Eur Child Adolesc Psychiatry DOI 10.1007/s00787-015-0676-6
ORIGINAL CONTRIBUTION
Mental health care use among children and adolescents in Germany: results of the longitudinal BELLA study Birte Hintzpeter · Fionna Klasen · Gerhard Schön · Catharina Voss · Heike Hölling · Ulrike Ravens‑Sieberer · The BELLA study group
Received: 26 April 2014 / Accepted: 3 January 2015 © Springer-Verlag Berlin Heidelberg 2015
Abstract Data on mental health care use of children and adolescents in Germany is scarce. This study investigates the degree of mental health care use, its trajectories and influencing factors among children and adolescents in Germany, using longitudinal data of the BELLA study. The BELLA study is the mental health module of the representative German National Health Interview and Examination Survey for children and adolescents (KiGGS). Baseline data of N = 2,863 participants aged 7–17 years were collected between 2003 and 2006. The study sample was
Members of the BELLA study group: Ulrike Ravens-Sieberer and Fionna Klasen, Hamburg (Principal Investigators); Claus Barkmann, Hamburg; Monika Bullinger, Hamburg; Manfred Döpfner, Köln; Beate Herpertz-Dahlmann, Aachen; Heike Hölling, Berlin; Franz Resch, Heidelberg; Aribert Rothenberger, Göttingen; Sylvia Schneider, Bochum; Michael SchulteMarkwort, Hamburg; Robert Schlack, Berlin; Frank Verhulst, Rotterdam; Hans-Ulrich Wittchen, Dresden.
followed up in three additional measurement points, assessing general mental health problems and impairment, specific mental health problems, and mental health care use. In the current study, we analysed data from the first three measurement points. At baseline, 5.9 % of all participants used mental health care in the past 12 months. Among those with general mental health problems, 29.5 % sought professional help. Only a minority of participants reporting mental health care use at baseline also sought help at the following two measurement points. Analysing a random intercept only model, mental health care use was found to be more likely among participants living in larger communities as well as in the Eastern part of Germany, among those participants with impairment of mental health problems, and signs of externalizing problems. Our results indicate a temporary character of mental health care use. Participants’ impairment was identified to be the strongest predictor of mental health care use.
Electronic supplementary material The online version of this article (doi:10.1007/s00787-015-0676-6) contains supplementary material, which is available to authorized users.
Keywords Mental health care use · Children and adolescents · Germany · BELLA study · Longitudinal · Random intercept only model
B. Hintzpeter · F. Klasen · C. Voss · U. Ravens‑Sieberer (*) Department of Child and Adolescent Psychiatry, Psychotherapy, and Psychosomatics, University Medical Center HamburgEppendorf, Martinistr. 52, 20246 Hamburg, Germany e-mail: ravens‑[email protected]
Introduction
B. Hintzpeter e-mail: [email protected] G. Schön Department of Medical Biometry and Epidemiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany H. Hölling Department of Epidemiology and Health Monitoring, Robert Koch Institute, Berlin, Germany
Worldwide, the prevalence of child and adolescent mental disorders is high. Recent global studies showed that up to 20 % of children and adolescents suffer from a disabling mental illness [1]. For Germany, an estimated prevalence rate of 17.6 % is reported for emotional and behavioural problems in children and adolescents [2]. Most adult mental disorders begin in childhood or adolescence [3]. About 50 % of all lifetime cases have an onset before the age of 14 years and 75 % before the age of 24 years [4]. However,
13
compared to adults, the level of coverage and quality of services for children and adolescents is generally worse [5]. Most children and adolescents with mental health problems do not receive any treatment. The percentage of children and adolescents with mental health care use ranged from 7.7 to 46.5 % according to several national surveys [6–9]. Thereby, the rate of mental health care use seems to vary between the type of mental disorder [7, 10], the number of comorbidities [7, 11] as well as developmental courses of mental health problems, e.g. acute/recurrent, persistent or remitted mental health problems [12]. Untreated mental health problems may not only have a negative impact on later mental health problems [13], but also have additional lasting consequences, such as substance use, academic failure, unemployment, and other social outcomes later in life [14]. National differences in mental health care use can partly be explained by the underlying health care system. In Germany, health care is funded by a statutory contribution system that ensures free health care (including mental health care) for the population. Health insurance in Germany is divided between statutory, covering about 90 % of the population, as well as private schemes. Previous findings from the baseline data of the KiGGS study and the affiliated BELLA study highlighted factors associated with mental health care use in children and adolescents in Germany [15, 16]. For example, in case of specific mental health problems, such as depression or anxiety, help-seeking behaviour is rather low [16]. In the current article, analyses of child and adolescent mental health care use are provided, using longitudinal data of the large representative sample of the BELLA study for the first time. A framework to better understand the underlying components of help-seeking behaviour and the factors associated with health care use is provided by Andersen [17]. The behavioral model of health service use includes individual need, predisposing characteristics, and enabling resources that have been identified as important influences on treatment seeking. Need factors involve objective (e.g. mental health problems) and subjective (e.g. distress) indicators of need. Predisposing characteristics consist of stable factors present before the illness (such as age or socioeconomic status). Enabling resources include factors that may facilitate or hinder service use (e.g. access to health service use or health insurance status) [17]. In this study, we aimed to analyse the degree of mental health care use and its trajectories as well as to identify its independent determinants among children and adolescents, using longitudinal data of the BELLA study. Thereby, the behavioral model by Andersen was applied to our data. We included specific mental health problems and the impact of mental health problems as need factors in our analyses, assuming that these variables are important predictors of
13
Eur Child Adolesc Psychiatry
mental health care use. Regarding predisposing characteristics, we added several socioeconomic variables to our analyses, e.g. socioeconomic status. With regard to enabling factors, information on the use of general practitioners or pediatricians was included in our analyses, serving as an indicator of primary health care use in Germany. We assume a “gatekeeper function”, as in most cases a general practitioner or pediatrician refers the patient to a psychologist, psychiatrist or psychotherapist. Further, health insurance status was included in our analyses.
Methods A detailed description of the study design and the methods used is provided in another article in this special issue [12]. In brief, the longitudinal BELLA study measures mental health, risk and protective factors, as well as mental health care use of children and adolescents. The BELLA study is the mental health module of the German National Health Interview and Examination Survey for children and adolescents (KiGGS), conducted by the Robert Koch Institute. In the BELLA study, baseline data of N = 2,863 participants (48.8 % female) with an age range from 7 to 17 years (onethird 7–10 years, 26 % 11–13 years and 41 % 14–17 years) were collected between 2003 and 2006. Non-responders reported low socioeconomic status more often than responders in our study [12]. The BELLA study sample was followed up in three additional measurement points: from 2004 to 2007 (1-year follow-up), 2005 to 2008 (2-year follow-up) as well as from 2009 to 2012 (6-year follow-up). Data were collected through telephone interviews and subsequent questionnaires by both, parent-report and self-report (from adolescents above 11 years of age). A table containing the assessed instruments by parent-report and self-report for all measurement points is provided in another article [12].
Measurements In the current analyses, we used socioeconomic variables from baseline and several standardized instruments assessing general and specific mental health problems as well as mental health care use from the first three measurement points of the BELLA study and KiGGS. Socioeconomic variables The information on parents’ income, occupational status, and education were combined in the Winkler Index as a score for socioeconomic status (SES), which was
Eur Child Adolesc Psychiatry
categorized into low, medium, and high [18, 19]. Furthermore, information on community size and region (Former Federal Republic of Germany vs. Former German Democratic Republic), health insurance status (private vs. statutory), and migrant background were available from baseline. A child was defined as having a migrant background if at least one of the child’s parents was not born in Germany and/or had no German citizenship [20]. Instruments assessing general and specific mental health problems The German version [21–23] of the Strengths and Difficulties Questionnaire (SDQ) [24] was used to screen for mental health symptoms in general using 25 items referring to the past 6 months. The SDQ was administered in children and adolescents above the age of 10 years and in all parents. There is evidence for the reliability and validity of the SDQ [25]. Standard normative data based on a large representative sample of the United Kingdom were used to classify participants according to their mental health problem score into normal, borderline, and abnormal [24] due to the fact that German norm data were available for parentreports only. The impact of the Strengths and Difficulties Questionnaire (SDQ impact) was used to assess the impairment of mental health problems [26] as an extension of the SDQ symptoms score. The first item enquires whether there is any perceived difficulty in at least one of the following areas: emotions, concentration, behaviour, or being able to get on with other people. Participants indicating at least minor difficulties are asked further items assessing chronicity of difficulties, associated distress, and social impairment at home life, friendships, classroom learning, leisure activities, and perceived burden. A total impact score was calculated [26] by adding the score of the distress item to the scores of the first four social impairments. Participants were then classified into normal vs. borderline or abnormal. The Center for Epidemiological Studies Depression Scale for Children (CES-DC) [27] was used to screen for depressive symptoms regarding the past week [28]. A German translation of the 20 items was used in the current study, showing satisfying reliability and validity [29]. Using a cutoff value of >15, participants were categorized into groups with normal and abnormal depressive symptoms. The 5-item short version of the Screen for Child Anxiety Related Emotional Disorders (SCARED) [30] was used to assess symptoms of anxiety in the past 3 months. An authorized German version was used in the present study [31]. The five items can be combined to a total score of anxiety symptoms, showing good psychometric properties comparable to the full version [30].
The Conners‘Rating Scales-Revised (CRS-R) [32] assess child behaviour problems. In the present study, we used the 10-item Hyperactivity Index [33] of the CRS-R to screen for hyperactivity and impulsivity in children and adolescents in the past month [34]. There is evidence for good psychometric properties of the different versions of the CRS-R [35, 36]. Using a cutoff value of >15, participants were categorized into groups with normal and abnormal hyperactivity and impulsivity. The German version [37] of the Child Behavior Checklist (CBCL) [38] was used to screen for externalizing problems (33 items) referring to the past 6 months including two subscales: aggressive behaviour and dissocial behaviour. An externalizing problem score can be generated. There is evidence that the externalizing problems scale shows satisfying reliability and validity [39]. Mental health care use Mental health care use was measured by three items asking respondents whether they have consulted a psychologist, psychiatrist or psychotherapist in the past 12 months. For the purpose of this study, we combined these items. Additionally, the use of a general practitioner and a pediatrician in the past 12 months was assessed. To ensure a similar approach for each measurement point and used measurement, a score for each mental health problem and health care use measurement was calculated, including self-reports for children and adolescents aged 14 years and older as well as proxy-reports for the younger ages (for the CBCL, only the proxy-report was available). This approach was necessary due to the fact that health care use was only measured by self-report for children and adolescents aged 14 years and older as well as proxy-report for the younger ages at baseline.
Statistical analyses A random intercept model with mental health care use as the dependent variable was estimated to identify important determinants. Due to the dichotomous outcome, we computed a logistic regression model. Analyses were restricted to the first three measurement points as some necessary covariates (such as the SDQ for the respective age groups) were not available in the 6-year follow-up. We included only those participants with information on help-seeking for at least one measurement point. All available data of an individual were taken into account. To handle missing data, we generated a complete cases data set. Longitudinal analyses for dichotomous outcomes lead to reasonable results, if there is a sufficient proportion of stability over the measurement points. We therefore
13
Eur Child Adolesc Psychiatry
Fig. 1 Trajectories (1- and 2-year follow-up) of mental health care use for participants reporting mental health care use at baseline (n = 166). Red bar number of participants using mental health care services, Green bar number of participants not using mental health
care services, Grey bar participants with missing data, Dotted bar participants dropped-out, Dashed lines users of mental health care services at 1-year follow-up
investigated trajectories of mental health care use for participants who used mental health care services at baseline. As no meaningful trajectories could be identified (see Fig. 1), we assumed a temporary character of utilization in our sample. Therefore, we treated the cluster structure of the data (up to three measurements per person) as a nuisance parameter and took into account the correlated data. We treated the person as the cluster unit and modeled it by a random intercept. As no reasonable trajectories could be estimated, we chose to estimate a random intercept only model. The alternative to a random intercept model would be an analysis of three unconnected time points with obviously less statistical power compared to the analysis with pooled data. All analyses were performed with SPSS version 20.0 (PASW Statistics for Windows, Version 20.0. Chicago: SPSS Inc.) and R version 3.0.3 [40] using the R-package lme4 [41].
the SCARED, CES-DC, Conner’s and CBCL as well as the SDQ impact were significantly more prevailing at all three measurement points compared to non-users. Figure 1 presents the longitudinal trajectories (1- and 2-year follow-up) of mental health care use for the participants (n = 166) that sought professional help at baseline. Of this initial subsample, 45.2 % (n = 75) did not report mental health care use 1 year later, while 29.5 % (n = 49) reported use of mental health care again; 10.2 % (n = 17) had missing data and 15.1 % (n = 25) did not participate in the 1-year follow-up at all. Two years later, 54.2 % (n = 90) of the initial subsample did not report mental health care use, of whom n = 21 sought help at baseline and at 1-year follow-up. In addition, 19.9 % (n = 33) of the initial sample used mental health care at 2-year follow-up, of whom n = 22 had also reported help-seeking at baseline and 1 year later. Overall, 13.3 % (n = 22) of the initial subsample reported mental health care use at all three measurement points. Figure 2 displays estimates of fixed effects of a random intercept only model for mental health care use. “Health insurance status” as well as “having a migrant background” were excluded from the analyses due to small case numbers. Regarding the final model, independent significant determinants included region, community size, signs of conduct disorders (characterized by abnormal CBCL), and reported impairment (indicated by abnormal SDQ impact). There was a significant negative association between region and mental health service use (OR 0.24; 95 % CI 0.11– 0.51) indicating that participants living in the Western part of Germany were less likely to seek treatment. Community size was positively associated with mental health care use (OR 1.72; 95 % CI 1.25–2.38) showing an increase from rural, small towns, medium-sized to large urban areas. In
Results The frequencies of mental health care use by predisposing, enabling, and need factors of Andersen’s behavioral model of health service use are summarized in Table 1. In the online appendix (Table 2), the same results are presented for the subsample of participants included in the random intercept only model. Overall prevalence of mental health care use was 5.9 % at baseline. Regarding only those participants with abnormal SDQ, the percentage increased to 29.5 %. Use of mental health care was significantly more prevalent among males, as well as among participants living in larger communities. Among users of professional care, specific mental health problems indicated by abnormal scores of
13
Eur Child Adolesc Psychiatry Table 1 A: Mental health care use (%) and B: Mental health care use by factors of Andersen’s behavioral model of health service use (%)
Differences between users and non-users of mental health care are tested using Chi square test statistic: * p
ORIGINAL CONTRIBUTION
Mental health care use among children and adolescents in Germany: results of the longitudinal BELLA study Birte Hintzpeter · Fionna Klasen · Gerhard Schön · Catharina Voss · Heike Hölling · Ulrike Ravens‑Sieberer · The BELLA study group
Received: 26 April 2014 / Accepted: 3 January 2015 © Springer-Verlag Berlin Heidelberg 2015
Abstract Data on mental health care use of children and adolescents in Germany is scarce. This study investigates the degree of mental health care use, its trajectories and influencing factors among children and adolescents in Germany, using longitudinal data of the BELLA study. The BELLA study is the mental health module of the representative German National Health Interview and Examination Survey for children and adolescents (KiGGS). Baseline data of N = 2,863 participants aged 7–17 years were collected between 2003 and 2006. The study sample was
Members of the BELLA study group: Ulrike Ravens-Sieberer and Fionna Klasen, Hamburg (Principal Investigators); Claus Barkmann, Hamburg; Monika Bullinger, Hamburg; Manfred Döpfner, Köln; Beate Herpertz-Dahlmann, Aachen; Heike Hölling, Berlin; Franz Resch, Heidelberg; Aribert Rothenberger, Göttingen; Sylvia Schneider, Bochum; Michael SchulteMarkwort, Hamburg; Robert Schlack, Berlin; Frank Verhulst, Rotterdam; Hans-Ulrich Wittchen, Dresden.
followed up in three additional measurement points, assessing general mental health problems and impairment, specific mental health problems, and mental health care use. In the current study, we analysed data from the first three measurement points. At baseline, 5.9 % of all participants used mental health care in the past 12 months. Among those with general mental health problems, 29.5 % sought professional help. Only a minority of participants reporting mental health care use at baseline also sought help at the following two measurement points. Analysing a random intercept only model, mental health care use was found to be more likely among participants living in larger communities as well as in the Eastern part of Germany, among those participants with impairment of mental health problems, and signs of externalizing problems. Our results indicate a temporary character of mental health care use. Participants’ impairment was identified to be the strongest predictor of mental health care use.
Electronic supplementary material The online version of this article (doi:10.1007/s00787-015-0676-6) contains supplementary material, which is available to authorized users.
Keywords Mental health care use · Children and adolescents · Germany · BELLA study · Longitudinal · Random intercept only model
B. Hintzpeter · F. Klasen · C. Voss · U. Ravens‑Sieberer (*) Department of Child and Adolescent Psychiatry, Psychotherapy, and Psychosomatics, University Medical Center HamburgEppendorf, Martinistr. 52, 20246 Hamburg, Germany e-mail: ravens‑[email protected]
Introduction
B. Hintzpeter e-mail: [email protected] G. Schön Department of Medical Biometry and Epidemiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany H. Hölling Department of Epidemiology and Health Monitoring, Robert Koch Institute, Berlin, Germany
Worldwide, the prevalence of child and adolescent mental disorders is high. Recent global studies showed that up to 20 % of children and adolescents suffer from a disabling mental illness [1]. For Germany, an estimated prevalence rate of 17.6 % is reported for emotional and behavioural problems in children and adolescents [2]. Most adult mental disorders begin in childhood or adolescence [3]. About 50 % of all lifetime cases have an onset before the age of 14 years and 75 % before the age of 24 years [4]. However,
13
compared to adults, the level of coverage and quality of services for children and adolescents is generally worse [5]. Most children and adolescents with mental health problems do not receive any treatment. The percentage of children and adolescents with mental health care use ranged from 7.7 to 46.5 % according to several national surveys [6–9]. Thereby, the rate of mental health care use seems to vary between the type of mental disorder [7, 10], the number of comorbidities [7, 11] as well as developmental courses of mental health problems, e.g. acute/recurrent, persistent or remitted mental health problems [12]. Untreated mental health problems may not only have a negative impact on later mental health problems [13], but also have additional lasting consequences, such as substance use, academic failure, unemployment, and other social outcomes later in life [14]. National differences in mental health care use can partly be explained by the underlying health care system. In Germany, health care is funded by a statutory contribution system that ensures free health care (including mental health care) for the population. Health insurance in Germany is divided between statutory, covering about 90 % of the population, as well as private schemes. Previous findings from the baseline data of the KiGGS study and the affiliated BELLA study highlighted factors associated with mental health care use in children and adolescents in Germany [15, 16]. For example, in case of specific mental health problems, such as depression or anxiety, help-seeking behaviour is rather low [16]. In the current article, analyses of child and adolescent mental health care use are provided, using longitudinal data of the large representative sample of the BELLA study for the first time. A framework to better understand the underlying components of help-seeking behaviour and the factors associated with health care use is provided by Andersen [17]. The behavioral model of health service use includes individual need, predisposing characteristics, and enabling resources that have been identified as important influences on treatment seeking. Need factors involve objective (e.g. mental health problems) and subjective (e.g. distress) indicators of need. Predisposing characteristics consist of stable factors present before the illness (such as age or socioeconomic status). Enabling resources include factors that may facilitate or hinder service use (e.g. access to health service use or health insurance status) [17]. In this study, we aimed to analyse the degree of mental health care use and its trajectories as well as to identify its independent determinants among children and adolescents, using longitudinal data of the BELLA study. Thereby, the behavioral model by Andersen was applied to our data. We included specific mental health problems and the impact of mental health problems as need factors in our analyses, assuming that these variables are important predictors of
13
Eur Child Adolesc Psychiatry
mental health care use. Regarding predisposing characteristics, we added several socioeconomic variables to our analyses, e.g. socioeconomic status. With regard to enabling factors, information on the use of general practitioners or pediatricians was included in our analyses, serving as an indicator of primary health care use in Germany. We assume a “gatekeeper function”, as in most cases a general practitioner or pediatrician refers the patient to a psychologist, psychiatrist or psychotherapist. Further, health insurance status was included in our analyses.
Methods A detailed description of the study design and the methods used is provided in another article in this special issue [12]. In brief, the longitudinal BELLA study measures mental health, risk and protective factors, as well as mental health care use of children and adolescents. The BELLA study is the mental health module of the German National Health Interview and Examination Survey for children and adolescents (KiGGS), conducted by the Robert Koch Institute. In the BELLA study, baseline data of N = 2,863 participants (48.8 % female) with an age range from 7 to 17 years (onethird 7–10 years, 26 % 11–13 years and 41 % 14–17 years) were collected between 2003 and 2006. Non-responders reported low socioeconomic status more often than responders in our study [12]. The BELLA study sample was followed up in three additional measurement points: from 2004 to 2007 (1-year follow-up), 2005 to 2008 (2-year follow-up) as well as from 2009 to 2012 (6-year follow-up). Data were collected through telephone interviews and subsequent questionnaires by both, parent-report and self-report (from adolescents above 11 years of age). A table containing the assessed instruments by parent-report and self-report for all measurement points is provided in another article [12].
Measurements In the current analyses, we used socioeconomic variables from baseline and several standardized instruments assessing general and specific mental health problems as well as mental health care use from the first three measurement points of the BELLA study and KiGGS. Socioeconomic variables The information on parents’ income, occupational status, and education were combined in the Winkler Index as a score for socioeconomic status (SES), which was
Eur Child Adolesc Psychiatry
categorized into low, medium, and high [18, 19]. Furthermore, information on community size and region (Former Federal Republic of Germany vs. Former German Democratic Republic), health insurance status (private vs. statutory), and migrant background were available from baseline. A child was defined as having a migrant background if at least one of the child’s parents was not born in Germany and/or had no German citizenship [20]. Instruments assessing general and specific mental health problems The German version [21–23] of the Strengths and Difficulties Questionnaire (SDQ) [24] was used to screen for mental health symptoms in general using 25 items referring to the past 6 months. The SDQ was administered in children and adolescents above the age of 10 years and in all parents. There is evidence for the reliability and validity of the SDQ [25]. Standard normative data based on a large representative sample of the United Kingdom were used to classify participants according to their mental health problem score into normal, borderline, and abnormal [24] due to the fact that German norm data were available for parentreports only. The impact of the Strengths and Difficulties Questionnaire (SDQ impact) was used to assess the impairment of mental health problems [26] as an extension of the SDQ symptoms score. The first item enquires whether there is any perceived difficulty in at least one of the following areas: emotions, concentration, behaviour, or being able to get on with other people. Participants indicating at least minor difficulties are asked further items assessing chronicity of difficulties, associated distress, and social impairment at home life, friendships, classroom learning, leisure activities, and perceived burden. A total impact score was calculated [26] by adding the score of the distress item to the scores of the first four social impairments. Participants were then classified into normal vs. borderline or abnormal. The Center for Epidemiological Studies Depression Scale for Children (CES-DC) [27] was used to screen for depressive symptoms regarding the past week [28]. A German translation of the 20 items was used in the current study, showing satisfying reliability and validity [29]. Using a cutoff value of >15, participants were categorized into groups with normal and abnormal depressive symptoms. The 5-item short version of the Screen for Child Anxiety Related Emotional Disorders (SCARED) [30] was used to assess symptoms of anxiety in the past 3 months. An authorized German version was used in the present study [31]. The five items can be combined to a total score of anxiety symptoms, showing good psychometric properties comparable to the full version [30].
The Conners‘Rating Scales-Revised (CRS-R) [32] assess child behaviour problems. In the present study, we used the 10-item Hyperactivity Index [33] of the CRS-R to screen for hyperactivity and impulsivity in children and adolescents in the past month [34]. There is evidence for good psychometric properties of the different versions of the CRS-R [35, 36]. Using a cutoff value of >15, participants were categorized into groups with normal and abnormal hyperactivity and impulsivity. The German version [37] of the Child Behavior Checklist (CBCL) [38] was used to screen for externalizing problems (33 items) referring to the past 6 months including two subscales: aggressive behaviour and dissocial behaviour. An externalizing problem score can be generated. There is evidence that the externalizing problems scale shows satisfying reliability and validity [39]. Mental health care use Mental health care use was measured by three items asking respondents whether they have consulted a psychologist, psychiatrist or psychotherapist in the past 12 months. For the purpose of this study, we combined these items. Additionally, the use of a general practitioner and a pediatrician in the past 12 months was assessed. To ensure a similar approach for each measurement point and used measurement, a score for each mental health problem and health care use measurement was calculated, including self-reports for children and adolescents aged 14 years and older as well as proxy-reports for the younger ages (for the CBCL, only the proxy-report was available). This approach was necessary due to the fact that health care use was only measured by self-report for children and adolescents aged 14 years and older as well as proxy-report for the younger ages at baseline.
Statistical analyses A random intercept model with mental health care use as the dependent variable was estimated to identify important determinants. Due to the dichotomous outcome, we computed a logistic regression model. Analyses were restricted to the first three measurement points as some necessary covariates (such as the SDQ for the respective age groups) were not available in the 6-year follow-up. We included only those participants with information on help-seeking for at least one measurement point. All available data of an individual were taken into account. To handle missing data, we generated a complete cases data set. Longitudinal analyses for dichotomous outcomes lead to reasonable results, if there is a sufficient proportion of stability over the measurement points. We therefore
13
Eur Child Adolesc Psychiatry
Fig. 1 Trajectories (1- and 2-year follow-up) of mental health care use for participants reporting mental health care use at baseline (n = 166). Red bar number of participants using mental health care services, Green bar number of participants not using mental health
care services, Grey bar participants with missing data, Dotted bar participants dropped-out, Dashed lines users of mental health care services at 1-year follow-up
investigated trajectories of mental health care use for participants who used mental health care services at baseline. As no meaningful trajectories could be identified (see Fig. 1), we assumed a temporary character of utilization in our sample. Therefore, we treated the cluster structure of the data (up to three measurements per person) as a nuisance parameter and took into account the correlated data. We treated the person as the cluster unit and modeled it by a random intercept. As no reasonable trajectories could be estimated, we chose to estimate a random intercept only model. The alternative to a random intercept model would be an analysis of three unconnected time points with obviously less statistical power compared to the analysis with pooled data. All analyses were performed with SPSS version 20.0 (PASW Statistics for Windows, Version 20.0. Chicago: SPSS Inc.) and R version 3.0.3 [40] using the R-package lme4 [41].
the SCARED, CES-DC, Conner’s and CBCL as well as the SDQ impact were significantly more prevailing at all three measurement points compared to non-users. Figure 1 presents the longitudinal trajectories (1- and 2-year follow-up) of mental health care use for the participants (n = 166) that sought professional help at baseline. Of this initial subsample, 45.2 % (n = 75) did not report mental health care use 1 year later, while 29.5 % (n = 49) reported use of mental health care again; 10.2 % (n = 17) had missing data and 15.1 % (n = 25) did not participate in the 1-year follow-up at all. Two years later, 54.2 % (n = 90) of the initial subsample did not report mental health care use, of whom n = 21 sought help at baseline and at 1-year follow-up. In addition, 19.9 % (n = 33) of the initial sample used mental health care at 2-year follow-up, of whom n = 22 had also reported help-seeking at baseline and 1 year later. Overall, 13.3 % (n = 22) of the initial subsample reported mental health care use at all three measurement points. Figure 2 displays estimates of fixed effects of a random intercept only model for mental health care use. “Health insurance status” as well as “having a migrant background” were excluded from the analyses due to small case numbers. Regarding the final model, independent significant determinants included region, community size, signs of conduct disorders (characterized by abnormal CBCL), and reported impairment (indicated by abnormal SDQ impact). There was a significant negative association between region and mental health service use (OR 0.24; 95 % CI 0.11– 0.51) indicating that participants living in the Western part of Germany were less likely to seek treatment. Community size was positively associated with mental health care use (OR 1.72; 95 % CI 1.25–2.38) showing an increase from rural, small towns, medium-sized to large urban areas. In
Results The frequencies of mental health care use by predisposing, enabling, and need factors of Andersen’s behavioral model of health service use are summarized in Table 1. In the online appendix (Table 2), the same results are presented for the subsample of participants included in the random intercept only model. Overall prevalence of mental health care use was 5.9 % at baseline. Regarding only those participants with abnormal SDQ, the percentage increased to 29.5 %. Use of mental health care was significantly more prevalent among males, as well as among participants living in larger communities. Among users of professional care, specific mental health problems indicated by abnormal scores of
13
Eur Child Adolesc Psychiatry Table 1 A: Mental health care use (%) and B: Mental health care use by factors of Andersen’s behavioral model of health service use (%)
Differences between users and non-users of mental health care are tested using Chi square test statistic: * p
