Validity and Reliability of the Turkish Version of the Salzburg Emotional Eating Scale: A Psychometric Study

Validity and Reliability of the Turkish Version of the Salzburg Emotional Eating Scale: A Psychometric Study | 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 Validity and Reliability of the Turkish Version of the Salzburg Emotional Eating Scale: A Psychometric Study Ayşenur Gültekin, Çiğdem Bozkır This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4706202/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 01 Sep, 2025 Read the published version in Journal of Eating Disorders → Version 1 posted 9 You are reading this latest preprint version Abstract Background: The Salzburg Emotional Eating Scale (SEES) measures emotional eating by evaluating responses to both positive and negative emotions. This study aimed to establish the validity and reliability of the Turkish version of the SEES (SEES-TR). Method: The SEES was translated into Turkish and back-translated into English. The translated version was reviewed by experts and pretested on a preliminary sample. The final version was administered to 303 participants from Namık Kemal University. The data collected included demographic information and responses to the SEES and the Emotional Eating subscale of the Dutch Eating Behavior Questionnaire (DEBQ). Reliability was assessed using Cronbach's alpha, McDonald's omega, and test-retest analyses. Validity was evaluated using exploratory and confirmatory factor analyses, along with content and surface validity. Results: The SEES-TR demonstrated high internal consistency, with Cronbach's alpha values of 0.924 for the total scale and above 0.90 for the subscales. McDonald's omega values supported these findings. Test-retest reliability indicated stability over time. Exploratory factor analysis confirmed a four-factor structure corresponding to happiness, sadness, anger, and anxiety, which was further supported by confirmatory factor analysis. Content and surface validity were established through expert reviews and pretesting. Conclusion: The Turkish version of the Salzburg Emotional Eating Scale is a valid and reliable instrument for assessing emotional eating behaviors in the Turkish population. This tool can be effectively used in both clinical and research settings to evaluate emotional eating in response to various emotional states. Salzburg Emotional Eating Scale Validation Reliability Turkish Population Emotional Eating Figures Figure 1 Plain English summary Emotional eating refers to eating in response to emotions rather than hunger. This study aimed to validate the Turkish version of the Salzburg Emotional Eating Scale (SEES), which measures changes in emotional eating behavior. The scale was translated, reviewed by experts, and tested on a sample from Namık Kemal University. The Turkish version demonstrated high reliability and validity, confirming its effectiveness in assessing emotional eating behaviors in the Turkish population. This validated tool can help researchers and clinicians better understand and address emotional eating in Turkiye. Background Emotional eating is characterized by a compulsion to consume food in response to emotional states rather than hunger ( 1 , 2 ). This behavior often involves excessive consumption to manage negative emotions such as anxiety, anger, and depression ( 3 ). While negative emotions are typically associated with emotional eating, recent findings indicate that individuals prone to this behavior also tend to eat more during positive emotional states than those who are not emotional eaters ( 4 , 5 ). The link between emotions and eating behavior has been extensively studied in the context of obesity. Various theories have provided insight into this relationship. Psychosomatic theory posits that individuals with obesity engage in emotional eating due to poor internal perceptual awareness, which impairs their ability to recognize hunger and satiety signals ( 6 , 8 ). According to Polivy and Herman’s restraint theory, emotional eating manifests as increased consumption beyond normal levels in individuals who consciously restrict their food intake when experiencing dysphoric states ( 9 , 10 ). Schachter's 'internal/external' obesity theory suggests that due to inadequate perception of physiological cues, individuals with obesity rely on external stimuli to regulate their eating behavior ( 11 ). Escape theory contends that individuals use eating as a means to evade negative emotions such as anxiety or depression ( 12 , 13 ). Given the low emotional awareness observed in individuals with obesity, enhancing emotional regulation skills may help mitigate emotional eating and serve as an effective intervention for obesity ( 14 , 15 ). Emotional eating has been implicated in various eating disorders. Binge eating episodes are associated with emotional eating in individuals with binge eating disorders ( 16 , 17 ). Moreover, individuals diagnosed with anorexia and bulimia nervosa exhibit altered eating behaviors related to emotional eating ( 18 , 19 ), and those with night eating syndrome score high on emotional eating measures ( 20 ). These findings underscore the importance of assessing emotional eating in the treatment of eating disorders ( 21 ). Recent research has identified elevated levels of emotional eating among individuals with obesity ( 22 ) and those with binge-eating syndrome ( 23 ). Factors contributing to emotional eating include the association of nutritional needs with emotional states, differences in hunger perception, escapism from negative situations, and loss of control due to dietary restrictions ( 6 ). Additionally, sleep duration, sex, and body mass index (BMI) significantly influenced emotional eating behavior. An inverse relationship exists between sleep duration and emotional eating scores ( 24 , 25 ), with shorter sleep duration correlating with higher BMI values linked to emotional eating ( 26 , 27 ). Gender differences also affect emotional eating behavior ( 28 , 29 ). Most studies of emotional eating rely on clinical observations and self-report questionnaires ( 30 ). Commonly used instruments to measure emotional eating include the Dutch Eating Behavior Questionnaire (DEBQ), Three-Factor Eating Questionnaire (TFEQ), Emotional Appetite Scale (EES), and Emotional Eating Scale ( 31 , 38 ). This study aimed to validate and assess the reliability of the Turkish version of the Salzburg Emotional Eating Scale (SEES) developed by Meule, Reichenberger, and Blecher ( 39 ). The SEES provides a comprehensive assessment of emotional eating by evaluating responses to specific emotions and distinguishing between overeating and undereating in various emotional contexts. Its versatility and applicability in both psychometric and experimental research highlight the necessity of validating the SEES in different cultural contexts. This study aimed to validate the psychometric characteristics of the SEES in the Turkish context, thereby enhancing the comprehension of emotional eating behaviors within the Turkish population. Methods Translation Permission was obtained from the responsible researcher who developed the Salzburg Emotional Eating Scale (SEES) for the scale's Turkish validation and reliability. In the subsequent stage of the study, the scale was translated from English to Turkish by 6 expert individuals proficient in English. Following the necessary evaluations, the scale was then back-translated from Turkish to English by 4 experts proficient in the English language. After the back-translation stage, the scale was evaluated by 6 experts who were proficient in both languages and knowledgeable about the construct to be measured and who were not involved in the translation and back-translation phases. Following the review conducted after both translations, the Turkish version of the scale that emerged was administered to a preliminary sample group consisting of 38 individuals meeting the sample criteria. Feedback regarding the appropriateness and comprehensibility of the scale items was gathered from the participants. In the subsequent step, the Turkish version of the scale was conveyed to the responsible researcher who developed the scale, and their opinions were obtained. Following necessary adjustments, the Turkish version of the scale to be used in the research was finalized. Participants The population of the research consisted of students, academicians, and administrative staff of Namık Kemal University in Tekirdağ. The inclusion criteria were age between 18 and 65 years and not having received a diagnosis of any illness. The exclusion criteria were a diagnosis of any chronic/psychological/psychiatric illness by a doctor, regular use of medication/vitamin supplements, and pregnancy or lactation. The study received ethical approval for its appropriateness from the Namık Kemal University Scientific Research and Publication Ethics Board (2021-02-24/T2021-585). Data collection was conducted between March and May of the 2020–2021 academic year. The scale was transferred to an online platform using Google Forms and sent via email to Namık Kemal University students, academicians, and administrative staff. Initially, 416 individuals completed the survey. However, 113 individuals who did not meet the inclusion criteria and/or who participated in the survey multiple times were excluded from the study. Therefore, the data of 303 individuals were utilized for the initial phase of the study. Subsequently, for the test-retest reliability analysis of the scale, data collection was completed by reapplying the scale to 30 individuals who participated in the initial phase. At the beginning of the study, participants were asked to create a username using the first letters of their names-surnames and the last 4 digits of their phone numbers to determine whether the same individuals were reached in both phases of data collection. Data collection The study utilized a demographic information form created by the researcher to obtain sociodemographic data from the students, academicians, and administrative staff involved. Additionally, participants were administered the Salzburg Emotional Eating Scale and the Emotional Eating subscale of the Dutch Eating Behavior Scale. Demographic Questionnaire Form The information form prepared by the researcher was used to assess the sociodemographic characteristics of the participants. This section inquired about the participants' sex, age, marital status, education level, occupation, monthly income, health status, medication usage, smoking habits, sleep duration, regular exercise habits, body weight, and height. Salzburg Emotional Eating Scale The 'Salzburg Emotional Eating Scale,' developed by Meule, Reichenberger, and Blecher ( 39 ) in the Salzburg region of Austria, is intended to measure changes in the amount of eating in response to positive and negative emotions. The scale consists of 20 items indicating how emotional expressions influence eating behavior and comprises four subscales: happiness, sadness, anger, and anxiety. Each item begins with the stem "When I am/feel..." followed by an adjective describing an emotional state. The response options ranged from 1 to 5, indicating "much less than usual" to "much more than usual" eating behaviors. Scores above three represent increased food intake, a score of three indicates unchanged food intake, and scores below three indicate decreased food intake ( 39 ). Dutch Eating Behavior Questionnaire (DEBQ) The DEBQ was developed in 1986 by Van Strien and colleagues, and its Turkish validation was conducted by Bozan ( 31 ). The scale evaluates three subscales of eating behavior—external eating, restrained eating, and emotional eating—comprising 33 items. In this study, the emotional eating subscale, which consists of 13 items, was utilized to assess emotional eating behavior using a 5-point Likert scale ( 40 ). Data Analysis The data were analysed using IBM SPSS 22 and AMOS 24 software. Validity and reliability analyses were conducted to assess the psychometric properties of the SSPE Scale. Cronbach's alpha and McDonald's omega values were examined for reliability, while for validity, the Kaiser‒Meyer‒Olkin (KMO) test, exploratory factor analysis, and confirmatory factor analysis were performed. Spearman correlation analysis was employed to determine criterion-related validity by examining the relationship between the emotional eating subscale of the Dutch Eating Behavior Questionnaire and the Salzburg Emotional Eating Scale. Paired sample t tests and Wilcoxon tests were utilized to assess the stability of the scale over time through retest measurements. A statistical significance level of p < 0.05 was considered for all analyses. Results The average age of the individuals in the research group was 22.1 ± 4.8 years (within the range of 18–50 years). A total of 89.1% of the participants were female, while 10.9% were male. The participants consisted of 96% students, 2% academics, and 2% administrative staff (Table 1 ). Similarly, 4% of the respondents had completed high school, 93% had completed undergraduate studies, and 3% had completed postgraduate studies. Table 1 Distribution of Participants' Demographic Characteristics (n = 303) Gender n % Regularly exercise habit n % Female 270 89 Yes 99 33 Male 33 11 No 204 67 Marital status Smoking Single 287 95 Yes 42 14 Married 16 5 No 261 86 Occupation Sleep duration Student 291 96 < 6 hours 21 7 Academic 6 2 6–8 hours 217 72 Administrative staff 6 2 8 hours < 65 21 Monthly income BMI 0-2800 TL 244 81 Underweight 42 14 2801–5000 TL 33 11 Normal 204 67 5001–7500 TL 16 5 Overweight 48 16 7500 TL< 10 3 Obese 9 3 TL: Turkish liras, BMI: Body mass index Results of the Reliability Analysis The Salzburg Emotional Eating Scale was subjected to reliability analysis using invariance, internal consistency, and parallel methods. Invariance was examined using a t test to investigate the relationship between the sadness, anger, and anxiety subscales of the scale administered at two different time points. The analysis revealed no significant difference among the responses given within the subdimensions of the SEES-TR. The test-retest analysis results for the SEES-TR subscales are presented in Table 2 . Table 2 Test-retest analyses of the SEES SEES-TR Subscales n Mean SD z/t p First test of Happiness 30 2.83 0.15 0.37 0.71 a Retest of Happiness 30 2.95 0.13 First test of Sadness 30 2.56 0.19 0.21 0.83 b Retest of Sadness 30 2.58 0.18 First Test of Anger 30 2.44 0.17 0.41 0.68 b Retest of Anger 30 2.48 0.19 The First Test of Anxiety 30 2.24 1.09 -1.33 0.19 b Retest of Anxiety 30 2.04 0.91 a Wilcoxon test, b paired sample t test, p < 0.05 As a result of the test-retest analysis of the SEES-TR, no significant difference was observed among the subscales. The 'reliability coefficient' for consistency between the two test results was determined by examining the correlation (Table 3 ). Table 3 Reliability correlations of the SEES test-retest analysis SEES-TR subscales n r p Sadness x Sadness 30 0.777 > 0.001 a Anger x Anger 30 0.825 > 0.001 a Anxiety x Anxiety 30 0.698 > 0.001 a Happiness x Happiness 30 0.490 0.006 b a Pearson correlation, b Spearman correlation, p < 0.001 Internal consistency analyses were conducted using Cronbach's α and McDonald's Omega coefficient (ω) for the SEES. The total scale reliability of the SEES-TR was calculated as 0.924 for Cronbach's α. The reliability coefficients for the happiness, sadness, anger, and anxiety subscales were determined to be 0.942, 0.913, 0.913, 0.913, and 0.922, respectively, for Cronbach's α. For McDonald's omega coefficient (ω), the total scale reliability of the SEES-TR was calculated as 0.932. McDonald's Omega coefficients for the Happiness, Sadness, Anger, and Anxiety subscales were determined to be 0.943, 0.917, 0.917, and 0.921, respectively. The reliability coefficients of the SEES-TR are presented in Table 4 . Table 4 McDonald's ω and Cronbach's α reliability coefficients of the SEES subscales SEES-TR Subscales McDonald's ω Cronbach α Happiness 0.943 0.942 Sadness 0.917 0.913 Anger 0.917 0.913 Anxiety 0.921 0.922 Total 0.932 0.924 To conduct the parallel-form analysis, the Emotional Subscale of the Dutch Eating Behavior Questionnaire (DEBQ) was utilized. There was no significant relationship between the Happiness subscale of the SEES and the other subscales of the SEES and the total score of the Emotional Subscale of the DEBQ. The relationships between the subscales of the SEE Scale and both of the other subscales and the Emotional Subscale of the DEBQ are presented in Table 5 . Table 5 Parallel Form Analysis of SEES Subscales and Total Scoring of the DEBQ Emotional Subscale 1 2 3 4 5 1. Happiness - 2. Sadness .006 - Anger − .001 .698** - Anxiety .053 .511** .653** - 5. DEBQ − .111 .522** .425** .308** - Validity Analysis Results Translation, back-translation, expert evaluation, and pilot/pretest studies were conducted under the headings of linguistic, content, and surface validity. For content validity, expert opinions were obtained using the Davis technique ( 41 ). The scope validity ratio (SVR) was obtained by comparing the original and Turkish translations of the scale items. An SVR value of ≥ 0.80 was expected, and according to expert evaluations, it was determined that the SVR values of the scale items were ≥ 0.80 ( 41 ) (Supplemental Table 1). For surface validity, a pilot/pretest study was conducted by collecting opinions from individuals who were not experts in the researched field but were consistent with the determined sampling ( 42 ). The scale was administered to 38 individuals. Participants were asked to read each scale item aloud, express the meaning evoked by each scale item, and fill out the scale appropriately. Additionally, the scale was sent to the scale owner via email, and their opinions were obtained. Based on the feedback received and appropriate changes, the final version of the scale was established (Supplemental Table 2). In the validation analysis of the SEES, confirmatory and exploratory factor analysis methods were employed. First, the Kaiser‒Meyer‒Olkin (KMO) test was conducted to determine the adequacy of the sample size for factor analysis, and Bartlett's sphericity test was performed to determine the correlations between variables necessary for factor analysis. The KMO coefficient was 0.897, the Bartlett's sphericity test X 2 value was 6033.95, and p = 0.000 (Table 3 ). Exploratory factor analysis results The structural validity of the SEES was assessed using exploratory factor analysis (EFA) methods, including principal component analysis and the scree plot technique. The number of factors for the SEE Scale, according to the EFA, was determined by examining the scree plot shown in Fig. 1 , selecting factors with eigenvalues greater than 1. In the EFA performed to establish the factor structure of the SEES, it was observed that the scale consists of 4 subscales. As a result of the exploratory factor analysis, the Happiness subscale of the scale formed Factor 2. The first 5 items of the scale were included in this subscale, showing factor loadings ranging from 0.873 to 0.931. Items 6, 7, 8, 9, and 10 formed the Sadness subscale, with factor loadings ranging from 0.562 to 0.839, representing Factor 3. The anger subscale, encompassed by Factor 4, was identified by items 11, 12, 13, 14, and 15, demonstrating factor loading values ranging from 0.393 to 0.881. Additionally, the anxiety subscale, represented as Factor 1, emerged from items 16, 17, 18, 19, and 20 of the scale, exhibiting factor loadings ranging from 0.753 to 0.909. The scale comprises a total of four subscales (Table 6 ). Table 6 Evaluation of the Factor Structure of the SEES-TR Scale Items Factor 1 Factor 2 Factor 3 Factor 4 SEES 1. .897 SEES 2. .924 SEES 3. .931 SEES 4. .873 SEES 5. .879 SEES 6. .839 SEES 7. .854 SEES 8. .834 SEES 9. .769 SEES 10. .562 SEES 11. .881 SEES 12. .875 SEES 13. .797 SEES 14. .487 SEES 15. .393 SEES 16. .761 SEES 17. .875 SEES 18. .909 SEES 19. .814 SEES 20. .753 Eigenvalue % Varying Cumulative Variance % 8.636 4.101 1.892 1.184 22.478 20.564 19.206 16.817 43.178 63.685 73.147 79.065 The bootstrap method was utilized in the confirmatory factor analysis. Within the framework of the employed method, the maximum likelihood (ML) estimation method comprised four latent variables on the confirmatory factor analysis (CFA) diagram, representing the scale as happiness, sadness, anger, and anxiety. Regarding the item distribution according to the latent variable in the confirmatory factor analysis, items 1, 2, 3, 4, and 5 represented the happiness subscale; items 6, 7, 8, 9, and 10 represented the sadness subscale; items 11, 12, 13, 14, and 15 represented the anger subscale; and items 16, 17, 18, 19, and 20 represented the anxiety subscale. The confirmatory factor analysis diagram, depicting the latent variables, covariances between latent variables, one-way effects between observable variables and latent variables, and error terms of independent variables, is illustrated in supplemental Fig. 2. The critical value calculated as 36.794 for the study data with AMOS indicated that the assumption of multivariate normality was not met, as it exceeded 8 (Supplementary Table 4). As the data did not exhibit a normal distribution, the 'Bollen-Stine Bootstrap' method was applied for CFA. The bootstrap method is used in AMOS to generate approximate standard errors for many statistics calculated without needing to fulfil the assumption of multivariate normality ( 43 ). Consequently, the bootstrap results were compared with the original ML estimation method outputs for the scale. The bootstrap method, which provides approximate standard errors without requiring the assumption of normality for the data, demonstrated that the confirmatory factor analysis was suitable for parametric statistics. In the context of bootstrapping for the SEES, examining the ML model fit indices, the model fit indices χ2/df, GFI, and AGFI were found to be 2.468, 0.877, and 0.830, respectively, while the CFI, RMSEA, NFI, TLI, and IFI were 0.967, 0.074, 0.945, 0.958, and 0.967, respectively (Table 7 ). Table 7 CFA fit index values of the SEES-TR Index Acceptable Values SEES-TR χ2/sd 2 ≤ or ≤ 5 2.468 GFI 0.90 ≤ GFI ≤ 0.95 .877 AGFI 0.85 ≤ AGFI ≤ 0.90 .830 CFI 0.90 ≤ CFI ≤ 0.95 .967 RMSEA 0.05 ≤ RMSEA ≤ 0.08 .074 NFI 0.90 ≤ NFI ≤ 0.95 .945 TLI 0.90 ≤ TLI ≤ 0.95 .958 IFI 0.90 ≤ IFI ≤ 0.95 .967 Discussion The Salzburg Emotional Eating Scale was developed by Meule et al. ( 39 ) to measure emotional eating behaviors by examining different food responses in possible positive and negative emotional states. On the basis of various scales developed in research focusing on emotional eating, such as the Emotional Eating subscale developed by Van Strien et al. ( 40 ), the Emotional Eating Scale by Arnow et al. ( 3 ), and the Emotional Overeating Scale developed by Masheb and Grilo ( 17 ), it was observed that these scales primarily investigated negative emotions ( 40 , 3 , 17 ). In contrast, the Positive and Negative Emotional Eating Scale encompasses both positive and negative emotions but has been shown to be reliable and valid only for female participants ( 45 ). The Emotional Appetite Questionnaire, which covers positive and negative emotional states and measures increased and decreased eating tendencies in response to emotions, was not developed based on experimental data during the scale development phase ( 46 ). The significance of the SEES lies in its detailed delineation of specific emotions and its ability to differentiate between overeating and undereating based on emotions, thus representing an expanded version of previous scales ( 39 ). In Turkey, scales examining emotional eating behaviors include the Emotional Appetite Questionnaire, which covers both positive and negative emotions. However, the Turkish validation analyses for this scale have not been completed ( 47 , 34 ). It is believed that the adaptation of the Salzburg Emotional Eating Scale to the Turkish population could offer a broader perspective for studies focused on emotional eating. In scale adaptation studies, sample sizes of 100 participants are considered weak for validity and reliability analyses, 200 are considered sufficient, and 300 are considered good ( 48 – 50 ). The present study was conducted using data obtained from 303 participants, including students, academics, and staff at Namık Kemal University in Tekirdağ. Women constituted 89.1% of the participants. In Meule ( 39 ) and Ghafouri et al.'s ( 51 ) studies, the majority of participants were also women (89.1%, 82.9%, 74.4%; 90%), indicating a similar sex distribution across all three studies. The disproportionate distribution of gender, with women being the majority in the present study, is presumed to potentially impact the study results, similar to the original study. For the validity analysis of the SEES, structural validity analysis methods, including content and surface validity, were used. During the translation phase of the SEES, as Coster and Mancini ( 52 ) and Bayık ( 53 ) suggested, translation was conducted by two commissions consisting of 6 and 4 expert individuals, respectively ( 52 , 53 ). Subsequently, the Davis method was used to analyse content validity. According to Davis ( 41 ), an assessment by at least 2 and up to 20 experts is needed; hence, the evaluation was carried out by 6 expert individuals, revealing KMO values indicating suitability for content validity (> 0.80). For structural validity, both exploratory and confirmatory factor analyses were employed. As Suhr ( 54 ) emphasized, the objective of exploratory factor analysis is to uncover and explore the factor structure underlying the statements representing the variables of an adapted scale. CFA aims to verify the adequacy of the original factor structure. These methods are frequently preferred for testing and validating models ( 54 , 55 ). Considering the criteria outlined by Beavers et al. ( 56 ), the KMO value (0.89) in factor analysis indicated a very good sample size for conducting factor analysis. Additionally, Bartlett's sphericity test (p < 0.001) confirmed sufficient relationships among the variables for factor analysis. Principal component analysis and scree plot methods were used in exploratory factor analysis to evaluate the 'number of factors or components' and 'factor loading of variables' to determine the structural characteristics of the variables ( 57 ). The EFA revealed that 20 items with factor loading values ranging from 0.393 to 0.931 formed four subscales. The study confirmed that the four subscales aligned with the adapted scale, maintaining compatibility with each other ( 39 ). In various studies, a criterion value of 0.30 has been considered adequate for factor loading ( 58 , 59 , 60 ). In the present study, the factor loading of each item was > 0.30. A high factor loading indicated the potential presence of the item in the respective subscale. Exploratory factor analysis revealed that the 20 items with factor loadings ranging from 0.393 to 0.931 formed four subscales. The current study demonstrated that the scale consisted of four subscales, and the items constituting each subscale were compatible with the adapted scale (SEES) as per the original study ( 39 ). Another analysis of construct validity was CFA. A confirmatory factor analysis was also conducted to assess construct validity. It has been reported that when ML and GLS methods are used for estimating factor loads in data that do not exhibit a normal distribution, they tend to inflate model fit indices and decrease standard error rates ( 61 ). Therefore, the method chosen for nonnormally distributed data is critical ( 43 ). ADF is an analysis method used when the data do not follow a normal distribution. However, this approach makes few assumptions about the distribution of data. Moreover, it requires a minimum sample size of n: 200 for 'simple' models and an extremely large sample size (n > 5,000) for 'complex' models ( 62 ). Additionally, ADF is prone to weak estimations when the model is misspecified due to the influence of sample size ( 63 ). The Bollen–Stine Bootstrap method is a second potential solution provided for multivariate nonnormally distributed data ( 64 ). Therefore, in the present study, the Bollen–Stine Bootstrap method was used for DFA. In evaluations of fit indices derived from Bollen–Stine Bootstrap analysis, it has been stated that Bollen–Stine Bootstrap analysis can provide strong evidence by avoiding biases in estimation values ( 62 , 65 ). Kaya and Çolakoğlu resorted to this method in their validity analysis ( 66 ). Yaman ( 67 ) mentioned that the application of the bootstrap procedure enhances the parametric statistical fit of the CFA (Yaman, 2016). In the present study, ML fit indices were evaluated within the Bollen–Stine Bootstrap framework. When examining model fit indices, the χ2 value for the hypothesized model, especially with a large sample size, typically indicates the rejection of the model. A CFI value of 0.96 suggests that this model represents a marginally good fit. The other model fit indices, χ2/sd at 2.46, RMSEA at 0.074, NFI at 0.94, TLI at 0.95, and IFI at 0.96, are within acceptable ranges, while the GFI at 0.87 and AGFI at 0.83 are very close to acceptable ranges. These data indicate that the scale fits well into the model. Meule et al. (2018) stated that within the context of confirmatory factor analysis, CFI = 0.917–0.932 and RMSEA = 0.051–0.073 are considered acceptable (Meule et al., 2018). Ghafouri et al.'s ( 51 ) study reported the model fit indices as CMIND/DF = 7.58, GFI = 0.91, CFI = 0.90, TLI = 0.89, and RMSEA = 0.061 ( 51 ). Similar to the current study, it was observed that some fit indices are very close to an acceptable range. Reliability analyses revealed that the Cronbach's α coefficients of the SEES-TR subscales of happiness, sadness, anger, and anxiety ranged from 0.913 to 0.942. The Cronbach's α coefficient of the total scale was determined to be 0.924. In scale adaptation studies, a Cronbach's α reliability coefficient > 0.80 indicates good reliability, while a value > 0.90 indicates excellent reliability ( 68 ). A total scale and subdimensions > 0.90 suggest that the SEES-TR has excellent reliability. According to McDonald's ω coefficient, which is a more general form of Cronbach's α, there is no optimal reliability measure, and it has been reported that the omega (ω) coefficient should be indicated for reliability estimation instead of α ( 69 , 70 ). Therefore, both reliability analysis methods were used in the current study. The omega coefficients of the total SEES-TR and the happiness, sadness, anger, and anxiety subscales were found to be 0.917–0.943. Watkins et al. (2017) mentioned that the omega coefficient should be above 0.75 ( 71 ), indicating that the current study's omega reliability coefficient is reliable. In a study by Meule et al. (2018), the Cronbach's α coefficient for the subdimensions of the scale ranged from α = 0.732–0.871. In the present study, the reliability coefficients of the total scale and subdimensions indicate that the reliability is consistent with that of the original scale ( 39 ). Another reliability analysis, the stability of the scale over time, involved readministering the scale to a subset of participants after 3 weeks. There was no statistically significant difference, and the reliability coefficient between the two test results was calculated. For the sadness and anger subscales of the study, the reliability coefficients were found to be 0.777 and 0.825, respectively, which are above the reported sufficient reliability coefficient ( 72 ). The reliability coefficient for the anxiety subscale was 0.698, which is very close to the 0.70 adequacy level, while the reliability coefficient for the happiness subscale was 0.490. Ghafouri et al. (2021) noted that the lack of a retest analysis was a limitation of their study and emphasized the need for this analysis to be conducted in the future for scale ( 51 ). In the current study, the term 'reliable scale' was reinforced through the stability method. In this study, the parallel form method, another reliability analysis method, was also used by sampling different items that could represent the same behavioral patterns to create two equivalent forms. These forms were simultaneously administered, and the DEBQ emotional subscale was used for the parallel-form method in accordance with the original study of the scale ( 39 ). The DEBQ emotional subscale showed a positive correlation with the sadness, anger, and anxiety subscales, demonstrating consistency with the SEES. A negative correlation between the SEES happiness subscale and the DEBQ emotional subscale was suggested ( 39 ); similarly, in the current study, it was found that the happiness subscale correlated negatively with the DEBQ emotional subscale but not significantly. Although the SEES-TR could allow for a more detailed analysis of emotional effects on eating behavior, it is still potentially biased based on self-reports. Specifically, the scale requires participants to have significant awareness of fluctuations in their daily emotions and their impact on food intake. Responses to the scale will be shaped by this awareness. A Turkish validation and reliability study of the SEES was conducted on individuals with higher education levels. Hence, to enhance the applicability of the study to all segments of society, future studies involving individuals with lower levels of education are recommended. For studies focusing on the impact of emotions on eating behavior, it is suggested that a scale be used to explore a broader range of emotions and changes in food intake. Conclusion The SEES-TR is positioned as a valuable tool for a comprehensive assessment of emotional eating, extending beyond psychometric domains to encompass experimental research. This instrument holds promise for exploring new avenues in the investigation of mechanisms underlying emotional eating and in clinical research. As an enhanced iteration of preceding scales, the SEES-TR allows for a nuanced examination of specific emotions and a differentiation between overeating and undereating based on emotional triggers, thereby establishing its significance. This study concluded that the SEES can be considered a valid and reliable instrument in the Turkish language. It is anticipated that its application will contribute meaningfully to research areas associated with emotional eating in Turkiye. Abbreviations SEES: Salzburg Emotional Eating Scale SEES-TR: Salzburg Emotional Eating Scale-Turkish KMO: Kaiser‒Meyer‒Olkin CFA: Confirmatory Factor Analysis Declarations Ethics approval consent to participate Ethical approval (2021-02-24/T2021-585) was obtained from the Tekirdag Namık Kemal University Research Ethics Committee. The study was performed in accordance with the ethical standards of the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. Online informed consent was obtained from all participants. Consent for publication Not applicable. Availability of data and materials The dataset used during the current study is available from the corresponding author upon reasonable request. Competing interests The authors declare no competing interests. Funding There was no funding to support the present study. C ontributions AG and ÇB designed the study. ÇB directed and supervised the project. AG collected the data. AG and ÇB conducted the data analysis. AG drafted the manuscript, with ÇB providing critical revisions. All authors have read and approved the final version of the manuscript. Acknowledgements We would like to thank the students, academics and administrative staff of Tekirdağ Namık Kemal University, who composed the sample of the study. References De Lauzon, B., Romon, M., Deschamps, V., Lafay, L., Borys, J. M., Karlsson, J., Ducimetière, P., & Charles, M. A. (2004). The Three-Factor Eating Questionnaire-R18 is able to distinguish among different eating patterns in a general population. Journal of Nutrition , 134 (9), 2372–2380. https://doi.org/10.1093/jn/134.9.2372 Rotella, F., Mannucci, E., Gemignani, S., Lazzeretti, L., Fioravanti, G., & Ricca, V. (2018). Emotional eating and temperamental traits in Eating Disorders: A dimensional approach. Psychiatry Research , 264 , 1–8. https://doi.org/10.1016/j.psychres.2018.03.066 Rotella, F., Mannucci, E., Gemignani, S., Lazzeretti, L., Fioravanti, G., & Ricca, V. (2018). Emotional eating and temperamental traits in Eating Disorders: A dimensional approach. Psychiatry Research , 264 , 1–8. https://doi.org/10.1016/j.psychres.2018.03.066V Arnow, B., Kenardy, J., & Agras, W. S. 1995. (n.d.). The Emotional Eating Scale: The Development of a Measure to Assess Coping with Negative Affect by Eating . Bongers, P., Jansen, A., Havermans, R., Roefs, A., & Nederkoorn, C. (2013). Happy eating: The underestimated role of overeating in a positive mood. Appetite , 67 , 74–80. https://doi.org/10.1016/j.appet.2013.03.017 Bongers, P., Jansen, A., Houben, K., & Roefs, A. (2013). Happy eating: The single target implicit association test predicts overeating after positive emotions. Eating Behaviors , 14 (3), 348–355. https://doi.org/10.1016/j.eatbeh.2013.06.007 McAtamney, K., Mantzios, M., Egan, H., & Wallis, D. J. (2021). Emotional eating during COVID-19 in the United Kingdom: Exploring the roles of alexithymia and emotion dysregulation. Appetite , 161 . https://doi.org/10.1016/J.APPET.2021.105120 Kaplan, H. I., & Kaplan, H. S. (1957). The psychosomatic concept of obesity. The Journal of Nervous and Mental Disease , 125 (2), 181–201. https://doi.org/10.1097/00005053-195704000-00004 Canetti, L., Bachar, E., & Berry, E. M. (2002). Food and emotion. Behavioural Processes , 60 (2), 157–164. https://doi.org/10.1016/S0376-6357(02)00082-7 Polivy, J., & Herman, C. P. (1985). Dieting and binging: A causal analysis. American Psychologist , 40 (2), 193–201. https://doi.org/10.1037//0003-066x.40.2.193 Ouwens, M. A., Van Strien, T., & Van Der Staak, C. P. F. (2003). Tendency toward overeating and restraint as predictors of food consumption. Appetite , 40 (3), 291–298. https://doi.org/10.1016/S0195-6663(03)00006-0 Schachter, S., Goldman, R., & Gordon, A. (1968). Effects of fear, food deprivation, and obesity on eating. Journal of Personality and Social Psychology , 10 (2), 91–97. https://doi.org/10.1037/h0026284 Heatherton, T. F., & Baumeister, R. F. (1991). Binge eating as escape from self-awareness. Psychological Bulletin , 110 (1), 86–108. https://doi.org/10.1037/0033-2909.110.1.86 Spoor, S. T. P., Bekker, M. H. J., Van Strien, T., & van Heck, G. L. (2007). Relations between negative affect, coping, and emotional eating. Appetite , 48 (3), 368–376. https://doi.org/10.1016/j.appet.2006.10.005 Fernandes, J., Ferreira-Santos, F., Miller, K., & Torres, S. (2018). Emotional processing in obesity: a systematic review and exploratory meta-analysis. In Obesity Reviews (Vol. 19, Issue 1, pp. 111–120). Blackwell Publishing Ltd. https://doi.org/10.1111/obr.12607 Aparicio, E., Canals, J., Arija, V., De Henauw, S., & Michels, N. (2016). The role of emotion regulation in childhood obesity: Implications for prevention and treatment. Nutrition Research Reviews , 29 (1), 17–29. https://doi.org/10.1017/S0954422415000153 Wolff, G. E., Crosby, R. D., Roberts, J. A., & Wittrock, D. A. (2000). Differences in daily stress, mood, coping, and eating behavior in binge eating and nonbinge eating college women. Addictive Behaviors , 25 (2), 205–216. https://doi.org/10.1016/S0306-4603(99)00049-0 Masheb, R. M., & Grilo, C. M. (2006a). Emotional overeating and its associations with eating disorder psychopathology among overweight patients with binge eating disorder. International Journal of Eating Disorders , 39 (2), 141–146. https://doi.org/10.1002/eat.20221 Ricca, V., Castellini, G., Fioravanti, G., Lo Sauro, C., Rotella, F., Ravaldi, C., Lazzeretti, L., & Faravelli, C. (2012). Emotional eating in anorexia nervosa and bulimia nervosa. Comprehensive Psychiatry , 53 (3), 245–251. https://doi.org/10.1016/j.comppsych.2011.04.062 Meule, A., Richard, A., Schnepper, R., Reichenberger, J., Georgii, C., Naab, S., Voderholzer, U., & Blechert, J. (2019). Emotion regulation and emotional eating in anorexia nervosa and bulimia nervosa. 29 (2), 175–191. https://doi.org/10.1080/10640266.2019.1642036 Meule, A., Allison, K. C., & Platte, P. (2014). Emotional Eating Moderates the Relationship of Night Eating with Binge Eating and Body Mass. European Eating Disorders Review , 22 (2), 147–151. https://doi.org/10.1002/erv.2272 Reichenberger, J., Schnepper, R., Arend, A., Richard, A., Voderholzer, U., Naab, S., & Blechert, J. (2021). Emotional eating across different eating disorders and the role of body mass, restriction, and binge eating. The International Journal of Eating Disorders , 54 (5), 773. https://doi.org/10.1002/EAT.23477 Vasileiou, V., & Abbott, S. (2023). Emotional eating among adults with healthy weight, overweight and obesity: a systematic review and meta-analysis. Journal of human nutrition and dietetics. 36(5), 1922–1930. https://doi.org/10.1111/jhn.13176 Roher, S., Latzer, Y., & Geliebter, A. (2014). Negative Emotional Eating among Obese Individuals with and without Binge Eating Behavior and Night Eating Syndrome. The Israel journal of psychiatry and related sciences, 51(3), 219–225. Konttinen, H. (2020). Emotional eating and obesity in adults: the role of depression, sleep and genes. Proceedings of the Nutrition Society , 79 (3), 283–289. https://doi.org/10.1017/S0029665120000166 Dweck, J. S., Jenkins, S. M., & Nolan, L. J. (2014). The role of emotional eating and stress in the influence of short sleep on food consumption. Appetite , 72 , 106–113. https://doi.org/10.1016/j.appet.2013.10.001 Van Strien, T., & Koenders, P. G. (2014). Effects of emotional eating and short sleep duration on weight gain in female employees. Journal of Occupational and Environmental Medicine , 56 (6), 659–666. https://doi.org/10.1097/JOM.0000000000000172 Konttinen, H., Van Strien, T., Männistö, S., Jousilahti, P., & Haukkala, A. (2019). Depression, emotional eating and long-term weight changes: A population-based prospective study. International Journal of Behavioral Nutrition and Physical Activity , 16 (1). https://doi.org/10.1186/s12966-019-0791-8 Keck, M. M., Vivier, H., Cassisi, J. E., Dvorak, R. D., Dunn, M. E., Neer, S. M., & Ross, E. J. (n.d.). Examining the Role of Anxiety and Depression in Dietary Choices among College Students . https://doi.org/10.3390/nu12072061 Sanlier, N., & Dilek Ogretir, A. (2008). The Relationship Between Stress and Eating Behaviors among Turkish Adolescence. World Applied Sciences Journal , 4 (2), 233–237. Bozan, N. (2009). Hollanda Yeme Davranışı (DEBQ) Anketinin Türk Üniversite Öğrencilerinde Geçerlik ve Güvenirliğinin Sınanması. Yüksek lisans Tezi , Başkent Üniversitesi Sağlık Bilimleri Enstitüsü Beslenme ve Diyetetik Anabilimdalı. Kirac, D., Kaspar, E., Avcilar, T., Cakir, O., Ulucan, K., Kurtel, H., Deyneli, O., & Guney, A. (2015). A New Method For Investigating Eating Behaviours Related With Obesity;Three-Factor Eating Questionnaire ". Journal of Marmara University Institute of Health Sciences , 5 (3), 1. https://doi.org/10.5455/musbed.20150602015512 Karakuş, S. Ş., Yıldırım, H., & Büyüköztürk, Ş. (2016). Adaptation of three factor eating questionnaire (TFEQ-R21) into Turkish culture: A validity and reliability study. Prev Med Bull , 15 , 229. https://doi.org/10.5455/pmb.1-1446540396 Demi̇rel, B., Yavuz, F. K., Karadere E., Şafak, Y., Türkçapar, H. (2014). Duygusal İştah Anketi’nin Türkçe Geçerlik ve Güvenilirliği, Beden Kitle İndeksi ve Duygusal Şemalarla İlişkisi. Bilişsel Davranışçı Psikoterapi ve Araştırmalar Dergisi. 3:171-181 Bektas, M., Bektas, I., Selekoğlu, Y., Akdeniz Kudubes, A., Sal Altan, S., & Ayar, D. (2016). Psychometric properties of the Turkish version of the Emotional Eating Scale for children and adolescents . https://doi.org/10.1016/j.eatbeh.2016.06.021 Karaçam, Z. (2019). Adaptation of Scales to Turkish. In Karaçam (Vol. 2, Issue 1). Akın, A., Yıldız, B., Özçelik, B. (2016). Duygusal Yeme Ölçeğinin Türkçe Versiyonunun Geçerlik Ve Güvenirliği. Uluslararası Sosyal Araştırmalar Dergisi. 9( 44): 776-781 Doǧan, T., Tekin, E. G., & Katrancioǧlu, A. (2011). Feeding your feelings: A self-report measure of emotional eating. Procedia - Social and Behavioral Sciences , 15 , 2074–2077. https://doi.org/10.1016/J.SBSPRO.2011.04.056 Meule, A., Reichenberger, J., Blechert, J., & Nolan, L. J. (2018). Development and Preliminary Validation of the Salzburg Emotional Eating Scale . 9 (February). https://doi.org/10.3389/fpsyg.2018.00088 Van Strien, T., Frijters, J. E. R., Bergers, G. P. A., & Defares, P. B. (1986). The Dutch Eating Behavior Questionnaire (DEBQ) for assessment of restrained, emotional, and external eating behavior. International Journal of Eating Disorders , 5 (2), 295–315. https://doi.org/10.1002/1098108 Davis, L. L. (1992). Instrument review: Getting the most from a panel of experts. Applied Nursing Research , 5 (4), 194–197. https://doi.org/10.1016/S0897-1897(05)80008-4 Öztürk, H., Babacan, E., (2012). A Study in Scale Development: The Occupational Safety Scale (OSS) for Health Care Personnel Working in Hospital. Hemşirelikte Eğitim ve Araştırma Dergisi (Vol. 9, Issue 1). Byrne, B.M. (2010). Structural Equation Modeling With AMOS: Basic Concepts, Applications, and Programming, Second Edition (2nd ed.). Routledge. https://doi.org/10.4324/9780203805534 Masheb, R. M., & Grilo, C. M. (2006b). Emotional overeating and its associations with eating disorder psychopathology among overweight patients with Binge eating disorder. International Journal of Eating Disorders , 39 (2), 141–146. https://doi.org/10.1002/eat.20221 Sultson, H., Kukk, K., & Akkermann, K. (2017). Positive and negative emotional eating have different associations with overeating and binge eating: Construction and validation of the Positive-Negative Emotional Eating Scale. Appetite , 116 , 423–430. https://doi.org/10.1016/j.appet.2017.05.035 Geliebter, A., & Aversa, A. (2003). Emotional eating in overweight, normal weight, and underweight individuals. Eating Behaviors , 3 (4), 341–347. https://doi.org/10.1016/S1471-0153(02)00100-9 Nolan, L. J., Halperin, L. B., Geliebter, A. (2010). Emotional Appetite Questionnaire. Construct Validity and Relationship with BMI. Appetite . 54 (2): 314–319 https://doi.org/10.1016/j.appet.2009.12.004 AKBAŞ, U., KARABAY, E., AYAZ, A., DEMİR, O. (2019). Türkiye Ölçme Araçları Dizininde Yer Alan Açımlayıcı Faktör Analizi Çalışmalarının Paralel Analiz Sonuçları İle Karşılaştırılması . Journal of Theoretical Educational Science , 12 (3): 1095–1123 https://doi.org/10.30831/akukeg.453786 COMREY, A. L. (1978). Common Methodological Problems İn Factor Analytic Studies. Journal of Consulting and Clinical Psychology . 46 (4): 648–659 https://doi.org/10.1037/0022-006X.46.4.648 DE WİNTER, J. C. F., DODOU, D., WİERİNGA, P. A. (2009). Exploratory Factor Analysis With Small Sample Sizes. Multivariate Behavioral Research . 44 (2): 147–181 https://doi.org/10.1080/00273170902794206 Ghafouri, S., Abdollahi, A., Suksatan, W. et al. (2022). Psychometric comparison of the Persian Salzburg Emotional Eating Scale and Emotional Eater Questionnaire among Iranian adults. J Eat Disord , 10, 17. https://doi.org/10.1186/s40337-022-00541-w Coster, W. J., & Mancini, M. C. (2015). Recommendations for translation and cross-cultural adaptation of instruments for occupational therapy research and practice. Revista de Terapia Ocupacional Da Universidade de São Paulo , 26 (1), 50. https://doi.org/10.11606/ISSN.2238-6149.V26I1P50-57 Bayık, M. E., & Gürbüz, S. (2016). Ölçek Uyarlamada Metodoloji Sorunu: Yönetim ve Örgüt Alanında Uyarlanan Ölçekler Üzerinden Bir Araştırma. İş Ve İnsan Dergisi, 3(1), 1-20. https://doi.org/10.18394/iid.15648 Suhr, D. D. (1999). Exploratory or Confirmatory Factor Analysis?. SUGI31. 200-231 Çapık, C. (2014). Geçerlik ve Güvenirlik Çalışmalarında Doğrulayıcı Faktör Analizinin Kullanımı. A nadolu Hemşirelik ve Sağlık Bilimleri Dergisi , 17(3), 196–205. https://dergipark.org.tr/tr/pub/ataunihem/34715 Beavers, A.S., John , L., Richards, J.K., Schuyler, W. H., Gary, J. S. (2013). Practical Considerations for Using Exploratory Factor Analysis in Educational Research. Practical Assessment, Research and Evaluation . 18(6): 1531-7714. https://doi.org/10.7275/qv2q-rk76 Saraçlı, S. (2013). Faktör Analizinde Yer Alan Döndürme Metotlarının Karşılaştırmalı İncelenmesi Üzerine Bir Uygulama. Düzce Üniversitesi Sağlık Bilimleri Enstitüsü Dergisi , 1 (3), 22–26. https://dergipark.org.tr/tr/pub/duzcesbed/66569 Akın, A., Abacı, R., Öveç, Ü. (2007). The Construct Validity and Reliability of The Turkish Version of Self-consciousness Scale. In Journal of Faculty of Educational Sciences . 40 (2): 257-276. Küçükerdönmez, Ö., Akder, R. N., Seçkiner, S., Oksel, E., Akpınar, Ş., & Köksal, E. (2021). Turkish version of the 'Three-Factor Eating Questionnaire-51' for obese individuals: a validity and reliability study. Public health nutrition, 24(11), 3269–3275. https://doi.org/10.1017/S1368980021000574 Çin,A., N.N., Whelan, K. & Özçelik, A.Ö.(2022). Food-related quality of life in inflammatory bowel disease: measuring the validity and reliability of the Turkish version of FR-QOL-29. Health Qual Life Outcomes 20, 103. https://doi.org/10.1186/s12955-022-02014-9 Schumacker, R. E., & Beyerlein, S. T. (2009). Confirmatory Factor Analysis With Different Correlation Types and Estimation Methods. Http://Dx.Doi.Org/10.1207/S15328007SEM0704_6 , 7 (4), 629–636. https://doi.org/10.1207/S15328007SEM0704_6 Walker, D. A., & Smith, T. J. (2017). Computing Robust, Bootstrap-Adjusted Fit Indices for Use With Nonnormal Data. 50 (1–2), 131–137. https://doi.org/10.1080/07481756.2017.1326748 Henning Olsson, U., Foss, T., Troye, S. V, Howell, R. D. (2009). Structural Equation Modelling The Performance of ML, GLS, and WLS Estimation. Structural Equation Modelling Under Conditions . 7:(4) : 557-595 https://doi.org/10.1207/S15328007SEM0704_3 Bollen, K. A., & Stine, R. A. (1992). Bootstrapping Goodness-of-Fit Measures in Structural Equation Models. Sociological Methods & Research , 21(2), 205-229. https://doi.org/10.1177/0049124192021002004 Kim, H., & Millsap, R. (2014). Using the Bollen-Stine Bootstrapping Method for Evaluating Approximate Fit Indices. Multivariate Behavioral Research , 49 (6), 581. https://doi.org/10.1080/00273171.2014.947352 Kaya, B., & Çolakoğlu, Ö. (2015). Empati Düzeyi Belirleme Ölçeği (EDBÖ) Uyarlama Çalışması. İnönü Üniversitesi Eğitim Fakültesi Dergisi , 16(1), 17–30. https://doi.org/10.17679/IUEFD.16127895 Yaman, S. (2016). Adapting of Science Learning Self-Efficacy Belief Scale for Middle School Students: Validity and Reliability Study. Inonu University Journal of the Faculty of Education , 17 (2), 123–140. https://doi.org/10.17679/iuefd.17282415 Gliem, J. A., Gliem, R. R. (2003). Calculating, Interpreting, and Reporting Cronbach’s Alpha Reliability Coefficient for Likert-Type Scales. Midwest Research to Practice Conference in Adult, Continuing, and Community Education . 82-88 Goodboy, A. K., Martin, M. M. (2020). Omega over alpha for reliability estimation of unidimensional communication measures. Annals Of The Internatıonal Communıcatıon Assocıatıon. 44(4): 422–439 https://doi.org/10.1080/23808985.2020.1846135 Hayes, A. F., Jacob, J. C. (2020). Use Omega Rather than Cronbach’s Alpha for Estimating Reliability. But… Communication Methods and Measures . 14 (1): 1–24. https://doi.org/10.1080/19312458.2020.1718629 Watkins, M. W., Dombrowski, S. C., & Canivez, G. L. (2017). Reliability and factorial validity of the Canadian Wechsler Intelligence Scale for Children–Fifth Edition. 6 (4), 252–265. https://doi.org/10.1080/21683603.2017.1342580 Şencan H. (2005). Sosyal ve Davranışsal Ölçümlerde Güvenilirlik ve Geçerlilik.Seçkin Yayıncılık. 8(2). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 01 Sep, 2025 Read the published version in Journal of Eating Disorders → Version 1 posted Editorial decision: Revision requested 22 Aug, 2024 Reviews received at journal 21 Aug, 2024 Reviews received at journal 16 Jul, 2024 Reviewers agreed at journal 11 Jul, 2024 Reviewers agreed at journal 10 Jul, 2024 Reviewers invited by journal 10 Jul, 2024 Editor assigned by journal 10 Jul, 2024 Submission checks completed at journal 10 Jul, 2024 First submitted to journal 08 Jul, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4706202","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":327908726,"identity":"004efafb-8d2b-4919-b51d-21ec844099bf","order_by":0,"name":"Ayşenur Gültekin","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABV0lEQVRIie3QMUvDQBQH8BcCdbkaxyuF5CtcCZQOgl/DMUfBLqVUAtKhSEIhXYpd029REVw9OajLqesNUhoEXRwCBRGU4qVaaRrpLJj/dvfux3v3APLk+dvRPQCGwQDQmDo6yQ0HqG0hmu8lpJRItiRaQjCg7QSAsDWi/0KMsBE9HgdTsA5pfxaLWsu+F4TH3YeWganP2x0MB2W2TrBs2vYocKEiqe+HErtV2SSMTZ7cUkg9HgrVZddJtZHNQrkYOFAJqd9DMaaXEilS4HQsFSkGiqQns2Tj+f2HfChyMRSKLDi9WpJFhhDpVPWEWGryHkhMx6AGuw5UF5wQL0Mq4sUuozsHERT5o4HANJRHbXZ7xl0sIvWXCUZIpIh504jm6MQxrX6dxW+TUzoc8vNZ55W3jH6dz9vdfXNnkN7y3tc2EGGwmVVp8974fmp5GbIq5cmTJ89/zyf7PoxAMYWz+gAAAABJRU5ErkJggg==","orcid":"","institution":"","correspondingAuthor":true,"prefix":"","firstName":"Ayşenur","middleName":"","lastName":"Gültekin","suffix":""},{"id":327908727,"identity":"a38ade87-4908-4608-a2ea-1eebe9c02541","order_by":1,"name":"Çiğdem Bozkır","email":"","orcid":"","institution":"Inonu University","correspondingAuthor":false,"prefix":"","firstName":"Çiğdem","middleName":"","lastName":"Bozkır","suffix":""}],"badges":[],"createdAt":"2024-07-08 14:15:54","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4706202/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4706202/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s40337-025-01359-y","type":"published","date":"2025-09-01T15:57:01+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":62157345,"identity":"0ac2840c-8fa3-4909-bbca-53eec29a684a","added_by":"auto","created_at":"2024-08-09 21:17:00","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":27524,"visible":true,"origin":"","legend":"\u003cp\u003e(Scree plot)\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4706202/v1/18fd8d874ccbf29286c76b39.png"},{"id":90827888,"identity":"f2b148b1-2032-48fa-afa2-4dae227f7e0f","added_by":"auto","created_at":"2025-09-08 16:02:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1128209,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4706202/v1/90eb4f05-8096-4d47-941e-b6d5bf33e308.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Validity and Reliability of the Turkish Version of the Salzburg Emotional Eating Scale: A Psychometric Study","fulltext":[{"header":"Plain English summary","content":"\u003cp\u003eEmotional eating refers to eating in response to emotions rather than hunger. This study aimed to validate the Turkish version of the Salzburg Emotional Eating Scale (SEES), which measures changes in emotional eating behavior. The scale was translated, reviewed by experts, and tested on a sample from Namık Kemal University. The Turkish version demonstrated high reliability and validity, confirming its effectiveness in assessing emotional eating behaviors in the Turkish population. This validated tool can help researchers and clinicians better understand and address emotional eating in Turkiye.\u003c/p\u003e"},{"header":"Background","content":"\u003cp\u003eEmotional eating is characterized by a compulsion to consume food in response to emotional states rather than hunger (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). This behavior often involves excessive consumption to manage negative emotions such as anxiety, anger, and depression (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). While negative emotions are typically associated with emotional eating, recent findings indicate that individuals prone to this behavior also tend to eat more during positive emotional states than those who are not emotional eaters (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe link between emotions and eating behavior has been extensively studied in the context of obesity. Various theories have provided insight into this relationship. Psychosomatic theory posits that individuals with obesity engage in emotional eating due to poor internal perceptual awareness, which impairs their ability to recognize hunger and satiety signals (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). According to Polivy and Herman\u0026rsquo;s restraint theory, emotional eating manifests as increased consumption beyond normal levels in individuals who consciously restrict their food intake when experiencing dysphoric states (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Schachter's 'internal/external' obesity theory suggests that due to inadequate perception of physiological cues, individuals with obesity rely on external stimuli to regulate their eating behavior (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Escape theory contends that individuals use eating as a means to evade negative emotions such as anxiety or depression (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGiven the low emotional awareness observed in individuals with obesity, enhancing emotional regulation skills may help mitigate emotional eating and serve as an effective intervention for obesity (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Emotional eating has been implicated in various eating disorders. Binge eating episodes are associated with emotional eating in individuals with binge eating disorders (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Moreover, individuals diagnosed with anorexia and bulimia nervosa exhibit altered eating behaviors related to emotional eating (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e), and those with night eating syndrome score high on emotional eating measures (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). These findings underscore the importance of assessing emotional eating in the treatment of eating disorders (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRecent research has identified elevated levels of emotional eating among individuals with obesity (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e) and those with binge-eating syndrome (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Factors contributing to emotional eating include the association of nutritional needs with emotional states, differences in hunger perception, escapism from negative situations, and loss of control due to dietary restrictions (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Additionally, sleep duration, sex, and body mass index (BMI) significantly influenced emotional eating behavior. An inverse relationship exists between sleep duration and emotional eating scores (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e), with shorter sleep duration correlating with higher BMI values linked to emotional eating (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Gender differences also affect emotional eating behavior (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMost studies of emotional eating rely on clinical observations and self-report questionnaires (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Commonly used instruments to measure emotional eating include the Dutch Eating Behavior Questionnaire (DEBQ), Three-Factor Eating Questionnaire (TFEQ), Emotional Appetite Scale (EES), and Emotional Eating Scale (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis study aimed to validate and assess the reliability of the Turkish version of the Salzburg Emotional Eating Scale (SEES) developed by Meule, Reichenberger, and Blecher (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). The SEES provides a comprehensive assessment of emotional eating by evaluating responses to specific emotions and distinguishing between overeating and undereating in various emotional contexts. Its versatility and applicability in both psychometric and experimental research highlight the necessity of validating the SEES in different cultural contexts. This study aimed to validate the psychometric characteristics of the SEES in the Turkish context, thereby enhancing the comprehension of emotional eating behaviors within the Turkish population.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eTranslation\u003c/h2\u003e \u003cp\u003ePermission was obtained from the responsible researcher who developed the Salzburg Emotional Eating Scale (SEES) for the scale's Turkish validation and reliability. In the subsequent stage of the study, the scale was translated from English to Turkish by 6 expert individuals proficient in English. Following the necessary evaluations, the scale was then back-translated from Turkish to English by 4 experts proficient in the English language. After the back-translation stage, the scale was evaluated by 6 experts who were proficient in both languages and knowledgeable about the construct to be measured and who were not involved in the translation and back-translation phases. Following the review conducted after both translations, the Turkish version of the scale that emerged was administered to a preliminary sample group consisting of 38 individuals meeting the sample criteria. Feedback regarding the appropriateness and comprehensibility of the scale items was gathered from the participants. In the subsequent step, the Turkish version of the scale was conveyed to the responsible researcher who developed the scale, and their opinions were obtained. Following necessary adjustments, the Turkish version of the scale to be used in the research was finalized.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eThe population of the research consisted of students, academicians, and administrative staff of Namık Kemal University in Tekirdağ. The inclusion criteria were age between 18 and 65 years and not having received a diagnosis of any illness. The exclusion criteria were a diagnosis of any chronic/psychological/psychiatric illness by a doctor, regular use of medication/vitamin supplements, and pregnancy or lactation. The study received ethical approval for its appropriateness from the Namık Kemal University Scientific Research and Publication Ethics Board (2021-02-24/T2021-585).\u003c/p\u003e \u003cp\u003eData collection was conducted between March and May of the 2020\u0026ndash;2021 academic year. The scale was transferred to an online platform using Google Forms and sent via email to Namık Kemal University students, academicians, and administrative staff. Initially, 416 individuals completed the survey. However, 113 individuals who did not meet the inclusion criteria and/or who participated in the survey multiple times were excluded from the study. Therefore, the data of 303 individuals were utilized for the initial phase of the study. Subsequently, for the test-retest reliability analysis of the scale, data collection was completed by reapplying the scale to 30 individuals who participated in the initial phase. At the beginning of the study, participants were asked to create a username using the first letters of their names-surnames and the last 4 digits of their phone numbers to determine whether the same individuals were reached in both phases of data collection.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eData collection\u003c/h2\u003e \u003cp\u003eThe study utilized a demographic information form created by the researcher to obtain sociodemographic data from the students, academicians, and administrative staff involved. Additionally, participants were administered the Salzburg Emotional Eating Scale and the Emotional Eating subscale of the Dutch Eating Behavior Scale.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eDemographic Questionnaire Form\u003c/h2\u003e \u003cp\u003eThe information form prepared by the researcher was used to assess the sociodemographic characteristics of the participants. This section inquired about the participants' sex, age, marital status, education level, occupation, monthly income, health status, medication usage, smoking habits, sleep duration, regular exercise habits, body weight, and height.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eSalzburg Emotional Eating Scale\u003c/h2\u003e \u003cp\u003eThe 'Salzburg Emotional Eating Scale,' developed by Meule, Reichenberger, and Blecher (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e) in the Salzburg region of Austria, is intended to measure changes in the amount of eating in response to positive and negative emotions. The scale consists of 20 items indicating how emotional expressions influence eating behavior and comprises four subscales: happiness, sadness, anger, and anxiety. Each item begins with the stem \"When I am/feel...\" followed by an adjective describing an emotional state. The response options ranged from 1 to 5, indicating \"much less than usual\" to \"much more than usual\" eating behaviors. Scores above three represent increased food intake, a score of three indicates unchanged food intake, and scores below three indicate decreased food intake (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eDutch Eating Behavior Questionnaire (DEBQ)\u003c/h2\u003e \u003cp\u003eThe DEBQ was developed in 1986 by Van Strien and colleagues, and its Turkish validation was conducted by Bozan (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). The scale evaluates three subscales of eating behavior\u0026mdash;external eating, restrained eating, and emotional eating\u0026mdash;comprising 33 items. In this study, the emotional eating subscale, which consists of 13 items, was utilized to assess emotional eating behavior using a 5-point Likert scale (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eThe data were analysed using IBM SPSS 22 and AMOS 24 software. Validity and reliability analyses were conducted to assess the psychometric properties of the SSPE Scale. Cronbach's alpha and McDonald's omega values were examined for reliability, while for validity, the Kaiser‒Meyer‒Olkin (KMO) test, exploratory factor analysis, and confirmatory factor analysis were performed. Spearman correlation analysis was employed to determine criterion-related validity by examining the relationship between the emotional eating subscale of the Dutch Eating Behavior Questionnaire and the Salzburg Emotional Eating Scale. Paired sample t tests and Wilcoxon tests were utilized to assess the stability of the scale over time through retest measurements. A statistical significance level of p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered for all analyses.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThe average age of the individuals in the research group was 22.1\u0026thinsp;\u0026plusmn;\u0026thinsp;4.8 years (within the range of 18\u0026ndash;50 years). A total of 89.1% of the participants were female, while 10.9% were male. The participants consisted of 96% students, 2% academics, and 2% administrative staff (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Similarly, 4% of the respondents had completed high school, 93% had completed undergraduate studies, and 3% had completed postgraduate studies.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistribution of Participants' Demographic Characteristics (n\u0026thinsp;=\u0026thinsp;303)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRegularly exercise habit\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e270\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e\u003cb\u003eSmoking\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e287\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e261\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOccupation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e\u003cb\u003eSleep duration\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e291\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;6 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcademic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u0026ndash;8 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdministrative staff\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 hours \u0026lt;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMonthly income\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e\u003cb\u003eBMI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0-2800 TL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e244\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUnderweight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2801\u0026ndash;5000 TL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5001\u0026ndash;7500 TL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOverweight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7500 TL\u0026lt;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eObese\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eTL: Turkish liras, BMI: Body mass index\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\u003cp\u003eResults of the \u003cb\u003eReliability Analysis\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe Salzburg Emotional Eating Scale was subjected to reliability analysis using invariance, internal consistency, and parallel methods. Invariance was examined using a t test to investigate the relationship between the sadness, anger, and anxiety subscales of the scale administered at two different time points. The analysis revealed no significant difference among the responses given within the subdimensions of the SEES-TR. The test-retest analysis results for the SEES-TR subscales are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTest-retest analyses of the SEES\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSEES-TR Subscales\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ez/t\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFirst test of Happiness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.71\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRetest of Happiness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFirst test of Sadness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.83\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRetest of Sadness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFirst Test of Anger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.68\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRetest of Anger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe First Test of Anxiety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-1.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.19\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRetest of Anxiety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003csup\u003ea\u003c/sup\u003e Wilcoxon test, \u003csup\u003eb\u003c/sup\u003e paired sample t test, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAs a result of the test-retest analysis of the SEES-TR, no significant difference was observed among the subscales. The 'reliability coefficient' for consistency between the two test results was determined by examining the correlation (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eReliability correlations of the SEES test-retest analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSEES-TR subscales\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSadness x Sadness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.777\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026gt;\u0026thinsp;0.001\u003c/b\u003e\u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnger x Anger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.825\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026gt;\u0026thinsp;0.001\u003c/b\u003e\u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnxiety x Anxiety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.698\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026gt;\u0026thinsp;0.001\u003c/b\u003e\u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHappiness x Happiness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.490\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003csup\u003e\u003cb\u003eb\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003ea\u003c/sup\u003e Pearson correlation, \u003csup\u003eb\u003c/sup\u003e Spearman correlation, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eInternal consistency analyses were conducted using Cronbach's α and McDonald's Omega coefficient (ω) for the SEES. The total scale reliability of the SEES-TR was calculated as 0.924 for Cronbach's α. The reliability coefficients for the happiness, sadness, anger, and anxiety subscales were determined to be 0.942, 0.913, 0.913, 0.913, and 0.922, respectively, for Cronbach's α. For McDonald's omega coefficient (ω), the total scale reliability of the SEES-TR was calculated as 0.932. McDonald's Omega coefficients for the Happiness, Sadness, Anger, and Anxiety subscales were determined to be 0.943, 0.917, 0.917, and 0.921, respectively. The reliability coefficients of the SEES-TR are presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMcDonald's ω and Cronbach's α reliability coefficients of the SEES subscales\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eSEES-TR\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubscales\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eMcDonald's\u003c/em\u003e ω\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCronbach α\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHappiness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.943\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.942\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSadness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.917\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.913\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.917\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.913\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnxiety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.921\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.922\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.932\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.924\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTo conduct the parallel-form analysis, the Emotional Subscale of the Dutch Eating Behavior Questionnaire (DEBQ) was utilized. There was no significant relationship between the Happiness subscale of the SEES and the other subscales of the SEES and the total score of the Emotional Subscale of the DEBQ. The relationships between the subscales of the SEE Scale and both of the other subscales and the Emotional Subscale of the DEBQ are presented in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eParallel Form Analysis of SEES Subscales and Total Scoring of the DEBQ Emotional Subscale\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e1. Happiness\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2. Sadness\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAnger\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.698**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAnxiety\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.053\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.511**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.653**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e5. DEBQ\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.522**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.425**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.308**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eValidity Analysis Results\u003c/h2\u003e \u003cp\u003eTranslation, back-translation, expert evaluation, and pilot/pretest studies were conducted under the headings of linguistic, content, and surface validity. For content validity, expert opinions were obtained using the Davis technique (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). The scope validity ratio (SVR) was obtained by comparing the original and Turkish translations of the scale items. An SVR value of \u0026ge;\u0026thinsp;0.80 was expected, and according to expert evaluations, it was determined that the SVR values of the scale items were \u0026ge;\u0026thinsp;0.80 (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e) (Supplemental Table\u0026nbsp;1).\u003c/p\u003e \u003cp\u003eFor surface validity, a pilot/pretest study was conducted by collecting opinions from individuals who were not experts in the researched field but were consistent with the determined sampling (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). The scale was administered to 38 individuals. Participants were asked to read each scale item aloud, express the meaning evoked by each scale item, and fill out the scale appropriately. Additionally, the scale was sent to the scale owner via email, and their opinions were obtained. Based on the feedback received and appropriate changes, the final version of the scale was established (Supplemental Table\u0026nbsp;2).\u003c/p\u003e \u003cp\u003eIn the validation analysis of the SEES, confirmatory and exploratory factor analysis methods were employed. First, the Kaiser‒Meyer‒Olkin (KMO) test was conducted to determine the adequacy of the sample size for factor analysis, and Bartlett's sphericity test was performed to determine the correlations between variables necessary for factor analysis. The KMO coefficient was 0.897, the Bartlett's sphericity test X\u003csup\u003e2\u003c/sup\u003e value was 6033.95, and p\u0026thinsp;=\u0026thinsp;0.000 (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eExploratory factor analysis results\u003c/h2\u003e \u003cp\u003eThe structural validity of the SEES was assessed using exploratory factor analysis (EFA) methods, including principal component analysis and the scree plot technique. The number of factors for the SEE Scale, according to the EFA, was determined by examining the scree plot shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, selecting factors with eigenvalues greater than 1. In the EFA performed to establish the factor structure of the SEES, it was observed that the scale consists of 4 subscales.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs a result of the exploratory factor analysis, the Happiness subscale of the scale formed Factor 2. The first 5 items of the scale were included in this subscale, showing factor loadings ranging from 0.873 to 0.931. Items 6, 7, 8, 9, and 10 formed the Sadness subscale, with factor loadings ranging from 0.562 to 0.839, representing Factor 3. The anger subscale, encompassed by Factor 4, was identified by items 11, 12, 13, 14, and 15, demonstrating factor loading values ranging from 0.393 to 0.881. Additionally, the anxiety subscale, represented as Factor 1, emerged from items 16, 17, 18, 19, and 20 of the scale, exhibiting factor loadings ranging from 0.753 to 0.909. The scale comprises a total of four subscales (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEvaluation of the Factor Structure of the SEES-TR\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScale Items\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFactor 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFactor 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFactor 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFactor 4\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSEES 1.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.897\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSEES 2.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.924\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSEES 3.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.931\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSEES 4.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.873\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSEES 5.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.879\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSEES 6.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.839\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSEES 7.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.854\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSEES 8.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.834\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSEES 9.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.769\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSEES 10.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.562\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSEES 11.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.881\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSEES 12.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.875\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSEES 13.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.797\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSEES 14.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.487\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSEES 15.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.393\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSEES 16.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.761\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSEES 17.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.875\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSEES 18.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.909\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSEES 19.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSEES 20.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.753\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eEigenvalue\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e% Varying\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eCumulative Variance %\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.636\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.892\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.184\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.478\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.564\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.206\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.817\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43.178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63.685\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e73.147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e79.065\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe bootstrap method was utilized in the confirmatory factor analysis. Within the framework of the employed method, the maximum likelihood (ML) estimation method comprised four latent variables on the confirmatory factor analysis (CFA) diagram, representing the scale as happiness, sadness, anger, and anxiety. Regarding the item distribution according to the latent variable in the confirmatory factor analysis, items 1, 2, 3, 4, and 5 represented the happiness subscale; items 6, 7, 8, 9, and 10 represented the sadness subscale; items 11, 12, 13, 14, and 15 represented the anger subscale; and items 16, 17, 18, 19, and 20 represented the anxiety subscale. The confirmatory factor analysis diagram, depicting the latent variables, covariances between latent variables, one-way effects between observable variables and latent variables, and error terms of independent variables, is illustrated in supplemental Fig.\u0026nbsp;2.\u003c/p\u003e \u003cp\u003eThe critical value calculated as 36.794 for the study data with AMOS indicated that the assumption of multivariate normality was not met, as it exceeded 8 (Supplementary Table\u0026nbsp;4). As the data did not exhibit a normal distribution, the 'Bollen-Stine Bootstrap' method was applied for CFA. The bootstrap method is used in AMOS to generate approximate standard errors for many statistics calculated without needing to fulfil the assumption of multivariate normality (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e). Consequently, the bootstrap results were compared with the original ML estimation method outputs for the scale. The bootstrap method, which provides approximate standard errors without requiring the assumption of normality for the data, demonstrated that the confirmatory factor analysis was suitable for parametric statistics.\u003c/p\u003e \u003cp\u003eIn the context of bootstrapping for the SEES, examining the ML model fit indices, the model fit indices χ2/df, GFI, and AGFI were found to be 2.468, 0.877, and 0.830, respectively, while the CFI, RMSEA, NFI, TLI, and IFI were 0.967, 0.074, 0.945, 0.958, and 0.967, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCFA fit index values of the SEES-TR\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndex\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAcceptable Values\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSEES-TR\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eχ2/sd\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u0026thinsp;\u0026le;\u0026thinsp;or \u0026le;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.468\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGFI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.90\u0026thinsp;\u0026le;\u0026thinsp;GFI\u0026thinsp;\u0026le;\u0026thinsp;0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.877\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAGFI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.85\u0026thinsp;\u0026le;\u0026thinsp;AGFI\u0026thinsp;\u0026le;\u0026thinsp;0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.830\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCFI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.90\u0026thinsp;\u0026le;\u0026thinsp;CFI\u0026thinsp;\u0026le;\u0026thinsp;0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.967\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRMSEA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.05\u0026thinsp;\u0026le;\u0026thinsp;RMSEA\u0026thinsp;\u0026le;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.074\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNFI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.90\u0026thinsp;\u0026le;\u0026thinsp;NFI\u0026thinsp;\u0026le;\u0026thinsp;0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.945\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTLI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.90\u0026thinsp;\u0026le;\u0026thinsp;TLI\u0026thinsp;\u0026le;\u0026thinsp;0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.958\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIFI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.90\u0026thinsp;\u0026le;\u0026thinsp;IFI\u0026thinsp;\u0026le;\u0026thinsp;0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.967\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe Salzburg Emotional Eating Scale was developed by Meule et al. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e) to measure emotional eating behaviors by examining different food responses in possible positive and negative emotional states. On the basis of various scales developed in research focusing on emotional eating, such as the Emotional Eating subscale developed by Van Strien et al. (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e), the Emotional Eating Scale by Arnow et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e), and the Emotional Overeating Scale developed by Masheb and Grilo (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e), it was observed that these scales primarily investigated negative emotions (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). In contrast, the Positive and Negative Emotional Eating Scale encompasses both positive and negative emotions but has been shown to be reliable and valid only for female participants (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e). The Emotional Appetite Questionnaire, which covers positive and negative emotional states and measures increased and decreased eating tendencies in response to emotions, was not developed based on experimental data during the scale development phase (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e). The significance of the SEES lies in its detailed delineation of specific emotions and its ability to differentiate between overeating and undereating based on emotions, thus representing an expanded version of previous scales (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn Turkey, scales examining emotional eating behaviors include the Emotional Appetite Questionnaire, which covers both positive and negative emotions. However, the Turkish validation analyses for this scale have not been completed (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). It is believed that the adaptation of the Salzburg Emotional Eating Scale to the Turkish population could offer a broader perspective for studies focused on emotional eating.\u003c/p\u003e \u003cp\u003eIn scale adaptation studies, sample sizes of 100 participants are considered weak for validity and reliability analyses, 200 are considered sufficient, and 300 are considered good (\u003cspan additionalcitationids=\"CR49\" citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e). The present study was conducted using data obtained from 303 participants, including students, academics, and staff at Namık Kemal University in Tekirdağ. Women constituted 89.1% of the participants. In Meule (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e) and Ghafouri et al.'s (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e) studies, the majority of participants were also women (89.1%, 82.9%, 74.4%; 90%), indicating a similar sex distribution across all three studies. The disproportionate distribution of gender, with women being the majority in the present study, is presumed to potentially impact the study results, similar to the original study.\u003c/p\u003e \u003cp\u003eFor the validity analysis of the SEES, structural validity analysis methods, including content and surface validity, were used. During the translation phase of the SEES, as Coster and Mancini (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e) and Bayık (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e) suggested, translation was conducted by two commissions consisting of 6 and 4 expert individuals, respectively (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e). Subsequently, the Davis method was used to analyse content validity. According to Davis (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e), an assessment by at least 2 and up to 20 experts is needed; hence, the evaluation was carried out by 6 expert individuals, revealing KMO values indicating suitability for content validity (\u0026gt;\u0026thinsp;0.80).\u003c/p\u003e \u003cp\u003eFor structural validity, both exploratory and confirmatory factor analyses were employed. As Suhr (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e) emphasized, the objective of exploratory factor analysis is to uncover and explore the factor structure underlying the statements representing the variables of an adapted scale. CFA aims to verify the adequacy of the original factor structure. These methods are frequently preferred for testing and validating models (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eConsidering the criteria outlined by Beavers et al. (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e), the KMO value (0.89) in factor analysis indicated a very good sample size for conducting factor analysis. Additionally, Bartlett's sphericity test (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) confirmed sufficient relationships among the variables for factor analysis. Principal component analysis and scree plot methods were used in exploratory factor analysis to evaluate the 'number of factors or components' and 'factor loading of variables' to determine the structural characteristics of the variables (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e). The EFA revealed that 20 items with factor loading values ranging from 0.393 to 0.931 formed four subscales. The study confirmed that the four subscales aligned with the adapted scale, maintaining compatibility with each other (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn various studies, a criterion value of 0.30 has been considered adequate for factor loading (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e). In the present study, the factor loading of each item was \u0026gt;\u0026thinsp;0.30. A high factor loading indicated the potential presence of the item in the respective subscale. Exploratory factor analysis revealed that the 20 items with factor loadings ranging from 0.393 to 0.931 formed four subscales. The current study demonstrated that the scale consisted of four subscales, and the items constituting each subscale were compatible with the adapted scale (SEES) as per the original study (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAnother analysis of construct validity was CFA. A confirmatory factor analysis was also conducted to assess construct validity. It has been reported that when ML and GLS methods are used for estimating factor loads in data that do not exhibit a normal distribution, they tend to inflate model fit indices and decrease standard error rates (\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e). Therefore, the method chosen for nonnormally distributed data is critical (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e). ADF is an analysis method used when the data do not follow a normal distribution. However, this approach makes few assumptions about the distribution of data. Moreover, it requires a minimum sample size of n: 200 for 'simple' models and an extremely large sample size (n\u0026thinsp;\u0026gt;\u0026thinsp;5,000) for 'complex' models (\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e). Additionally, ADF is prone to weak estimations when the model is misspecified due to the influence of sample size (\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e). The Bollen\u0026ndash;Stine Bootstrap method is a second potential solution provided for multivariate nonnormally distributed data (\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e). Therefore, in the present study, the Bollen\u0026ndash;Stine Bootstrap method was used for DFA.\u003c/p\u003e \u003cp\u003eIn evaluations of fit indices derived from Bollen\u0026ndash;Stine Bootstrap analysis, it has been stated that Bollen\u0026ndash;Stine Bootstrap analysis can provide strong evidence by avoiding biases in estimation values (\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e). Kaya and \u0026Ccedil;olakoğlu resorted to this method in their validity analysis (\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e). Yaman (\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e) mentioned that the application of the bootstrap procedure enhances the parametric statistical fit of the CFA (Yaman, 2016). In the present study, ML fit indices were evaluated within the Bollen\u0026ndash;Stine Bootstrap framework. When examining model fit indices, the χ2 value for the hypothesized model, especially with a large sample size, typically indicates the rejection of the model. A CFI value of 0.96 suggests that this model represents a marginally good fit. The other model fit indices, χ2/sd at 2.46, RMSEA at 0.074, NFI at 0.94, TLI at 0.95, and IFI at 0.96, are within acceptable ranges, while the GFI at 0.87 and AGFI at 0.83 are very close to acceptable ranges. These data indicate that the scale fits well into the model. Meule et al. (2018) stated that within the context of confirmatory factor analysis, CFI\u0026thinsp;=\u0026thinsp;0.917\u0026ndash;0.932 and RMSEA\u0026thinsp;=\u0026thinsp;0.051\u0026ndash;0.073 are considered acceptable (Meule et al., 2018). Ghafouri et al.'s (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e) study reported the model fit indices as CMIND/DF\u0026thinsp;=\u0026thinsp;7.58, GFI\u0026thinsp;=\u0026thinsp;0.91, CFI\u0026thinsp;=\u0026thinsp;0.90, TLI\u0026thinsp;=\u0026thinsp;0.89, and RMSEA\u0026thinsp;=\u0026thinsp;0.061 (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e). Similar to the current study, it was observed that some fit indices are very close to an acceptable range.\u003c/p\u003e \u003cp\u003eReliability analyses revealed that the Cronbach's α coefficients of the SEES-TR subscales of happiness, sadness, anger, and anxiety ranged from 0.913 to 0.942. The Cronbach's α coefficient of the total scale was determined to be 0.924. In scale adaptation studies, a Cronbach's α reliability coefficient\u0026thinsp;\u0026gt;\u0026thinsp;0.80 indicates good reliability, while a value\u0026thinsp;\u0026gt;\u0026thinsp;0.90 indicates excellent reliability (\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e). A total scale and subdimensions\u0026thinsp;\u0026gt;\u0026thinsp;0.90 suggest that the SEES-TR has excellent reliability. According to McDonald's ω coefficient, which is a more general form of Cronbach's α, there is no optimal reliability measure, and it has been reported that the omega (ω) coefficient should be indicated for reliability estimation instead of α (\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e). Therefore, both reliability analysis methods were used in the current study. The omega coefficients of the total SEES-TR and the happiness, sadness, anger, and anxiety subscales were found to be 0.917\u0026ndash;0.943. Watkins et al. (2017) mentioned that the omega coefficient should be above 0.75 (\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e), indicating that the current study's omega reliability coefficient is reliable. In a study by Meule et al. (2018), the Cronbach's α coefficient for the subdimensions of the scale ranged from α\u0026thinsp;=\u0026thinsp;0.732\u0026ndash;0.871. In the present study, the reliability coefficients of the total scale and subdimensions indicate that the reliability is consistent with that of the original scale (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAnother reliability analysis, the stability of the scale over time, involved readministering the scale to a subset of participants after 3 weeks. There was no statistically significant difference, and the reliability coefficient between the two test results was calculated. For the sadness and anger subscales of the study, the reliability coefficients were found to be 0.777 and 0.825, respectively, which are above the reported sufficient reliability coefficient (\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e). The reliability coefficient for the anxiety subscale was 0.698, which is very close to the 0.70 adequacy level, while the reliability coefficient for the happiness subscale was 0.490. Ghafouri et al. (2021) noted that the lack of a retest analysis was a limitation of their study and emphasized the need for this analysis to be conducted in the future for scale (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e). In the current study, the term 'reliable scale' was reinforced through the stability method.\u003c/p\u003e \u003cp\u003eIn this study, the parallel form method, another reliability analysis method, was also used by sampling different items that could represent the same behavioral patterns to create two equivalent forms. These forms were simultaneously administered, and the DEBQ emotional subscale was used for the parallel-form method in accordance with the original study of the scale (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). The DEBQ emotional subscale showed a positive correlation with the sadness, anger, and anxiety subscales, demonstrating consistency with the SEES. A negative correlation between the SEES happiness subscale and the DEBQ emotional subscale was suggested (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e); similarly, in the current study, it was found that the happiness subscale correlated negatively with the DEBQ emotional subscale but not significantly.\u003c/p\u003e \u003cp\u003eAlthough the SEES-TR could allow for a more detailed analysis of emotional effects on eating behavior, it is still potentially biased based on self-reports. Specifically, the scale requires participants to have significant awareness of fluctuations in their daily emotions and their impact on food intake. Responses to the scale will be shaped by this awareness. A Turkish validation and reliability study of the SEES was conducted on individuals with higher education levels. Hence, to enhance the applicability of the study to all segments of society, future studies involving individuals with lower levels of education are recommended. For studies focusing on the impact of emotions on eating behavior, it is suggested that a scale be used to explore a broader range of emotions and changes in food intake.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe SEES-TR is positioned as a valuable tool for a comprehensive assessment of emotional eating, extending beyond psychometric domains to encompass experimental research. This instrument holds promise for exploring new avenues in the investigation of mechanisms underlying emotional eating and in clinical research. As an enhanced iteration of preceding scales, the SEES-TR allows for a nuanced examination of specific emotions and a differentiation between overeating and undereating based on emotional triggers, thereby establishing its significance. This study concluded that the SEES can be considered a valid and reliable instrument in the Turkish language. It is anticipated that its application will contribute meaningfully to research areas associated with emotional eating in Turkiye.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eSEES: Salzburg Emotional Eating Scale\u003c/p\u003e\n\u003cp\u003eSEES-TR: Salzburg Emotional Eating Scale-Turkish\u003c/p\u003e\n\u003cp\u003eKMO: Kaiser‒Meyer‒Olkin\u003c/p\u003e\n\u003cp\u003eCFA: Confirmatory Factor Analysis\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval (2021-02-24/T2021-585) was obtained from the Tekirdag Namık Kemal University Research Ethics Committee. The study was performed in accordance with the ethical standards of the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. Online informed consent was obtained from all participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe dataset used during the current study is available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere was no funding to support the present study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eC\u003c/strong\u003e\u003cstrong\u003eontributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAG and \u0026Ccedil;B designed the study. \u0026Ccedil;B directed and supervised the project. AG collected the data. AG and \u0026Ccedil;B conducted the data analysis. AG drafted the manuscript, with \u0026Ccedil;B providing critical revisions. All authors have read and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank the students, academics and administrative staff of Tekirdağ Namık Kemal University, who composed the sample of the study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eDe Lauzon, B., Romon, M., Deschamps, V., Lafay, L., Borys, J. M., Karlsson, J., Ducimeti\u0026egrave;re, P., \u0026amp; Charles, M. A. (2004). The Three-Factor Eating Questionnaire-R18 is able to distinguish among different eating patterns in a general population. \u003cem\u003eJournal of Nutrition\u003c/em\u003e, \u003cem\u003e134\u003c/em\u003e(9), 2372\u0026ndash;2380. https://doi.org/10.1093/jn/134.9.2372\u003c/li\u003e\n\u003cli\u003eRotella, F., Mannucci, E., Gemignani, S., Lazzeretti, L., Fioravanti, G., \u0026amp; Ricca, V. (2018). Emotional eating and temperamental traits in Eating Disorders: A dimensional approach. \u003cem\u003ePsychiatry Research\u003c/em\u003e, \u003cem\u003e264\u003c/em\u003e, 1\u0026ndash;8. https://doi.org/10.1016/j.psychres.2018.03.066\u003c/li\u003e\n\u003cli\u003eRotella, F., Mannucci, E., Gemignani, S., Lazzeretti, L., Fioravanti, G., \u0026amp; Ricca, V. (2018). Emotional eating and temperamental traits in Eating Disorders: A dimensional approach. \u003cem\u003ePsychiatry Research\u003c/em\u003e, \u003cem\u003e264\u003c/em\u003e, 1\u0026ndash;8. https://doi.org/10.1016/j.psychres.2018.03.066V\u003c/li\u003e\n\u003cli\u003eArnow, B., Kenardy, J., \u0026amp; Agras, W. S. 1995. (n.d.). \u003cem\u003eThe Emotional Eating Scale: The Development of a Measure to Assess Coping with Negative Affect by Eating\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eBongers, P., Jansen, A., Havermans, R., Roefs, A., \u0026amp; Nederkoorn, C. (2013). Happy eating: The underestimated role of overeating in a positive mood. \u003cem\u003eAppetite\u003c/em\u003e, \u003cem\u003e67\u003c/em\u003e, 74\u0026ndash;80. https://doi.org/10.1016/j.appet.2013.03.017\u003c/li\u003e\n\u003cli\u003eBongers, P., Jansen, A., Houben, K., \u0026amp; Roefs, A. (2013). Happy eating: The single target implicit association test predicts overeating after positive emotions. \u003cem\u003eEating Behaviors\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e(3), 348\u0026ndash;355. https://doi.org/10.1016/j.eatbeh.2013.06.007\u003c/li\u003e\n\u003cli\u003eMcAtamney, K., Mantzios, M., Egan, H., \u0026amp; Wallis, D. J. (2021). Emotional eating during COVID-19 in the United Kingdom: Exploring the roles of alexithymia and emotion dysregulation. \u003cem\u003eAppetite\u003c/em\u003e, \u003cem\u003e161\u003c/em\u003e. https://doi.org/10.1016/J.APPET.2021.105120 \u003c/li\u003e\n\u003cli\u003eKaplan, H. I., \u0026amp; Kaplan, H. S. (1957). The psychosomatic concept of obesity. \u003cem\u003eThe Journal of Nervous and Mental Disease\u003c/em\u003e, \u003cem\u003e125\u003c/em\u003e(2), 181\u0026ndash;201. https://doi.org/10.1097/00005053-195704000-00004 \u003c/li\u003e\n\u003cli\u003eCanetti, L., Bachar, E., \u0026amp; Berry, E. M. (2002). Food and emotion. \u003cem\u003eBehavioural Processes\u003c/em\u003e, \u003cem\u003e60\u003c/em\u003e(2), 157\u0026ndash;164. https://doi.org/10.1016/S0376-6357(02)00082-7\u003c/li\u003e\n\u003cli\u003ePolivy, J., \u0026amp; Herman, C. P. (1985). Dieting and binging: A causal analysis. \u003cem\u003eAmerican Psychologist\u003c/em\u003e, \u003cem\u003e40\u003c/em\u003e(2), 193\u0026ndash;201. https://doi.org/10.1037//0003-066x.40.2.193 \u003c/li\u003e\n\u003cli\u003eOuwens, M. A., Van Strien, T., \u0026amp; Van Der Staak, C. P. F. (2003). Tendency toward overeating and restraint as predictors of food consumption. \u003cem\u003eAppetite\u003c/em\u003e, \u003cem\u003e40\u003c/em\u003e(3), 291\u0026ndash;298. https://doi.org/10.1016/S0195-6663(03)00006-0 \u003c/li\u003e\n\u003cli\u003eSchachter, S., Goldman, R., \u0026amp; Gordon, A. (1968). Effects of fear, food deprivation, and obesity on eating. \u003cem\u003eJournal of Personality and Social Psychology\u003c/em\u003e, \u003cem\u003e10\u003c/em\u003e(2), 91\u0026ndash;97. https://doi.org/10.1037/h0026284 \u003c/li\u003e\n\u003cli\u003eHeatherton, T. F., \u0026amp; Baumeister, R. F. (1991). Binge eating as escape from self-awareness. \u003cem\u003ePsychological Bulletin\u003c/em\u003e, \u003cem\u003e110\u003c/em\u003e(1), 86\u0026ndash;108. https://doi.org/10.1037/0033-2909.110.1.86 \u003c/li\u003e\n\u003cli\u003eSpoor, S. T. P., Bekker, M. H. J., Van Strien, T., \u0026amp; van Heck, G. L. (2007). Relations between negative affect, coping, and emotional eating. \u003cem\u003eAppetite\u003c/em\u003e, \u003cem\u003e48\u003c/em\u003e(3), 368\u0026ndash;376. https://doi.org/10.1016/j.appet.2006.10.005 \u003c/li\u003e\n\u003cli\u003eFernandes, J., Ferreira-Santos, F., Miller, K., \u0026amp; Torres, S. (2018). Emotional processing in obesity: a systematic review and exploratory meta-analysis. In \u003cem\u003eObesity Reviews\u003c/em\u003e (Vol. 19, Issue 1, pp. 111\u0026ndash;120). Blackwell Publishing Ltd. https://doi.org/10.1111/obr.12607 \u003c/li\u003e\n\u003cli\u003eAparicio, E., Canals, J., Arija, V., De Henauw, S., \u0026amp; Michels, N. (2016). The role of emotion regulation in childhood obesity: Implications for prevention and treatment. \u003cem\u003eNutrition Research Reviews\u003c/em\u003e, \u003cem\u003e29\u003c/em\u003e(1), 17\u0026ndash;29. https://doi.org/10.1017/S0954422415000153 \u003c/li\u003e\n\u003cli\u003eWolff, G. E., Crosby, R. D., Roberts, J. A., \u0026amp; Wittrock, D. A. (2000). Differences in daily stress, mood, coping, and eating behavior in binge eating and nonbinge eating college women. \u003cem\u003eAddictive Behaviors\u003c/em\u003e, \u003cem\u003e25\u003c/em\u003e(2), 205\u0026ndash;216. https://doi.org/10.1016/S0306-4603(99)00049-0 \u003c/li\u003e\n\u003cli\u003eMasheb, R. M., \u0026amp; Grilo, C. M. (2006a). Emotional overeating and its associations with eating disorder psychopathology among overweight patients with binge eating disorder. \u003cem\u003eInternational Journal of Eating Disorders\u003c/em\u003e, \u003cem\u003e39\u003c/em\u003e(2), 141\u0026ndash;146. https://doi.org/10.1002/eat.20221 \u003c/li\u003e\n\u003cli\u003eRicca, V., Castellini, G., Fioravanti, G., Lo Sauro, C., Rotella, F., Ravaldi, C., Lazzeretti, L., \u0026amp; Faravelli, C. (2012). Emotional eating in anorexia nervosa and bulimia nervosa. \u003cem\u003eComprehensive Psychiatry\u003c/em\u003e, \u003cem\u003e53\u003c/em\u003e(3), 245\u0026ndash;251. https://doi.org/10.1016/j.comppsych.2011.04.062 \u003c/li\u003e\n\u003cli\u003eMeule, A., Richard, A., Schnepper, R., Reichenberger, J., Georgii, C., Naab, S., Voderholzer, U., \u0026amp; Blechert, J. (2019). Emotion regulation and emotional eating in anorexia nervosa and bulimia nervosa.\u003cem\u003e29\u003c/em\u003e(2), 175\u0026ndash;191. https://doi.org/10.1080/10640266.2019.1642036\u003c/li\u003e\n\u003cli\u003eMeule, A., Allison, K. C., \u0026amp; Platte, P. (2014). Emotional Eating Moderates the Relationship of Night Eating with Binge Eating and Body Mass. \u003cem\u003eEuropean Eating Disorders Review\u003c/em\u003e, \u003cem\u003e22\u003c/em\u003e(2), 147\u0026ndash;151. https://doi.org/10.1002/erv.2272 \u003c/li\u003e\n\u003cli\u003eReichenberger, J., Schnepper, R., Arend, A., Richard, A., Voderholzer, U., Naab, S., \u0026amp; Blechert, J. (2021). Emotional eating across different eating disorders and the role of body mass, restriction, and binge eating. \u003cem\u003eThe International Journal of Eating Disorders\u003c/em\u003e, \u003cem\u003e54\u003c/em\u003e(5), 773. https://doi.org/10.1002/EAT.23477 \u003c/li\u003e\n\u003cli\u003eVasileiou, V., \u0026amp; Abbott, S. (2023). Emotional eating among adults with healthy weight, overweight and obesity: a systematic review and meta-analysis. Journal of human nutrition and dietetics. 36(5), 1922\u0026ndash;1930. https://doi.org/10.1111/jhn.13176\u003c/li\u003e\n\u003cli\u003eRoher, S., Latzer, Y., \u0026amp; Geliebter, A. (2014). Negative Emotional Eating among Obese Individuals with and without Binge Eating Behavior and Night Eating Syndrome. The Israel journal of psychiatry and related sciences, 51(3), 219\u0026ndash;225.\u003c/li\u003e\n\u003cli\u003eKonttinen, H. (2020). Emotional eating and obesity in adults: the role of depression, sleep and genes. \u003cem\u003eProceedings of the Nutrition Society\u003c/em\u003e, \u003cem\u003e79\u003c/em\u003e(3), 283\u0026ndash;289. https://doi.org/10.1017/S0029665120000166 \u003c/li\u003e\n\u003cli\u003eDweck, J. S., Jenkins, S. M., \u0026amp; Nolan, L. J. (2014). The role of emotional eating and stress in the influence of short sleep on food consumption. \u003cem\u003eAppetite\u003c/em\u003e, \u003cem\u003e72\u003c/em\u003e, 106\u0026ndash;113. https://doi.org/10.1016/j.appet.2013.10.001 \u003c/li\u003e\n\u003cli\u003eVan Strien, T., \u0026amp; Koenders, P. G. (2014). Effects of emotional eating and short sleep duration on weight gain in female employees. \u003cem\u003eJournal of Occupational and Environmental Medicine\u003c/em\u003e, \u003cem\u003e56\u003c/em\u003e(6), 659\u0026ndash;666. https://doi.org/10.1097/JOM.0000000000000172 \u003c/li\u003e\n\u003cli\u003eKonttinen, H., Van Strien, T., M\u0026auml;nnist\u0026ouml;, S., Jousilahti, P., \u0026amp; Haukkala, A. (2019). Depression, emotional eating and long-term weight changes: A population-based prospective study. \u003cem\u003eInternational Journal of Behavioral Nutrition and Physical Activity\u003c/em\u003e, \u003cem\u003e16\u003c/em\u003e(1). https://doi.org/10.1186/s12966-019-0791-8\u003c/li\u003e\n\u003cli\u003eKeck, M. M., Vivier, H., Cassisi, J. E., Dvorak, R. D., Dunn, M. E., Neer, S. M., \u0026amp; Ross, E. J. (n.d.). \u003cem\u003eExamining the Role of Anxiety and Depression in Dietary Choices among College Students\u003c/em\u003e. https://doi.org/10.3390/nu12072061\u003c/li\u003e\n\u003cli\u003eSanlier, N., \u0026amp; Dilek Ogretir, A. (2008). The Relationship Between Stress and Eating Behaviors among Turkish Adolescence. \u003cem\u003eWorld Applied Sciences Journal\u003c/em\u003e, \u003cem\u003e4\u003c/em\u003e(2), 233\u0026ndash;237.\u003c/li\u003e\n\u003cli\u003eBozan, N. (2009). Hollanda Yeme Davranışı (DEBQ) Anketinin T\u0026uuml;rk \u0026Uuml;niversite \u0026Ouml;ğrencilerinde Ge\u0026ccedil;erlik ve G\u0026uuml;venirliğinin Sınanması.\u003cem\u003eY\u0026uuml;ksek lisans Tezi\u003c/em\u003e, \u003cem\u003eBaşkent \u0026Uuml;niversitesi Sağlık Bilimleri Enstit\u0026uuml;s\u0026uuml; Beslenme \u003c/em\u003e\u003cem\u003eve Diyetetik Anabilimdalı.\u003c/em\u003e\u003c/li\u003e\n\u003cli\u003eKirac, D., Kaspar, E., Avcilar, T., Cakir, O., Ulucan, K., Kurtel, H., Deyneli, O., \u0026amp; Guney, A. (2015). A New Method For Investigating Eating Behaviours Related With Obesity;Three-Factor Eating Questionnaire \u0026quot;. \u003cem\u003eJournal of Marmara University Institute of Health Sciences\u003c/em\u003e, \u003cem\u003e5\u003c/em\u003e(3), 1. https://doi.org/10.5455/musbed.20150602015512 \u003c/li\u003e\n\u003cli\u003eKarakuş, S. Ş., Yıldırım, H., \u0026amp; B\u0026uuml;y\u0026uuml;k\u0026ouml;zt\u0026uuml;rk, Ş. (2016). Adaptation of three factor eating questionnaire (TFEQ-R21) into Turkish culture: A validity and reliability study. \u003cem\u003ePrev Med Bull\u003c/em\u003e, \u003cem\u003e15\u003c/em\u003e, 229. https://doi.org/10.5455/pmb.1-1446540396 \u003c/li\u003e\n\u003cli\u003eDemi̇rel, B., Yavuz, F. K., Karadere E., Şafak, Y., T\u0026uuml;rk\u0026ccedil;apar, H. (2014). Duygusal İştah Anketi\u0026rsquo;nin T\u0026uuml;rk\u0026ccedil;e Ge\u0026ccedil;erlik ve G\u0026uuml;venilirliği, Beden Kitle İndeksi ve Duygusal Şemalarla İlişkisi. \u003cem\u003eBilişsel Davranış\u0026ccedil;ı Psikoterapi ve Araştırmalar Dergisi.\u003c/em\u003e 3:171-181\u003c/li\u003e\n\u003cli\u003eBektas, M., Bektas, I., Selekoğlu, Y., Akdeniz Kudubes, A., Sal Altan, S., \u0026amp; Ayar, D. (2016). \u003cem\u003ePsychometric properties of the Turkish version of the Emotional Eating Scale for children and adolescents\u003c/em\u003e. https://doi.org/10.1016/j.eatbeh.2016.06.021 \u003c/li\u003e\n\u003cli\u003eKara\u0026ccedil;am, Z. (2019). Adaptation of Scales to Turkish. In \u003cem\u003eKara\u0026ccedil;am\u003c/em\u003e (Vol. 2, Issue 1).\u003c/li\u003e\n\u003cli\u003eAkın, A., Yıldız, B., \u0026Ouml;z\u0026ccedil;elik, B. (2016). Duygusal Yeme \u0026Ouml;l\u0026ccedil;eğinin T\u0026uuml;rk\u0026ccedil;e Versiyonunun Ge\u0026ccedil;erlik Ve G\u0026uuml;venirliği. \u003cem\u003eUluslararası Sosyal Araştırmalar Dergisi. 9(\u003c/em\u003e44): 776-781 \u003c/li\u003e\n\u003cli\u003eDoǧan, T., Tekin, E. G., \u0026amp; Katrancioǧlu, A. (2011). Feeding your feelings: A self-report measure of emotional eating. \u003cem\u003eProcedia - Social and Behavioral Sciences\u003c/em\u003e, \u003cem\u003e15\u003c/em\u003e, 2074\u0026ndash;2077. https://doi.org/10.1016/J.SBSPRO.2011.04.056 \u003c/li\u003e\n\u003cli\u003eMeule, A., Reichenberger, J., Blechert, J., \u0026amp; Nolan, L. J. (2018). \u003cem\u003eDevelopment and Preliminary Validation of the Salzburg Emotional Eating Scale\u003c/em\u003e. \u003cem\u003e9\u003c/em\u003e(February). https://doi.org/10.3389/fpsyg.2018.00088 \u003c/li\u003e\n\u003cli\u003eVan Strien, T., Frijters, J. E. R., Bergers, G. P. A., \u0026amp; Defares, P. B. (1986). The Dutch Eating Behavior Questionnaire (DEBQ) for assessment of restrained, emotional, and external eating behavior. \u003cem\u003eInternational Journal of Eating Disorders\u003c/em\u003e, \u003cem\u003e5\u003c/em\u003e(2), 295\u0026ndash;315. https://doi.org/10.1002/1098108 \u003c/li\u003e\n\u003cli\u003eDavis, L. L. (1992). Instrument review: Getting the most from a panel of experts. \u003cem\u003eApplied Nursing Research\u003c/em\u003e, \u003cem\u003e5\u003c/em\u003e(4), 194\u0026ndash;197. https://doi.org/10.1016/S0897-1897(05)80008-4 \u003c/li\u003e\n\u003cli\u003e\u0026Ouml;zt\u0026uuml;rk, H., Babacan, E., (2012). A Study in Scale Development: The Occupational Safety Scale (OSS) for Health Care Personnel Working in Hospital. \u003cem\u003eHemşirelikte Eğitim ve Araştırma Dergisi\u003c/em\u003e (Vol. 9, Issue 1).\u003c/li\u003e\n\u003cli\u003eByrne, B.M. (2010). Structural Equation Modeling With AMOS: Basic Concepts, Applications, and Programming, Second Edition (2nd ed.). Routledge. https://doi.org/10.4324/9780203805534\u003c/li\u003e\n\u003cli\u003eMasheb, R. M., \u0026amp; Grilo, C. M. (2006b). Emotional overeating and its associations with eating disorder psychopathology among overweight patients with Binge eating disorder. \u003cem\u003eInternational Journal of Eating Disorders\u003c/em\u003e, \u003cem\u003e39\u003c/em\u003e(2), 141\u0026ndash;146. https://doi.org/10.1002/eat.20221 \u003c/li\u003e\n\u003cli\u003eSultson, H., Kukk, K., \u0026amp; Akkermann, K. (2017). Positive and negative emotional eating have different associations with overeating and binge eating: Construction and validation of the Positive-Negative Emotional Eating Scale. \u003cem\u003eAppetite\u003c/em\u003e, \u003cem\u003e116\u003c/em\u003e, 423\u0026ndash;430. https://doi.org/10.1016/j.appet.2017.05.035 \u003c/li\u003e\n\u003cli\u003eGeliebter, A., \u0026amp; Aversa, A. (2003). Emotional eating in overweight, normal weight, and underweight individuals. \u003cem\u003eEating Behaviors\u003c/em\u003e, \u003cem\u003e3\u003c/em\u003e(4), 341\u0026ndash;347. https://doi.org/10.1016/S1471-0153(02)00100-9\u003c/li\u003e\n\u003cli\u003eNolan, L. J., Halperin, L. B., Geliebter, A. (2010). Emotional Appetite Questionnaire. Construct Validity and Relationship with BMI. \u003cem\u003eAppetite\u003c/em\u003e. \u003cem\u003e54\u003c/em\u003e(2): 314\u0026ndash;319 https://doi.org/10.1016/j.appet.2009.12.004\u003c/li\u003e\n\u003cli\u003eAKBAŞ, U., KARABAY, E., AYAZ, A., DEMİR, O. (2019). T\u0026uuml;rkiye \u0026Ouml;l\u0026ccedil;me Ara\u0026ccedil;ları Dizininde Yer Alan A\u0026ccedil;ımlayıcı Fakt\u0026ouml;r Analizi \u0026Ccedil;alışmalarının Paralel Analiz Sonu\u0026ccedil;ları İle Karşılaştırılması\u003cem\u003e. Journal of Theoretical Educational Science\u003c/em\u003e, \u003cem\u003e12\u003c/em\u003e(3): 1095\u0026ndash;1123 https://doi.org/10.30831/akukeg.453786 \u003c/li\u003e\n\u003cli\u003eCOMREY, A. L. (1978). Common Methodological Problems İn Factor Analytic Studies. \u003cem\u003eJournal of Consulting and Clinical Psychology\u003c/em\u003e. \u003cem\u003e46\u003c/em\u003e(4): 648\u0026ndash;659 https://doi.org/10.1037/0022-006X.46.4.648\u003c/li\u003e\n\u003cli\u003eDE WİNTER, J. C. F., DODOU, D., WİERİNGA, P. A. (2009). Exploratory Factor Analysis With Small Sample Sizes. \u003cem\u003eMultivariate Behavioral Research\u003c/em\u003e. \u003cem\u003e44\u003c/em\u003e(2): 147\u0026ndash;181 https://doi.org/10.1080/00273170902794206\u003c/li\u003e\n\u003cli\u003eGhafouri, S., Abdollahi, A., Suksatan, W. et al. (2022). Psychometric comparison of the Persian Salzburg Emotional Eating Scale and Emotional Eater Questionnaire among Iranian adults. \u003cem\u003eJ Eat Disord\u003c/em\u003e\u003cem\u003e, \u003c/em\u003e10, 17. https://doi.org/10.1186/s40337-022-00541-w\u003c/li\u003e\n\u003cli\u003eCoster, W. J., \u0026amp; Mancini, M. C. (2015). Recommendations for translation and cross-cultural adaptation of instruments for occupational therapy research and practice. \u003cem\u003eRevista de Terapia Ocupacional Da Universidade de S\u0026atilde;o Paulo\u003c/em\u003e, \u003cem\u003e26\u003c/em\u003e(1), 50. https://doi.org/10.11606/ISSN.2238-6149.V26I1P50-57\u003c/li\u003e\n\u003cli\u003eBayık, M. E., \u0026amp; G\u0026uuml;rb\u0026uuml;z, S. (2016). \u0026Ouml;l\u0026ccedil;ek Uyarlamada Metodoloji Sorunu: Y\u0026ouml;netim ve \u0026Ouml;rg\u0026uuml;t Alanında Uyarlanan \u0026Ouml;l\u0026ccedil;ekler \u0026Uuml;zerinden Bir Araştırma. İş Ve İnsan Dergisi, 3(1), 1-20. https://doi.org/10.18394/iid.15648\u003c/li\u003e\n\u003cli\u003eSuhr, D. D. (1999). Exploratory or Confirmatory Factor Analysis?. SUGI31. 200-231\u003c/li\u003e\n\u003cli\u003e\u0026Ccedil;apık, C. (2014). Ge\u0026ccedil;erlik ve G\u0026uuml;venirlik \u0026Ccedil;alışmalarında Doğrulayıcı Fakt\u0026ouml;r Analizinin Kullanımı. A\u003cem\u003enadolu Hemşirelik ve Sağlık Bilimleri Dergisi\u003c/em\u003e, 17(3), 196\u0026ndash;205. https://dergipark.org.tr/tr/pub/ataunihem/34715\u003c/li\u003e\n\u003cli\u003eBeavers, A.S., John , L., Richards, J.K., Schuyler, W. H., Gary, J. S. (2013). Practical Considerations for Using Exploratory Factor Analysis in Educational Research. \u003cem\u003ePractical Assessment, Research and Evaluation\u003c/em\u003e. 18(6): 1531-7714. https://doi.org/10.7275/qv2q-rk76\u003c/li\u003e\n\u003cli\u003eSara\u0026ccedil;lı, S. (2013). Fakt\u0026ouml;r Analizinde Yer Alan D\u0026ouml;nd\u0026uuml;rme Metotlarının Karşılaştırmalı İncelenmesi \u0026Uuml;zerine Bir Uygulama. \u003cem\u003eD\u0026uuml;zce \u0026Uuml;niversitesi Sağlık Bilimleri Enstit\u0026uuml;s\u0026uuml; Dergisi\u003c/em\u003e, \u003cem\u003e1\u003c/em\u003e(3), 22\u0026ndash;26. https://dergipark.org.tr/tr/pub/duzcesbed/66569\u003c/li\u003e\n\u003cli\u003eAkın, A., Abacı, R., \u0026Ouml;ve\u0026ccedil;, \u0026Uuml;. (2007). The Construct Validity and Reliability of The Turkish Version of Self-consciousness Scale. In \u003cem\u003eJournal of Faculty of Educational Sciences\u003c/em\u003e. 40 (2): 257-276.\u003c/li\u003e\n\u003cli\u003eK\u0026uuml;\u0026ccedil;\u0026uuml;kerd\u0026ouml;nmez, \u0026Ouml;., Akder, R. N., Se\u0026ccedil;kiner, S., Oksel, E., Akpınar, Ş., \u0026amp; K\u0026ouml;ksal, E. (2021). Turkish version of the \u0026apos;Three-Factor Eating Questionnaire-51\u0026apos; for obese individuals: a validity and reliability study. Public health nutrition, 24(11), 3269\u0026ndash;3275. https://doi.org/10.1017/S1368980021000574\u003c/li\u003e\n\u003cli\u003e\u0026Ccedil;in,A., N.N., Whelan, K. \u0026amp; \u0026Ouml;z\u0026ccedil;elik, A.\u0026Ouml;.(2022). Food-related quality of life in inflammatory bowel disease: measuring the validity and reliability of the Turkish version of FR-QOL-29. Health Qual Life Outcomes 20, 103. https://doi.org/10.1186/s12955-022-02014-9\u003c/li\u003e\n\u003cli\u003eSchumacker, R. E., \u0026amp; Beyerlein, S. T. (2009). Confirmatory Factor Analysis With Different Correlation Types and Estimation Methods. \u003cem\u003eHttp://Dx.Doi.Org/10.1207/S15328007SEM0704_6\u003c/em\u003e, \u003cem\u003e7\u003c/em\u003e(4), 629\u0026ndash;636. https://doi.org/10.1207/S15328007SEM0704_6 \u003c/li\u003e\n\u003cli\u003eWalker, D. A., \u0026amp; Smith, T. J. (2017). Computing Robust, Bootstrap-Adjusted Fit Indices for Use With Nonnormal Data. \u003cem\u003e50\u003c/em\u003e(1\u0026ndash;2), 131\u0026ndash;137. https://doi.org/10.1080/07481756.2017.1326748\u003c/li\u003e\n\u003cli\u003eHenning Olsson, U., Foss, T., Troye, S. V, Howell, R. D. (2009). Structural Equation Modelling The Performance of ML, GLS, and WLS Estimation. \u003cem\u003eStructural Equation Modelling Under Conditions\u003c/em\u003e. 7:(4) : 557-595\u003cem\u003e \u003c/em\u003ehttps://doi.org/10.1207/S15328007SEM0704_3\u003c/li\u003e\n\u003cli\u003eBollen, K. A., \u0026amp; Stine, R. A. (1992). Bootstrapping Goodness-of-Fit Measures in Structural Equation Models. \u003cem\u003eSociological Methods \u0026amp; Research\u003c/em\u003e, 21(2), 205-229. https://doi.org/10.1177/0049124192021002004\u003c/li\u003e\n\u003cli\u003eKim, H., \u0026amp; Millsap, R. (2014). Using the Bollen-Stine Bootstrapping Method for Evaluating Approximate Fit Indices. \u003cem\u003eMultivariate Behavioral Research\u003c/em\u003e, \u003cem\u003e49\u003c/em\u003e(6), 581. https://doi.org/10.1080/00273171.2014.947352 \u003c/li\u003e\n\u003cli\u003eKaya, B., \u0026amp; \u0026Ccedil;olakoğlu, \u0026Ouml;. (2015). Empati D\u0026uuml;zeyi Belirleme \u0026Ouml;l\u0026ccedil;eği (EDB\u0026Ouml;) Uyarlama \u0026Ccedil;alışması. \u003cem\u003eİn\u0026ouml;n\u0026uuml; \u0026Uuml;niversitesi Eğitim Fak\u0026uuml;ltesi Dergisi\u003c/em\u003e, 16(1), 17\u0026ndash;30. https://doi.org/10.17679/IUEFD.16127895\u003c/li\u003e\n\u003cli\u003eYaman, S. (2016). Adapting of Science Learning Self-Efficacy Belief Scale for Middle School Students: Validity and Reliability Study. \u003cem\u003eInonu University Journal of the Faculty of Education\u003c/em\u003e, \u003cem\u003e17\u003c/em\u003e(2), 123\u0026ndash;140. https://doi.org/10.17679/iuefd.17282415\u003c/li\u003e\n\u003cli\u003eGliem, J. A., Gliem, R. R. (2003). Calculating, Interpreting, and Reporting Cronbach\u0026rsquo;s Alpha Reliability Coefficient for Likert-Type Scales. \u003cem\u003eMidwest Research to Practice Conference in Adult, Continuing, and Community Education\u003c/em\u003e. 82-88\u003c/li\u003e\n\u003cli\u003eGoodboy, A. K., Martin, M. M. (2020). Omega over alpha for reliability estimation of unidimensional communication measures. \u003cem\u003eAnnals Of The Internatıonal Communıcatıon Assocıatıon.\u003c/em\u003e 44(4): 422\u0026ndash;439 https://doi.org/10.1080/23808985.2020.1846135 \u003c/li\u003e\n\u003cli\u003eHayes, A. F., Jacob, J. C. (2020). Use Omega Rather than Cronbach\u0026rsquo;s Alpha for Estimating Reliability. But\u0026hellip;\u003cem\u003e Communication Methods and Measures\u003c/em\u003e. \u003cem\u003e14\u003c/em\u003e(1): 1\u0026ndash;24. https://doi.org/10.1080/19312458.2020.1718629 \u003c/li\u003e\n\u003cli\u003eWatkins, M. W., Dombrowski, S. C., \u0026amp; Canivez, G. L. (2017). Reliability and factorial validity of the Canadian Wechsler Intelligence Scale for Children\u0026ndash;Fifth Edition. \u003cem\u003e6\u003c/em\u003e(4), 252\u0026ndash;265. https://doi.org/10.1080/21683603.2017.1342580\u003c/li\u003e\n\u003cli\u003eŞencan H. (2005). Sosyal ve Davranışsal \u0026Ouml;l\u0026ccedil;\u0026uuml;mlerde G\u0026uuml;venilirlik ve Ge\u0026ccedil;erlilik.Se\u0026ccedil;kin Yayıncılık. 8(2).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-eating-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"joed","sideBox":"Learn more about [Journal of Eating Disorders](http://jeatdisord.biomedcentral.com)","snPcode":"40337","submissionUrl":"https://submission.nature.com/new-submission/40337/3","title":"Journal of Eating Disorders","twitterHandle":"@JEatDisord","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Salzburg Emotional Eating Scale, Validation, Reliability, Turkish Population, Emotional Eating","lastPublishedDoi":"10.21203/rs.3.rs-4706202/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4706202/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eThe Salzburg Emotional Eating Scale (SEES) measures emotional eating by evaluating responses to both positive and negative emotions. This study aimed to establish the validity and reliability of the Turkish version of the SEES (SEES-TR).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethod: \u003c/strong\u003eThe SEES was translated into Turkish and back-translated into English. The translated version was reviewed by experts and pretested on a preliminary sample. The final version was administered to 303 participants from Namık Kemal University. The data collected included demographic information and responses to the SEES and the Emotional Eating subscale of the Dutch Eating Behavior Questionnaire (DEBQ). Reliability was assessed using Cronbach's alpha, McDonald's omega, and test-retest analyses. Validity was evaluated using exploratory and confirmatory factor analyses, along with content and surface validity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eThe SEES-TR demonstrated high internal consistency, with Cronbach's alpha values of 0.924 for the total scale and above 0.90 for the subscales. McDonald's omega values supported these findings. Test-retest reliability indicated stability over time. Exploratory factor analysis confirmed a four-factor structure corresponding to happiness, sadness, anger, and anxiety, which was further supported by confirmatory factor analysis. Content and surface validity were established through expert reviews and pretesting.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eThe Turkish version of the Salzburg Emotional Eating Scale is a valid and reliable instrument for assessing emotional eating behaviors in the Turkish population. This tool can be effectively used in both clinical and research settings to evaluate emotional eating in response to various emotional states.\u003c/p\u003e","manuscriptTitle":"Validity and Reliability of the Turkish Version of the Salzburg Emotional Eating Scale: A Psychometric Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-09 21:16:55","doi":"10.21203/rs.3.rs-4706202/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-08-22T07:32:12+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-21T08:34:13+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-16T22:27:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"143727062151012351582688975876080181828","date":"2024-07-11T08:59:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"245855399974102720024972916052596028402","date":"2024-07-11T03:01:00+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-07-11T02:36:08+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-07-10T09:17:19+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-07-10T09:15:57+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Eating Disorders","date":"2024-07-08T14:14:36+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-eating-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"joed","sideBox":"Learn more about [Journal of Eating Disorders](http://jeatdisord.biomedcentral.com)","snPcode":"40337","submissionUrl":"https://submission.nature.com/new-submission/40337/3","title":"Journal of Eating Disorders","twitterHandle":"@JEatDisord","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2c26a2e4-8b9b-4230-9b79-05584ba510af","owner":[],"postedDate":"August 9th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-09-08T15:58:46+00:00","versionOfRecord":{"articleIdentity":"rs-4706202","link":"https://doi.org/10.1186/s40337-025-01359-y","journal":{"identity":"journal-of-eating-disorders","isVorOnly":false,"title":"Journal of Eating Disorders"},"publishedOn":"2025-09-01 15:57:01","publishedOnDateReadable":"September 1st, 2025"},"versionCreatedAt":"2024-08-09 21:16:55","video":"","vorDoi":"10.1186/s40337-025-01359-y","vorDoiUrl":"https://doi.org/10.1186/s40337-025-01359-y","workflowStages":[]},"version":"v1","identity":"rs-4706202","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4706202","identity":"rs-4706202","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}