It is important to cultivate this preliminary practice in the translation process especially among graduate students. Pilot study should be done after vigorous translation and cultural adaptation process for assessing suitability of the Three-FactorEatingQuestionnaire R21 (TFEQ-R21) to the target population. It is a small scale study to test the feasibility of methods, procedures and instruments for later use on a larger scale study to avoid potentially unwanted disastrous consequences 17 . Poor item writing following
Kavazidou E, Proios M, Liolios I, Doganis G, Petrou K, Tsatsoulis A, Tsiligiroglou-Fachantidou A. Structure validity of the Three-FactorEatingQuestionnaire-R18 in Greek population. J. Hum. Sport Exerc. Vol. 7, No. 1, pp. 218-226, 2012. The aim of the present study was to examine the factor structure of the TFEQ-R18. The project was conducted in Greek population; thus, the questionnaire was translated in Greek language. 495 males and females aged between 12-45 years old participated in the present study. There were used a series of CFA techniques for structure analysis. Confirmatory and exploratory analyses were conducted. Several criteria were used to test the hypotheses factor structures of the AIMS. The results of CFA’s showed that the R-18 item instrument had adequate psychometric properties for measuring three dimensions of eating behavior of the Greek population However these results \revealed that an R-16 item instrument was better adapted to the Greek population. The present study provided encouraging preliminary evidence supporting selected psychometric properties of the TFEQ-R18. This instrument seems to be a valid measure of the tendencies of cognitive restraint, uncontrolled eating and emotional eating of Greek population. Key words: TFEQ-R18, QUESTIONNAIRE, EATING BEHAVIOR, FACTOR STRUCTURE, GREEK POPULATION.
composition analyzer all in standard situations. We used Omron HBF-500 BIA (Omron Co., Japan) device, which involved 8 electrodes, tetrapolar electrodes in footpads, and another 4 sets of electrodes in the handle. Each participant stood on the metal footpads in bare feet and grasped a pair of electrodes fixed to a handle with arms extended in front of the chest. This instrument assesses total body fat, visceral fat, lean body mass, and basal metabolic rate as well as body weight and BMI. The clinical validity of this instrument in measuring body composition has already been approved in comparison with Dual-Energy X-Ray Absorptiometry and Magnetic Resonance Imaging (MRI) (13). Then, the participants were asked to fill in the Three-FactorEatingQuestionnaire-R18 (TFEQ- R18), Beck Depression Inventory, Spielberger Anxiety Scale, Appetite Visual Analogue Scale, and Compulsive Eating Scale. Furthermore, the participants were asked to fill in a 3-day food record, which was completed at home on 2 nonsequential weekdays, and on 1 day in the weekend, with the days being assigned randomly. The participants were instructed to record everything that they ate or drank including liquids, sweets, and snacks. A guide on portion sizes and scales were also delivered to them. They were required to deliver the 3-day food records 2 weeks later in the second visit. Two weeks later, the tests (TFEQ-R18) were repeated for 126 participants in similar situations. Instruments
Model analysis has been long linked to data analysis in various research fields, construct validation using both approaches has rarely been used by medical researchers. The type of approach selected depends on the norm practice, availability of statistical tools in research facility, analysis justification, and presence of expertise in assisting data analysis and interpretation. The uniqueness of this article is to assess construct validity from two approaches for a set of translated version questionnaire. In a great hope, this dual approach may be able to give comprehensive evidence for determining suitability of the items among Malay population. Each approach have unique features to analyse data suited to the analysis objective but the former displayed lack of ability for Item Response Theory to measure underlying traits, such as attribute, proficiency, ability or skill, which are reflected in the endorsed responses to the study questionnaires. 1 This lacking can be complemented by
We also slightly modified one of the items of the original TFEQ-R18 questionnaire. The question "When I smell a sizzling steak or a juicy piece of meat, I find it very difficult to keep from eating, even if I have just finished a meal." (item 1) was replaced with "When I smell a delicious food, I find it very difficult to keep from eating, even if I have just finished a meal." The item is supposed to measure the tendency to uncontrolled eating in the absence of hunger, when tempted by external stimuli. In the Finnish culture, steaks and meat are not necessarily considered the most desired foods – definitely not among girls and young women. Steaks are thus a poor example of a tempting food in this population, and the original item needed to be changed in order for it to produce valid responses. The data we gathered using the TFEQ-R18 behaved in the analyses in a very similar manner when compared to earlier analyses of TFEQ-R18 data [6,8,18], suggesting that the instrument
Table 3.1 Daily frequency equivalent response conversions 46 Table 3.2 Twenty-nine food groups used in principal component factor analysis 47 Table 3.3 Reference ranges for scoring the Three-factoreatingquestionnaire 49 Table 3.4 Ascending concentrations of oleic acid (OA) used to measure OA taste
The literature on eating behaviour suggested six areas for consideration. (1) Satiety responsiveness : this is usually mea- sured behaviourally by seeing whether food intake is reduced to compensate for a prior snack. (2) Responsiveness to food cues \ external eating : this is assessed behaviourally on the basis of the amount of good-tasting versus less-good-tasting food consumed in standard conditions. Two psychometric instruments include subscales for external eating, the ThreeFactorEatingQuestionnaire (TFEQ ; Stunkard & Messick, 1985) and the Dutch Eating Behaviour Questionnaire (DEBQ ; Van Strien, Frijters, Bergers, & Defares, 1986 ; Wardle, 1987), assessing it with items on self-reported desire for food follow- ing exposure to attractive food cues. (3) Emotional eating : this usually refers to eating more food during negative emotional states, although recent work has begun to dis- tinguish emotional overeating from emotional undereating (Oliver & Wardle, 1999 ; Wardle & Gibson, 2001). Emotional overeating is measured psychometrically in the TFEQ and DEBQ by self-reported increases in appetite in a range of emotional states. (4) General interest in eating : this includes hunger, desire to eat, and enjoyment of food. These concepts are measured psychometrically with self-report questions in the TFEQ hunger scale (e.g., ‘‘ I often feel so hungry, I just have to eat something ’’). The opposite characteristic, lack of interest in food, emerges as a common problem in the literature on children’s eating problems, and the Children’s Eating Behavior Inventory (Archer et al., 1991) includes several items concerned with the child’s (lack of ) enjoyment of food and mealtimes. (5) Speed of eating : this is usually measured be- haviourally, but in the clinical literature is based on parental reports of the child dawdling or taking more than 30 minutes over a meal. (6) Food fussiness : this consists of being highly selective about the range of foods that are accepted. It emerges strongly in the literature on children’s eating problems, and has been assessed using a range of ad hoc measures often based on lists of foods that might be accepted or rejected.
During the last decades, Chile has experienced a nutrition transition, with a rapid decline in undernutrition and an increase in the prevalence of obesity as a consequence of social changes leading to a rise in consumption of high- calorie foods and sedentary habits [1,2]. This transition has occurred at a much faster rate than in other countries . As a consequence, it is conceivable that attitudes and practices of many Chilean mothers on feeding and nutri- tion are somehow still dominated by a sense of protection against childhood undernutrition instead of the preven- tion of obesity. In this context, it is important to note that obesity is currently the most frequent nutritional disease in Chilean children, with a prevalence that has tripled over the past 15 years; it is currently 21% among 6 year- old children [3,4]. Since obesity prevention should start early in life, it is important to determine the factors that influence weight excess and eating behavior in preschool children . It is generally accepted that parents' practices about feeding, especially mother's practices, are impor- tant factors to consider in order to achieve a better nutri- tion during childhood [6-10]. However, it is still difficult to define the best parental strategy in relation to child- hood feeding, especially under the strong social influ- ences that characterize the "obesogenic" environment. Research about the effect of food intake on childhood obesity has traditionally focused on the amount and type of foods usually consumed. However, a better under- standing of the link between eating behavior and mater- nal feeding practices with childhood obesity is also of interest. Computed standardized questionnaires using behavior scores covering different eating dimensions such as the Child Eating Behavior Questionnaire and the Three- factorEatingQuestionnaire can be used for this purpose . The use of psychometric tools to assess how eating practices and attitudes of parents, measured for example through the Child Feeding Questionnaire (CFQ), may influence eating behavior and the nutritional status of children can yield valuable information to better define successful intervention strategies .
Disordered eating and eating disorders are commonly reported in T1D, with a 2–3 fold increase in prevalence of eating disorders compared to individuals without T1D according to meta-analyses [1–3]. Disordered eating, and especially behavior leading to incorrect insulin dos- ing, is a major hindrance to optimal blood glucose con- trol which is necessary to prevent severe late diabetes complications, and increased mortality. Prevalence of disordered eating varies largely across individual studies, most likely due to assessment differences. Specifically, generic eating disorder measures made for the general population, including the Eating Attitudes Test (EAT) , the SCOFF (acronym created from the letters of the items, i.e. do you make yourself Sick because you feel un- comfortably full; do you worry you have lost Control over how much you eat; have you recently lost more than One stone in a 3 month period; do you believe yourself to be Fat when others say you are too thin; and would you say that Food dominates your life) , and the Eating Dis- order Examination – Questionnaire (EDE-Q) , have been reported to yield elevated prevalence estimates among patients with T1D compared to diabetes-specific tools . This may be related to the dietary monitoring naturally occurring as part of standard T1D treatment being scored pathologically, implying a risk of false posi- tives. Additionally, generic assessment tools do not ac- count for intentional insulin under dosing or omission to control weight, a diabetes-specific compensatory be- havior reported in up to 37% of females with T1D [7 – 9] and associated with a three-fold mortality rate . As such, diabetes-specific measures to assess disordered eating are recommended in diabetes populations .
The AEBQ (Hunot et al., 2016) consists of 35 items measured along a 5-point Likert scale (1 = “strongly disagree”; 5 = “strongly agree”), constituting eight subscales, conceptually grouped into Food Approach and Food Avoidance scales, based on them being either positively or negatively related to weight (Wardle et al., 2001; Hunot et al., 2016). Four Food Approach scales are comprised of: Hunger (five items, e.g., “I often feel so hungry that I have to eat something right away”); Food Responsiveness (four items, e.g., “When I see or smell food that I like, it makes me want to eat”); Emotional Over- Eating (five items, e.g., “I eat more when I’m anxious”); and Enjoyment of Food (three items, e.g., “I love food”). Four Food Avoidance scales include: Satiety Responsiveness (four items, e.g., “I often leave food on my plate at the end of a meal”); Emotional Under-Eating (five items, e.g., “I eat less when I’m worried”); Food Fussiness (five items, e.g., “I refuse new foods at first”) and Slowness in Eating (i.e., eating rate, four items, e.g., “I am often last at finishing a meal”). Before the AEBQ was given to the adolescents, Think Aloud interviews
The focus of the current available instruments used to screen eating disorders is on behaviors and diagnostic criteria but some of them such as Eating disorders belief questionnaire (EDBQ) and ThreeFactorEating Ques- tionnaire (TFEQ) are based on the drive from thinness and the fear of fatness . The Eating Disorder Belief Questionnaire (EDBQ) is a relatively brief questionnaire intended for use within the eating disorder population. It is a multi-dimensional and self-report measure with 32 items and four subscales as follows:  negative self-beliefs,  weight and shape as a means to accept- ance by others,  weight and shape as a means to self-acceptance and  control over eating. The negative self-beliefs subscale appears to measure generic beliefs associated with depression. The other three subscales appear to measure beliefs specific to eating disorders . The EDBQ’s ability to distinguish assumptions about weight and shape from assumptions about eat- ing is important, as it has been proposed that the core psychopathology of eating disorders lies in the personal meaning attached to weight and shape . This questionnaire has been validated in the Persian language .
Background: The aims of this study were to evaluate the factor structure of the newly developed Adult Eating Behaviour Questionnaire (AEBQ) (Hunot et al., Appetite 105:356-63, 2016) in an Australian sample, and examine associations between the four food approach and four food avoidance appetitive traits with body mass index (BMI). Methods: Participants ( N = 998) recruited between May and October 2016 via a university research participation scheme and online social network sites completed an online version of the AEBQ and self-reported demographic and anthropometric data. Of the sample, 84.8% were females, 29.6% had completed a university degree and the overall mean age was 24.32 years (SD = 8.32). Confirmatory factor analysis (CFA) was used to test three alternative factor structures (derived from issues raised in the original development study): the original 8 factor model, a 7 factor model with Food Responsiveness and Hunger scales combined, and a 7 factor model with the Hunger scale removed. Results: The CFA revealed that the original 8 factor model was a better fit to the data than the 7 factor model in which Food Responsiveness and Hunger scales were combined. However, while reliability estimates for 7 of the 8 scales were good (Cronbach ’ s α between 0.70-0.86), the reliability of the Hunger scale was modest (0.67) and dropping this factor resulted in a good fitting model. All food avoidance scales (except Food Fussiness) were negatively associated with body mass index (BMI) whereas Emotional Overeating was the only food approach scale positively associated with BMI. Conclusions: The study supports the use of the AEBQ as a reliable and valid measure of food approach and avoidance appetitive traits in adults. Longitudinal studies that examine continuity and stability of appetitive traits across the lifespan will be facilitated by the addition of this measurement tool to the literature.
Results: A confirmatory factor analysis on the original four factor model of the EDE-Q produced an inadmissible model with a poor fit. Exploratory factor analysis using principal axis factoring produced an alternative threefactor model of the EDE-Q among adolescents. The Shape and Weight Concerns, Restriction and Preoccupation and Eating Concern subscales accounted for 65% of the total variance. Subscale and global scores were significantly higher for girls than for boys. A high proportion of both girls (53.6%) and boys (30.5%) reported participating in at least one key eating disordered behaviour during the previous 28 days.
The study included 684 students, most of whom studied medicine, psychology or engineering, and 369 persons who were treated at a local psychotherapeutic hospital. Stu- dents’ mean age was 23.3 years (SD = 3.5), 53.6% were fe- male. Mean age of people diagnosed with mental disorders was 36.0 years (SD =14.6), 71.2% were female. The most common primary diagnoses were Major Depressive Dis- order (40.4%) and Eating Disorders (29.3%). Diagnoses were verified in a two step procedure: First, the diagnoses were assessed by the responsible therapist using a clinical interview in which the International Diagnostic Checklists (IDCL)  were applied. The IDCL are checklists that can be used to make a careful evaluation of the symptoms and classification criteria, and thus help to arrive at precise diagnoses according to ICD-10 criteria. Results of this as- sessment were discussed with a supervising senior psycho- therapist. In case that ambiguity about main and comorbid diagnoses persisted after this it was decided that a full form of the German Version of the Structured Clinical Interview for DSM-IV (SKID)  was conducted in addition. The clinical interviews were conducted by clinical psycholo- gists. In the second step, diagnoses were verified through clinical conferences including senior psychotherapists and psychiatrists. Table 1 shows detailed demographic and clin- ical characteristics of the samples. The students were ran- domly divided into two subsamples to allow for cross validation. The two random groups did not differ in age (t = 1.34, p = .184) or sex (χ 2 =1.42, p = .251). Students volunteered to participate after class meetings. Persons seeking treatment for mental disorders were tested during admission as part of a standard diagnostic assessment. They gave written informed consent for their data to be included in research. Ethical approval was given by the local ethics committee of the Medical Faculty of the RWTH Aachen University. None of the participants was paid.
is rated on a four-point, Likert-type scale (0, 1, 2, and 3) that reflects the severity of symptoms. The TSI-A includes eight clinical scales and three validity scales. Five clinical scales (anxious arousal, depression, anger/irritability, intrusive experiences, and defensive avoidance) measure symptoms that are closely related to those listed in the DSM-IV for posttraumatic stress disorder. The other three clinical scales (dissociation, impaired self-reference, and tension-reduction behavior) measure additional symptoms often seen in trauma survivors, especially victims of childhood trauma. The three validity scales (response level, inconsistent response, and atypical response) measure exaggerated, inconsistent, or unusual responding. Average TSI-A scores in a nonclinical population is 1.01 ± 0.5.
Data came from the Stepwise database, a nationwide Swedish longitudinal clinical database of ED patients seek- ing treatment at specialist psychiatric treatment units . All patients aged 13–17 registered in the database from 2005-03-07 (start of the database) through 2015-06-16 were extracted (N = 3982). Inclusion criteria were medical or self-referral to one of the participating treatment units, a diagnosed DSM-IV ED, and consent to research use of data. Three thousand two hundred and fifty-five patients fulfilled inclusion criteria, and 95.7% were girls. Diagnoses were anorexia nervosa (AN), bulimia nervosa (BN) and ED not otherwise specified (EDNOS). Patients received treatment of various modalities (e.g., medical, psycho- logical, pedagogical, nutritional, social, physical), length, and intensity (e.g., residential, day and/or out-patient treatment).
The current study included young adults recruited at Utrecht University. Although generalizability of (prevalence) data from a convenience sample is often regarded as problem- atic, this is of less concern when investigating associations. Nevertheless, the age range of our study is small, and as most participants were students, it can be questioned whether our sample is representative for the general population as a whole. Hence, this study should be replicated in a nonstudent population; recruiting participants from a wider age range, and preferably also include a group of participants who are formally diagnosed as having an ED. It then may also be of interest to differentiate between participants having different EDs, which is not possible when using the ESP screening questionnaire, and determine whether participants may have comorbid mood disorders such as anxiety and depression that may also affect sleep. Finally, the subjective nature (self-report) of the data and the risk of recall bias are inher- ent to survey research. Hence, no causal relationships can be drawn from our data. Other factors affecting health status such as smoking and drinking alcohol all may play a role in the relationship between EDs and sleep disorders. Our survey should therefore be considered as a pilot study providing potential leads for future research.
Item 21 (Can you resist eating delicious food?) had low loading value and high residual covariance value with multiple items and was thus removed. The particular item was found to be problematic in the original Dutch version too, in which it was reverse scored (27), but not in the edited English version which does not involve reverse scoring (25). The problematic loading of the item in this study is unexpected as the English version was translated into the Malay language. Modification indices showed that correlating the error term of Item 21 to the restraint scale would result in a huge reduction in χ 2 values (42.449). This could indicate