original article Neuropsychiatr (2014) 28:198–207 DOI 10.1007/s40211-014-0131-9
The Mental Health in Austrian Teenagers (MHAT)Study: preliminary results from a pilot study Julia Philipp · Michael Zeiler · Karin Waldherr · Martina Nitsch · Wolfgang Dür · Andreas Karwautz · Gudrun Wagner
Received: 7 November 2014 / Accepted: 18 November 2014 / Published online: 28 November 2014 © Springer-Verlag Wien 2014
Summary Background No epidemiological data on prevalence rates of mental disorders based on a representative sample are available for Austrian adolescents up to now. However, the knowledge of psychiatric disorders, related risk and protective factors is of great significance for treatment and prevention. The purpose of the MHATStudy (Mental Health in Austrian Teenagers), the first epidemiological study on mental health in Austria, is to obtain prevalence rates of mental disorders and to examine risk factors, protective factors and quality of life in a representative sample of adolescents aged 10–18. Aims of this pilot study were to evaluate the feasibility and acceptability of the screening instruments, pre-estimate the frequency of mental health problems and estimate possible non-responder bias. Methods Twenty-one schools in eastern Austria were asked to participate. Data on mental health problems were derived from self-rating questionnaires containing standardized screening measures (Youth Self-Report, measuring emotional and behavioral problems and the
Prof. Dr. A. Karwautz () · Dr. J. Philipp · Mag. Dr. G. Wagner Department of Child and Adolescent Psychiatry, Medical University of Vienna, Währinger Gürtel 18-20, 1090 Vienna, Austria e-mail: [email protected] Dr. J. Philipp e-mail: [email protected] Mag. M. Zeiler · Mag. Dr. M. Nitsch · Priv. Doz. Dr. W. Dür Ludwig Boltzmann Institute Health Promotion Research, Vienna, Austria Mag. Dr. K. Waldherr Ludwig Boltzmann Institute Health Promotion Research, Ferdinand Porsche Distance University of Applied Sciences (FernFH), Vienna, Austria
SCOFF, indicating eating problems. Quality of life as well as related risk and protective factors were also obtained. Results Four hundred and eight adolescents of five schools were recruited. The prevalence of mental health problems was 18.9 % [CI 95 %: 14.9–22.7]. Moreover, emotional and behavioral problems were highly correlated with quality of life measures. A Non-Responder Analysis indicated that non-responders (16.7 %) differ from responders with regard of school related problems. Conclusions The results demonstrate that mental health problems affect approximately one fifth of the adolescents. A Non-Responder Analysis suggests that the prevalence of behavioral and emotional problems is underestimated. Keywords Mental health · Psychiatric disorders · Epidemiology · Adolescence
Die Mental Health in Austrian Teenagers (MHAT)Studie: erste Ergebnisse aus einer Pilotstudie Zusammenfassung Grundlagen Bisher sind keine epidemiologischen Daten zu Prävalenzraten für psychische Störungen für österreichische Jugendliche, basierend auf einer repräsentativen Stichprobe, verfügbar. Das Wissen über psychiatrische Störungen sowie Risiko- und Schutzfaktoren ist jedoch essentiell für Therapie und Prävention. Im Rahmen der MHAT-Studie (Mental Health in Austrian Teenagers, Psychische Gesundheit bei österreichischen Jugendlichen), der ersten epidemiologischen Studie zur psychischen Gesundheit in Österreich, sollen Prävalenzraten psychischer Störungen bei einer repräsentativen Stichprobe von Jugendlichen zwischen 10 und 18 Jahren erhoben und Risiko- und Schutzfaktoren sowie Lebensqualität untersucht werden. Zweck der Pilotstudie war die Evaluation der Durchführbarkeit und Akzeptanz der Scree-
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ning-Phase, eine Häufigkeitsschätzung von Verhaltensauffälligkeiten und emotionalen Problemen sowie die Abschätzung eines möglichen Non-Responder-Bias. Methodik 21 Schulen im Osten Österreichs wurden eingeladen, an der Studie teilzunehmen. Daten zur psychischen Gesundheit wurden im Rahmen eines Screenings mithilfe standardisierter Selbstbeurteilungsbögen wie dem Youth Self-Report erhoben, der emotionale und Verhaltensprobleme erhebt, und dem SCOFF, der Hinweise für Essstörungen liefert. Lebensqualität und Risiko- und Schutzfaktoren wurden ebenfalls erhoben. Ergebnisse 408 Jugendliche an 5 Schulen wurden in die Studie eingeschlossen. Die Prävalenzrate für psychische Probleme lag bei 18,9 % [CI 95 %:14,9–22,7]. Weiters korrelierten emotionale und Verhaltensauffälligkeiten hoch mit gesundheitsbezogener Lebensqualität. Die Non-Responder Analyse weist darauf hin, dass sich NonResponder (16.7 %) von Respondern hinsichtlich schulischer Probleme unterscheiden. Schlussfolgerungen Die Ergebnisse weisen darauf hin, dass jeder fünfte Jugendlichen von einem psychischen Problem betroffen ist. Die Non-Responder Analyse deutet auf eine Unterschätzung der Prävalenzraten hin. Schlüsselwörter Psychische Gesundheit · Psychische Störungen · Epidemiologie · Jugendliche
Introduction Mental disorders tend to develop during adolescence [1, 2], show high comorbidity rates (45 % [1]) and tend to persist into adulthood [3]. Therefore, research should particularly focus on adolescents’ mental health. The knowledge about prevalence rates of psychiatric disorders in childhood and adolescence as well as related risk and protective factors is essential for the development of suitable prevention strategies and treatment approaches [2]. However, no epidemiological data on prevalence rates of mental disorders are available for adolescents in Austria. Due to this lack of epidemiological data in Austria, international studies and results from other European countries served as an overview of mental health and well-being in teenagers so far. Using only screening questionnaires, Rescorla et al. [4] investigated rates of behavioral and emotional problems and compared self-reports from adolescents aged 12–18 (Youth Self-Report [5]) with parental ratings (Child Behavior Checklist [6]) from 25 societies. With respect to the total problem score, parents perceived 21.4 % of their children to have problems, whereas 34.6 % of the children themselves reported problems. In Germany, the BELLA study was established to assess mental health problems in teenagers [7, 8]. Problems were assessed by parents, using the Strength and Difficulties Questionnaire (SDQ [9]). 21.9 % of children and adolescents between 7 and 17 years showed signs of
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mental health problems. 14.5 % reported mental health problems associated with severe impairment [10]. The Great Smoky Mountains Study [11] assessed psychiatric disorders in children aged 9, 11 and 13 with a 3-year and 6-year follow up. The 3-month prevalence rate of all examined disorders was 13.3 %. However, 36.7 % of the children had at least one psychiatric disorder during the study period. Merikangas et al. [12] interviewed 10123 adolescents aged 13 to 18 years within the National Comorbidity Survey Replication—Adolescent Supplement (NCS-A) in the US. Lifetime prevalence for any disorder was 49.5 %. When including only adolescents with severe impairment, prevalence rates decrease to 22.2 %. In the last decades, some reviews were published presenting prevalence rates of mental disorders. Robert, Attkisson and Rosenblatt [13] identified 52 studies conducted in over 20 countries published between 1963 and 1996 estimating the prevalence of psychiatric disorder. Prevalence estimates ranged from 1 to 51 % with a mean prevalence of 15.8 %. Ihle and Esser [2] as well compared 19 results from 9 countries between 1970 and 2000, presenting a mean prevalence of 18 % (6.8–37.4 %). A review concentrating on results from more recent studies in Great Britain and the United States between 2000 and 2007 including children and adolescents between 5 and 17 years summarized that one person in four suffered from a psychiatric disorder during the past year and even one out of three throughout the whole life [14]. A review including 29 studies in Germany between 1949 and 2003 presented an overall prevalence rate of 17.2 % for emotional and behavioral disorders [15]. A very recent review presented a prevalence rate of 15 % for any disorder [3]. Anxiety disorders are the most common disorders, followed by behavior (conduct disorders and attention deficit hyperactivity disorder), mood and substance use disorders [2, 7, 14]. Some studies additionally examined risk, protective and other associated factors. In general, older adolescents present higher prevalence rates and more problems than younger ones [4, 7, 13]. Boys report more behavioral and emotional problems than girls [4]. Behavior disorders and substance use disorders are more common in boys whereas girls more often suffer from eating disorders and psychosomatic disorders. No difference is found for psychotic disorders. Prevalence rates of anxiety and mood disorders are inconsistent. They seem to be more common in boys during childhood and school age and in girls during adolescence and young adulthood [2]. Children with mental health problems furthermore show impaired quality of life compared to healthy controls [7]. There are variations in the findings of prevalence rates in epidemiologic studies due to methodological differences [14], like different definitions, criteria, methods, age groups and sources of information [13]. Still, there is strong evidence for behavioral and emotional problems and mental disorders in a large amount of adolescents.
The Mental Health in Austrian Teenagers (MHAT)-Study: preliminary results from a pilot study
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original article Objectives The Mental Health in Austrian Teenagers (MHAT) – Study was initiated to collect epidemiological data on mental health, emotional and behavioral problems, psychiatric disorders, related risk and protective factors and quality of life in a representative sample of adolescents between 10 and 18 years in Austria for the first time. A two-step design was chosen for the MHAT-Study. Phase 1 (screening phase) consists of a questionnaire assessing emotional and behavioral problems, social and demographic correlates, risk and protective factors and quality of life. In phase 2 (interview phase), positive screened adolescents as well as a sample of negative screened participants are further contacted for a standardized clinical interview in order to obtain DSM-5 diagnosis. A pilot study was conducted in 2013. The aims of the present pilot study were a) to evaluate the feasibility and acceptability of the screening phase b) to pre-estimate prevalence rates in order to plan necessary resources for the interview phase of the MHAT study and c) to estimate possible non-responder bias.
Methods For this pilot study, phase 1 (screening phase) was conducted with a small sample of Austrian adolescents. The MHAT-Study is approved by the ethics committee of the Medical University of Vienna and the Austrian Federal Ministry of Education and Women’s Affairs.
Sampling, recruitment and procedure Adolescents between 10 and 18 were recruited from five secondary schools in Lower Austria and Burgenland. Four age groups were included in the sample: 5th graders (aged 10–11, resp.), 7th graders (aged 12–13, resp.), 9th graders (aged 14–15, resp.) and 11th graders (ages 16–17, resp.). Information sheets about background and procedure of the study, as well as a sample questionnaire was sent to the schools’ administration office. Adolescents and parents concerned were given a description of the study. Written informed consent was obtained from adolescents and parents. Screening questionnaires were administered either by paper-pencil administration or by a corresponding online questionnaire. The assessment was designed for the duration of one lesson (approximately 50 min). Class teachers were asked to administer the survey autonomously. Therefore, teachers were given detailed instructions for the procedure, technical instructions for the online questionnaire as well as predefined answers to possible “FAQs (Frequently Asked Questions)”. A study member was present in the classroom during data collection and acted as non-participating observer. The study member documented the duration of the assess-
ment, occurring problems and difficulties, as well as all content-related questions by the participants. During the assessment, teachers were also asked to fill in a short teacher’s questionnaire to collect basic demographic data and data on observed behavioral problems of all pupils in their class as well as their hypotheses on reasons for non-participation serving as a basis for NonResponder Analysis and estimation of possible nonresponder bias. A Non-Responder Analysis is essential for epidemiologic studies [15] in order to evaluate the representativeness of the sample. Teachers gave basic information concerning survey participation, sex and class repetition and rated all pupils in respect of school absenteeism, willingness to make an effort during lessons, ability to concentrate during lessons, social integration in class, passivity, disciplinary problems and making contact to parents or teacher conference because of behavioral problems. Subsequent to the assessment, a short interview with the class teacher was conducted. They were asked if they felt well informed about the study and if they would need any additional information or help for the next time they would have to moderate this assessment. Data obtained by documentation of survey process (e.g. duration of data collection) as well as qualitative data from the teacher’s interview served as the basis for the evaluation of feasibility and acceptability of the MHAT screening phase and is part of the process evaluation of the MHAT-Study.
Instruments The MHAT questionnaire consists of several instruments. Mental health data were assessed using the Youth Self-Report (YSR [5], German version: ArbeitsgruppeDeutsche-Child-Behavior-Checklist [16, 17]). The YSR consists of 103 problem items measuring behavioral and emotional problems in a six-month time period. The items are answered using a three-point scale (0 = not true, 1 = somewhat or sometimes true, 2 = very true or often true) and sum up to three broad-band scales, a total problem score, internalizing problems, externalizing problems, as well as eight syndrome scales: withdrawn, somatic complaints, anxious/depressed, social problems, thought problems, attention problems, delinquent behavior and aggressive behavior. The broad-band scales show good internal consistency (Cronbach’s alpha > 0.86). For the syndrome scales, Cronbach’s alphas of 0.56–0.86 were reported. T-Scores are calculated using German norm data (1991) according to the manual, whereby higher scores indicate more problems. As the YSR is lacking items concerning eating disorders, the SCOFF questionnaire was used to determine signs of disturbed eating habits [18] (German version [19]). The SCOFF is a very brief questionnaire, consisting of five items to be answered with yes or no (Do you ever make yourself Sick because you feel uncomfortably full? Do you worry you have lost Control over how much you eat? Have you recently lost more than One stone (6 kg)
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in a three month period? Do you believe yourself to be Fat when others say you are too thin? Would you say that Food dominates your life?). Item ratings (yes = 1, no = 0) can be summed up to a total score (0–5) indicating a risk for an eating disorder at a score of two or more positive answers. The SCOFF proved to be 100 % sensitive with a false positive rate of 12.5 % [20]. In a German study, one out of five adolescents aged 11–17 reported signs of disordered eating [19]. For the MHAT-Study, we propose alternative cut-off criteria that are based on the clinical relevance of the SCOFF items. As judged by clinical psychologists working in the field of eating disorders at the child and adolescent psychiatry of the General Hospital of Vienna, vomiting (item 1) and weight reduction (item 3) are a stronger indication of an eating disorder than the other items. Therefore, we propose that additionally to the criteria from the authors (score ≥ 2), at least one of these two items has to be confirmed by the adolescents. To measure the socioeconomic status, the Family Affluence Scale (FAS [21]) was used. The FAS was developed within the WHO-Health Behaviour in School-aged Children (HBSC) survey and consists of four items; higher scores indicating a higher level of family affluence. The FAS has good internal consistency. Three groups can be described: low family affluence, moderate family affluence and high family affluence. The KIDSCREEN [22] was used to assess quality of life in children and adolescents aged 8–18 within the last week. The following dimensions of the KIDSCREEN-52 version (KS-52) and the KIDSCREEN-27 version (KS-27) are selected for the purpose of the MHAT-Study: Self-Perception (KS-52), Parent-Relation and Home Life (KS-52), Social Support and Peers (KS-27), School Environment (KS-27) and Bullying (KS-52). Additional six items from the KIDSCREEN questionnaire were included enabling the calculation of the KIDSCREEN-10 score. Items are rated on a five-point scale. Higher scores indicate higher quality of life. The KIDSCREEN demonstrates good internal consistency, with a Cronbach’s alpha of 0.77 to 0.89, 0.80 to 0.84 and 0.82 for the three versions (KIDSCREEN-52, KIDSCREEN-27 and KIDSCREEN-10). An own KIDSCREEN-questionnaire was composed by single scales of the original KS-52 and KS-27 versions. Sociodemographic data (sex, age, migration background, family and residential environment, school grade, type of school) were collected as well as several factors known as risk and protective factors for mental health (including e.g. family-structure, physical and mental diseases of the participant and near relatives, lifetime-occurrence of traumatic events [23, 24]).
lated in order to check if respondents and non-respondents equally distribute to the categories of the other variables depicted in Table 2. Item ratings of the YSR were summed up per scale and transferred into T-scores. A cut-off score of T > 70 for the syndrome scales and T > 63 for the broad-band scales was used to define clinically relevant cases, as suggested in the manual. Participants in this study are defined as high-riskcases with a score above the cut-off for clinical relevance in at least one YSR syndrome scale or a SCOFF score of two or more positive answers including at least one of the following: “Do you ever make yourself sick because you feel uncomfortably full?”, “Have you recently lost more than one stone (6 kg) in a 3 month period?” A 2 × 4 ANOVA is conducted to examine the impact of sex and school grade on YSR sum scores. KIDSCREEN item rating were recoded if necessary and summed up for each dimension. Pearson correlation coefficients were calculated to examine the association between behavioral and emotional problems as obtained by the YSR total problem score and health-related quality of life as obtained by the KIDSCREEN scales.
Results Sample Figure 1 shows the flow diagram of the recruitment process. From the 21 schools invited for participation, five schools agreed to participate. These schools provided 27 classes for inclusion in the study: 8 classes of 5th graders (aged 10–11, resp.), 7 classes of 7th graders (aged 12–13, resp.), 5 classes of 9th graders (aged 14–15, resp.),
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Statistical analyses Data from the teacher’s questionnaire and the MHAT questionnaire were entered into and analyzed with IBM Statistics 22.0 software. 2 × 2 and 2 × 3 contingency tables with study participation (yes vs. no) and other variables captured with the teacher’s questionnaire were calcu-
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Fig.1 Flow diagram of participants
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Table 1 Adolescents’ demographic information n
%
408
100
Male
170
41.7
Female
238
58.3
5th
134
32.8
7
Total Sex
School grade 106
26.0
9th
84
20.6
11th
84
20.6
th
Migration background No migration background
365
89.5
1st generationa
17
4.2
2nd generationb
26
6.4
Low
4
1.0
Moderate
71
17.4
High
327
80.1
Missing
6
1.5
Yes
324
79.4
No
84
20.6
No parent
6
1.5
One parent
78
19.1
Both parents
321
78.7
Missing
3
0.7
No
322
78.9
Yes
82
20.1
Missing
4
1.0
FAS category
c
Completeness of familiyd
Acceptability and feasibility All of the five schools had a computer lab with a sufficient number of computers. Due to occupancy of computer lab, concurrent data collection in several classes and technical problems, a quite small number of participants completed the online version (n = 81; 19.9 %). The overall duration of data collection from the beginning of the lesson to the completion of the last questionnaire ranged from 37 to 82 min with a median of 46 min. The duration from the beginning of the lesson to the beginning of completing the questionnaire (including other activities before starting and reading the instruction) was quite long (median of 13 min, minimum 7 min; maximum 22 min). The median net duration for completing the questionnaire as automatically recorded by the online questionnaire was 24.6 min (minimum 13.5 min; maximum 44.6 min). Twenty-two out of 23 teachers agreed that they would be able to conduct data collection without any help of a study member. Some aspects were mentioned as improvements for the main study: better information transfer from administration office to teachers (n = 2), more time for obtaining informed consent (n = 2), extension of “FAQs” (n = 2), further information concerning the procedure (n = 2) and adaptation for 5th graders (n = 1).
Occupation of parents
Diagnosed physical illness
Own birth-place in Austria and birth-place of both parents in foreign country b Own birth-place and birth-place of both parents in foreign country c Family affluence scale d Adolescents living with both biological parents a
6 classes of 11th graders (aged 16–17, resp.) and 1 class dropped out. Altogether, 590 adolescents were recruited and asked to give informed consent for the study. 408 adolescents and their parents (69.2 %) agreed to participate. Of the 182 non-responders (30.8 %), 93 (51 %) had no informed consent, 46 (25 %) were sick, 4 (2 %) broke off the assessment, 16 (9 %) were absent due to other reasons like sport events and 23 (13 %) were absent due to unknown reasons. Sociodemographic information of participants is provided in Table 1. There were more female adolescents and more 5th graders participating in the study. Most of the participants reported no migration background, high socioeconomic status and occupation of both parents.
Mental health problems Prevalence rates of behavioral and emotional problems obtained by the Youth Self-Report and the SCOFF-questionnaire are depicted in Table 2. 15.9 % of the screened adolescents showed signs of mental health problems using the Youth Self-Report total problem score. Internalizing behavioral problems appear more frequent (18.5 %) than externalizing problems (5.7 %). Regarding the YSR second-order scales, withdrawn problems and somatic complaints were most prevalent, in contrast to aggressive behavior which appeared as the least prevalent problem area. 25 % [CI 95 %: 20.7–29.3 %] of the participants scored in at least one of the first or second order problem scales. Differences between sex and school grades according to YSR problem scores as analyzed by a 2 × 4 ANOVA are depicted in Table 3. A main effect of sex was observed for the total problem score, internalizing problems, withdrawn behavior, somatic complaints and anxious/ depressed mood with larger problem scores for girls compared to boys. A significant main effect of school grade was observed for externalizing problems, thought problems, attention problems and delinquent behaviors. Due to significant interaction effects, the interpretation regarding the impact of the school grade is not clear in some cases. However, there is a tendency for larger problem scores for participants in higher school grades. Significant sex*school grade interaction effects occurred in seven of eleven YSR scales. For the significant YSR scales, mean problem scores constantly increased with higher
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Table 2 Percentage of at-risk cases according to YSR scales and SCOFF and 95 % CIs Scale
5th grade
7th grade
9th grade
11th grade
Overall
YSR Total
12.3 [6.4; 18.2]
14.6 [7.5; 21.7]
13.1 [5.8; 20.4]
25.6 [16.1; 35.1]
15.9 [12.2; 19.6]
YSR Int
14.8 [8.5; 21.1]
16.7 [9.2; 24.2]
15.5 [7.7; 23.3]
29.3 [19.4; 39.2]
18.5 [14.6; 22.4]
YSR Ext
2.5 [0; 5.3]
8.3 [2.8; 13.8]
4.8 [0.2; 9.4]
8.5 [2.4; 14.6]
5.7 [3.4; 8.0]
YSR WD
4.1 [0.6; 7.6]
3.1 [0; 6.6]
7.1 [1.6; 12.6]
7.3 [1.6; 13.0]
5.2 [3.0; 7.4]
YSR SC
4.9 [1.1; 8.7]
4.2 [0.2; 8.2]
3.6 [0; 7.6]
6.1 [0.9; 11.3]
4.7 [2.6; 6.8]
YSR Anx/Dep
4.1 [0.6; 7.6]
2.1 [0; 5.0]
3.6 [0; 7.6]
3.7 [0; 7.8]
3.4 [1.6; 5.2]
YSR SP
1.6 [0; 3.8]
4.2 [0.2; 8.2]
1.2 [0; 3.5]
2.4 [0; 5.7]
2.3 [0.8; 3.8]
YSR TP
2.5 [0; 5.3]
2.1 [0; 5.0]
2.4 [0; 5.7]
4.9 [0.2; 9.6]
2.9 [1.2; 4.6]
YSR AT
0.0
5.2 [0.7; 9.7]
2.4 [0; 5.7]
3.7 [0; 7.8]
2.6 [1.0; 4.2]
YSR Del
0.8 [0; 2.4]
2.1 [0; 5.0]
1.2 [0; 3.5]
6.1 [0.9; 11.3]
2.3 [0.8; 3.8]
YSR Agg
0.8 [0; 2.4]
2.1 [0; 5.0]
0.0
1.2 [0; 3.6]
1.0 [0; 2.0]
SCOFFa
17.2 [10.8; 23.6]
24.5 [16.3; 32.7]
16.7 [8.7; 24.7]
26.2 [16.7; 35.7]
20.8 [16.9; 24.7]
SCOFFb
8.2 [3.5; 12.9]
6.6 [1.9; 11.3]
4.8 [0.2; 9.4]
6.0 [0.9; 11.1]
6.6 [4.2; 9.0]
16.8 [10.2; 23.4]
18.6 [10.8; 26.4]
14.3 [6.8; 21.8]
26.8 [17.2; 36.4]
18.8 [14.9; 22.7]
YSR and SCOFF
c
YSR Youth self-report, Int Internalizing, Ext Externalizing, WD Withdrawn, SC Somatic complaints, Anx/Dep Anxious/depressed, SP Social problems, TP Thought problems, AT Attention problems, Del Delinquent behavior, Agg Aggressive behavior a SCOFF Score ≥ 2 b SCOFF Score ≥ 2 and at least one of the following SCOFF items is marked as applicable: “Do you make yourself sick because you feel uncomfortably full?”, “Have you recently lost more than one stone (6 kg) in a 3month period?” c Above cut-off score of clinical relevance in at least one YSR syndrome scale OR SCOFF Score ≥ 2 and at least one of the following SCOFF items is marked as applicable: “Do you make yourself sick because you feel uncomfortably full?”, “Have you recently lost more than one stone (6 kg) in a 3month period?”
school grades for female participants. For males, the picture is not as clear as for females. Whereas mean scores remained almost stable for the total problem scale, mean scores decreased from low to high school grades for internalizing problems, somatic complaints and social problems. No clear association between school grade and problem scores could have been observed in males for externalizing problems including delinquent behavior and aggressive behavior. In the SCOFF-questionnaire, 20.8 % of the screened adolescents scored above the clinical cut-off applying the criteria (score ≥ 2) proposed by the authors. Since the SCOFF is known for its very high sensitivity leading to a high rate of positive screened adolescents, we propose that additionally to the criteria from the authors (score ≥ 2), at least one of the two clinically relevant items (vomiting, weight reduction) has to be confirmed by the adolescents. Applying these new criteria, the percentage of positive screened adolescents decreased to 6.6 %. High-risk cases for mental disorders were defined as scoring above the clinical cut-off in at least one of the YSR syndrome scales or the SCOFF applying the new criteria as described above. Following this definition, the overall prevalence of mental health problems was 18.9 % [CI 95 %: 14.9–22.7]. YSR total problem scores were significantly correlated with health related quality of life measures as derived by the KIDSCREEN questionnaire (KIDSCREEN-10: r = − .628; Self Perception: r = − .572; Parent Relation and Home Life: r = − .484; Bullying: r = − .356; Social Support and Peers: − .298; School Environment: − .512, all p-values
The Mental Health in Austrian Teenagers (MHAT)Study: preliminary results from a pilot study Julia Philipp · Michael Zeiler · Karin Waldherr · Martina Nitsch · Wolfgang Dür · Andreas Karwautz · Gudrun Wagner
Received: 7 November 2014 / Accepted: 18 November 2014 / Published online: 28 November 2014 © Springer-Verlag Wien 2014
Summary Background No epidemiological data on prevalence rates of mental disorders based on a representative sample are available for Austrian adolescents up to now. However, the knowledge of psychiatric disorders, related risk and protective factors is of great significance for treatment and prevention. The purpose of the MHATStudy (Mental Health in Austrian Teenagers), the first epidemiological study on mental health in Austria, is to obtain prevalence rates of mental disorders and to examine risk factors, protective factors and quality of life in a representative sample of adolescents aged 10–18. Aims of this pilot study were to evaluate the feasibility and acceptability of the screening instruments, pre-estimate the frequency of mental health problems and estimate possible non-responder bias. Methods Twenty-one schools in eastern Austria were asked to participate. Data on mental health problems were derived from self-rating questionnaires containing standardized screening measures (Youth Self-Report, measuring emotional and behavioral problems and the
Prof. Dr. A. Karwautz () · Dr. J. Philipp · Mag. Dr. G. Wagner Department of Child and Adolescent Psychiatry, Medical University of Vienna, Währinger Gürtel 18-20, 1090 Vienna, Austria e-mail: [email protected] Dr. J. Philipp e-mail: [email protected] Mag. M. Zeiler · Mag. Dr. M. Nitsch · Priv. Doz. Dr. W. Dür Ludwig Boltzmann Institute Health Promotion Research, Vienna, Austria Mag. Dr. K. Waldherr Ludwig Boltzmann Institute Health Promotion Research, Ferdinand Porsche Distance University of Applied Sciences (FernFH), Vienna, Austria
SCOFF, indicating eating problems. Quality of life as well as related risk and protective factors were also obtained. Results Four hundred and eight adolescents of five schools were recruited. The prevalence of mental health problems was 18.9 % [CI 95 %: 14.9–22.7]. Moreover, emotional and behavioral problems were highly correlated with quality of life measures. A Non-Responder Analysis indicated that non-responders (16.7 %) differ from responders with regard of school related problems. Conclusions The results demonstrate that mental health problems affect approximately one fifth of the adolescents. A Non-Responder Analysis suggests that the prevalence of behavioral and emotional problems is underestimated. Keywords Mental health · Psychiatric disorders · Epidemiology · Adolescence
Die Mental Health in Austrian Teenagers (MHAT)Studie: erste Ergebnisse aus einer Pilotstudie Zusammenfassung Grundlagen Bisher sind keine epidemiologischen Daten zu Prävalenzraten für psychische Störungen für österreichische Jugendliche, basierend auf einer repräsentativen Stichprobe, verfügbar. Das Wissen über psychiatrische Störungen sowie Risiko- und Schutzfaktoren ist jedoch essentiell für Therapie und Prävention. Im Rahmen der MHAT-Studie (Mental Health in Austrian Teenagers, Psychische Gesundheit bei österreichischen Jugendlichen), der ersten epidemiologischen Studie zur psychischen Gesundheit in Österreich, sollen Prävalenzraten psychischer Störungen bei einer repräsentativen Stichprobe von Jugendlichen zwischen 10 und 18 Jahren erhoben und Risiko- und Schutzfaktoren sowie Lebensqualität untersucht werden. Zweck der Pilotstudie war die Evaluation der Durchführbarkeit und Akzeptanz der Scree-
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ning-Phase, eine Häufigkeitsschätzung von Verhaltensauffälligkeiten und emotionalen Problemen sowie die Abschätzung eines möglichen Non-Responder-Bias. Methodik 21 Schulen im Osten Österreichs wurden eingeladen, an der Studie teilzunehmen. Daten zur psychischen Gesundheit wurden im Rahmen eines Screenings mithilfe standardisierter Selbstbeurteilungsbögen wie dem Youth Self-Report erhoben, der emotionale und Verhaltensprobleme erhebt, und dem SCOFF, der Hinweise für Essstörungen liefert. Lebensqualität und Risiko- und Schutzfaktoren wurden ebenfalls erhoben. Ergebnisse 408 Jugendliche an 5 Schulen wurden in die Studie eingeschlossen. Die Prävalenzrate für psychische Probleme lag bei 18,9 % [CI 95 %:14,9–22,7]. Weiters korrelierten emotionale und Verhaltensauffälligkeiten hoch mit gesundheitsbezogener Lebensqualität. Die Non-Responder Analyse weist darauf hin, dass sich NonResponder (16.7 %) von Respondern hinsichtlich schulischer Probleme unterscheiden. Schlussfolgerungen Die Ergebnisse weisen darauf hin, dass jeder fünfte Jugendlichen von einem psychischen Problem betroffen ist. Die Non-Responder Analyse deutet auf eine Unterschätzung der Prävalenzraten hin. Schlüsselwörter Psychische Gesundheit · Psychische Störungen · Epidemiologie · Jugendliche
Introduction Mental disorders tend to develop during adolescence [1, 2], show high comorbidity rates (45 % [1]) and tend to persist into adulthood [3]. Therefore, research should particularly focus on adolescents’ mental health. The knowledge about prevalence rates of psychiatric disorders in childhood and adolescence as well as related risk and protective factors is essential for the development of suitable prevention strategies and treatment approaches [2]. However, no epidemiological data on prevalence rates of mental disorders are available for adolescents in Austria. Due to this lack of epidemiological data in Austria, international studies and results from other European countries served as an overview of mental health and well-being in teenagers so far. Using only screening questionnaires, Rescorla et al. [4] investigated rates of behavioral and emotional problems and compared self-reports from adolescents aged 12–18 (Youth Self-Report [5]) with parental ratings (Child Behavior Checklist [6]) from 25 societies. With respect to the total problem score, parents perceived 21.4 % of their children to have problems, whereas 34.6 % of the children themselves reported problems. In Germany, the BELLA study was established to assess mental health problems in teenagers [7, 8]. Problems were assessed by parents, using the Strength and Difficulties Questionnaire (SDQ [9]). 21.9 % of children and adolescents between 7 and 17 years showed signs of
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mental health problems. 14.5 % reported mental health problems associated with severe impairment [10]. The Great Smoky Mountains Study [11] assessed psychiatric disorders in children aged 9, 11 and 13 with a 3-year and 6-year follow up. The 3-month prevalence rate of all examined disorders was 13.3 %. However, 36.7 % of the children had at least one psychiatric disorder during the study period. Merikangas et al. [12] interviewed 10123 adolescents aged 13 to 18 years within the National Comorbidity Survey Replication—Adolescent Supplement (NCS-A) in the US. Lifetime prevalence for any disorder was 49.5 %. When including only adolescents with severe impairment, prevalence rates decrease to 22.2 %. In the last decades, some reviews were published presenting prevalence rates of mental disorders. Robert, Attkisson and Rosenblatt [13] identified 52 studies conducted in over 20 countries published between 1963 and 1996 estimating the prevalence of psychiatric disorder. Prevalence estimates ranged from 1 to 51 % with a mean prevalence of 15.8 %. Ihle and Esser [2] as well compared 19 results from 9 countries between 1970 and 2000, presenting a mean prevalence of 18 % (6.8–37.4 %). A review concentrating on results from more recent studies in Great Britain and the United States between 2000 and 2007 including children and adolescents between 5 and 17 years summarized that one person in four suffered from a psychiatric disorder during the past year and even one out of three throughout the whole life [14]. A review including 29 studies in Germany between 1949 and 2003 presented an overall prevalence rate of 17.2 % for emotional and behavioral disorders [15]. A very recent review presented a prevalence rate of 15 % for any disorder [3]. Anxiety disorders are the most common disorders, followed by behavior (conduct disorders and attention deficit hyperactivity disorder), mood and substance use disorders [2, 7, 14]. Some studies additionally examined risk, protective and other associated factors. In general, older adolescents present higher prevalence rates and more problems than younger ones [4, 7, 13]. Boys report more behavioral and emotional problems than girls [4]. Behavior disorders and substance use disorders are more common in boys whereas girls more often suffer from eating disorders and psychosomatic disorders. No difference is found for psychotic disorders. Prevalence rates of anxiety and mood disorders are inconsistent. They seem to be more common in boys during childhood and school age and in girls during adolescence and young adulthood [2]. Children with mental health problems furthermore show impaired quality of life compared to healthy controls [7]. There are variations in the findings of prevalence rates in epidemiologic studies due to methodological differences [14], like different definitions, criteria, methods, age groups and sources of information [13]. Still, there is strong evidence for behavioral and emotional problems and mental disorders in a large amount of adolescents.
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original article Objectives The Mental Health in Austrian Teenagers (MHAT) – Study was initiated to collect epidemiological data on mental health, emotional and behavioral problems, psychiatric disorders, related risk and protective factors and quality of life in a representative sample of adolescents between 10 and 18 years in Austria for the first time. A two-step design was chosen for the MHAT-Study. Phase 1 (screening phase) consists of a questionnaire assessing emotional and behavioral problems, social and demographic correlates, risk and protective factors and quality of life. In phase 2 (interview phase), positive screened adolescents as well as a sample of negative screened participants are further contacted for a standardized clinical interview in order to obtain DSM-5 diagnosis. A pilot study was conducted in 2013. The aims of the present pilot study were a) to evaluate the feasibility and acceptability of the screening phase b) to pre-estimate prevalence rates in order to plan necessary resources for the interview phase of the MHAT study and c) to estimate possible non-responder bias.
Methods For this pilot study, phase 1 (screening phase) was conducted with a small sample of Austrian adolescents. The MHAT-Study is approved by the ethics committee of the Medical University of Vienna and the Austrian Federal Ministry of Education and Women’s Affairs.
Sampling, recruitment and procedure Adolescents between 10 and 18 were recruited from five secondary schools in Lower Austria and Burgenland. Four age groups were included in the sample: 5th graders (aged 10–11, resp.), 7th graders (aged 12–13, resp.), 9th graders (aged 14–15, resp.) and 11th graders (ages 16–17, resp.). Information sheets about background and procedure of the study, as well as a sample questionnaire was sent to the schools’ administration office. Adolescents and parents concerned were given a description of the study. Written informed consent was obtained from adolescents and parents. Screening questionnaires were administered either by paper-pencil administration or by a corresponding online questionnaire. The assessment was designed for the duration of one lesson (approximately 50 min). Class teachers were asked to administer the survey autonomously. Therefore, teachers were given detailed instructions for the procedure, technical instructions for the online questionnaire as well as predefined answers to possible “FAQs (Frequently Asked Questions)”. A study member was present in the classroom during data collection and acted as non-participating observer. The study member documented the duration of the assess-
ment, occurring problems and difficulties, as well as all content-related questions by the participants. During the assessment, teachers were also asked to fill in a short teacher’s questionnaire to collect basic demographic data and data on observed behavioral problems of all pupils in their class as well as their hypotheses on reasons for non-participation serving as a basis for NonResponder Analysis and estimation of possible nonresponder bias. A Non-Responder Analysis is essential for epidemiologic studies [15] in order to evaluate the representativeness of the sample. Teachers gave basic information concerning survey participation, sex and class repetition and rated all pupils in respect of school absenteeism, willingness to make an effort during lessons, ability to concentrate during lessons, social integration in class, passivity, disciplinary problems and making contact to parents or teacher conference because of behavioral problems. Subsequent to the assessment, a short interview with the class teacher was conducted. They were asked if they felt well informed about the study and if they would need any additional information or help for the next time they would have to moderate this assessment. Data obtained by documentation of survey process (e.g. duration of data collection) as well as qualitative data from the teacher’s interview served as the basis for the evaluation of feasibility and acceptability of the MHAT screening phase and is part of the process evaluation of the MHAT-Study.
Instruments The MHAT questionnaire consists of several instruments. Mental health data were assessed using the Youth Self-Report (YSR [5], German version: ArbeitsgruppeDeutsche-Child-Behavior-Checklist [16, 17]). The YSR consists of 103 problem items measuring behavioral and emotional problems in a six-month time period. The items are answered using a three-point scale (0 = not true, 1 = somewhat or sometimes true, 2 = very true or often true) and sum up to three broad-band scales, a total problem score, internalizing problems, externalizing problems, as well as eight syndrome scales: withdrawn, somatic complaints, anxious/depressed, social problems, thought problems, attention problems, delinquent behavior and aggressive behavior. The broad-band scales show good internal consistency (Cronbach’s alpha > 0.86). For the syndrome scales, Cronbach’s alphas of 0.56–0.86 were reported. T-Scores are calculated using German norm data (1991) according to the manual, whereby higher scores indicate more problems. As the YSR is lacking items concerning eating disorders, the SCOFF questionnaire was used to determine signs of disturbed eating habits [18] (German version [19]). The SCOFF is a very brief questionnaire, consisting of five items to be answered with yes or no (Do you ever make yourself Sick because you feel uncomfortably full? Do you worry you have lost Control over how much you eat? Have you recently lost more than One stone (6 kg)
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in a three month period? Do you believe yourself to be Fat when others say you are too thin? Would you say that Food dominates your life?). Item ratings (yes = 1, no = 0) can be summed up to a total score (0–5) indicating a risk for an eating disorder at a score of two or more positive answers. The SCOFF proved to be 100 % sensitive with a false positive rate of 12.5 % [20]. In a German study, one out of five adolescents aged 11–17 reported signs of disordered eating [19]. For the MHAT-Study, we propose alternative cut-off criteria that are based on the clinical relevance of the SCOFF items. As judged by clinical psychologists working in the field of eating disorders at the child and adolescent psychiatry of the General Hospital of Vienna, vomiting (item 1) and weight reduction (item 3) are a stronger indication of an eating disorder than the other items. Therefore, we propose that additionally to the criteria from the authors (score ≥ 2), at least one of these two items has to be confirmed by the adolescents. To measure the socioeconomic status, the Family Affluence Scale (FAS [21]) was used. The FAS was developed within the WHO-Health Behaviour in School-aged Children (HBSC) survey and consists of four items; higher scores indicating a higher level of family affluence. The FAS has good internal consistency. Three groups can be described: low family affluence, moderate family affluence and high family affluence. The KIDSCREEN [22] was used to assess quality of life in children and adolescents aged 8–18 within the last week. The following dimensions of the KIDSCREEN-52 version (KS-52) and the KIDSCREEN-27 version (KS-27) are selected for the purpose of the MHAT-Study: Self-Perception (KS-52), Parent-Relation and Home Life (KS-52), Social Support and Peers (KS-27), School Environment (KS-27) and Bullying (KS-52). Additional six items from the KIDSCREEN questionnaire were included enabling the calculation of the KIDSCREEN-10 score. Items are rated on a five-point scale. Higher scores indicate higher quality of life. The KIDSCREEN demonstrates good internal consistency, with a Cronbach’s alpha of 0.77 to 0.89, 0.80 to 0.84 and 0.82 for the three versions (KIDSCREEN-52, KIDSCREEN-27 and KIDSCREEN-10). An own KIDSCREEN-questionnaire was composed by single scales of the original KS-52 and KS-27 versions. Sociodemographic data (sex, age, migration background, family and residential environment, school grade, type of school) were collected as well as several factors known as risk and protective factors for mental health (including e.g. family-structure, physical and mental diseases of the participant and near relatives, lifetime-occurrence of traumatic events [23, 24]).
lated in order to check if respondents and non-respondents equally distribute to the categories of the other variables depicted in Table 2. Item ratings of the YSR were summed up per scale and transferred into T-scores. A cut-off score of T > 70 for the syndrome scales and T > 63 for the broad-band scales was used to define clinically relevant cases, as suggested in the manual. Participants in this study are defined as high-riskcases with a score above the cut-off for clinical relevance in at least one YSR syndrome scale or a SCOFF score of two or more positive answers including at least one of the following: “Do you ever make yourself sick because you feel uncomfortably full?”, “Have you recently lost more than one stone (6 kg) in a 3 month period?” A 2 × 4 ANOVA is conducted to examine the impact of sex and school grade on YSR sum scores. KIDSCREEN item rating were recoded if necessary and summed up for each dimension. Pearson correlation coefficients were calculated to examine the association between behavioral and emotional problems as obtained by the YSR total problem score and health-related quality of life as obtained by the KIDSCREEN scales.
Results Sample Figure 1 shows the flow diagram of the recruitment process. From the 21 schools invited for participation, five schools agreed to participate. These schools provided 27 classes for inclusion in the study: 8 classes of 5th graders (aged 10–11, resp.), 7 classes of 7th graders (aged 12–13, resp.), 5 classes of 9th graders (aged 14–15, resp.),
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Statistical analyses Data from the teacher’s questionnaire and the MHAT questionnaire were entered into and analyzed with IBM Statistics 22.0 software. 2 × 2 and 2 × 3 contingency tables with study participation (yes vs. no) and other variables captured with the teacher’s questionnaire were calcu-
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Fig.1 Flow diagram of participants
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Table 1 Adolescents’ demographic information n
%
408
100
Male
170
41.7
Female
238
58.3
5th
134
32.8
7
Total Sex
School grade 106
26.0
9th
84
20.6
11th
84
20.6
th
Migration background No migration background
365
89.5
1st generationa
17
4.2
2nd generationb
26
6.4
Low
4
1.0
Moderate
71
17.4
High
327
80.1
Missing
6
1.5
Yes
324
79.4
No
84
20.6
No parent
6
1.5
One parent
78
19.1
Both parents
321
78.7
Missing
3
0.7
No
322
78.9
Yes
82
20.1
Missing
4
1.0
FAS category
c
Completeness of familiyd
Acceptability and feasibility All of the five schools had a computer lab with a sufficient number of computers. Due to occupancy of computer lab, concurrent data collection in several classes and technical problems, a quite small number of participants completed the online version (n = 81; 19.9 %). The overall duration of data collection from the beginning of the lesson to the completion of the last questionnaire ranged from 37 to 82 min with a median of 46 min. The duration from the beginning of the lesson to the beginning of completing the questionnaire (including other activities before starting and reading the instruction) was quite long (median of 13 min, minimum 7 min; maximum 22 min). The median net duration for completing the questionnaire as automatically recorded by the online questionnaire was 24.6 min (minimum 13.5 min; maximum 44.6 min). Twenty-two out of 23 teachers agreed that they would be able to conduct data collection without any help of a study member. Some aspects were mentioned as improvements for the main study: better information transfer from administration office to teachers (n = 2), more time for obtaining informed consent (n = 2), extension of “FAQs” (n = 2), further information concerning the procedure (n = 2) and adaptation for 5th graders (n = 1).
Occupation of parents
Diagnosed physical illness
Own birth-place in Austria and birth-place of both parents in foreign country b Own birth-place and birth-place of both parents in foreign country c Family affluence scale d Adolescents living with both biological parents a
6 classes of 11th graders (aged 16–17, resp.) and 1 class dropped out. Altogether, 590 adolescents were recruited and asked to give informed consent for the study. 408 adolescents and their parents (69.2 %) agreed to participate. Of the 182 non-responders (30.8 %), 93 (51 %) had no informed consent, 46 (25 %) were sick, 4 (2 %) broke off the assessment, 16 (9 %) were absent due to other reasons like sport events and 23 (13 %) were absent due to unknown reasons. Sociodemographic information of participants is provided in Table 1. There were more female adolescents and more 5th graders participating in the study. Most of the participants reported no migration background, high socioeconomic status and occupation of both parents.
Mental health problems Prevalence rates of behavioral and emotional problems obtained by the Youth Self-Report and the SCOFF-questionnaire are depicted in Table 2. 15.9 % of the screened adolescents showed signs of mental health problems using the Youth Self-Report total problem score. Internalizing behavioral problems appear more frequent (18.5 %) than externalizing problems (5.7 %). Regarding the YSR second-order scales, withdrawn problems and somatic complaints were most prevalent, in contrast to aggressive behavior which appeared as the least prevalent problem area. 25 % [CI 95 %: 20.7–29.3 %] of the participants scored in at least one of the first or second order problem scales. Differences between sex and school grades according to YSR problem scores as analyzed by a 2 × 4 ANOVA are depicted in Table 3. A main effect of sex was observed for the total problem score, internalizing problems, withdrawn behavior, somatic complaints and anxious/ depressed mood with larger problem scores for girls compared to boys. A significant main effect of school grade was observed for externalizing problems, thought problems, attention problems and delinquent behaviors. Due to significant interaction effects, the interpretation regarding the impact of the school grade is not clear in some cases. However, there is a tendency for larger problem scores for participants in higher school grades. Significant sex*school grade interaction effects occurred in seven of eleven YSR scales. For the significant YSR scales, mean problem scores constantly increased with higher
202 The Mental Health in Austrian Teenagers (MHAT)-Study: preliminary results from a pilot study
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Table 2 Percentage of at-risk cases according to YSR scales and SCOFF and 95 % CIs Scale
5th grade
7th grade
9th grade
11th grade
Overall
YSR Total
12.3 [6.4; 18.2]
14.6 [7.5; 21.7]
13.1 [5.8; 20.4]
25.6 [16.1; 35.1]
15.9 [12.2; 19.6]
YSR Int
14.8 [8.5; 21.1]
16.7 [9.2; 24.2]
15.5 [7.7; 23.3]
29.3 [19.4; 39.2]
18.5 [14.6; 22.4]
YSR Ext
2.5 [0; 5.3]
8.3 [2.8; 13.8]
4.8 [0.2; 9.4]
8.5 [2.4; 14.6]
5.7 [3.4; 8.0]
YSR WD
4.1 [0.6; 7.6]
3.1 [0; 6.6]
7.1 [1.6; 12.6]
7.3 [1.6; 13.0]
5.2 [3.0; 7.4]
YSR SC
4.9 [1.1; 8.7]
4.2 [0.2; 8.2]
3.6 [0; 7.6]
6.1 [0.9; 11.3]
4.7 [2.6; 6.8]
YSR Anx/Dep
4.1 [0.6; 7.6]
2.1 [0; 5.0]
3.6 [0; 7.6]
3.7 [0; 7.8]
3.4 [1.6; 5.2]
YSR SP
1.6 [0; 3.8]
4.2 [0.2; 8.2]
1.2 [0; 3.5]
2.4 [0; 5.7]
2.3 [0.8; 3.8]
YSR TP
2.5 [0; 5.3]
2.1 [0; 5.0]
2.4 [0; 5.7]
4.9 [0.2; 9.6]
2.9 [1.2; 4.6]
YSR AT
0.0
5.2 [0.7; 9.7]
2.4 [0; 5.7]
3.7 [0; 7.8]
2.6 [1.0; 4.2]
YSR Del
0.8 [0; 2.4]
2.1 [0; 5.0]
1.2 [0; 3.5]
6.1 [0.9; 11.3]
2.3 [0.8; 3.8]
YSR Agg
0.8 [0; 2.4]
2.1 [0; 5.0]
0.0
1.2 [0; 3.6]
1.0 [0; 2.0]
SCOFFa
17.2 [10.8; 23.6]
24.5 [16.3; 32.7]
16.7 [8.7; 24.7]
26.2 [16.7; 35.7]
20.8 [16.9; 24.7]
SCOFFb
8.2 [3.5; 12.9]
6.6 [1.9; 11.3]
4.8 [0.2; 9.4]
6.0 [0.9; 11.1]
6.6 [4.2; 9.0]
16.8 [10.2; 23.4]
18.6 [10.8; 26.4]
14.3 [6.8; 21.8]
26.8 [17.2; 36.4]
18.8 [14.9; 22.7]
YSR and SCOFF
c
YSR Youth self-report, Int Internalizing, Ext Externalizing, WD Withdrawn, SC Somatic complaints, Anx/Dep Anxious/depressed, SP Social problems, TP Thought problems, AT Attention problems, Del Delinquent behavior, Agg Aggressive behavior a SCOFF Score ≥ 2 b SCOFF Score ≥ 2 and at least one of the following SCOFF items is marked as applicable: “Do you make yourself sick because you feel uncomfortably full?”, “Have you recently lost more than one stone (6 kg) in a 3month period?” c Above cut-off score of clinical relevance in at least one YSR syndrome scale OR SCOFF Score ≥ 2 and at least one of the following SCOFF items is marked as applicable: “Do you make yourself sick because you feel uncomfortably full?”, “Have you recently lost more than one stone (6 kg) in a 3month period?”
school grades for female participants. For males, the picture is not as clear as for females. Whereas mean scores remained almost stable for the total problem scale, mean scores decreased from low to high school grades for internalizing problems, somatic complaints and social problems. No clear association between school grade and problem scores could have been observed in males for externalizing problems including delinquent behavior and aggressive behavior. In the SCOFF-questionnaire, 20.8 % of the screened adolescents scored above the clinical cut-off applying the criteria (score ≥ 2) proposed by the authors. Since the SCOFF is known for its very high sensitivity leading to a high rate of positive screened adolescents, we propose that additionally to the criteria from the authors (score ≥ 2), at least one of the two clinically relevant items (vomiting, weight reduction) has to be confirmed by the adolescents. Applying these new criteria, the percentage of positive screened adolescents decreased to 6.6 %. High-risk cases for mental disorders were defined as scoring above the clinical cut-off in at least one of the YSR syndrome scales or the SCOFF applying the new criteria as described above. Following this definition, the overall prevalence of mental health problems was 18.9 % [CI 95 %: 14.9–22.7]. YSR total problem scores were significantly correlated with health related quality of life measures as derived by the KIDSCREEN questionnaire (KIDSCREEN-10: r = − .628; Self Perception: r = − .572; Parent Relation and Home Life: r = − .484; Bullying: r = − .356; Social Support and Peers: − .298; School Environment: − .512, all p-values
