicability of respecified models \u003cem\u003ea priori\u003c/em\u003e (see Brockway et al., \u003cspan class=\"CitationRef\"\u003e2002\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eWe began the specification search by re-estimating the four-factor model using the data of the Development Sample and examining the modification index (MI), also known as the Lagrange multiplier, for each parameter that was fixed to zero in the model. Each MI estimates the reduction in the model\u0026rsquo;s goodness-of-fit \u0026chi;\u003csup\u003e2\u003c/sup\u003e value (with \u003cem\u003edf\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1) that would be expected if a particular fixed parameter were to be freely estimated in the model (MI values\u0026thinsp;\u0026gt;\u0026thinsp;3.84 represent \u003cem\u003ep\u003c/em\u003e \u0026lt; .05). The largest MI in the four-factor model (MI\u0026thinsp;=\u0026thinsp;47.17) was the cross-loading of SBI item 12\u0026mdash;a negatively-worded item intended to reflect Reminiscence (i.e., \u0026ldquo;When I reminisce about pleasant memories, I often start to feel sad or disappointed\u0026rdquo;)\u0026mdash;on the \u003cem\u003eSavoring the Moment\u003c/em\u003e factor.\u003c/p\u003e\n\u003cp\u003eWe thus freed the cross-loading of SBI item 12 on the Savoring the Moment factor, so item 12 loaded on both Reminiscence and Savoring the Moment, and estimated this respecified model (Model 5). As expected, this cross-loading was statistically significant in the modified four-factor model (completely standardized loading\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.50; 25% variance explained in the item, \u003cem\u003ep\u003c/em\u003e \u0026lt; .0001). As seen in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, the modified four-factor model fit the SBI data significantly better than the original four-factor model, \u0026Delta;\u0026chi;\u003csup\u003e2\u003c/sup\u003e(1)\u0026thinsp;=\u0026thinsp;57.94, \u003cem\u003ep\u003c/em\u003e \u0026lt; .0001, \u003cem\u003ew\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.21, and provided a reasonable measurement model for the Italian SBI (RMSEA and SRMR \u0026lt; .08, fit indices \u0026gt; .92).\u003c/p\u003e\n\u003cp\u003eHowever, inspection of the CFA solution for Model 5 revealed that when allowing SBI item 12 to cross-load on the Savoring the Moment factor, the completely standardized loading of this item on the Reminiscence factor was dramatically reduced from \u0026minus;\u0026thinsp;.35 in \u003cem\u003eModel 4\u003c/em\u003e (i.e., 12% variance explained), \u003cem\u003ez\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5.81, \u003cem\u003ep\u003c/em\u003e \u0026lt; .0001, to a nonsignificant value of \u0026minus;\u0026thinsp;.08 in \u003cem\u003eModel 5\u003c/em\u003e (i.e., \u0026lt; 1% variance explained), \u003cem\u003ez\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.34, \u003cem\u003ep\u003c/em\u003e = .18. Clearly, scoring low on negatively-worded item 12 (i.e., rejecting the notion that one often gets sad or disappointed when reminiscing about pleasant memories) is more diagnostic of the ability to savor the moment than of the ability to savor past positive memories in the Italian data.\u003c/p\u003e\n\u003cp\u003eBased on the fact that the loading of SBI item 12 on its intended Reminiscence factor disappeared when allowing item 12 also to load on the Savoring the Moment factor in Model 5, we decided to estimate a final version of the four-factor model that constrained SBI item 12 to load only on the Savoring the Moment factor (Model 6). As seen in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, the resulting CFA model demonstrated comparable fit to Model 5, \u0026Delta;\u0026chi;\u003csup\u003e2\u003c/sup\u003e(1, \u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;276)\u0026thinsp;=\u0026thinsp;1.69, \u003cem\u003ep\u003c/em\u003e = .19, \u003cem\u003ew\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.08 (RMSEA = .078, SRMR = .076, CFI = .92, NNFI = .91), but offered a more parsimonious structure and a lower AIC.(Model 6 also avoids inflating the correlation between the Savoring the Moment and Reminiscence composite subscales as a result of the item cross-loading.) The standardized loading of SBI item 12 on Savoring the Moment was \u0026minus;\u0026thinsp;.54, \u003cem\u003ez\u003c/em\u003e\u0026thinsp;=\u0026thinsp;9.44, \u003cem\u003ep\u003c/em\u003e \u0026lt; .0001. Thus, when forcing item 12 to load on only one or the other factor, more than twice as much of its variance reflects \u003cem\u003epresent\u003c/em\u003e-focused savoring ability (29% in Model 6), as opposed to \u003cem\u003epast\u003c/em\u003e-focused savoring ability (12% in Model 4).\u003c/p\u003e\n\u003cp\u003eConfirming the cross-sample generalizability of Model 6, imposing the final four-factor model on the data of the Confirmation sample (\u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;277) produced goodness-of-fit statistics that were comparable to those of the Development sample. As a final step in measurement modeling, imposing this final four-factor model on the data of the full sample (\u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;553) likewise produced acceptable model fit (see Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Note that the final four-factor model (Model 6) has the same \u003cem\u003edf\u003c/em\u003e as the initial four-factor model (Model 4), but provides a superior goodness-of-fit in terms of a lower \u0026chi;\u003csup\u003e2\u003c/sup\u003e (951.51 vs. 1047.39), lower RMSEA (.076 vs. .082), lower SRMR (.073 vs. .077), higher CFI (.93 vs. .92), higher NNFI (.92 vs. .91), and lower AIC (1119.30 vs. 1245.32). Thus, we have chosen the final four-factor model as the measurement model for the Italian SBI.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n\u003ch2\u003eAnalysis of Estimated Parameters in the Final Four-Factor Model\u003c/h2\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e displays the completely standardized factor loadings (i.e., when standardizing factors as well as items), squared multiple correlations for items (i.e., the proportion of variance that the model explains in each item), and factor intercorrelations from the final four-factor CFA model for the Italian SBI. Standardized absolute values of factor loadings of the SBI items on their intended savoring factors were moderate overall (\u003cem\u003eM\u003c/em\u003e = .57, \u003cem\u003eMdn\u003c/em\u003e = .55, \u003cem\u003erange\u003c/em\u003e = .23\u0026ndash;.80) and were somewhat larger on the \u003cem\u003eSavoring the Moment\u003c/em\u003e factor (\u003cem\u003eM\u003c/em\u003e = .65, 95% CI [.56, .75], range = .44\u0026ndash;.80) than on the \u003cem\u003eAnticipation\u003c/em\u003e (\u003cem\u003eM\u003c/em\u003e = .49, 95% CI [.34, .64], range = .23\u0026ndash;.75) and \u003cem\u003eReminiscence\u003c/em\u003e (\u003cem\u003eM\u003c/em\u003e = .57, 95% CI [.44, .70], range = .39\u0026ndash;.73) factors.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cp\u003eOn average, the final four-factor CFA model explained 40% of the variance in each SBI item (\u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e range = .07\u0026ndash;.68). Squaring the standardized loadings on the savoring factors, \u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e values were appreciably larger for items reflecting the \u003cem\u003eSavoring the Moment\u003c/em\u003e factor (\u003cem\u003eM\u003c/em\u003e = .52, 95% CI [.38, .66]), compared to items reflecting the \u003cem\u003eAnticipation\u003c/em\u003e (\u003cem\u003eM\u003c/em\u003e = .32, 95% CI [.18-.46]) or \u003cem\u003eReminiscence\u003c/em\u003e (\u003cem\u003eM\u003c/em\u003e = .37, 95% CI [.27, .46]) factors. Following Worthington and Whittaker\u0026rsquo;s (\u003cspan class=\"CitationRef\"\u003e2006\u003c/span\u003e) guidelines for scale development, three of the 24 SBI items (i.e., 1, 2, and 22)\u0026mdash;each designed to tap Anticipation\u0026mdash;had factor loadings \u0026lt; |.40, suggesting some limitations in their ability to adequately reflect future-focused savoring beliefs within the Italian sample.\u003c/p\u003e\n\u003cp\u003eConsistent with the notion that negatively-anchored items are potentially confusing to respondents (Garrido et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e; Weijters \u0026amp; Baumgartner, \u003cspan class=\"CitationRef\"\u003e2012\u003c/span\u003e), \u003cem\u003enegatively\u003c/em\u003e-worded items had somewhat lower absolute standardized loadings (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.52, 95% CI [-.42, \u0026minus;\u0026thinsp;.62], mean \u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e = .27) on their respective savoring factors, compared to \u003cem\u003epositively\u003c/em\u003e-worded items (\u003cem\u003eM\u003c/em\u003e = .63, 95% CI [.54, .72], mean \u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e = .40), even after controlling for the effects of the negative method factor. Standardized loadings of the negatively-worded items on the negative method factor were moderate in size (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.34, \u003cem\u003eMdn\u003c/em\u003e = .36, range\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.13 \u0026ndash; \u0026minus;\u0026thinsp;.46), indicating that on average roughly 12% of the variance in responses to the negatively-worded items was method-specific (i.e., mean squared standardized loading on method factor = .12).\u003c/p\u003e\n\u003cp\u003eAs hypothesized, the three savoring factors were moderately intercorrelated (\u003cem\u003er\u003c/em\u003es = .42\u0026ndash;.59; see Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). Anticipation and Savoring the Moment shared 20% of their variance (i.e., .45\u003csup\u003e2\u003c/sup\u003e); Anticipation and Reminiscence shared 35% of their variance (i.e., .59\u003csup\u003e2\u003c/sup\u003e); and Reminiscence and Savoring the Moment shared 18% of their variance (i.e., .42\u003csup\u003e2\u003c/sup\u003e). Thus, 65\u0026ndash;82% of the variance in each factor is independent of the variance of the other two savoring factors, supporting the distinctiveness of the three temporal forms of savoring ability as separate constructs.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n\u003ch2\u003eAssessing the Construct Validity of the Italian SBI\u003c/h2\u003e\n\u003cp\u003eIn the final stage of the data analysis, we tested \u003cem\u003ea priori\u003c/em\u003e hypotheses designed to evaluate the convergent and discriminant validity of the three savoring factors in the Italian SBI. First, we used \u003cem\u003ecorrelational analyses\u003c/em\u003e to: (a) assess the convergent and discriminant validity of SBI total score and subscale scores in relation to the six criterion measures; and (b) test the hypothesis that the Savoring the Moment subscale would correlate more strongly than the Anticipation and Reminiscence subscales with the six criterion measures. Second, we used \u003cem\u003emultiple regression analyses\u003c/em\u003e to test the hypotheses that: (a) Savoring the Moment would show stronger unique relationships with the criterion measures than the Anticipation and Reminiscence subscales when controlling for the effects of the other two subscales; and (b) each SBI subscale would show a different pattern of relationships with the three savoring factors, when predicting scores on individual criterion measures. Finally, we tested for hypothesized differences in levels of savoring ability across the three SBI subscales \u003cem\u003ewithin\u003c/em\u003e individuals and \u003cem\u003ebetween\u003c/em\u003e men and women.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConstructing Composite Measures.\u003c/strong\u003e In assessing the convergent and discriminant validity of the Italian SBI, we first reverse-scored the negatively-worded SBI items and then computed mean scores for unit-weighted composite measures of: (a) the Anticipation, Savoring the Moment, and Reminiscence subscales, and SBI Total score; and (b) the criterion measures of life satisfaction, flourishing, happiness, mindfulness, positive affect, and negative affect.\u003c/p\u003e\n\u003cp\u003eWe constructed two versions of the Savoring the Moment and Reminiscence subscales: an 8-item original version based on Bryant (\u003cspan class=\"CitationRef\"\u003e2003\u003c/span\u003e), and an Italian version (9 items for Savoring the Moment, 7 for Reminiscence) based on the final four-factor CFA model. The correlation between the original and Italian versions was .99 for Savoring the Moment (94% shared variance) and .97 (98% shared variance) for Reminiscing. We used only the Italian versions of the SBI subscales in our validity analyses.\u003c/p\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e displays descriptive statistics (means and standard deviations), internal consistency reliability coefficients (Cronbach\u0026rsquo;s \u0026alpha;s), intercorrelations, and pairwise sample sizes, for these composite measures. As seen in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e, internal consistency reliabilities ranged from \u003cem\u003eacceptable\u003c/em\u003e (for Anticipation, \u0026alpha;\u0026thinsp;=\u0026thinsp;.72; for Reminiscence, \u0026alpha;\u0026thinsp;=\u0026thinsp;.77) to \u003cem\u003egood\u003c/em\u003e (for Savoring the Moment, \u0026alpha;\u0026thinsp;=\u0026thinsp;.87; for Total score, \u0026alpha;\u0026thinsp;=\u0026thinsp;.87); reliabilities for the criterion measures were \u003cem\u003egood\u003c/em\u003e and ranged from .84 for happiness and mindfulness to .89 for negative affect. Thus, following Aghaie et al. (2016), all Cronbach\u0026rsquo;s alphas were in the discrete-good range.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorrelational Analyses\u003c/strong\u003e. We first examined correlations to evaluate the convergent and discriminant validity of the three SBI subscales. Supporting \u003cem\u003econvergent\u003c/em\u003e validity, all three SBI subscales correlated positively with life satisfaction, flourishing, happiness, and mindfulness. In addition, the Anticipation and Savoring the Moment subscales correlated positively with positive affect; and the Savoring the Moment subscale correlated negatively with negative affect.\u003c/p\u003e\n\u003cp\u003eWe assessed the \u003cem\u003ediscriminant\u003c/em\u003e validity of the Savoring the Moment subscale, relative to the Anticipation and Reminiscence subscales, by testing the hypothesis that the Savoring the Moment subscale would correlate more strongly than the other two SBI subscales with all six criterion measures. To do this, we first computed a 95% confidence interval (CI) for the correlation between each SBI subscale and each criterion measure (see rows 1\u0026ndash;3 of Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). For each criterion measure, we then determined whether or not (a) the 95% CI of its correlation with the Savoring the Moment subscale overlapped with (b) the 95% CIs of its correlations with each of the other two SBI subscales. Correlations with nonoverlapping 95% CIs were significantly different at \u003cem\u003ep\u003c/em\u003e \u0026lt; .05 (see Tryon, \u003cspan class=\"CitationRef\"\u003e2001\u003c/span\u003e). Supporting discriminant validity, the Savoring the Moment subscale correlated more strongly with life satisfaction, flourishing, happiness, and mindfulness than did the Anticipation or Reminiscence subscales (\u003cem\u003ep\u003c/em\u003es \u0026lt; .05). Contrary to our hypothesis, the 95% CIs of the correlations of all three SBI subscales with positive affect had overlapping 95% CIs, as did the correlations of all three SBI subscales with negative affect, indicating a lack of discriminant validity for the SBI subscales. (We note that the correlations with positive and negative affect had much smaller sample sizes, compared to correlations with other criterion measures, making their 95% CIs much wider and reducing power to detect nonoverlapping CIs.)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMultiple Regression Analyses.\u003c/strong\u003e In a second set of validity analyses, we used multiple regression to examine the independent relationships of each SBI subscale with each criterion measure when controlling for the associations of the other two SBI subscales (see Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). To assess multicollinearity in these analyses, we examined each predictor\u0026rsquo;s variance inflation factor (VIF). Following Neter, Wasserman, and Kutner (\u003cspan class=\"CitationRef\"\u003e1990\u003c/span\u003e), multicollinearity was not as issue, given that the VIFs for all predictors in each analysis were well below 10 (range\u0026thinsp;=\u0026thinsp;1.20\u0026ndash;1.36).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cp\u003eAs hypothesized, when controlling for the effects of the other two subscales, the Savoring the Moment subscale showed the strongest and most consistent unique relationships with the six criterion measures, compared to the Anticipation and Reminiscence subscales. Further supporting the discriminant validity of the three SBI subscales, each subscale showed a different pattern of relationships with the six criterion measures when controlling for the other two subscales (see Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). Specifically, Savoring the Moment uniquely predicted all six criterion measures, Anticipation uniquely predicted only Flourishing, and Reminiscence had no unique relationships with the criterion measures. The absence of unique associations for Reminiscence suggests that it does not provide predictive information over and above the other SBI subscales for this set of validational measures.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnalyses of Within-Person Differences in Savoring Ability across Subscales.\u003c/strong\u003e As an additional test of the discriminant validity of the Italian SBI, we examined hypothesized differences in levels of savoring beliefs within individuals. In assessing the discriminant validity of the original SBI factors, Bryant (\u003cspan class=\"CitationRef\"\u003e2003\u003c/span\u003e) found that scores on the Reminiscing subscale were significantly higher than on the other two temporal subscales, and scores on the Savoring the Moment subscale were significantly higher than were scores on the Anticipating subscale.\u003c/p\u003e\n\u003cp\u003eConfirming hypotheses, pairwise \u003cem\u003et\u003c/em\u003e-tests using the present data revealed that subscale scores on Reminiscence were higher than on both Savoring the Moment, \u003cem\u003et\u003c/em\u003e(552)\u0026thinsp;=\u0026thinsp;13.12, \u003cem\u003ep\u003c/em\u003e \u0026lt; .0001, \u003cem\u003ed\u003c/em\u003e = .56, and Anticipation, \u003cem\u003et\u003c/em\u003e(552)\u0026thinsp;=\u0026thinsp;7.25, \u003cem\u003ep\u003c/em\u003e \u0026lt; .0001, \u003cem\u003ed\u003c/em\u003e = .31, subscales. Contrary to expectation, however, scores on the Savoring the Moment subscale were \u003cem\u003elower\u003c/em\u003e than on the Anticipation subscale, \u003cem\u003et\u003c/em\u003e(552)\u0026thinsp;=\u0026thinsp;7.59, \u003cem\u003ep\u003c/em\u003e \u0026lt; .0001, \u003cem\u003ed\u003c/em\u003e = .32. Thus, whereas the original American sample felt more capable of savoring the moment than savoring through anticipation, the opposite was true for the Italian sample. Nevertheless, these within-person differences in levels of savoring ability across the three temporal forms of savoring support the discriminant validity of the Italian SBI.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\n\u003ch2\u003eAssessing Gender Invariance of the Final-Four Factor Model\u003c/h2\u003e\n\u003cp\u003eThe issue of measurement invariance concerns whether an instrument, such as the SBI, functions comparably across different groups of people. Although composite scores are often used to compare levels of responses across different groups, these analyses of mean differences assume that the scores being contrasted are in fact comparable across groups. Three types of measurement invariance are relevant and can be assessed using nested multigroup CFA in a series of progressively more restrictive hypotheses about group equality in the pattern (configural invariance) and magnitude (metric invariance) of factor loadings, and in the magnitude of item intercepts (scalar invariance) (see Vandenberg \u0026amp; Lance, \u003cspan class=\"CitationRef\"\u003e2000\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eConfigural\u003c/em\u003e invariance exists if the same model provides an acceptable fit to the data of different groups. Assuming that configural invariance holds, then \u003cem\u003emetric\u003c/em\u003e invariance exists if constraining each item\u0026rsquo;s factor loading to be equal across groups does not worsen model fit, compared to separately estimating loadings for each group. A lack of metric invariance would indicate that one or more factors have a different meaning across groups, preventing valid between-group comparisons of subscale scores for these noninvariant factors.\u003c/p\u003e\n\u003cp\u003eAssuming that metric invariance holds, then \u003cem\u003escalar\u003c/em\u003e invariance exists if constraining each item\u0026rsquo;s intercept to be equal across groups (when fixing factor means to zero) does not worsen model fit, compared to estimating intercepts separately for each group. Differences in item intercepts when fixing factor means to zero in each group would reflect instances of differential item functioning (McDonald, \u003cspan class=\"CitationRef\"\u003e1999\u003c/span\u003e) that indicate these items produce different mean responses for members of different groups who have the same value on the underlying factor. In this case, group differences in observed subscale scores would reflect not only true differences in the underlying latent factor but also group-specific biases in how people use the measurement scale.\u003c/p\u003e\n\u003cp\u003eBecause we wanted to examine potential gender differences in levels of savoring ability using the Italian SBI, we evaluated the gender invariance of loadings on the three savoring factors (but not loadings on the negative method factor). In testing metric and scalar invariance, we assessed the size of the difference in CFI values across nested models, with difference in the CFIs (\u0026Delta;CFI) \u0026le; .01 considered evidence of measurement invariance (Cheung \u0026amp; Rensvold, \u003cspan class=\"CitationRef\"\u003e1999\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eSeparate single-group CFAs demonstrated that the final four-factor model provided an acceptable goodness-of-fit for both the male and female data (configural invariance). In addition, multigroup CFA tests of gender invariance revealed that males and females had comparable loadings on all three savoring factors, \u0026Delta;CFI = .0005, and comparable intercepts for all 24 items, \u0026Delta;CFI = .0065 (i.e., changes in model CFI across nested models fell below the .01 threshold for inferring noninvariance). These results indicate that the items in the final four-factor model function comparably for men and women, thus enabling meaningful comparisons of subscale scores between groups.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\n\u003ch2\u003eAssessing Gender Differences in Savoring Beliefs\u003c/h2\u003e\n\u003cp\u003eBoth the original SBI (Bryant, \u003cspan class=\"CitationRef\"\u003e2003\u003c/span\u003e) as well as cross-cultural adaptations of the SBI in Hungary (Nagy et al, \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e), Japan (Kawakubo et al., \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e), and Korea (Kim \u0026amp; Bryant, \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e) produced subscales or global scales on which females reported higher mean scores than males. Based on these findings and on the notion that women are typically more expressive of their feelings and tend to have a richer inner life than men (Bryant \u0026amp; Veroff, \u003cspan class=\"CitationRef\"\u003e2007\u003c/span\u003e), we hypothesized than females would score higher than males on the Italian SBI subscales and total score.\u003c/p\u003e\n\u003cp\u003ePartially supporting our hypothesis, females had higher scores than males on: (a) the \u003cem\u003eAnticipation\u003c/em\u003e subscale (females: \u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5.00, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.86; males: \u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;4.79, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.88), \u003cem\u003et\u003c/em\u003e(546)\u0026thinsp;=\u0026thinsp;2.64, \u003cem\u003ep\u003c/em\u003e \u0026lt; .01, \u003cem\u003ed\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.25; (b) the \u003cem\u003eReminiscence\u003c/em\u003e subscale (females: \u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5.37, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.83; males: \u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;4.94, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.98), \u003cem\u003et\u003c/em\u003e(547)\u0026thinsp;=\u0026thinsp;5.28, \u003cem\u003ep\u003c/em\u003e \u0026lt; .0001, \u003cem\u003ed\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.49; and (c) \u003cem\u003eSBI total score\u003c/em\u003e, (females: \u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;4.95, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.75; males: \u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;4.76, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.77), \u003cem\u003et\u003c/em\u003e(546)\u0026thinsp;=\u0026thinsp;2.70, \u003cem\u003ep\u003c/em\u003e \u0026lt; .01, \u003cem\u003ed\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.25. But there was no gender difference on the \u003cem\u003eSavoring the Moment\u003c/em\u003e subscale (females: \u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;4.95, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.75; males: \u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;4.76, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.77), \u003cem\u003et\u003c/em\u003e(546)\u0026thinsp;=\u0026thinsp;0.15, \u003cem\u003ep\u003c/em\u003e = .88, \u003cem\u003ed\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.01. This pattern of results provides further support for the discriminant validity of the Italian SBI.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present study adds to existing literature on positive emotion regulation by developing an Italian version of the Savoring Beliefs Inventory (SBI) and examining its psychometric properties in a sample of Italian young adults. \u003cem\u003eSavoring\u003c/em\u003e has been defined as the ability to attend to, appreciate, and increase the positive experiences that occur in one\u0026rsquo;s life (Bryant \u0026amp; Veroff, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) and several studies have provided evidence that this capacity represents a critical factor for the individual\u0026rsquo;s well-being (e.g., Boelen, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Ford et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Growney et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Smith \u0026amp; Bryant, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). While the SBI was originally developed in the United States as an instrument to measure individual differences in the (self-reported) ability to savor positive experiences (Bryant, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2003\u003c/span\u003e), a growing body of research has recently developed cross-cultural adaptations of the original English scale in numerous languages, including for instance French (Golay et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), Japanese (Kawakubo et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), and Russian (Titova et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). To the best of our knowledge, however, there is no evidence of the validity and reliability of the SBI in the Italian context.\u003c/p\u003e \u003cp\u003eTo achieve our research goals, we first used confirmatory factor analysis (CFA) to assess the goodness-of-fit of four alternative, \u003cem\u003ea priori\u003c/em\u003e measurement models for the Italian SBI data. According to the theoretical conceptualization of savoring (Bryant, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2003\u003c/span\u003e), the construct is multidimensional in its nature, comprising three interrelated temporal orientations (i.e., anticipation, savoring the moment, and reminiscence) through which people regulate their positive emotions in a given moment. Consistent with theory and with most studies that have tested the factorial structure of the SBI (Aghaie et al., 2016; Golay et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Kawakubo et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Limp\u0026auml;cher \u0026amp; Hoyer, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2026\u003c/span\u003e; Titova et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; for an exception see Metin-Orta, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), our results revealed that the three-factor measurement model provided a better representation of responses to the Italian SBI than a unidimensional model. These results suggest that Italian respondents make separate self-evaluations of their ability to savor positive experience concerning the three assumed temporal orientations.\u003c/p\u003e \u003cp\u003eNonetheless, as found in previous studies (Bryant, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Kawakubo et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Limp\u0026auml;cher \u0026amp; Hoyer, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2026\u003c/span\u003e), we also observed that the five-factor solution provided a better fit to the Italian data than the three-factor one, supporting the need to include separate method factors in the measurement model that reflect the variation in responses due to either positive or negative item wording. In this regard, several studies using different instruments have repeatedly shown that using both positively- and negatively-worded items in a questionnaire can introduce significant method effects and that this source of variance has to be accounted for to avoid inaccurate conclusions about the validity and reliability of a scale (e.g., Garrido et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Lindwall et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Zeng et al., \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBecause the inspection of the five-factor solution (i.e., Anticipation, Savoring the Moment, and Reminiscence, plus a Positive and Negative Method factor) revealed anomalous parameter estimates (i.e., null correlations among the theoretical factors), in subsequent steps of analysis, we tested a more parsimonious, four-factor model that included the Negative Method factor only (Titova et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The results showed that this model provided better fit compared to the others, suggesting stronger support for the method effect of negatively-worded items compared to the effect associated with positively-worded items. In other words, participants exhibited a systematic response style in which they differentiated less among temporal orientations when answering negatively-worded items, producing more uniform responses across the three temporal dimensions of savoring for these items. Although some research has shown that negatively-worded items often create stronger method effects than positively-worded items (DiStefano \u0026amp; Motl, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), it is generally agreed that the direction in which valence of wording impacts the strengths of method effects can depend on a number of variables, such as the specific scale, population, and cultural context (Lindwall et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Zeng et al., \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Of note, however, in our results, standardized factor loadings on the Negative Method factor were overall moderate in size and a small proportion (around 12%) of the variance in responses to the negatively-worded items was method-specific.\u003c/p\u003e \u003cp\u003eAlthough the four-factor solution appeared to provide the best fit to the Italian data, we observed that SBI item 12 (\u003cem\u003efeeling disappointed when reminiscing\u003c/em\u003e) cross loaded on the Savoring the Moment factor. Adequate fit was achieved after the model was respecified and item 12 was allowed to load on Savoring the Moment rather than on its intended Reminiscence factor. Thus, it seems that in the Italian sample, experiencing negative emotions such as sadness and disappointment when reminiscing about pleasant memories is more indicative of a low capacity for \u003cem\u003epresent\u003c/em\u003e-focused savoring than an inability to engage in \u003cem\u003epast\u003c/em\u003e-focused savoring.\u003c/p\u003e \u003cp\u003eAlthough recalling pleasant autobiographical memories is a well-established method for boosting positive affect (Bryant et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Joseph et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), recent research has shown that reminiscing about good times that are gone and cannot be repeated may lead to the experience of mixed emotions such as happiness and sadness because of a sense of \u0026ldquo;no-longer-having\u0026rdquo; those good times in the present (Larsen et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Likewise, it has been suggested that making unfavorable comparisons between past happy memories and current life circumstances may decrease rather than enhance positive affect (Nelis et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Along this line of reasoning, SBI item 12 may reflect a form of nostalgic rumination that can hinder the ability to savor the present moment. Specifically, an excessive focus on pleasant past positive events (i.e., \u0026ldquo;how great things were\u0026rdquo;) can induce disappointment or a sense of loss, causing an individual to overlook and undervalue current positive experiences. Of note, other validation studies have found low (\u0026lt;. |40|) factor loadings for this item: \u0026minus;\u0026thinsp;.35 (Bryant, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2003\u003c/span\u003e), \u0026minus;\u0026thinsp;.38 (Golay et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), \u0026minus;\u0026thinsp;.26 (Titova et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe finding that not feeling sad or disappointed when reminiscing has more to do with \u003cem\u003epresent\u003c/em\u003e-focused savoring ability than \u003cem\u003epast\u003c/em\u003e-focused savoring ability is consistent with the notion that enjoying the process of sharing pleasant memories with others is closely related to savoring the moment in Italian culture. Along these lines, Italian culture has traditionally emphasized strong social connections and shared celebration, with Italian society \u0026ldquo;characterized by a deep sense of community and interconnectedness\u0026rdquo; (Lo Bianco \u0026amp; Schatman, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, p. 2939). In this regard, Italians have a long-standing oral tradition of sharing stories and reminiscing about past events with loved ones during social gatherings as a way to strengthen bonds, enhance the present moment, and foster a sense of belonging (Timpanelli, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). Viewed from this perspective, it makes sense that disavowing negative feelings associated with reminiscing is a sign of being fully able to appreciate present positive experiences for Italians.\u003c/p\u003e \u003cp\u003eBut why does SBI item 12 reflect Savoring the Moment more strongly than the other measured indicators of Reminiscence? We note that the other Reminiscence items predominantly focus on solitary, intrapersonal experiences in which one generates positive feelings by \u003cem\u003ethinking about pleasant memories\u003c/em\u003e by oneself. This focus is evident in both \u003cem\u003epositively-worded\u003c/em\u003e items (item 3: \u0026ldquo;I enjoy looking back on\u0026hellip;my past\u0026rdquo;; item 9: \u0026ldquo;I can make myself feel good by remembering\u0026hellip;my past; item 15: \u0026ldquo;I like to store memories\u0026hellip;so I can recall them later\u0026rdquo;; item 21: \u0026ldquo;It\u0026rsquo;s easy for me to rekindle the joy from pleasant memories\u0026rdquo;), as well as \u003cem\u003enegatively\u003c/em\u003e-worded items (item 6: \u0026ldquo;I don\u0026rsquo;t like to look back on good times from the past\u0026hellip;\u0026rdquo;; item 18: \u0026ldquo;Thinking about...the past is basically a waste of time\u0026rdquo;). As opposed to items that emphasize thinking about or remembering positive memories, SBI item 12 is the only Reminiscence indicator that focuses on how respondents feel when they \u0026ldquo;reminisce,\u0026rdquo; which we argue encompasses the interpersonal behavior of sharing memories with others during social occasions.\u003c/p\u003e \u003cp\u003eStandardized absolute values of factor loadings of the SBI items on their intended savoring factors were moderate and \u0026ndash; although some items of the Anticipation subscale (i.e., items 1, 4, and 22) showed weak factor loadings \u0026ndash; overall they were comparable with prior research. Since other studies have observed low values in standardized factor loadings of some items (e.g., items 1, 7, 12, 22; Aghaie et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Bryant, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Kawakubo et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Titova et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), we retained all items to facilitate cross-cultural comparisons. We believe that future studies with more representative samples are needed to replicate these findings and to evaluate whether these items should be modified or replaced by new items that are more reliable indicators of future-focused savoring beliefs in Italian samples. Finally, consistent with prior research and hypotheses, the three savoring factors were moderately intercorrelated (e.g., Bryant, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Titova et al., 2020), thus supporting the distinctiveness of the three temporal forms of savoring ability as conceptually related but separate constructs. The results also revealed that the three temporal subscales of the Italian adaptation of the SBI (as well as SBI Total score) have acceptable levels of reliability in terms of internal consistency, as Cronbach\u0026rsquo;s α coefficients were in the discrete-good range (Aghaie et al., 2016). Although the SBI is best conceptualized as a multidimensional measure reflecting distinct temporal facets of savoring, concerns may arise regarding the use of a Total score when a one-factor model does not optimally represent the data. Nevertheless, as noted by Limp\u0026auml;cher and Hoyer (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2026\u003c/span\u003e), the use of a composite score may still be justified for pragmatic reasons\u0026mdash;such as comparability with prior research and applicability in clinical contexts\u0026mdash;while acknowledging that the subscales provide more differentiated information and remain preferable for theory-driven analyses.\u003c/p\u003e \u003cp\u003eConcerning convergent validity of the Italian SBI, all three SBI subscales were significantly and positively associated with criterion measures of well-being, such as life satisfaction (Aghaie et al., 2016; Limp\u0026auml;cher \u0026amp; Hoyer, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2026\u003c/span\u003e; Titova et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), happiness (Bryant, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Kawakubo et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Titova et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), and flourishing, as well as with dispositional mindfulness (Cheung \u0026amp; Ng, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Kiken et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The ability to savor the moment was also associated with higher positive affect and lower negative affect (Titova et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2022\u003c/span\u003e); in contrast, anticipation correlated with greater positive affect only, while reminiscence was uncorrelated with dispositional emotion. Likewise, the results concerning the 95% confidence intervals (\u003cem\u003eCI\u003c/em\u003es) for the correlations and the regression analyses overall confirmed our hypothesis regarding the discriminant validity of the temporal savoring factors: The ability to savor the moment predicted higher life satisfaction, happiness, positive affect, dispositional mindfulness, and lower negative affect above and beyond reminiscence and anticipation facets of savoring (Bryant, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2003\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Kawakubo et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Titova et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The ability to anticipate positive experiences that may happen in the future contributed (together with savoring the moment) to higher levels flourishing, whereas the ability to savor through reminiscence did not show any differential association with these measures. In contrast, after partialing out the variance in reminiscence scores that is shared with the other two SBI facets, the remaining variance in Reminiscence was associated (though not significantly) with lower levels of happiness and positive affect.\u003c/p\u003e \u003cp\u003eAdding evidence in support of the discriminant validity of the Italian SBI, our results revealed within-person differences in levels of savoring ability across the three temporal forms of savoring. In particular, when asked to rate their savoring capacities, Italian respondents reported being most capable of savoring through reminiscence, moderately capable of savoring through anticipation, and least capable of savoring the moment. This pattern of results is roughly consistent with those found in the original construction of the scale (Bryant, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Finally, we examined gender differences in levels of savoring ability across subscales. The results of separate single-group and multi-group CFA provided evidence of measurement invariance across gender, thus enabling meaningful comparisons of subscale scores between the male and female groups. Consistent with previous research (Bryant, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Kawakubo et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Titova et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), we found that Italian females reported higher scores than males on the ability to savor through reminiscence and anticipation; however, no significant difference emerged in the ability to savor the moment. Although most studies conducted so far have consistently found that females tend to report higher levels of savoring abilities than males across all three savoring facets, other studies conducted in the European context have failed to observe gender differences (Golay et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Limp\u0026auml;cher \u0026amp; Hoyer, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2026\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOverall, these findings support the construct validity of the Italian SBI as a measure of savoring beliefs about anticipating, savoring the moment, and reminiscing among Italian adults. Our study provides evidence that the Italian SBI can become a reliable and useful instrument with sound psychometric properties for basic and applied research. In this regard, the developed Italian adaptation of the SBI could be helpful to expand existing studies in the Italian context to deepen our understanding of the role of savoring capacities for enhancing or maintaining individuals\u0026rsquo; well-being (Colombo et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and in developing interventions to improve people\u0026rsquo;s capacity to value positive events (Villani et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eLimitations and Future Directions\u003c/h2\u003e \u003cp\u003eSeveral limitations are worth considering and could be the focus of future studies. First, a potential source of bias is the non-representative nature of our sample, which was predominantly female and limited to young adults. Although other studies examining the psychometric properties of the SBI have focused on the young population (e.g., Aghaie et al., 2016; Bryant, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2003\u003c/span\u003e Studies 1\u0026ndash;5; Golay et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Mertin-Orta, 2018), future research involving a more representative sample of the Italian-Speaking population is needed to establish the generalizability of our results with respect to reliability, factor structure, and construct validity. Further research on the psychometric properties of this measure could also include clinical groups, such as people diagnosed with depression (Limp\u0026auml;cher \u0026amp; Hoyer, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2026\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAnother limitation of the present study concerns the use of nonindependent samples to develop and confirm the final measurement model of the Italian SBI, which limits its cross-sample generalizability. As we noted above commenting on the items that showed weak standardized factor loadings, future work is needed to collect data with independent samples to replicate the final four-factor model. Additionally, to further validate the Italian version of the SBI, test-retest reliability should be assessed to provide information about the temporal stability of the measurement of the construct.\u003c/p\u003e \u003cp\u003eLast, we used self-report measures only as criteria in evaluating the construct validity of the Italian SBI, which is also a self-report measure. Future studies should thus possibly include a wider array of validational criterion measures, such as behavioral and neuropsychological criterion measures, to move beyond self-report measures.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. Material preparation and data collection were performed by EP, DV, SB. Data analysis were performed by SB, FBB. The first draft of the manuscript was written by FBB and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eThe dataset generated and analyzed during this study is available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAghaie, E., Roshan, R., Mohamadkhani, P., Shaeeri, M., \u0026amp; Gholami-Fesharaki, M. (2017). Factor analysis and psychometric characteristics of the Persian version of the Savoring Belief Inventory (SBI). \u003cem\u003eAvicenna Journal of Neuropsychophysiology\u003c/em\u003e, 4(1), e58768.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAkaike, H. (1973). Information theory and an extension of the maximum likelihood principle. In B. N. Petrov \u0026amp; F. Cs\u0026aacute;ki (Eds.), \u003cem\u003e2nd international symposium on information theory\u003c/em\u003e (pp. 267\u0026ndash;281). 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The method effects in the Undergraduate Learning Burnout Scale. \u003cem\u003eFrontiers in Psychology\u003c/em\u003e, \u003cem\u003e11\u003c/em\u003e, 585179.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e \u003cem\u003eDescriptive statistics, internal consistency reliability coefficients, and correlations among composite measures\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"859\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStudy Measures\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eM\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eSD\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eN\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026alpha;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSBI MOM\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSBI REM\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSBI TOT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSAT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFLOUR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHAPP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMIND\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eSBI Anticipation\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e4.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e553\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e.40\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(553)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e.44\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(553)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003e.75\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(553)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e.29\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e[.19, .38]\u003c/p\u003e\n \u003cp\u003e(351)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e.35\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e[.26, .43]\u003c/p\u003e\n \u003cp\u003e(412)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e.31\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e[.19, .41]\u003c/p\u003e\n \u003cp\u003e(260)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e.14\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e[.01, .26]\u003c/p\u003e\n \u003cp\u003e(226)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e.27\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e[.06, .47]\u003c/p\u003e\n \u003cp\u003e(79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e-.09\u003csup\u003e\u0026nbsp;ns\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e[-.31, .13]\u003c/p\u003e\n \u003cp\u003e(78)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eSBI Momentary\u003c/p\u003e\n \u003cp\u003e(SBI MOM)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e4.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e1.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e553\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e.36\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(553)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003e.84\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(553)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e.55\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e[.48, .62]\u003c/p\u003e\n \u003cp\u003e(351)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e.58\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e[.51, .64]\u0026nbsp;(412)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e.73\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e[.66, .78]\u0026nbsp;(260\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e.44\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e[.33, .54]\u0026nbsp;(226)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e.30\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e[.08, .49]\u0026nbsp;(79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e-.38\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e[-.55, -.17]\u0026nbsp;(78)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eSBI Reminiscence\u003c/p\u003e\n \u003cp\u003e(SBI REM)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e5.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e553\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003e.71\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(553)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e.20\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e[.10, .30]\u0026nbsp;(351)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e.31\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e[.22, .39]\u0026nbsp;(413)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e.21\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e[.09, .32]\u0026nbsp;(261)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e.18\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e[.05, .30]\u0026nbsp;(226)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;-.01\u003csup\u003ens\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e[-.22, .21]\u0026nbsp;(79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e-.01\u003csup\u003ens\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e[-.21, .23]\u0026nbsp;(78)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eSBI Total score\u003c/p\u003e\n \u003cp\u003e(SBI TOT)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e4.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e553\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e.50\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(351)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e.57\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(412)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e.59\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(260)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e.37\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(226)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e.27\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e-.23\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(78)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eSatisfaction with Life\u003c/p\u003e\n \u003cp\u003e(SAT)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e4.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e1.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e352\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e.68\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(299)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e.68\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(145)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e.27\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(142)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e.46\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e-.33\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(78)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eFlourishing\u003c/p\u003e\n \u003cp\u003e(FLOURISH)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e5.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e416\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e.61\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(262)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e.26\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(142)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e.50\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e-.22\u003csup\u003ens\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(78)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eSubjective Happiness (HAPP)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e4.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e1.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e263\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e.28\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(141)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003cp\u003e(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003cp\u003e(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eMindfulness\u003c/p\u003e\n \u003cp\u003e(MIND)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e4.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e226\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003cp\u003e(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003cp\u003e(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003ePositive Affect\u003c/p\u003e\n \u003cp\u003e(PA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e3.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e-.11\u003csup\u003ens\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(78)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eNegative Affect\u003c/p\u003e\n \u003cp\u003e(NA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e2.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ens\u003c/sup\u003e \u003cem\u003ep\u003c/em\u003e \u0026gt; .05. \u0026nbsp;\u003csup\u003e*\u003c/sup\u003e \u003cem\u003ep\u003c/em\u003e \u0026lt; .05. \u0026nbsp;\u003csup\u003e**\u0026nbsp;\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e \u0026lt; .01. \u0026nbsp;\u003csup\u003e***\u0026nbsp;\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e \u0026lt; .001.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNote\u003c/em\u003e. \u003cem\u003eM\u003c/em\u003e = mean. \u003cem\u003eSD\u003c/em\u003e = standard deviation.\u0026nbsp;\u003cem\u003eN\u003c/em\u003e = sample size. \u0026alpha; = Cronbach\u0026rsquo;s alpha. SBI Anticipation = SBI Anticipation subscale. SBI MOM = SBI Savoring the Moment subscale. SBI REM = SBI Reminiscence subscale. SBI TOT = SBI Total score. SAT = Satisfaction with Life Scale. FLOURISH = Flourishing Scale. HAPP = Subjective Happiness Scale. MIND = Mindful Attention Awareness Scale. PA = PANAS Positive Affect subscale; NA = PANAS Negative Affect subscale. The 95% confidence interval is tabled in brackets for the correlation between each SBI subscale and each criterion measure. Pairwise sample size is tabled in parentheses for each correlation. All participants completed the SBI, and different subsets of participants completed different sets of criterion measures. None of the participants who completed the Positive and Negative Affect subscales also completed the Happiness or Mindfulness measures.\u0026nbsp;\u003cbr clear=\"all\"\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e \u003cem\u003eGoodness-of-fit statistics from confirmatory factor analysis models for the Italian Savoring Beliefs Inventory\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 329px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCFA Model\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSample\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003edf\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRMSEA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSRMR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCFI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNNFI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAIC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 329px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 1:\u003c/strong\u003e One factor\u003c/p\u003e\n \u003cp\u003e(Global savoring)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003ePooled\u003c/p\u003e\n \u003cp\u003e(\u003cem\u003eN\u003c/em\u003e = 553)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;2224.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e252\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e.146\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e.108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e3329.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 329px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 2:\u003c/strong\u003e Three savoring factors\u003c/p\u003e\n \u003cp\u003e(Anticipation, Savoring the Moment, and Reminiscence)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003ePooled\u003c/p\u003e\n \u003cp\u003e(\u003cem\u003eN\u003c/em\u003e = 553)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;1414.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e249\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e.102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e.089\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e1776.12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 329px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 3:\u003c/strong\u003e Five factors (three savoring factors and Positive and Negative method factors)\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003ePooled\u003c/p\u003e\n \u003cp\u003e(N = 553)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;745.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e224\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e.066\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e.054\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e905.89\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 329px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 4:\u003c/strong\u003e Four factors (three savoring factors and a Negative Method factor)\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003ePooled\u003c/p\u003e\n \u003cp\u003e(N = 553)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;1047.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e237\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e.082\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e.077\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e1245.32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003eDevelopment \u003csup\u003ec\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(N = 276)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;635.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e237\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e.081\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e.080\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e789.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 329px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 5:\u003c/strong\u003e Four factors (three savoring factors and a Negative Method factor) adding a\u003c/p\u003e\n \u003cp\u003ecross-loading for SBI item 12 on the\u003c/p\u003e\n \u003cp\u003eSavoring the Moment factor\u003csup\u003e\u0026nbsp;d\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003eDevelopment\u003c/p\u003e\n \u003cp\u003e(N = 276)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;577.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e236\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e.073\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e.079\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e710.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 329px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 6:\u003c/strong\u003e Four factors (three savoring factors and a Negative Method factor) with SBI item 12 loading on the Savoring the Moment factor instead of on the Reminiscence factor\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003eDevelopment\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e(N = 276)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;579.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e237\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e.073\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e.078\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e709.64\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003eConfirmation\u003c/p\u003e\n \u003cp\u003e(N = 276)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;618.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e237\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e.078\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e.076\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e764.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003ePooled\u003c/p\u003e\n \u003cp\u003e(N = 553)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;951.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e237\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e.076\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e.073\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e1119.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003ea\u0026nbsp;\u003c/sup\u003eAlthough the five-factor model with three savoring factor and separate positive and negative method factors (Model 3) provided an acceptable goodness-of-fit, it produced \u003cem\u003enonsignificant\u003c/em\u003e correlations among the three temporal SBI factors, in contrast to all other multifactor models in which the SBI factors were moderately intercorrelated. These anomalous parameter estimates suggest that the method factors contain variance associated with the savoring factors themselves, and are a sign of an ill-conditioned CFA solution (see Garrido et al., 2025; Marsh, 1989). For this reason, we rejected the five-factor model as a measurement model for responses to the Italian SBI.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003eb\u003c/sup\u003e Although the four-factor model with three temporal savoring factors and a single negative method factor (Model 4) produced the hypothesized significant correlations among the three temporal savoring factors, its RMSEA value exceeded the .08 threshold for acceptable fit, paralleling the misfit of this model for the Russian SBI (Titova et al, 2022).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ec\u003c/sup\u003e To conduct a specification search for a better-fitting measurement model, we randomly split the full sample in half and estimated Model 4 using the data of the first random-half (i.e., the Development sample; \u003cem\u003eN\u003c/em\u003e = 276) and using the data of the second random-half (i.e., the Confirmation sample; \u003cem\u003eN\u003c/em\u003e = 277) to assess the cross-sample generalizability of the final model. We freed the fixed parameter in Model 4 that had the largest model modification index (i.e., the cross-loading of SBI Reminiscence item 12 on the Savoring the Moment factor to create Model 5.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ed\u003c/sup\u003e Inspection of the CFA solution for Model 5 revealed that when SBI item 12 was allowed to cross-load on the Savoring the Moment factor, the Reminiscence factor explained only 1% of the variance in SBI item 12 and the loading of item 12 on the Reminiscence factor was nonsignificant. Thus, we fixed the loading of SBI item 12 on the Reminiscence factor to 0.0 to create Model 6, which we then confirmed using the data of the Confirmation sample, as well as the data of the Pooled sample. Model 6 represent the formal measurement model for the Italian SBI.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNote\u003c/em\u003e. In all CFA models, we fixed the variance of each factor to 1.0, to define the units of variance for the latent variables. In all multi-factor CFA models, the three savoring factors were allowed to intercorrelate. In the five-factor model, the positive and negative method factors were allowed to intercorrelate, but were constrained to be uncorrelated with the three savoring factors. In the four-factor models, the negative method factor was constrained to be uncorrelated with the three savoring factors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u003c/strong\u003e \u003cem\u003eCompletely standardized factor loadings, squared multiple correlations for items, and factor loadings from the final four-factor CFA model for the Italian Savoring Beliefs Inventory\u0026nbsp;\u0026nbsp;\u003c/em\u003e\u003cem\u003e(N = 553)\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 340px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eSBI Items (item numbers)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 168px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSavoring Factors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNegative\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMethod Factor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eR\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eANT\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMOM\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eREM\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 340px;\"\u003e\n \u003cp\u003eGet pleasure from looking forward (SBI 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 340px;\"\u003e\n \u003cp\u003eDon\u0026rsquo;t like to look forward too much (SBI 4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp; -.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 340px;\"\u003e\n \u003cp\u003eCan feel the joy of anticipation (SBI 7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e.56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 340px;\"\u003e\n \u003cp\u003eAnticipating is a waste of time (SBI 10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp; -.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 340px;\"\u003e\n \u003cp\u003eCan enjoy events before they occur (SBI 13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e.48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 340px;\"\u003e\n \u003cp\u003eHard to get excited beforehand (SBI 16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp; -.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e.43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 340px;\"\u003e\n \u003cp\u003eCan feel good by imagining outcome (SBI 19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 340px;\"\u003e\n \u003cp\u003eFeel uncomfortable when anticipate (SBI 22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp; -.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e.36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 340px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 340px;\"\u003e\n \u003cp\u003eKnow how to make the most of good time (SBI 5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e.55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 340px;\"\u003e\n \u003cp\u003eFind it hard to hang onto a good feeling (SBI 2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp; -.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 340px;\"\u003e\n \u003cp\u003eCan prolong enjoyment by own effort (SBI 11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e.64\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 340px;\"\u003e\n \u003cp\u003eAm own \u0026ldquo;worst enemy\u0026rdquo; in enjoying (SBI 8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e-.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e.43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 340px;\"\u003e\n \u003cp\u003eFeel fully able to appreciate good things (SBI 17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e. 66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 340px;\"\u003e\n \u003cp\u003eCan\u0026rsquo;t capture the joy of happy moments (SBI 14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e-.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 340px;\"\u003e\n \u003cp\u003eFind it easy to enjoy self when want to (SBI 23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e.19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 340px;\"\u003e\n \u003cp\u003eDon\u0026rsquo;t enjoy things as much as should (SBI 20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e-.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e.65\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 340px;\"\u003e\n \u003cp\u003eFeel disappointed when reminisce (SBI 12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e-.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 340px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 340px;\"\u003e\n \u003cp\u003eEnjoy looking back on happy times (SBI 3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e\u0026nbsp;.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 340px;\"\u003e\n \u003cp\u003eDon\u0026rsquo;t like to look back afterwards (SBI 6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e\u0026nbsp;-.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 340px;\"\u003e\n \u003cp\u003eCan feel good by remembering past (SBI 9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 340px;\"\u003e\n \u003cp\u003eLike to store memories for later recall (SBI 15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e.45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 340px;\"\u003e\n \u003cp\u003eReminiscing is a waste of time (SBI 18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e\u0026nbsp;-.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 340px;\"\u003e\n \u003cp\u003eEasy to rekindle joy of happy memories (SBI 21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e\u0026nbsp;.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 340px;\"\u003e\n \u003cp\u003eBest not to recall past fun times (SBI 24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e\u0026nbsp;-.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e.29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 342px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFactor Correlations\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eANT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMOM\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 342px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Savoring the Moment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 342px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Reminiscence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e.42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNote\u003c/em\u003e. ANT = Anticipation. MOM = Savoring the Moment. REM = Reminiscence. \u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e = proportion of variance that the model explains in each item. Items have been paraphrased and re-ordered to streamline presentation. Blank loadings were fixed at zero in the CFA model. The negative method factor was constrained to be uncorrelated with the three Savoring factors. All model parameter estimates were statistically significant at \u003cem\u003ep\u003c/em\u003e \u0026lt; .0001.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4\u003c/strong\u003e. \u003cem\u003eResults of multiple regression analyses using the three SBI subscales to predict criterion measures: Standardized coefficients\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 210px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSBI Subscales\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eCriterion Measures\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eN\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eF\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003edf\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eANT\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMOM\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eREM\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003eSatisfaction with Life\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e351\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e52.52\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e3, 347\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;.08\u003csup\u003ens\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;.52\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp; -.01\u003csup\u003ens\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003eFlourishing\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e412\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e75.20\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e3, 408\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;.12\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;.50\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e.07\u003csup\u003ens\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003eSubjective Happiness\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e260\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e99.49\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e3, 256\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;.04\u003csup\u003ens\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;.76\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp; -.13\u003csup\u003ens\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003eMindfulness\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e226\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e17.25\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e3, 222\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-.01\u003csup\u003ens\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;.43\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e.01\u003csup\u003ens\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003ePositive Affect\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e4.20\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e3, 75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e.23\u003csup\u003ens\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e.26\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp; -.19\u003csup\u003e\u0026nbsp;ns\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003eNegative Affect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;4.99\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e3, 74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e.06\u003csup\u003ens\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e-.46\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e.15\u003csup\u003ens\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003ens\u003c/sup\u003e \u003cem\u003ep\u003c/em\u003e \u0026gt; .05. \u0026nbsp;\u003csup\u003e*\u003c/sup\u003e \u003cem\u003ep\u003c/em\u003e \u0026lt; .05. \u0026nbsp;\u003csup\u003e**\u0026nbsp;\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e \u0026lt; .01. \u0026nbsp;\u003csup\u003e***\u0026nbsp;\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e \u0026lt; .001.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNote\u003c/em\u003e. ANT = Anticipation. MOM = Savoring the Moment. REM = Reminiscenc\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","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":"Savoring, savoring beliefs, well-being, positive psychology, Italian adults","lastPublishedDoi":"10.21203/rs.3.rs-8871514/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8871514/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSavoring (i.e., the process of noticing, attending to, and appreciating positive experience) is a critical determinant of positive emotion, and the ability to savor is an important aspect of well-being. The present study reports the development and validation of an Italian-language version of Bryant\u0026rsquo;s (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) Savoring Beliefs Inventory (SBI), which measures individual differences in savoring ability. A large sample of Italian young adults (\u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;553; age range\u0026thinsp;=\u0026thinsp;17\u0026ndash;31) completed the adapted SBI along with measures of life satisfaction, flourishing, happiness, mindfulness, and positive and negative affect. Confirmatory factor analyses were used to develop a four-factor measurement model consisting of separate intercorrelated factors reflecting the ability to savor \u003cem\u003efuture\u003c/em\u003e positive experiences through Anticipation, \u003cem\u003epresent\u003c/em\u003e positive experiences through Savoring the Moment, and \u003cem\u003epast\u003c/em\u003e positive experiences through Reminiscence (along with a negative method factor on which negatively-worded items loaded). Analyses supported the reliability, convergent and discriminant validity, and gender invariance of the three SBI subscales. These results provide evidence that the Italian SBI is a valid and reliable measure of individuals\u0026rsquo; beliefs about their ability to savor positive experience.\u003c/p\u003e","manuscriptTitle":"Validation of an Italian Version of the Savoring Beliefs Inventory","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-09 13:20:28","doi":"10.21203/rs.3.rs-8871514/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","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":"1ac07984-08c7-4f0b-b6e2-74efd40b2927","owner":[],"postedDate":"April 9th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"191430552234387435257283986034469407837","date":"2026-05-19T09:06:00+00:00","index":78,"fulltext":""},{"type":"reviewerAgreed","content":"313271167935832587249975289588099325517","date":"2026-05-14T19:29:51+00:00","index":74,"fulltext":""},{"type":"reviewerAgreed","content":"228510531600292584965283055077470276806","date":"2026-05-14T09:17:36+00:00","index":70,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-09T13:20:28+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-09 13:20:28","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8871514","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8871514","identity":"rs-8871514","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}