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

doi:10.21203/rs.3.rs-4706202/v1

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

https://doi.org/10.21203/rs.3.rs-4706202/v1

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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

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.

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.

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.

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	0.37	0.71^a
First test of Sadness	30	2.56	0.19	0.21	0.83^b
Retest of Sadness	30	2.58	0.18	0.21	0.83^b
First Test of Anger	30	2.44	0.17	0.41	0.68^b
Retest of Anger	30	2.48	0.19	0.41	0.68^b
The First Test of Anxiety	30	2.24	1.09	-1.33	0.19^b
Retest of Anxiety	30	2.04	0.91	-1.33	0.19^b
^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 X² 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

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.

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.

SEES: Salzburg Emotional Eating Scale

SEES-TR: Salzburg Emotional Eating Scale-Turkish

KMO: Kaiser‒Meyer‒Olkin

CFA: Confirmatory Factor Analysis

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.

Contributions

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.

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. Anadolu 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).

No competing interests reported.

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

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Background

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Translation

Participants

Data collection

Demographic Questionnaire Form

Salzburg Emotional Eating Scale

Dutch Eating Behavior Questionnaire (DEBQ)

Data Analysis

Results

Validity Analysis Results

Exploratory factor analysis results

Discussion

Conclusion

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