MD Paul Brunault
email: paul.brunault@univ-tours.fr

MD, PhD Nicolas Ballon

MD Philippe Gaillard

PhD Christian Réveillère

MD, PhD Robert Courtois

Its Factor Structure, Reliability and Construct Validity in a Nonclinical Sample

Keywords: food addiction, addiction, addictive behaviour, Yale Food Addiction Scale, French, psychometrics, factor analysis, binge eating disorder, Bulimic Investigatory Test Edinburgh, Binge Eating Scale BITE Bulimic Investigatory Test, Edinburgh BMIbody mass index DSM

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Drug addictions are chronic relapsing disorders characterized by compulsion to seek and take the drug, a loss of control over drug-seeking and drug-taking behaviours, and the addictions typically involve maintaining drug use despite adverse consequences. [START_REF]DSM-IV-TR: Diagnostic and Statistical Manual of Mental Disorders[END_REF] In recent years, interesting clinical and scientific shifts in perspective have occurred, with many believing that addiction should include a person's compulsive engagement in activities, such as gaming, internet use, and shopping, in addition to pharmacologic rewards. [START_REF] Grant | Introduction to behavioral addictions[END_REF] Current debates have even extended the definition of addiction to socalled behavioural addictions (also called nonchemical addictions or nondrug addictions), that include the use of natural rewards, such as behaviours that are intrinsically necessary for our survival and in which we freely engage with pleasure and without social sanction, including sex, gambling, and eating. [START_REF] Davis | The eating disorders as addiction: a psychobiological perspective[END_REF][START_REF] Nestler | Is there a common molecular pathway for addiction?[END_REF] A growing body of evidence suggests that behavioural addictions resemble substance addictions across numerous domains, including natural history, phenomenology, tolerance, comorbidity, overlapping genetic contributions, neurobiological mechanisms, and responses to treatment. [START_REF] Grant | Introduction to behavioral addictions[END_REF] As a part of this growing body of research, the concept of food addiction has recently been proposed by applying the DSM-IV-TR criteria for substance dependence to eating behaviours. Patients who exhibit eating patterns that are similar to behaviours classically seen in patients with drug addiction are described as having a food addiction. [START_REF] Gearhardt | Food addiction: an examination of the diagnostic criteria for dependence[END_REF] This concept has received increasing attention given the role it may play in binge eating, eating disorders, and the recent increase in obesity prevalence. [START_REF] Corsica | Food addiction: true or false?[END_REF] Although the evidence for and against the food addiction or compulsive eating model is debatable, [START_REF] Corsica | Food addiction: true or false?[END_REF][START_REF] Corwin | Symposium overview-food addiction: fact or fiction?[END_REF][START_REF] Davis | Compulsive overeating as an addiction disorder. A review of theory and evidence[END_REF] and it is unclear whether this model explains the increased prevalence in obesity, 9,[START_REF] Ifland | Refined food addiction: a classic substance use disorder[END_REF] the possibility that addiction to food represents a reliable phenotypical description of numerous patients is increasingly supported by research with humans and animals. [START_REF] Gearhardt | Food addiction: an examination of the diagnostic criteria for dependence[END_REF][START_REF] Avena | Food and addiction-sugars, fats and hedonic overeating[END_REF][START_REF] Blumenthal | Neurobiology of food addiction[END_REF] Current literature [START_REF] Gearhardt | Food addiction: an examination of the diagnostic criteria for dependence[END_REF][START_REF] Blumenthal | Neurobiology of food addiction[END_REF] suggests that a wide range of patients exhibit significant distress in their relations to food, lose control over their food consumption, suffer from repeated failed attempts to reduce their intake, and are unable to abstain from specific types of foods or reduce their consumption despite negative consequences.

Specifically, a growing body of research [START_REF] Ifland | Refined food addiction: a classic substance use disorder[END_REF][START_REF] Avena | Evidence for sugar addiction: behavioral and neurochemical effects of intermittent, excessive sugar intake[END_REF] supports the hypothesis that specific types of food (for example, refined foods that are high fat and sugar) may have addictive properties similar to those of classic substances, such as alcohol, tobacco, or cocaine. Refined food addiction has been proposed as a classic SUD. [START_REF] Ifland | Refined food addiction: a classic substance use disorder[END_REF] Thus, researchers have been motivated to apply the DSM-IV-TR substance dependence criteria to the field of eating behaviours.Food addiction is diagnosed when at least 3 symptoms (1 of 7) are present during the past 12 months and a clinically significant impairment or level of distress is endorsed.

Therefore, a psychometrically sound tool for assessing food addiction that applies the DSM-IV-TR substance dependence criteria to the field of eating behaviours is needed. Gearhardt et al [START_REF] Gearhardt | Preliminary validation of the Yale Food Addiction Scale[END_REF] developed the YFAS to identify people who are exhibiting signs of addiction regarding specific types of food (for example, high fat and sugar) by extrapolating the 7 DSM-IV-TR criteria for substance dependence to the field of eating behaviours. This self-administered scale has demonstrated adequate reliability and validity and has been used with clinical and nonclinical samples, and is considered the gold standard for assessing food addiction. Studies using this scale have shown that food addiction is highly prevalent in a subpopulation of obese patients and in patients with binge eating disorders. [START_REF] Davis | Evidence that ‗food addiction' is a valid phenotype of obesity[END_REF][START_REF] Gearhardt | An examination of food addiction in a racially diverse sample of obese patients with binge eating disorder in primary care settings[END_REF] In an examination of obese patients with binge eating disorders, the criteria for food addiction was met by 57% of the sample, and food addiction scores were significant predictors of binge eating frequencies, even when controlling for other factors, such as eating disorder psychopathology and negative affect. [START_REF] Gearhardt | An examination of the food addiction construct in obese patients with binge eating disorder[END_REF] Moreover, scores on the YFAS correlated with neural activation patterns in a manner consistent with findings regarding substance dependence (for example, elevated activation in reward circuitry in response to food cues and reduced activation in inhibitory regions). [START_REF] Gearhardt | Neural correlates of food addiction[END_REF] These findings support the appropriateness of this scale for assessing food addiction.

To our knowledge, there is not currently a French version of the YFAS, and only a limited number of studies have assessed food addiction in non-United States and non-European locations. To date, no studies have been conducted in French-speaking countries, and Meule et al [START_REF] Meule | How prevalent is food addiction?[END_REF] highlighted the need for studies that assess the prevalence of food addiction and the factors associated with food addiction. Our study aimed to measure the psychometric properties of a French version of the YFAS with a nonclinical sample by establishing its factor structure, internal consistency, and construct convergent validity with measures of binge eating behaviours.

Methods

Participants and Procedures

A total of 553 participants participated in our study. Participants completed a web-based questionnaire, which was created using Sphinx software (Sphinx Plus 2 version 5.1.0.4). [START_REF] Sphinx | Mise en place d'une enquête avec Sphinx, support d'utilisation, Service formations[END_REF] The questionnaire included items regarding sociodemographic characteristics (for example, age, sex, and current BMI) and the following 3 self-administered scales: the YFAS, the BITE, and the BES.

We obtained permission from Ashley Gearhardt for the translation and validation of a French version of the YFAS. The YFAS translation procedure used in our study was consistent with existing guidelines for scale validation. [START_REF] Guillemin | Cross-cultural adaptation of health-related quality of life measures: literature review and proposed guidelines[END_REF] First, the YFAS was translated from English to French by 3 translators who were qualified specialists in addiction, psychology, and psychiatry and who were native French speakers. This step ensured the production of a translation that achieved consensus from all of the translators. Second, a translator whose native language was English performed a blindbackward translation of the initially translated version of the YFAS. Finally, a committee of 3 expert psychiatrists from the fields of addictive behaviours and eating disorders compared the backtranslated scale with the initially translated version of the YFAS to produce a final French version of the YFAS. The committee's aims were to verify the cross-cultural equivalence of the source and final versions, ensure that the translation was fully comprehensible, and modify the items, instructions, or format if necessary. Finally, a pilot version of the scale was tested with a small sample of French participants to evaluate the scale's instructions, response format, and items for clarity. The Appendix presents the final French version of the YFAS.

Measures

The Yale Food Addiction Scale

The YFAS is a 25-item self-report scale designed by Gearhardt et al [START_REF] Gearhardt | Preliminary validation of the Yale Food Addiction Scale[END_REF] to measure the symptoms of food addiction that have occurred over the past 12 months. The authors developed this scale to identify people exhibiting signs of addiction regarding specific types of foods (for example, high fat and sugar) by extrapolating the DSM-IV-TR criteria for substance dependence to the field of eating behaviours. [START_REF] Gearhardt | Food addiction: an examination of the diagnostic criteria for dependence[END_REF] This scale includes mixed response categories (that is, items that are presented in either a dichotomous or Likert-type format). In accordance with the diagnostic criteria for substance dependence, as stated by the DSM-IV-TR, 2 this scale assesses the following 7 food addiction criteria [START_REF] Gearhardt | Preliminary validation of the Yale Food Addiction Scale[END_REF] :A) tolerance (items 20 and 21); B) withdrawal (items 12, 13, and 14); C) the substance is often taken in larger amounts or over a longer period than was intended (items 1, 2, and 3); D) a persistent desire or unsuccessful effort to cut down or control substance use (items 4, 22, 24, and 25); E) spending a great deal of time in activities necessary to obtain the substance, use the substance, or recover from its effects (items 5, 6, and 7); F) giving up social, occupational, or recreational activities because of substance use (items 8, 9, 10, and 11); and G) continuing substance use with the knowledge that it is causing or exacerbating a persistent or recurrent physical or psychological problem (item 19). The YFAS has 2 additional items that assess peoples' clinically significant impairment or distress caused by eating (items 15 and 16). Items 17, 18, and 23 are primers for other questions and are not scored.

Gearhardt et al [START_REF] Gearhardt | Preliminary validation of the Yale Food Addiction Scale[END_REF] defined specific cut-offs such that each of the 7 diagnostic criteria was satisfied when 1 or more item representing that criterion was endorsed. The YFAS provides 2 scoring options, which are a symptom count version and a diagnostic version. The symptom count version reflects the number of dependence symptoms experienced in the past 12 months (that is, YFAS symptom count scores range from 0 to 7). In the diagnostic version, food addiction is diagnosed when 3 or more symptoms were present during the past 12 months and clinically significant impairment or distress was endorsed.

This scale has been validated in English, has exhibited adequate internal consistency (Cronbach's alpha= 0.86), and has shown good construct convergent validity with measures of similar constructs and good discriminant validity relative to with measures of related but dissimilar constructs. [START_REF] Gearhardt | Preliminary validation of the Yale Food Addiction Scale[END_REF] Additionally, this scale has been validated in German with clinical [START_REF] Meule | Factor structure and item analysis of the Yale Food Addiction Scale in obese candidates for bariatric surgery[END_REF] and nonclinical samples [START_REF] Meule | German translation and validation of the Yale Food Addiction Scale[END_REF] with similar psychometric properties.

The Binge Eating Scale

The BES is a 16-item scale designed to assess peoples' severity of binge eating using behavioural, affective, and cognitive symptoms. [START_REF] Gormally | The assessment of binge eating severity among obese persons[END_REF] The BES is a widely used scale to assess binge eating disorder [START_REF] Wilfley | The clinical significance of binge eating disorder[END_REF] and provides an overall score by summing each of the items (each ranging from 0 to 3), with a higher score reflecting more severe binge eating problems. Internal consistency in our sample for this measure was excellent (Cronbach'sα= 0.92).

The Bulimic Investigatory Test, Edinburgh

The BITE is a 33-item self-report measure developed by Henderson and Freeman to assess the severity and frequency of binge eating symptoms. [START_REF] Henderson | A self-rating scale for bulimia. The ‗BITE[END_REF] The severity of peoples' binge eating behaviour is assessed according to the symptom score from this scale, which ranges from 0 to 30. According to Henderson and Freeman, [START_REF] Henderson | A self-rating scale for bulimia. The ‗BITE[END_REF] this scale has satisfactory reliability and validity when used with binge eating patients. Internal consistency in our sample for this measure was excellent (KR-20 internal reliability coefficient was 0.96).

Statistical Analyses and Ethical Considerations

Analyses were conducted using the R statistical package version 2.15.2 [START_REF]R: a language and environment for statistical computing[END_REF] with the psych package. [START_REF] Revelle | Psych: procedures for personality and psychological research[END_REF] Statistical analyses included descriptive statistics and tests examining the psychometric properties of the scale, including its factor structure, the item statistics, internal consistency, and construct convergent validity.

To test the scale's factor structure, we used the procedure used in Gearhardt's original publication. [START_REF] Gearhardt | Preliminary validation of the Yale Food Addiction Scale[END_REF] Therefore, we conducted a factor analysis for dichotomous data based on polychoric correlation coefficients [START_REF] Kubinger | On artificial results due to using factor analysis for dichotomous variables[END_REF] to explore the number of underlying factors. The initial factor analysis for the original 22 dichotomous items revealed that 1 item (item 24) did not strongly correlate with the remaining items of the scale, as it had a low factor loading of -0.03. In accordance with Gearhardt et al's previous research, we excluded this item from the analysis and performed new statistical analyses. We determined the number of factors to extract by examining the scree plot (eigenvalues and by examining Cattell's scree test [START_REF] Cattell | The scree test for the number of factors[END_REF][START_REF] Jolliffe | Principal component analysis[END_REF] ), and by conducting Horn's parallel analysis test. [START_REF] Horn | A rationale and test for the number of factors in factor analysis[END_REF] Final factor analysis was thus based on the original 21 items that were included in the YFAS (excluding the significance questions), and was conducted using a varimax rotation. We also tested the factor structure of the YFAS in its diagnosis version, by conducting a factor analysis using a varimax rotation for the 8 dichotomous diagnostic criteria (7 diagnostic DSM criteria in addition to significance questions).

We tested the internal consistency of the scale, as in the extent to which the items in a dimension were correlated with each other, using the KR-20 coefficient, given that the items were all dichotomous. [START_REF] Kuder | The theory of the estimation of test reliability[END_REF] Construct convergent validity was assessed by examining the associations between the YFAS scores and the measures of binge eating behaviours. First, we described the construct convergent validity of the YFAS symptom count, and then we described that of the diagnosis version. We examined the associations between the YFAS symptom count score and both the BES total score and the BITE symptom score (Spearman rho correlation coefficients). We used nonparametric tests for these analyses; given that we rejected the normality hypothesis for the YFAS symptom scores (a Shapiro-Wilk test was significant). Next, we tested construct convergent validity for the diagnosis version. We used Mann-WhitneyU tests to assess the associations between the diagnosis of food addiction and binge eating, as assessed by the BES and BITE. All analyses were 2-tailed, with Pvalues of less than 0.05 considered statistically significant. There were no missing data, as all of the questions required responses to proceed to the next page of the survey. Our study did not require institutional review board approval because it was not considered biomedical research under French law; however, it followed the tenets of the Declaration of Helsinki.

Results

Sample Characteristics

Participants had a mean age of 28.9 years (SD 12.0; 95%CI 27.9 to 29.9), a mean current BMI of 22.5 kg/m2 (SD 4.5; 95%CI 22.2 to 22.9). Food addiction was diagnosed in 8.7% of our sample. The median YFAS symptom count (the number of criteria satisfied for food dependence) was 1, and the mean YFAS symptom count score was 1.9 (SD 1.4; 95%CI 1.8 to 2.0). The mean BES total score was 8.2 (SD 8.9; 95%CI 7.4 to 8.9), and the mean BITE symptom score was 7.7 (SD 6.4; 95%CI 7.1 to 8.2).

Item Statistics, Factor Structure, and Reliability

Table 1 summarizes the item statistics, including the mean, standard deviation, and itemtotal correlation for each item.

By examining the scree plot, the factor analysis based on the original 21 items identified 2 factors based on their eigenvalues (factor 1: 10.96 and factor 2: 1.48), suggesting a 1-or a 2-factor structure. An examination of Cattell's scree and a parallel analysis suggested the extraction of 1 factor (Figure 1). Following Cattell's advice, [START_REF] Gorsuch | Factor analysis[END_REF] we extracted an extra factor and studied the 1-and 2-factors solutions.

A 1-factor structure explained 54.1% of the variance. For this 1-factor structure, all of the factor loadings were greater than 0.57 except for item 6, which had a factor loading of 0.46, and the KR-20 internal reliability coefficient was good (KR-20 = 0.84) for these items (Table 2). An alternative 2-factor structure explained an additional 9.5% of the variance (factor 1 explained 34.3% of variance and factor 2 explained 29.4% of variance). For the 2-factor structure, all of the factor loadings were greater than 0.43 (Table 3), and the KR-20 internal reliability coefficient was good for the first factor (KR-20 = 0.81) and adequate for the second factor (KR-20 = 0.67). In this 2-factor solution, the first factor consisted of items belonging primarily to DSM criteria A, criteria B, criteria C, criteria E, criteria F, and criteria G (Table 2). The second factor consisted of items belonging primarily to DSM criteria D (persistent desire or unsuccessful efforts to limit or control substance use), criteria F (giving up social, occupational, or recreational activities because of substance use), and significant distress (Table 2). Thus, our results mainly support a 1-factor structure, which explained 54.1% of the variance.

As for the factor structure of the YFAS in its diagnosis version, a parallel factor analysis based on the 8 dichotomous diagnostic criteria (7 diagnostic DSM criteria in addition to significance questions) identified a single-factor structure. In this single-factor structure, all of the criteria had factor loadings for the single factor of 0.61 or greater. The KR-20 internal reliability coefficient was 0.76 when taking into account all of the diagnostic criteria.

Construct Validation Convergent Validity

First, we assessed construct convergent validity by examining the correlations between the YFAS symptom count scores and the measures of binge eating behaviours (that is, the BES total and BITE symptom scores). The YFAS symptom score was significantly correlated with the BITE symptom score (Spearman ρ= 0.59; P< 0.001) and the BES total score (Spearman ρ= 0.58; P< 0.001). Second, we evaluated the associations between the diagnosis of a food addiction and binge eating scores. The diagnosis of a food addiction was associated with higher binge eating scores, as assessed by the BITE symptom score (20.5 [SD 5.1], compared with 6.5 [SD 5.0]; P<0.001) and the BES total score (26.0 [SD 10.2], compared with 6.5 [SD 6.6]; P<0.001).

Discussion

Our study aimed to measure the psychometric properties of a French version of the YFAS and to establish its reliability and construct validity in a nonclinical sample. We demonstrated that this scale had a 1-factorial structure, good internal consistency, and high construct convergent validity with 1 measure of binge eating, both in its diagnosis and symptom count versions. We found that the previously proposed 1-factor structure for this scale was the best factorial structure and explained a high proportion of the variance for the French version of this scale, which is consistent with Gearhardt et al's original results. [START_REF] Gearhardt | Preliminary validation of the Yale Food Addiction Scale[END_REF] This 1-factor structure was obtained after excluding item 24, which assessed the existence of failed attempts to limit the consumption of high fat and sugar foods. This item is categorized within the fourth DSM-IV-TR addiction criterion, known as -persistent desire or repeated unsuccessful attempts to quit‖ (items 4, 22, 24, and 25). The low factor loadings and high standard deviations for items 22 and 24 have been discussed by Meule et al, [START_REF] Meule | Factor structure and item analysis of the Yale Food Addiction Scale in obese candidates for bariatric surgery[END_REF] suggesting that these items do not sufficiently differentiate between people with and without food addictions. These 2 items (22 and 24) refer to the persistent desire to control food that may be experienced by patients with obesity, who binge eat, who are foodaddicted, or who are suffering from bulimianervosa or anorexia nervosa. Therefore, item 24 could be eliminated from the scale or rephrased given its low psychometric qualities, and replaced by a more specific item for food addiction. Additional items assessing -persistent desire or repeated unsuccessful attempts to control food‖ would be necessary to better differentiate between control owing to food addiction and control owing to fear of weight gain, as this latter dimension is frequently evident in patients with anorexia nervosa and a subtype of bulimia nervosa. We confirmed the adequate reliability of this scale, both in its diagnosis and symptom count versions. The high factor loadings evident in the factor analysis for the dichotomous criteria support the use of the 7 DSM-IV-TR criteria for substance dependence in the fields of eating behaviours and food addiction. Our results support the adequate reliability of the food addiction concept, as assessed by the DSM-IV-TR addiction criteria. In our study, we found a prevalence rate for food addiction (8.7%) that was comparable with the rates reported for the United States (11.4%) and Germany (8.8%). [START_REF] Gearhardt | Preliminary validation of the Yale Food Addiction Scale[END_REF][START_REF] Meule | How prevalent is food addiction?[END_REF] Additionally, the median number of food addiction criteria found in this sample was 1, which was comparable with the United States and German versions. These results suggest that the French version of the YFAS has similar psychometric properties to the previously validated United States and German versions in nonclinical samples. These results support the use of the YFAS as an interesting tool for assessing food addiction in the overall population.

We demonstrated that the French version of the YFAS has highly construct convergent validity with measures of binge eating. This result is consistent with previous research showing a strong association between food addiction and binge eating. [START_REF] Gearhardt | Binge eating disorder and food addiction[END_REF] In addition, our results suggest that a 2-factor structure of the scale slightly improved the explained variance. Interestingly, this 2-factor solution may help differentiate between the following 2 subtypes of patients with foodaddiction: patients with high and low insight regarding addiction symptoms. Factor 1 includes the DSM criteria that assess addiction symptoms independent of the patients' level of insight regarding their addiction (criteria A, B, C, F, and G), whereas factor 2 includes the DSM criteria that assess this level of insight (criteria D: persistent desire or unsuccessful efforts to limit or control substance use; criteria F: giving up social, occupational, or recreational activities because of substance use; and significant distress). The dimension of high or low insight may be important for both clinical practice and research because it implies different therapeutic strategies. Approaches that develop adequate management strategies for patients depending on their level of insight into their addiction may be optimal. Future research should better assess this dimension of insight among patients with foodaddiction. Among the potential limitations of our study, we studied the YFAS only in a nonclinical population. Future studies should assess reliability and construct validity of the YFAS in clinical samples, including patients with binge eating disorder, bulimia nervosa, and anorexia nervosa, as well as the test-retest reliability validity of this scale. Future studies should also assess food addiction using both semi-structured interviews and self-administered scales to establish the sensitivity and specificity of the YFAS. To be consistent with recent DSM-5 criteria for food addiction, the YFAS could be updated in the future by adding items that could assess the 4 additional DSM-5 criteria.

Conclusions

In conclusion, we demonstrated that this French version of the YFAS is a psychometrically sound tool that can be used in future food addiction studies to assess patients who experience addiction-related symptoms in their eating behaviours. One future aim is to use this scale with a clinical sample to better understand the psychopathologic and psychiatric factors associated with food addiction. Another interesting future aim is to study peoples' insights into their addictions in these populations. A deeper understanding of these issues will provide a crucial preliminary step that will aid in the development of effective psychotherapeutic and psychopharmacological strategies for patients with foodaddiction.

TABLES

Figure 2 .

 2 Figure 2. Scree plot and eigenvalues of the French version of the Yale Food AddictionScale

Table 1 . Item statistics for the Yale Food Addiction Scale

 1

	Mean	SD	Item-total correlation

Table 2 . Factor loadings for the one and two-factor structures of the Yale Food Addiction Scale (factor analysis)

 2

	One-factor	Two-factor structure
	structure
	Factor 1	Factor 1	Factor 2
	loading	loading	loading

French version of the Yale Food Addiction Scale DSM-IV-TR Consignes pour remplir l'échelle:Ce questionnaire

  porte sur vos habitudes alimentaires de l'année passée. Les gens ont parfois du mal à maîtriser leur consommation de certains aliments telles que: -Les aliments sucrés comme la crème glacée, le chocolat, les beignets, les paquets de biscuits, les gâteaux et les bonbons.-Les féculents comme le pain blanc, les petits pains, les pâtes et le riz.-Les aliments salés comme les chips, les bretzels et les biscuits.-Les aliments gras comme le steak, le bacon, les hamburgers, les cheeseburgers, les pizzas et les frites.-Les boissons sucrées comme le soda. Pour les questions suivantes qui portent sur « CERTAINS ALIMENTS », pensez à tout aliment équivalent à ceux qui sont énumérés ci-dessus ou d'autres aliments avec lesquels vous avez eu des difficultés au cours de l'année passée.

						Plus de
		Jamais	Une fois par mois	2 à 4 fois par mois	2 à 4 fois par semaine	4 fois par semaine ou tous
						les jours
	13. J'ai consommé certains aliments pour éviter de me sentir anxieux, agité ou de développer d'autres symptômes	❑ 0	❑ 1	❑ 2	❑ 3	❑ 4
	physiques (Merci de ne pas inclure ceux provoqués par
	l'arrêt de boissons contenant de la caféine comme certains
	sodas, le café, le thé, les boissons énergisantes, etc.).
	diminuais la consommation ou lorsque j'arrêtais d'en Au cours des 12 derniers mois : 14. J'ai constaté que j'avais un besoin plus important ou une envie irrésistible de manger certains aliments lorsque j'en	❑ 0	❑ 1	❑ 2	❑ 3	❑ 4
	manger.					Plus de
	15. Mon comportement vis-à-vis la nourriture et de l'alimentation est source d'une souffrance marquée. l'école, les activités sociales, les activités familiales, 16. Je rencontre des difficultés importantes pour mener à bien mes activités (pour les tâches quotidiennes, le travail /	Jamais ❑ 0 ❑ 0	Une fois par mois ❑ 1 ❑ 1	2 à 4 fois par mois ❑ 2 ❑ 2	2 à 4 ❑ 3 fois par semaine ❑ 3	4 fois par ❑ 4 semaine ou tous les jours ❑ 4
	1. Je pense que lorsque je commence à manger certains aliments, je finis par manger beaucoup plus que prévu. problèmes de santé) à cause de la nourriture et de l'alimentation.	❑ 0	❑ 1	❑ 2	❑ 3	❑ 4
	2. Je constate que je continue à manger certains aliments même lorsque je n'ai plus faim. Au	❑ 0	❑ 1	❑ 2	❑ 3	❑ 4
	3. Je mange jusqu'à me sentir « mal » physiquement.	❑ 0	❑ 1	❑ 2	❑ 3	❑ 4
	4. Le fait d'arrêter de manger certains types d'aliments ou de les réduire, est quelque chose qui me préoccupe.	❑ 0	❑ 1	❑ 2	❑ 3	❑ 4
	5. Je passe beaucoup de temps à me sentir endormi(e) ou fatigué(e) après avoir trop mangé.	❑ 0	❑ 1	❑ 2	❑ 3	❑ 4
	6. Je me retrouve fréquemment en train de manger certains aliments tout au long de la journée.	❑ 0	❑ 1	❑ 2	❑ 3	❑ 4
	7. Lorsque certains aliments ne sont pas disponibles, je vais aller les acheter. Par exemple, je ne vais pas hésiter à me	❑ 0	❑ 1	❑ 2	❑ 3	❑ 4
	rendre dans un magasin pour en acheter alors que j'ai
	d'autres aliments à la maison.
	8. Il m'est arrivé de consommer certains aliments si souvent ou en si grandes quantités que je mangeais au lieu de	❑ 0	❑ 1	❑ 2	❑ 3	❑ 4
	travailler, au lieu de passer du temps avec ma famille ou
	mes amis, ou de réaliser des activités importantes ou des
	activités de loisirs que j'apprécie habituellement.
	9. Il m'est arrivé de consommer certains aliments si souvent ou en si grandes quantités que je passais mon temps à avoir	❑ 0	❑ 1	❑ 2	❑ 3	❑ 4
	des pensées négatives sur ma consommation excessive, au
	lieu de passer du temps avec ma famille ou mes amis, ou
	de réaliser des activités importantes ou des activités de
	loisir que j'apprécie habituellement.
	10. Il m'est arrivé d'éviter certaines situations professionnelles ou relationnelles au cours desquelles certains aliments	❑ 0	❑ 1	❑ 2	❑ 3	❑ 4
	étaient disponibles car j'avais peur d'en manger en excès.
	11. Il m'est arrivé d'éviter certaines situations professionnelles ou relationnelles, car je ne me sentais pas capable d'y	❑ 0	❑ 1	❑ 2	❑ 3	❑ 4
	consommer certains aliments.
	12. J'ai eu des symptômes de sevrage (agitation, anxiété ou autres symptômes physiques) quand j'ai diminué ou arrêté	❑ 0	❑ 1	❑ 2	❑ 3	❑ 4
	de consommer certains aliments (Merci de ne pas inclure
	ceux provoqués par l'arrêt de boissons contenant de la
	caféine comme certains sodas, le café, le thé, les boissons
	énergisantes, etc…).

cours de ces 12 derniers mois : Non Oui

		❑ 0	❑ 1
	18. Ma consommation de nourriture a provoqué ou aggravé d'importants problèmes physiques.	❑ 0 ❑ ❑ 0 ❑ 1
	20. Au fil du temps, j'ai constaté que j'avais besoin de manger de plus en plus pour obtenir le même effet, qu'il s'agisse de la diminution d'émotions négatives ou d'un plus grand	❑ 0	❑ 1
	plaisir.
	21. J'ai l'impression que le fait de manger la même quantité de nourriture ne diminue pas mes émotions négatives ou n'augmente pas le plaisir que je peux ressentir comme par le	❑ 0	❑ 1
	passé.
	22. Je veux réduire ou arrêter de manger certains types d'aliments.	❑ 0	❑ 1
	23. J'ai essayé de réduire ou d'arrêter de manger certains types d'aliments.	❑ 0	❑ 1
	24. J'ai réussi à arrêter ou à ne pas manger ce genre d'aliments.	❑ 0	❑ 1

17. Ma consommation de nourriture a provoqué d'importants problèmes psychologiques comme de la dépression, de l'anxiété, un dégoût de moi-même ou de la culpabilité. 1

19

. J'ai continué à consommer les mêmes types d'aliments ou la même quantité de nourriture malgré l'existence de problèmes physiques et/ou psychologiques.

Au cours de ces 12 derniers mois : 25

  . Au cours de la dernière année, combien de fois en tout avez-vous essayé de réduire ou d'arrêter de manger certains aliments ? Merci de lister ici quels sont les autres aliments avec lesquels vous avez des difficultés (merci de ne mentionner que les aliments n'étant pas déjà dans la liste ci-dessus) ……………………………..….. Pour obtenir le fichier permettant de calculer automatiquement les scores en fonction des réponses obtenues, vous pouvez envoyer un mail à : paul.brunault@univ-tours.fr) Les items de l'échelle permettent d'évaluer chacun des 7 critères de dépendance et l'existence d'une souffrance significative selon les critères DSM-IV-TR : 1) Tolérance (items 20 et 21) 2) Sevrage (items 12, 13 et 14) 3) Substance prise en quantité plus importante ou pendant une durée plus importante que prévue (items 1, 2 et 3). 4) Désir persistant ou efforts infructueux pour limiter ou arrêter la consummation de la substance (items 4, 22, 24, 25). 5) Beaucoup de temps passé pour consommer la substance ou pour se remettre de ses effets (items 5, 6 et 7). 6) Abandon d'activités sociales, professionnelles ou de loisirs (items 8, 9, 10 et 11). 7) Poursuite de la consommation malgré l'existence de conséquences physiques et/ou psychologiques (item 19). Souffrance marquée : items 15 et 16. Pour parler d'addiction à l'alimentation, il faut que la personne ait au moins 3 critères sur 7 positifs ET qu'elle remplisse également le critère "souffrance marquée". Pour qu'un critère soit considéré comme "positif", il faut qu'au moins un des items du critère ait un score significatif. Les cut-offs de significativité sont les suivants : -Items 25 : score significatif si réponse ≥ 4. -Items 1, 2, 4 et 6 : score significatif si réponse ≥ 4. -Items 3, 5, 7, 9, 12, 13, 14, 15 et 16 : score significatif si réponse ≥ 3. -Items 8, 10, 11 : score significatif si réponse ≥ 2. -Item 24 : score significatif si réponse est "non". -Items 19, 20, 21, 22 : score significatif si réponse est "oui". Les items 17, 18 et 23 ne font pas l'objet de cotation (il s'agit de questions servant d'amorces pour les questions suivantes).

		Une fois	2 fois	3 fois	4 fois	5 fois ou
						plus
		❑ 0		❑ 1	❑ 2	❑ 3	❑ 4
	26. Merci d'encercler TOUS les aliments avec lesquels vous avez actuellement des difficultés.
	Crème glacée	Chocolat	Pommes	Beignets
	Brocoli	Paquets de biscuits	Gâteaux	Pain	blanc
	Les petits pains	Laitue	Pâtes		Fraises
	Riz	Crackers	Bretzels	Frites
	Carottes	Steak	Bananes	Bacon
	Hamburgers	Pizzas	Soda		Esquimau
	Bonbons	Chips	Cheeseburgers	Aucun de ces aliments
	27. Modalités de cotation :

(

indicates items associated with the first factor of the two-factor structure.

indicates items associated with the second factor of the two-factor structure.

Item 24 was not included in the analysis because of its low factor loading.

Acknowledgments

We thank Yacine Raouf Dendane for assistance with data collection. We thank Ashley Gearhardt for the kind permission to translate and use the YFAS and for providing us references that helped us in the validation of this French version. We thank William Revelle for helping us in using the psych statistical package. We thank AJE for editing our manuscript. The authors declare that they have no potential or perceived conflicts of interest. The authors received no funding for this study.


Michael Beisswenger
email: michael.beisswenger@uni-due.de

Thierry Chanier
email: thierry.chanier@univ-bpclermont.fr

Isabella Chiari
email: isabella.chiari@uniroma1.it

Tomaž Erjavec
email: tomaz.erjavec@ijs.si

Darja Fišer
email: darja.fiser@ff.uni-lj.si

Axel Herold
email: herold@bbaw.de

Nikola Ljubešić
email: nikola.ljubesic@ffzg.hr

Harald Lüngen
email: luengen@ids-mannheim.de

Egon Céline Poudat
email: poudat@unice.fr

Michael Beißwenger

Egon Stemle
email: egon.stemle@eurac.edu

Angelika Storrer
email: astorrer@mail.uni-mannheim.de

Ciara Wigham
email: ciara.wigham@univ-bpclermont.fr

Closing a gap in the language resources landscape : Groundwork and best practices from projects on computer-mediated communication in four European countries

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

The paper presents best practices and results from projects in four countries dedicated to the creation of corpora of computer-mediated communication and social media interactions (henceforth referred to as CMC). The projects relate to each other via a bottom-up network of researchers interested in fostering the transfer of expertise and solutions for handling this relatively new type of language resources and for modeling the structural and linguistic peculiarities of (written and multimodal) discourse that is found in chat, forum, sms and whatsapp interactions, in weblogs and wikis, on social network sites or in multimodal CMC environments. This new type of discourse exhibits features that cannot be adequately handled through the application of schemas, categories and tools which have been developed for the representation, annotation and processing of discourse which conforms to the written standard and the structural conventions of established text types (e.g., newspaper articles, prose, scientific articles). In addition, the collection and redistribution of CMC data in linguistic corpora faces corpus creators with legal and ethical issues which are not yet completely covered by existing laws and ethical standards. Last but not least there are no established standards for metadata and for the documentation of the (technological, hypermedial and social) context in which CMC data are typically embedded, produced and used.

Corpus-linguistic approaches to CMC have so far not found answers to all of these challenges. Nevertheless, existing projects in the field have created an encouraging range of results and best practices which have been tested with existing corpora and which are worth further discussions. The joint goal of the projects described in this paper is to pave the ground for future standards which will allow CMC corpora to be interoperable (a) with each other and (b) with language resources for other types of discourse (text and speech corpora).

In the following sections we describe existing initiatives for the development of standards and for the exchange of knowledge related to the collection and representation of CMC corpora (Sect. 2) and give an overview of results and best practices from CMC corpus projects in four countries which may be useful for other projects in the field and which may serve as a starting point for a more precise discussion of how future standards for CMC corpora may (and should) be shaped like (Sect. 3).

Initiatives and previous cooperation in the field

Since 2013 a loose network of projects with a joint interest in building and annotating CMC corpora has set up two initiatives in order to (1) strengthen the exchange of expertise and best practices between projects and (2) lead the discussion of a representation standard for CMC genres in the context of a well-acknowledged standardization initiative in the Digital Humanities:

 The network has established a series of international workshops and conferences dedicated to the creation of CMC corpora with previous events held in Dortmund/DE (2013, 2014), Rennes/F (2015) and Ljubljana/SI (2016). Since 2015 these conferences are defined as peerreviewed international events with a coordinating and a scientific committee (Conference on CMC and Social Media Corpora for the Humanities, http://www.cmc-corpora.org).

 The network succeeded with a proposal for the creation of a new special interest group (SIG) on Computer-Mediated Communication in the Text Encoding Initiative (TEI, http:///tei-c.org) in 2013. The goal of this SIG is to extend the TEI framework with additions dedicated to the representation of the structural and linguistic peculiarities of CMC genres. Starting from a discussion of a first schema draft defined by Beißwenger et al. (2012) the SIG created two advanced schema drafts ('CoMeRe schema ', 2014', , 'CLARIN-D schema', 2015) ) which have been tested with French and German corpora and which are currently being adopted by further projects.

Overview of projects and best practices from the cmc-corpora network

France

The CoMeRe project ('Communication Médiée par les Réseaux', 2013-2015, National Consortium on Written Corpora, TGIR Huma-Num) brought together researchers who had previously collected different types of CMC corpora in their local research teams or in previous research projects, and had structured these in a variety of formats (different XML schemas for text chat corpora, SMS corpora, for LEarning and TEaching Corpora). The primary aim of the project was to design a common model for CMC discourse that would fit the pre-existing CMC corpora, as well as new corpora collected both during the project or post-project. The secondary aim was to release these corpora in a common repository as open data, in order to provide access to a dataset with significant coverage to colleagues working within the field of discourse analysis and who are interested in the linguistic study of CMC genres. To address the project's primary goal, it was first necessary to settle on a common document model that would fit different types of multimodal CMC data. Rather than working genre by genre, the project members initially worked within the abstract concept of the 'Interaction Space'. This concept is detailed in [START_REF] Chanier | [END_REF]. Briefly, an Interaction Space is located within a timeframe, during which interactions occur between a set of participants within an online location. This location is defined by the properties of the set of environments used by the participants who may be either individual members or groups. The environments may be synchronous or asynchronous, mono-or multimodal, simple or complex. The traces of actions within an environment and one particular modality are termed an 'act'. Working from this concept, a TEI schema was proposed ('CoMeRe schema ', 2014). Relationships between the Interaction Space definitions of the environment, found in the <teiHeader>, and its actual use by participants in interactions, described in the <body> part of the TEI file, appear through the attribute @type of the <post> element. All 14 corpora in the CoMeRe repository ( 2016) have been structured in this manner.

Germany

First ideas towards an annotation schema for CMC in Germany have been discussed in the context of the DFG scientific network Empirikom (http://www.empirikom.net) and together with the concept for a reference corpus of German CMC (DeRiK, Beißwenger et al., 2013). More recently, the idea to create one large reference corpus comprising several CMC genres developed into the concept of a collection of corpora which are annotated on the basis of the same schema. First corpora of that type are the "CLARINified" version of the Dortmund Chat Corpus [START_REF] Lüngen | [END_REF], the Wikipedia Corpus [START_REF][END_REF] and the Usenet Corpus in DEREKO (Schröck and Lüngen, 2015). Further resources are in preparation. In the context of the CLARIN-D curation project ChatCorpus2CLARIN schema drafts from the TEI CMC-SIG (cf. Sect. 2) have been further developed ('CLARIN-D schema', 2015) and used for the representation of a 1 million token chat corpus with part-of-speech annotations. In addition, the project initiated writing of a legal opinion on republishing CMC data as part of the CLARIN corpus infrastructure (iRights, 2016). Linguistic annotation was done partially automatically on the basis of an extended version of the STTS tag set which is a de-facto standard for German text corpora. The extensions to this tag set include tags for typical phenomena of CMC discourse; the tag set as a whole ('STTS 2.0', Beißwenger et al., 2015) is downwardly compatible with the "standard" STTS and with the STTS version used for PoS tagging the FOLK corpus of spoken language at IDS Mannheim [START_REF] Westpfahl | [END_REF]. STTS 2.0 was originally developed as a resource for the community shared task EmpiriST2015 which was designed to foster the adaptation of NLP tools to the linguistic peculiarities of German CMC [START_REF] Beißwenger | [END_REF]. All resources from EmpiriST2015 are available on the web (http://sites.google.com/site/empirist2015/). The TEI version of the PoS-annotated chat corpus will be integrated into the CLARIN-D corpus infrastructures.

Italy

In the DiDi project at the EURAC, Bozen, [START_REF] Frey | [END_REF] created a CMC corpus of South Tyrolean German from Facebook (FB) users' wall posts, comments on wall posts and private messages, supplemented with user-provided socio-demographic data. All FB data was automatically annotated with language codes, and manually normalized and anonymized. Semi-automatic token level annotations include part-of-speech tags and CMC phenomena (e.g. emoticons, emojis, and iteration of graphemes and punctuation). The corpus was collected with an integrated web strategy for mixed sociolinguistic research methodologies in the context of social media corpora, and also resulted in recommendations for collecting private, non-public CMC data. With a meticulously crafted procedure where users had to explicitly agree with the distribution of their data and were also able to restrict the collection of data to the publicly available part, the anonymized corpus without the private messages is now freely available for researchers, and the complete anonymized corpus is available after signing an agreement.

Web2Corpus ("Corpus italiano di comunicazione mediata dal computer") is a project funded by Sapienza University of Rome in 2011 aimed at investigating meaning negotiation strategies in CMC (http://www.glottoweb.org/web2corpus/). It focuses on conversational, interactive, public, written communication in order to build a genre-balanced CMC corpus of the Italian language. The genres included are forums, blogs, newsgroups, social networks and chats [START_REF] Chiari | [END_REF]. The corpus has been fully anonymized (by masking) and XML-annotated both for macro-structural properties (thread, post, sender details, subject, date, time, links and embedded media, web action elements and CMC-specific emoticons and tags and addressing terms, etc.). The anonymization guidelines will soon be released in the form of best practices taking into account current legislation and technical solutions. At present the corpus is being processed linguistically with a statistical PoS tagger and lemmatizer, including a reference machine dictionary (Common Lexicon of Italian) developed in order to include CMC-specific lexical items, and will be subsequently manually checked. A first qualitative and quantitative analysis is presented in Chiari (ed., 2016 in press).

Slovenia

The Janes project (http://nl.ijs.si/janes/) is compiling a corpus of Slovene (Erjavec et al., 2015a) that contains tweets, forum posts, news comments, blogs and blog comments, and user and talk pages from Wikipedia. The current version v0.4 contains around 9 million posts comprising 200 million tokens. In addition to the metadata obtained during crawling or from the text, such as date and time of posting, username, post URL, discussion thread, and the number of likes and retweets, the corpus is also annotated with metadata that were added manually, such as user type and gender, or automatically, such as user's region, text sentiment and standardness level. The standard linguistic annotation workflow has been adapted to better tackle CMC-specific features and comprises tokenization, sentence segmentation, rediacritisation, normalization, morphosyntactic tagging and lemmatization [START_REF] Ljubešić | [END_REF]. The corpus is encoded in bespoke XML that closely reflects the structure of the corpus and all its metadata. Version 1 will be encoded in a CMC-aware TEI proposed by Beißwenger et al. (2012). Apart from the XML source files, the corpus is also made available to linguists on the local installation of the noSketchEngine and SketchEngine concordancers (Rychlý, 2007), both as the entire Janes v0.4 corpus with the metadata that all the subcorpora have in common and as separate subcorpora with all the metadata available for the given subcorpus. Access to the corpus is currently restricted to project members but steps are being taken to comply with the copyright, terms of use and privacy issues in order to make an annonymised, sampled and shuffled corpus available to other researchers as well by the end of the project (Erjavec et al., 2015b).

Outlook

In this paper we gave an overview of first results and best practices from projects in four countries dedicated to the creation of corpora of computer-mediated communication and social media interactions (CMC). The joint goal of the projects is to establish standards for the collection and representation of CMC corpora and for their integration into common resources infrastructures.

Up to now the network has brought forward two main initiatives: a conference series dedicated to all issues related to building and annotating CMC corpora and a TEI-SIG focused on the integration of standards for CMC resources into the TEI framework. Both initiatives are "bottom up" approaches with the goal to connect researchers all over Europe and to work on solutions driven by practices that have proven useful in ongoing projects. The latest edition of the conference included 22 contributions by 40 authors from 24 research institutions in 11 countries (Fišer and Beißwenger, 2016).

Nevertheless, there's still a lot of open, non-trivial issues in the field. One example is the lack of legal standards for collecting and republishing CMC data as part of language resources. Corpus builders are typically laymen when it comes to legal issues. A general legal opinion on these issues commissioned and disseminated by and via an acknowledged language resources initiative would therefore be an important prerequisite for the further development of the CMC corpora landscape and community.

In view of the importance of CMC in everyday communication, in business, public administration, science and education, efforts in the field of establishing state-of-the-art research resources infrastructures for the analysis of CMC phenomena are an investment in our future knowledge about how the adoption of CMC technologies affects society and how communicative practices reflect the presence of CMC as an innovative means for the organization of social interaction.