Screening disordered eating in a representative sample of the German population: Usefulness and psychometric properties of the German SCOFF questionnaire

EATBEH-01087; No of Pages 8 Eating Behaviors xxx (2016) xxx–xxx

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Eating Behaviors

Screening disordered eating in a representative sample of the German population: Usefulness and psychometric properties of the German SCOFF questionnaire Felicitas Richter a,⁎, Bernhard Strauss a, Elmar Braehler b,c, Luise Adametz a, Uwe Berger a a b c

Jena University Hospital, Institute of Psychosocial Medicine and Psychotherapy, Stoystr. 3, D-07740 Jena, Germany Leipzig University Hospital, Department of Medical Psychology and Medical Sociology, Philipp-Rosenthal-Straße 55, D-04103 Leipzig, Germany Universal Medical Center Mainz, Department of Psychosomatic Medicine and Psychotherapy, Untere Zahlbacher Str. 8, D-55131 Mainz, Germany

a r t i c l e

i n f o

Article history: Received 29 September 2015 Received in revised form 11 April 2016 Accepted 15 June 2016 Available online xxxx

a b s t r a c t The prevention of eating disorders and the identification of high-risk individuals are essential for the public health sector. There is need for sensitive and specific screening instruments of disordered eating that can be applied in universal samples as an initial step into disease prevention. The SCOFF is a screening instrument for disordered eating, frequently used in international and cross-cultural contexts to detect individuals at risk. The objective of this research is to evaluate whether the SCOFF can be used as a screening tool for disordered eating in universal samples. This is the first study which examined the psychometric properties of the German version of the SCOFF in a general population sample. A representative sample (N = 2527) of the German population, aged 14–95 years, was recruited. Psychometric properties were determined including reliability, concurrent and construct validity, and factor structure. The prevalence of disordered eating was assessed. The prevalence of disordered eating in the general population was 10%. Using the established cutoff point of ≥2, values for diagnostic accuracy were 26% (sensitivity), 97% (specificity), 80% (positive predictive value), and 74% (negative predictive value). Factorial analyses revealed an excellent model fit of a unidimensional model. Due to its low sensitivity and a high percentage of false negatives, there are limitations in using the German version of the SCOFF in general population samples with wide age ranges. © 2016 Elsevier Ltd. All rights reserved.

1. Introduction The prevention of eating disorders and the identification of high-risk individuals are essential for the public health sector. There is need for sensitive and specific screening instruments of disordered eating that can be applied in universal samples as an initial step into disease prevention (Jacobi, Abascal, & Taylor, 2004; Sallis, Owen, & Fotheringham, 2000). In the general population, the lifetime prevalence of clinical eating disorders is approximately 5% (Treasure, Claudino, & Zucker, 2010). Despite that, subclinical cases − which mean people who show some eating disorder symptoms, but do not fulfill all classification criteria−are more widespread among the population (Stice, Marti, Shaw, & Jaconis, 2009; Treasure et al., 2010). In general, disordered eating is

described as a non-normative eating pattern, which does not fulfill the criteria of a clinical eating disorder, but has an important impact on body and health (Tanofsky-Kraff & Yanovski, 2004). It is associated with several body and weight associated symptoms such as persistent dieting or body dissatisfaction. In the current paper, the term “eating disorder” is used only where a clinical diagnosis was received through a diagnostic interview. By contrast, the term “disordered eating” is used to refer to all individuals who show some eating disorder symptoms, and who may be at risk of developing an eating disorder but no clinical diagnosis was made by an interview. To avoid confusion, this terminology is used throughout the entire paper, even if the original studies used other terms. 1.1. Disordered eating as a public health issue

⁎ Corresponding author. E-mail addresses: [email protected] (F. Richter), [email protected] (B. Strauss), [email protected] (E. Braehler), [email protected] (L. Adametz), [email protected] (U. Berger).

Identifying persons in universal samples with disordered eating behaviour is an important task from a general public health perspective, for several reasons. Firstly, disordered eating is a significant predictor of a clinical eating disorder (American Psychiatric Association, 2013).

http://dx.doi.org/10.1016/j.eatbeh.2016.06.022 1471-0153/© 2016 Elsevier Ltd. All rights reserved.

Please cite this article as: Richter, F., et al., Screening disordered eating in a representative sample of the German population: Usefulness and psychometric properties of the Ger..., Eating Behaviors (2016), http://dx.doi.org/10.1016/j.eatbeh.2016.06.022

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F. Richter et al. / Eating Behaviors xxx (2016) xxx–xxx

Secondly, disordered eating is associated with higher psychopathology (Aspen et al., 2014; Herpertz-Dahlmann, Wille, Hoelling, Vloet, & Ravens-Sieberer, 2008; Meng & D'Arcy, 2015). Thirdly, disordered eating is associated with a lower quality of life (Herpertz-Dahlmann et al., 2008; Sanftner, 2011; Zeiler et al., 2015). Fourthly, longitudinal studies indicate that disordered eating behaviour remains stable or increases from adolescence to young adulthood (Eisenberg, Nicklett, Roeder, & Kirz, 2011; Herpertz-Dahlmann, Dempfle, Konrad, Klasen, & Ravens-Sieberer, 2014; Neumark-Sztainer, Wall, Larson, Eisenberg, & Loth, 2011). Hence, disordered eating behaviour is not an isolated syndrome which occurs in adolescence and then disappears in adulthood. Therefore, the assessment of disordered eating is an important issue in universal disease prevention. 1.2. Screening in public samples and universal prevention An issue of great interest in the public sector for accomplishing universal prevention is to develop and evaluate valid and reliable screening instruments, aimed at detecting people at risk of developing an eating disorder. Such instruments should be effective for screening purposes in epidemiological studies, school-settings, as well as in primary care. Applying a short and cost-efficient screening may be the first step to detecting early predictors of an eating disorder. As a second step, sensitive and specific screening instruments are needed in order to identify people in large universal samples, who may benefit from prevention programmes or clinical interventions. Additionally, useful screenings may support evaluations of universal prevention programmes. In general health research, such screenings can be used to identify correlates and predictors of health and the development of eating disorders. To detect risk groups in general health practice, the diagnostic instrument needs to fulfill defined psychometric requirements. According to Jacobi et al. (2004), relevant criteria for the evaluation of screening tests for disordered eating are the following: 1. Relevancy and usability of the screening instrument for different populations and efficiency in administration; 2. Development of the screening instrument and its psychometric characteristics (test-retest reliability, internal consistency, concurrent validity with other measures) 3. External validation by comparing the test with a gold standard (e.g. an interview based on the Diagnostic and Statistical Manual for Mental Disorders (American Psychiatric Association, 2013). Developing sensitive and specific measures of risk and health behaviour is one of the important tasks in research on health promotion and universal disease prevention (Jacobi et al., 2004; Sallis et al., 2000; Striegel-Moore, 2005). According to the Society of Prevention Research one important standard in efficacy trials considers the measures and their properties. It is stated that all measures used in prevention research must be psychometrically sound, including reliability and construct validity (Gottfredson et al., 2015). Unfortunately, screening instruments of disordered eating and clinical eating disorders were developed, but they have rarely been tested in large and universal samples. Furthermore, few studies have investigated the external validity of the available screening instruments (Jacobi et al., 2004; Striegel-Moore et al., 2008). 1.3. The SCOFF — application, strengths and limitations The SCOFF questionnaire is a frequently used screening-instrument for disordered eating. It was first developed as a screening tool for eating disorders in primary care, especially for anorexia and bulimia nervosa (Morgan, Reid, & Lacey, 1999). Due to its brevity, the SCOFF is easy to administer and score, even when dealing with very large samples. Therefore, it is commonly used for screening purposes in general health. Although it was originally designed to detect only anorexia and bulimia nervosa, in recent research, it has often been used to detect disordered

eating in general health surveys and epidemiological studies (Herpertz-Dahlmann et al., 2014; Hoelling & Schlack, 2007; Zeiler et al., 2015). The SCOFF stimulated much research in the field of early detection of eating disorders. It has been applied widely in cross-cultural settings and has been translated into different languages, e.g. Chinese (Leung et al., 2009), Italian (Pannocchia, Fiorino, Giannini, & Vanderlinden, 2011), Finnish (Lahteenmaki et al., 2009), Spanish (Garcia-Campayo et al., 2005), Catalan (Muro-Sans, Amador-Campos, & Morgan, 2008), French (Garcia et al., 2010), and German. Recently a meta-analysis of the diagnostic accuracy of the SCOFF integrated results from studies in different languages (Botella, Sepulveda, Huang, & Gambara, 2013). The diagnostic efficacy of the SCOFF was associated with gender, indicating that the sensitivity and specificity increased in accordance with the proportion of females in the sample. Furthermore, the sensitivity and specificity were higher when an interview was used as a gold standard. Interestingly, the authors found a higher diagnostic efficacy for EDNOS (eating disorders not otherwise specified, including binge-eating disorder) than for bulimia or anorexia nervosa, although the SCOFF was originally designed to detect the latter. However, in that study, the use of SCOFF as a screening instrument for disordered eating was highly recommended. An analysis of previous research on the SCOFF reveals two main limiting aspects. At first, it is striking that most of the studies investigated female samples in a limited age range (mainly young people) and of White European or Northern American ethnicity (Solmi, Hatch, Hotopf, Treasure, & Micali, 2015). However, samples which are homogeneous regarding demographic variables (e.g. younger age, female sex, and white European or Northern American ethnicity) may lead to an overestimation of diagnostic accuracy and, further, preclude generalisations for the general population. Second, earlier research often applied the SCOFF to risk populations (e.g. people attending primary care practice), where prevalence of disordered eating is higher than in the general population (Lahteenmaki et al., 2009). In such studies, a frequently used research frame was to test the SCOFF in a healthy control sample (mainly students) against a sample with clinical eating disorders, where ill and healthy individuals were easy to differentiate. Therefore, the assumption may be made that the SCOFF seems to work very well in risk populations. Overall, these research designs produced results of high validity but may have overestimated sensitivity. 1.4. The SCOFF in general population surveys Contrastingly, recent research has indicated that the SCOFF is a suboptimal measure when used to detect disordered eating in general population samples. Lahteenmaki et al. (2009) found limitations using the SCOFF in a general population sample of Finnish young adults, mainly due to very low positive predictive value. Solmi et al. (2015) found a low sensitivity and high percentage of false negatives for the SCOFF in a multiethnic general population sample in Great Britain. Both research teams concluded that the SCOFF had its limitations when used in general population samples. In this regard, in terms of universal prevention, a screening instrument capable of being used in general population samples is highly desirable. The populations hitherto tested differed in some important aspects from the aforementioned samples. They represented all segments of the population living in a country, including all ages, socio-economic statuses, ethnicities etc. Furthermore, in such samples, the prevalence of clinical eating disorders was low, and participants may have had other (mental) diseases (a condition which is often an exclusionary criterion in other studies). These factors may have contributed to the lower sensitivity for the SCOFF in general population samples. To our knowledge, except for the two studies of Lahteenmaki et al. (2009) and Solmi et al. (2015), there are no other studies on psychometric properties in general population samples. Therefore, there is a need for further investigation of psychometric data in more heterogeneous samples to ascertain whether the SCOFF is useful in different

Please cite this article as: Richter, F., et al., Screening disordered eating in a representative sample of the German population: Usefulness and psychometric properties of the Ger..., Eating Behaviors (2016), http://dx.doi.org/10.1016/j.eatbeh.2016.06.022

F. Richter et al. / Eating Behaviors xxx (2016) xxx–xxx

populations, sexes, and age groups. If the SCOFF fulfills these requirements, it could be useful in epidemiological studies and in general public health research. However, the SCOFF is often used to determine the prevalence of disordered eating in general populations without collecting psychometric data (Table 1). In these studies, the SCOFF was administered to large representative samples in Europe to detect individuals at risk in the context of public health concerns. Prevalence of disordered eating ranged from 3% in adults aged 50 years and older in Great Britain (Ng, Cheung, & Chou, 2013) to 49% in female European and Latin American immigrants aged 13 to 17 years in Madrid, Spain (Esteban-Gonzalo et al., 2014). In general, the prevalence of disordered eating determined by the SCOFF was lower in samples which were heterogeneous regarding age (age range more than 15 years), sex (males and females) and ethnicity (at least two different ethnicities) (Lahteenmaki et al., 2009; McBride, McManus, Thompson, Palmer, & Brugha, 2013; Ng et al., 2013; Solmi, Hatch, Hotopf, Treasure, & Micali, 2014). However, in samples of adolescents and young adults, the reported prevalence of disordered eating was higher (Esteban-Gonzalo et al., 2014; Herpertz-Dahlmann et al., 2008; Hoelling & Schlack, 2007; Zeiler et al., 2015). In epidemiological studies the lifetime prevalence of clinical eating disorders reached approximately 5%, when these diagnoses were based on clinician-administered diagnostic interviews (Treasure et al., 2010). Compared with this result, the SCOFF screened a higher number of people with an elevated risk and may overestimate the prevalence of eating disorders in most studies (Table 1). These findings may be attributable to the fact that the SCOFF produced a high percentage of false positives, which necessarily implies that participants were detected as “ill” although they were healthy. 1.5. The German SCOFF Although the SCOFF is frequently used for screening purposes in German speaking countries (Herpertz-Dahlmann et al., 2014; Hoelling & Schlack, 2007; Zeiler et al., 2015), very little is known about the psychometric properties and usefulness of the German version for the general population. Only one study assessed the diagnostic accuracy of the German SCOFF in a sample of 12 year-old boys and girls (Berger et al., 2011). Due to the limited age range of the sample, generalisations regarding the psychometric quality of the German version could not be established. The current study aimed to provide more information about the usability of the German SCOFF, analysing the three main criteria Jacobi et al. (2004) mentioned earlier: 1) Examining the relevancy and usability of the SCOFF for different populations (which are heterogeneous with respect to age, sex, and socioeconomic status); 2) Assessing psychometric data for internal consistency and concurrent validity with other measures; and 3) Providing external validation by comparing the SCOFF with a reference criterion. The objective of this research was to evaluate whether the German SCOFF could be used as a screening tool for disordered eating in general public health research. As a first step, we investigated the screening procedure in a general population sample in order

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to detect people at risk of developing an eating disorder. The next steps in the prevention sequence should involve the identification of potential risk factors and predictors of eating disorders, and to assign preventive or clinical interventions in order to prevent the onset and sequelae of such disorders. 2. Material and methods 2.1. Participants and procedure Data were retrieved from a representative general-population survey in Germany conducted by the University of Leipzig. The study was approved by the Ethics Committees of the Universities of Leipzig and Jena (Germany). An independent agency specialising in market, opinion, and social, research (USUMA, Germany) recruited participants between February and April 2014. A total of 4644 households from all German states were selected by a three-stage random-route sampling procedure, which ensured the random selection of households. Firstly, 258 regions in rural and urban parts of Germany were determined based on representative data. Secondly, target households were determined following defined rules of walking from a random starting address. Thirdly, the target person was selected according to a kishselection-grid. Participants were recruited where they were 14 years or older and had sufficient knowledge of the German language. A total of 2539 participants (55.1%) gave their informed consent prior to inclusion; for participants under 18 years, additional parental consent was necessary. Data collection was carried out with the help of trained interviewers; demographic information was assessed face-to-face; questionnaires for disordered eating were assessed via self-report. The data of twelve participants were not analysable (0.3%). The final sample resulted in 2,527 participants (53.4% females) aged 14 to 95 years (M = 49.44, SD = 17.83). Sample characteristics are displayed in Table 2. There were no differences in age between males and females (t = −1.45; df = 2525; p = 0.23). The mean body mass index (BMI) in the adult sample (≥ 18 years) was 25.94 kg/m² (SD = 4.48 kg/m², range 10.69–63.51 kg/m²), males showing a significant higher BMI than females (26.4 vs. 25.5 kg/m²; t = 4.99; df = 2401; p b 0.001). 2.2. Measures The SCOFF questionnaire (Morgan et al., 1999) is a five-item self-report screening tool for disordered eating. The name SCOFF is an acronym for its five questions. It measures core symptoms of anorexia and bulimia nervosa, including intentional vomiting, loss of control eating, recent weight loss, body image concerns, and food thoughts, using a dichotomised answering scale (“yes” or “no”). A total score of ≥ 2 is used as a cutoff point to select persons at risk. The first paper concerning the SCOFF found 100% sensitivity and 87.5% specificity with a false positive rate of 12.5% in a female sample of clinical cases of diagnosed anorexia or bulimia nervosa and female healthy controls (aged 18–40) in the UK (Morgan et al., 1999). Later, Hill, Reid, Morgan, and Lacey (2010) reported a sensitivity of 84.6% and a specificity of 89.6% in a

Table 1 Studies of prevalence of disordered eating measured with the SCOFF in representative samples in Europe. Study

N

Sample

Country

% female

Age (in years)

Prevalence % (♀/♂)

Esteban-Gonzalo et al. (2014) Herpertz-Dahlmann et al. (2008) Hoelling and Schlack (2007) Lahteenmaki et al. (2009) McBride et al. (2013) Ng et al. (2013) Solmi et al. (2014) Zeiler et al. (2015)

2077 1843 6634 1863 7001 2870 1698 3610

Children and adolescents Children and adolescents Children and adolescents Young adults General population Older adults General population Children and adolescents

Spain Germany Germany Finland Great Britain Great Britain Great Britain Austria

50.6 48.7 48.8 – 55.9 70.7 56.6 55.3

13–17 14–17 11–17 20–35 16–65+ 50–70+ 16–90 10–18

− (28.9–48.5/17.4–17.9) − (29.4/14.4) 21.9 (28.9/15.2) 9.7 6.3 (9.1/3.4) 2.61 10.0 (12.2/5.9) 23.6 (30.9/14.6)

SCOFF = screening instrument for disordered eating (Morgan et al., 1999); − = information was missing in the present article; prevalence of disordered eating was determined by the SCOFF using a total score ≥2.

Please cite this article as: Richter, F., et al., Screening disordered eating in a representative sample of the German population: Usefulness and psychometric properties of the Ger..., Eating Behaviors (2016), http://dx.doi.org/10.1016/j.eatbeh.2016.06.022

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Table 2 Sample characteristics and prevalence of disordered eating measured with the SCOFF.

Age (in years)

Education (in years) Nationality Marital Status

Weight Status

Self-reported lifetime diagnosis of eating disorder

Disordered eating (SCOFF)

≤29 30–49 50–69 ≥70 b12 ≥12 German Other Married Single, divorced, widowed Missing Underweight Normal weight Overweight Obese Missing Anorexia nervosa Bulimia nervosa Binge-eating disorder EDNOS No risk Risk (score ≥2)

Female (n =

Male (n =

1350)

1177)

N (%)

N (%)

215 (15.9) 439 (32.5) 482 (35.7) 214 (15.9) 1108 (82.1) 242 (17.9) 1299 (96.2) 51 (3.8) 625 (46.3) 725 (53.7)

208 (17.7) 367 (31.2) 444 (37.7) 158 (13.4) 926 (78.7) 251 (21.3) 1133 (96.3) 44 (3.7) 593 (50.4) 582 (49.4)

0 (0) 21 (1.6) 694 (51.4) 422 (31.2) 189 (14.0) 24 (1.8) 4 (0.3) 3 (0.2) 6 (0.4)

2 (0.2) 8 (0.7) 458 (38.9) 531 (45.1) 161 (13.7) 19 (1.6) 2 (0.2) 0 (0) 3 (0.3)

9 (0.7) 1195 (88.5) 155 (11.5)

3 (0.3) 1077 (91.5) 100 (8.5)

EDNOS = Eating disorder not otherwise specified. Body Mass Index was classified for adolescents ≤18 years according to Kromeyer-Hauschild et al. (2001) and for adults N18 years according to WHO (1995). SCOFF = screening instrument for disordered eating (Morgan et al., 1999)

technique (Myers, 2011). Analyses were performed using IBM SPSS Statistics 21 (IBM Corporation, 2012), the free software R (R Core Team, 2012), and Mplus (Muthén & Muthén, 1998-2010). All p-values were reported two-tailed; a p-value ≤ 0.05 was interpreted as statistically significant. Psychometric properties were described with distribution (Kolmogorov-Smirnov-Test), sum, mean, SD, and corrected item-total correlations. Cronbach's α was used as a measure of reliability. Validity was examined by using the ISR-E as a reference criterion with a cutoff point of ≥0.67. To determine sensitivity, specificity, positive (PPV) and negative predictive value (NPV), the ROC (Receiver Operating Characteristic)-curve with the area under curve (AUC) were computed. Construct validity was computed using bivariate correlations with ISR-E. According to Fisseni (1997), correlations r b 0.40 were evaluated as low, correlations between 0.40 and 0.60 as medium, and correlations N0.60 as high. Factor analyses consisted of two steps; firstly, the unidimensionality of the SCOFF was tested by computing an exploratory factor analysis (principal component analysis). Secondly, one-factorial structure was confirmed using confirmatory factor analysis. The SCOFF used a dichotomised answering scale; therefore logistic models were applied according to item-response theory. A two-parameter-logistic latent trait model, with the parameters difficulty (severity/location along the latent continuum) and discrimination (slope of the logistic curve), was determined. The model was tested using weighted least square parameter estimates (WLSMV). Goodness of fit of the model was evaluated by applying the following criteria: Root Mean Square Error of Approximation RMSEA b 0.06, Comparative Fit Index CFI N 0.95, and Tucker-Lewis Index TLI N 0.95 (Hu & Bentler, 1999). 3. Results

primary care population of female attendees aged 18 to 50 years in London. Apart from the study by Berger et al. (2011), psychometric properties for the German version have scarcely been examined. This study showed a sensitivity of 79% and a specificity of 74% in reference to the Eating Attitudes Test (Garner, Olmstedt, Bohr, & Garfinkel, 1982). A meta-analysis of the diagnostic accuracy of the SCOFF revealed a pooled sensitivity of 80% and a specificity of 93% (Botella et al., 2013). The conduct of a representative general-population study necessarily requires enormous time and financial investments. The use of expert interviews as a gold standard for validation of the SCOFF was not possible in the current research due to limited time and financial capacities. Therefore, we decided to establish a subscale of the “ICD-10-Symptom-Rating” questionnaire (ISR-E) as a reference criterion (Tritt et al., 2008). The ISR-E assesses the core symptoms of eating disorders according to the diagnostic criteria of the International Classification of Diseases (ICD) via self-report. The following three items should assess the eating disorders syndrome: 1) “I control my weight with low-calorie foods, by vomiting, with drugs (such as laxatives), or through extensive exercise.” 2) “I think a lot about food and worry constantly about gaining weight.” 3) “I spend a lot of time thinking of ways to lose weight.” Symptoms are assessed via self-report using a 5-point Likert scale (0 = “does not apply” to 4 = “applies strongly”). The severity of symptoms was assigned by mean, with a mean of ≥ 0.67 as a cutoff point for symptomatic burden. German norms for the ISR-E were determined in clinical and nonclinical samples (Tritt, 2015). Psychometric properties were reported with sensitivity (67%) and specificity (74%) (Tritt, 2015), retest-reliability of r = 0.83–0.94 (Fischer, Schirmer, Tritt, Klapp, & Fliege, 2011), internal consistency with Cronbach α = 0.83–0.85 and, corrected item-total correlations between r = 0.59– 0.83 (Fischer, Tritt, Klapp, & Fliege, 2010; Tritt, 2015). 2.3. Data analyses The number of missing values for all items of SCOFF was quite low (≤0.5% per item); all missing values were imputed using the hot deck

3.1. Item and scale characteristics The Kolmogorov-Smirnov test revealed a positively skewed distribution of the items, indicating that participants more often answered with a “no”. All SCOFF items and the total scores showed a significant deviation of raw scores from normative distribution (KolmogorovSmirnov-Z = 21.88, p b 0.001). Psychometric characteristics of the SCOFF items with the number of participants who scored positively on the items and corrected item total correlations (ritc) are displayed in Table 3. The SCOFF total scores ranged from 0 to 5, with mean scores ranging from M = 0.03 (SD = 0.16) for item 1 to M = 0.17 (SD = 0.37) for item 5. Females showed significantly higher means than males (0.44 (SD = 0.88) vs. 0.37 (SD = 0.87); Mann-Whitney-U = 752873, p = 0.002). The number of participants who endorsed two items or more of the SCOFF was 10.1% [95%CI: 8.9; 11.3], (female: 11.5% [9.8; 13.2], male: 8.5% [6.9; 10.1]). Analysing only the subsample of adolescents aged ≤17 years (n = 77), a determined prevalence of disordered eating was 13.3% [95%CI: 1.1; 25.5] for females and 4.3% [95%CI: 0; 10.1] for males. 3.2. Reliability, construct and concurrent validity Inter-item correlations ranged from r = 0.21 to r = 0.41. Cronbach’s α for the total sample was α = 0.66, for the male subsample it was higher (α = 0.71) than for the female subsample (α = 0.62). To determine construct validity, bivariate correlation with ISR-E was computed. The SCOFF total score was positively correlated with the ISR-E mean (r = 0.44 [95%CI: 0.43; 0.51], p b 0.001). The concurrent validity was determined by using the ISR-E as reference standard. The diagnostic accuracy was AUC = 0.69 [95%CI: 0.67; 0.71]. Based on the cutoff point of ≥2, the following parameters for the entire sample were computed: sensitivity = 25.7% [95%CI: 22.7; 28.9], specificity = 97.0% [96.1; 97.8], PPV = 79.6% [74.8; 82.1], and NPV = 74.2% [70.9; 79.5]. The number of false positives was 52 (2.1%), and

Please cite this article as: Richter, F., et al., Screening disordered eating in a representative sample of the German population: Usefulness and psychometric properties of the Ger..., Eating Behaviors (2016), http://dx.doi.org/10.1016/j.eatbeh.2016.06.022

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Table 3 Number of the participants who scored positively on the SCOFF items, corrected item total correlations (ritc) and results of factor analyses with estimated parameters of two-parameter logistic latent trait model. Item

Descriptive N

1. Do you make yourself sick because you feel uncomfortably full?(Übergeben Sie sich, wenn Sie sich unangenehm voll fühlen?) 2. Do you worry you have lost control over how much you eat? (Machen Sie sich Sorgen, weil Sie manchmal nicht mit dem Essen aufhören können?) 3. Have you recently lost more than one stone in a 3 month period? (Haben Sie in letzter Zeit mehr als 6 kg in 3 Monaten abgenommen?) 4. Do you believe yourself to be fat when others say you are too thin? (Finden Sie sich zu dick, während andere Sie zu dünn finden?) 5. Would you say that food dominates your life? (Würden Sie sagen, dass Essen Ihr Leben sehr beeinflusst?)

%

Discrimination Difficulty ritc

Est.

SE

Est.

SE

69

2.7 0.40 1.51

0.25

2.30 0.13

207

8.2 0.51 1.71

0.18

1.61 0.06

136

5.4 0.36 1.02

0.10

2.26 0.13

198

7.8 0.44 1.21

0.11

1.84 0.09

422 16.7 0.45 1.26

0.10

1.23 0.06

SCOFF = screening instrument for disordered eating (Morgan et al., 1999), N (%) = number and percentage of people who endorsed an item, ritc = corrected item-total correlation. Discrimination = slope of the logistic curve in item response modelling, higher values indicate a better discrimination between people. Difficulty = severity of the item, higher values indicate a lower likelihood to endorse the item. Parameters are reported in probit-metric. Est. = Estimate.

the number of false negatives was 586 (23.2%). To detect differences in diagnostic accuracy, ROC-curves with associated parameters for different ages and sexes were computed (Table 4). In general, a higher sensitivity for females than for males was found. Females in the age group between 14 and 29 years and males in the age group between 30 and 49 years showed the highest values for sensitivity and specificity. Because of the very low sensitivity and the high number of false negatives, the cutoff point was reduced to ≥1 in an additional analysis. This resulted in a higher sensitivity of 49.4%, whereas specificity decreased to 86.9%. The PPV decreased to 63.3% and the NPV reached 79.1%, respectively. Values for sensitivity and specificity changed due to an increase in the number of false positives and a decrease in the number of false negatives.

3.3. Factorial validity The Bartlett test of sphericity (χ² = 1749.41; df = 10; p b 0.001) and the Kaiser-Meyer-Olkin coefficient (KMO = 0.74) indicated that the present data were appropriate for an exploratory factor analysis. The exploratory factor analysis revealed a one factorial solution with Eigenvalue N 1, explaining 43.98% of variance. The unidimensionality of the SCOFF was confirmed. Due to the categorical nature of the SCOFF variables, item response modelling was used for the confirmatory factor analysis. To fit the one-factor model, a two-parameter-logistic latent trait model was computed. The estimated parameters item difficulty and item discrimination with their standard errors are reported in Table 3. The analysis showed an excellent model fit (RMSEA = 0.045 [90%CI: 0.03; 0.06]; CFI = 0.985; TLI = 0.969). Chi-Square test of model fit was significant (χ² = 30.14; df = 5; p b 0.001), which was to be expected due to the sample size and the skewness of the variable. Table 4 External validation of the SCOFF with reference to the ICD-10-Symptom-Rating Scale displayed separately for different sexes and ages. Female all

Se Sp PPV NPV

27% 97% 86% 70%

Male

14–29

30–49

50–69

≥70

y

y

y

y

31% 97% 88% 63%

29% 97% 88% 68%

22% 97% 83% 69%

27% 98% 83% 79%

all

24% 97% 70% 79%

14–29

30–49

50–69

y

y

y

20% 97% 68% 77%

30% 96% 72% 82%

23% 96% 69% 78%

≥70y 18% 98% 67% 81%

SCOFF = screening instrument for disordered eating (Morgan et al., 1999), ISR-E = ICD10-Symptom-Rating Scale (Tritt et al., 2008), Se = sensitivity, Sp = specificity, PPV = positive predictive value, NPV = negative predictive value.

4. Discussion According to the Society of Prevention Research, the application of reliable and valid measures in prevention research is an important standard (Gottfredson et al., 2015). Developing sensitive and specific screening instruments of disordered eating that can be applied in universal samples are an initial step into disease prevention. Unfortunately, there is a lack of research examining the basic psychometric requirements including the external validity of the available screening instruments (Jacobi et al., 2004; Striegel-Moore et al., 2008). This research was conducted in order to investigate the usefulness of the German version of the SCOFF for screening purposes in a universal sample of the general population. Although, the German SCOFF is a frequently used screening instrument for disordered eating in general population samples, until now, there have been no investigations carried out concerning its suitability for universal samples in Germany. For these reasons, it was decided to carry out a survey in Germany to determine the psychometric data, diagnostic accuracy, and prevalence of disordered eating in a representative population sample aged 14 to 95 years. As the sample was very heterogeneous, the usability of the German SCOFF for different ages and sexes was assessed. Results are discussed within the framework of previous studies evaluating psychometric properties of the SCOFF in different languages and samples.

4.1. Prevalence of disordered eating in general population In the present study, the overall point prevalence of disordered eating measured with the SCOFF and applying the established cutoff point of ≥2 was 10%, with 12% for females and 9% for males. In the German general population, this prevalence was nearly consistent with that reported by Solmi et al. (2014) in a British general population, also using the SCOFF. Our findings are consistent with previous literature. These findings suggested that within heterogeneous samples which are characterised by a wide age range, different sexes and ethnicities, the prevalence of disordered eating is low (McBride et al., 2013; Solmi et al., 2014). In samples with a lower age range, especially in samples with young participants, the reported prevalence of disordered eating measured with the SCOFF was even higher. Analysing only the subsample of adolescents aged ≤17 years in the present study, the determined prevalence of disordered eating was lower than the prevalence reported by other studies in Germany (Berger et al., 2011; Hoelling & Schlack, 2007). Nevertheless, the subsample in the present study was small and confidence intervals were wide. Therefore, the results in this subsample need to be interpreted with caution.

Please cite this article as: Richter, F., et al., Screening disordered eating in a representative sample of the German population: Usefulness and psychometric properties of the Ger..., Eating Behaviors (2016), http://dx.doi.org/10.1016/j.eatbeh.2016.06.022

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4.2. Psychometric properties of the German SCOFF Psychometric properties revealed a low internal consistency (Cronbach's alpha) which suggests that the SCOFF assessed heterogeneous aspects of disordered eating. Convergent validity with the ISR-E was medium, which could indicate that the measures were assessing different aspects of disordered eating. Concerning factorial structure, the expected unidimensionality of the SCOFF was approved in exploratory factor analysis and latent response modelling. This indicated that the five items measured an underlying continuous variable suggested as “disordered eating”. Analysing item discrimination (slope of the logistic curve), all values exceeded a discrimination of 1 which can be considered as very satisfactory. Analysing item difficulty (index of symptom severity or location along the latent continuum), nearly all items identified persons in the medium to upper range of the latent continuum. There was a lack of items identifying less “severe” (low item difficulty) and very “severe” symptoms (high item difficulty) on the latent continuum of disordered eating. External validation of the German SCOFF was carried out determining the diagnostic accuracy with reference to the ISR-E, a measure which assesses core symptoms of eating disorders according to ICD10. In accordance with previous studies, a higher specificity than sensitivity was found. Nevertheless, the sensitivity was very low compared with previous studies (Botella et al., 2013), revealing a high number of false negative identifications. Overall values for sensitivity and specificity were better for female than for male participants. Overall, 73% of females and 76% of males at risk were not detected. Seventy percent of the detected males and 68% of the detected females were at risk. Contrastingly, general PPV was higher when compared with previous studies. Healthy individuals were frequently detected (NPV). The performance of the SCOFF was lowest for men aged 14–29 years and men aged 70 years and older, revealing difficulties in detecting disordered eating in these subsamples. Within the framework of previous studies reporting diagnostic accuracy of the SCOFF, our findings were striking due to very low sensitivity when using the established cutoff point of ≥2. In the recent meta-analysis of the SCOFF, none of the included studies revealed a sensitivity b50% (Botella et al., 2013). To discuss these findings, the following influential aspects must be considered: 1) the reference criterion ISR-E; 2) the SCOFF itself; 3) the chosen cutoff point; and 4) the sample. Firstly, the chosen reference criterion ISR-E is a self-report measure. It assesses the diagnostic criteria of all eating disorders but it is not a clinical interview. Thus, diagnostic accuracy is expected to be low (Botella et al., 2013). Furthermore, it assesses only some disordered eating behaviours excluding symptoms such as bingeing behaviour. It is not capable of differentiating between various types of eating disorders. To gain further information about psychometric data, the validation of the German SCOFF using clinical interviews is crucial. Secondly, there are some limitations concerning the SCOFF. It does not assess all important disordered eating behaviours (e.g. bingeing, laxative misuse). As binge-eating disorder is the most prevalent eating disorder in males and females (Treasure et al., 2010), the SCOFF fails to capture this important issue in diagnostic criteria. In addition, one item of the SCOFF focuses only on recent weight loss, thus failing to capture individuals who are chronically underweight. Furthermore, the German translation of the SCOFF stimulated a measure of discussion, because there were items that were not accurately translated (Zeiler et al., 2015). In a professional back translation, Zeiler et al. (2015) revealed different wording in the German and English versions of items 2 and 5, which could lead to underreporting of the symptoms. Therefore, further research concerning the German SCOFF is needed, wherein the different versions of the SCOFF could be compared. Thirdly, it seems that the cutoff point of ≥2 is not the optimal cutoff in the present sample. The number of false negatives was very high, indicating that nearly one quarter of individuals at risk in the sample was missed. Individuals at risk who were not detected by the SCOFF were

preponderantly female who tended to have a higher BMI. When reducing the cutoff point to ≥1, the sensitivity increased by reducing the number of false negatives, whereas the specificity decreased. Fourthly, the representative sample in the current study was very heterogeneous regarding age, sex and socioeconomic status, reflecting all segments of the German general population. Frequently applied to female, clinical populations, the SCOFF may not be suitable for all people. This hypothesis could be partly confirmed in the subsample analyses; especially males showed the lowest values for sensitivity. This result may be explained by the fact that the prevalence of disordered eating in males is lower. Furthermore, disordered eating in males may be associated with symptoms which are not assessed by the SCOFF, e.g. the desire to gain muscle (as against the desire to be thinner) (Strother, Lemberg, Stanford, & Turberville, 2012). Nevertheless, there is further need to discuss these findings and to identify what other variables influence the results in these age groups. 4.3. Study limitations This study shows its strength through representativeness and sample size. However, some limitations must be mentioned. Firstly, a fairly high number of dropouts occurred during the recruitment procedure. Although non-responders did not differ in demographic variables, they may have differed in other important variables (e.g. disordered eating); therefore, the results could be biased. Secondly, the current research used a cross-sectional design. No statements about the prognostic validity of the SCOFF could be made. Thirdly, only self-report measures were used which could have led to a reporting bias particularly in participants with ego-syntonic eating disorders such as anorexia nervosa. Therefore, results should be replicated with a clinical interview as a reference criterion. 4.4. Implications for further research The implications of the present findings are that further research is needed to either modify the present version of the SCOFF, or to develop a new screening tool for disordered eating for the general population. As some important symptoms such as binge-eating or purging are not assessed by the SCOFF, renewed discussion is required to formulate new items to cover all aspects of different eating. This task has particular importance in light of the fact that binge-eating is a very prevalent disorder in males and females (Treasure et al., 2010). Additionally, symptoms which are known to be risk factors for eating disorders e.g. low body self-esteem, could be incorporated into additional items (Stice, Marti, & Durant, 2011). Furthermore, because males show the lowest detection rates, more emphasis should be laid on male-specific symptoms of eating disorders. There are some established questionnaires in existence for disordered eating, e.g. the Eating Disorder Examination Questionnaire (Fairburn & Beglin, 1994) or the Weight Concerns Scale (Killen et al., 1994). However, most of such questionnaires are fairly long and too complex to use in wide-ranging general health surveys. Therefore, recent efforts have been made to shorten established questionnaires on disordered eating for screening purposes, e.g. the Eating Attitudes Test (Berger et al., 2012; Richter, Braehler, Strauss, & Berger, 2014). 4.5. Conclusion To our knowledge, this is the first study which assessed the usefulness and psychometric properties of the German version of the SCOFF in a general population sample. Unfortunately, the results were quite mixed with excellent factorial validity but rather low values for concurrent validity. Values for specificity were very satisfactory, whereas values for sensitivity were fairly low, due to a high number of false negatives. There is urgent need for a replication of these results. Nevertheless, our findings are in line with recent research by Solmi et al. (2015)

Please cite this article as: Richter, F., et al., Screening disordered eating in a representative sample of the German population: Usefulness and psychometric properties of the Ger..., Eating Behaviors (2016), http://dx.doi.org/10.1016/j.eatbeh.2016.06.022

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concluding that, in general population samples, the SCOFF is a suboptimal measure for identifying individuals at risk of developing an eating disorder. Considerably more research is required on the comparative value of the different measures in use for disordered eating, on their usability as screening instruments, and on the optimal instruments available for detecting individuals at risk in general population. Role of funding source Expenses necessary for the completion of this research were paid by internal funds from the University Hospital of Jena and the University Hospital of Leipzig as part of the regular budget for research support for faculties. Contributors BS, EB, UB and FR designed the study. FR conducted the statistical analysis. FR wrote the paper in full. All authors were involved in writing and revising the manuscript and approved the final version. Conflict of interest All authors declare that they have no conflict of interest.

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Please cite this article as: Richter, F., et al., Screening disordered eating in a representative sample of the German population: Usefulness and psychometric properties of the Ger..., Eating Behaviors (2016), http://dx.doi.org/10.1016/j.eatbeh.2016.06.022