The consortium project INTEGRATE-ADHD - Comparison and integration of administrative and epidemiological ADHD diagnostic data by clinical assessment: study description and sample characteristics

doi:10.21203/rs.3.rs-4901197/v1

Background

The consortium project INTEGRATE-ADHD examines differences between administrative and epidemiologically parent-reported Attention-deficit/hyperactivity disorder (ADHD) diagnostic data of children and adolescents in Germany. Therefore, parents of youths with an administrative ADHD diagnoses were surveyed using the questionnaires of the German Health Interview and Examination Survey for Children and Adolescents (KiGGS) and a subsample was clinically examined.

Methods

Parents of children and adolescents insured with the third largest German statutory health insurance DAK-Gesundheit with at least one confirmed administrative ADHD diagnosis in one quarter of the insurance year 2020 were surveyed online. The epidemiological questionnaire contained information on ADHD diagnosis, disorder-specific and comorbid psychopathology, health care utilisation, quality and satisfaction with care, risk and protective factors, and health-related quality of life. A subsample participated in a guideline-based clinical online assessment. Administrative, epidemiological and clinical data were linked on person-level.

Results

A total of n = 5,461 parents of children and adolescents with an administratively documented ADHD diagnosis (mean age = 12.5 years, 25.4% girls) responded to the online questionnaire (response rate: 21.5%). A representative subsample consisting of 202 families participated in the clinical online assessment. In 201 children and adolescents, it was possible to determine whether ADHD was clinically present.

Conclusion

Combining administrative, epidemiological and clinical ADHD diagnostic data on person-level, the consortium project INTEGRATE-ADHD offers an innovative and unique data-linkage approach that will provide a better understanding of the meaning and validity of ADHD prevalence data originating from various data sources. In addition, information on treatment satisfaction in affected child and adolescents and their families and potential deficits of health care in the context of ADHD as well as disorder-related direct health care costs may be derived.

ADHD

administrative

epidemiological

prevalence

clinical assessment

data-linkage

Attention-deficit/hyperactivity disorder (ADHD) is one of the most frequently diagnosed mental disorders in children and adolescents both in Germany and worldwide (1–3). Prevalence rates are usually derived from claims (administrative) data or from population-based epidemiological surveys. However, these data sources are not compared easily and are sometimes even contradictory (4–6). In Germany, ADHD prevalence rates from claims data rose constantly from the beginning of the century (7–10) while those from epidemiological survey data based on parent-reported lifetime diagnoses of the child remained stable or even declined (3, 11, 12). Whether the diagnoses from either source are clinically valid is unknown (13). Valid prevalence data, however, is crucial for health policy and health care planning.

To examine the existing discrepancies between the various data sources the consortium project INTEGRATE-ADHD was formed in order to directly compare administrative and epidemiologically reported ADHD diagnostic data of German youths on person-level. Parents of statutorily insured youths with an administrative ADHD diagnosis were surveyed online using modified questionnaires of the epidemiological German Health Interview and Examination Survey for Children and Adolescents (KiGGS study; 14, 15, 16) and its in-depth module on child mental health (BELLA study; 17). Additionally, a subsample of youths was clinically examined online. Also, information on health care quality of ADHD patients and their families as well as the health economics of ADHD were assessed. The following partners have formed the consortium INTEGRATE-ADHD: 1) Robert Koch Institute, Department of Epidemiology and Health Monitoring, Berlin (consortium leader); 2) University Hospital Würzburg, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy; 3) University Medical Centre Hamburg-Eppendorf, Department of Child and Adolescent Psychiatry, Psychotherapy, and Psychosomatics; 4) Vandage GmbH, Bielefeld; 5) University of Würzburg, Institute of Clinical Epidemiology and Biometry, and 6) the statutory health insurance DAK-Gesundheit.

Here we describe the study design and sample characteristics of this first study to simultaneously include administrative, epidemiological and clinical ADHD diagnostic data of youths in Germany.

Inclusion criteria and case definitions

The consortium project INTEGRATE-ADHD was carried out as cross-sectional interview and examination survey of parents (respondents) of youths (cases) who were insured with the third-largest German statutory health insurance company, DAK-Gesundheit. Children and adolescents were included if they displayed at least one confirmed outpatient or inpatient ADHD diagnosis (ICD-10 F90.0-9, main and/or secondary diagnosis) in 2020 (M1Q criterion), were born between 2003 and 2020 and had not changed their health insurance company within 2020.

Sampling and conduct of the online sample

The source population of the study comprised 848,110 children and adolescents insured with DAK-Gesundheit in 2020 (see Fig. 1). Of these, n = 30,101 met the inclusion criteria for the study. In a next step, a reduction sample of n = 25,000 children and adolescents was randomly drawn for study participation. This was necessary because the number of children and adolescents insured with DAK-Gesundheit had increased by around 200,000 within the period between study application and study approval, and the funding had only been calculated for a gross sample of 25,000. For 120 families, either no contact information was available or they refused to be contacted by the DAK-Gesundheit so that finally 24,880 parents or legal guardians (hereafter referred to as parents) were contacted and invited to participate in the study.

The online survey was conducted in four waves from October 2021 to August 2022 (first wave October 2021, second wave January 2022, third wave April 2022, fourth wave June 2022). In each wave, the parents of all selected children received a postal invitation from DAK-Gesundheit which included a brief information about the study, data protection issues, a link to log in to the questionnaire and a personal identification number (PIN). When following the link, the parents received comprehensive information on the objectives and conduct of the study, on the linkage of their survey and administrative data as well as on data privacy. Before starting the questionnaire, the parents gave their informed consent by clicking on a confirmation box. In the same way, youths aged 14 years and older gave separately their informed consent for their parents to provide information about them. After completing the questionnaire, a shopping voucher worth 30 € was sent to the participants as an incentive.

Sampling and conduct of the clinical subsample

After finishing the online questionnaire, the parents were asked about their willingness to participate in an additional clinical assessment with their child. If they agreed they were asked for their consent to share their contact details with the University Hospital Würzburg. Children aged 14 years and older were asked for their consent separately. In total, n = 3,511 families (i.e., 59,3% of all participants of the online survey) agreed.

Of those, a subsample was drawn for the clinical assessment with a stratified random procedure. As the planned analyses included the comparison of two equally sized groups of youths with (ED+) and without epidemiologically parent-reported ADHD diagnosis (ED-) a sample size of n = 200 was calculated. Because ED- was expected to be less frequent than ED+, an oversampling of ED- was carried out resulting in a pool of n = 576 subjects (n = 288 ED + and n = 288 ED-) preselected for the clinical assessment. A surplus sampling was employed because a number of participants was expected to withdraw their consent. The contact data (telephone number, address) of the preselected subjects were transferred to the University Hospital Würzburg by DAK-Gesundheit.

The clinical assessment took place from January 2022 to January 2023. It was carried out online by psychologists and psychotherapists in training according to the current German guideline "Attention Deficit/Hyperactivity Disorder (ADHD) in Childhood, Adolescence, and Adulthood" (registry number 028–045; 18). The preselected families received first an invitation letter, followed by a telephone call with general information about the aims and procedures. Further, n = 431 families received a letter with more detailed information, a declaration of consent, and a confidentiality release form. Finally, a total of n = 203 families took part in the clinical assessment (see Fig. 2). After completion, the families received a written report with the results as well as €200 as an incentive.

Topics and instruments of the online survey

In the online survey, questionnaires of the German Health Interview and Examination Survey for Children and Adolescents (KiGGS study; 14, 15, 16, 19) and its in-depth module on child mental health (BELLA study; 17, 20) were used. Following their procedure, age-specific self-administered parent-rated questionnaires were deployed for the age groups 0–2, 3–6, 7–10, 11–13 and 14–19 years (pertaining to child age at the time of the survey) including proved items and instruments including instruments specific to ADHD, psychopathology and health care utilisation. Besides socio-demographics, child height and weight, risk and protective factors such as premature birth, postnatal complications, birth size and weight of the child, mothers smoking and alcohol consumption during pregnancy as well as current parental smoking and smoke exposure of the child, personal resources, family cohesion, social support, and health-related quality of life were assessed (14, 16, 17). The validated instruments used in INTEGRATE-ADHD can be taken from Table 1.

Table 1

Validated instruments in the INTEGRATE-ADHD online survey
Construct	Age group	Instrument/Method
Child and parental ADHD symptoms
ADHD symptom screening	0–6 5–19	Fremdbeurteilungsbogen für Aufmerksamkeitsdefizit-/Hyperaktivitätsstörungen (FBB-ADHS-V; 28), preschool version FBB-ADHS (28)
ADHD symptom screening	5–19	Restless-impulsive subscale of Global Index Connor’s scale (40, 41)
ADHD symptom screening	3–19	Hyperactivity/inattention subscale of Strengths and Difficulties Questionnaire (SDQ; 42)
Parental ADHD symptom screening	parents	ADHD Self-Report Scale (ASRS; 43, 44, 45)
Other child and parental psychopathological symptoms
Emotional problems and peer problems	3–19	Emotional problems and peer problems subscales of SDQ (42)
Impact of mental health problems	3–19	SDQ impact supplement (46)
Depressive symptoms	7–19	Centre for Epidemiological Studies Depression Scale for Children (CES-DC; 47)
Symptoms of anxiety	7–19	Screen for Child Anxiety-Related Emotional Disorders (SCARED; 48, 49)
Irritability	7–13	Diagnostic Tool for Affective Dysregulation in Children—Screening Questionnaire (DADYS-Screen; 50)
Irritability	7–19	Patient Reported Outcomes Measurement Information System Anger Scale (PROMIS Anger-Scale; 51, 52)
Disruptive behaviour disorders	0–6 7–19	Externalising subscale of the Child Behavior Checklist 1,5–5 years (CBCL 1,5–5; 53) Externalising subscale of the Child Behavior Checklist (CBCL; 54)
Parental psychopathology	parents	Short version of the Symptom Checklist (SCL-K-9; 55)
Parental strain	parents	Parental Strain Scale (56)
Risks and resources and health-related quality of life
Personal resources	7–19	Personal Resource Scale (57)
Social support	7–19	Adapted version of the Social Support Scale (58)
Family cohesion	0–19	Family Climate Scale (59)
Parents’ health literacy	parents	16-item version of the European Health Literacy Survey (60)
Health-related quality of life	7–19	KIDSCREEN 27 (61)

[insert Table 1]

Pertaining to ADHD, parents were asked whether their child had ever been diagnosed with ADHD by a medical doctor or a psychologist and whether the disorder had been present during the past 12 months (11, 12, 21, 22). If the parents reported an ADHD diagnosis of their child, they were asked whether they accepted their child’s diagnosis, when the diagnosis was first made, whether the child ever received ADHD medication and if so, which preparations were applied in the past seven days, whether they utilised further treatment, whether they sought treatment in 2020 due their child's ADHD, and whether they perceived discrimination of their child in kindergarten or at school. Parental ADHD was assessed both for mother and father by asking the respondents about a lifetime diagnosis by a physician or psychologist. If a parental diagnosis was reported, a question followed about when the diagnosis was made.

Further, the child’s utilisation of paediatric, psychiatric or psychotherapeutic, or general medical care as well as the utilisation of alternative practitioners, physiotherapists, occupational or speech therapists in the past 12 months were asked. If a specific utilisation was confirmed, respondents were asked about their satisfaction with treatment. If no utilisation was reported, respondents were asked about potential barriers.

In order to consider putative COVID-19-related issues, the questionnaire included additional items with respect to the child’s school and family situation, peer contact and the general living situation during the pandemic (23).

Topics and instruments of the online clinical assessment

The clinical assessment according to the S3 guideline of the Association of the Scientific Medical Societies in Germany (AWMF; 18) included two videochat sessions per participant, each lasting about two to four hours. In addition, parents, teachers and─from 11 years on─the child itself filled in online questionnaires. Furthermore, performance tests with the child were carried out online.

The parent was interviewed about basic demographic and anamnestic data and reported the child’s medical history focusing both on somatic and psychological health as well as on previous medication. Psychological stress was evaluated using a screener on the basis of the Axis V − abnormal psychosocial conditions − of the multiaxial classification system of ICD-10, chapter V (F) (MAS; 24). In order to screen for comorbidity, the “Interviewleitfaden Screen” (ILF-Screen; 25) was applied to one parent and the child (from eight years on). In the case of abnormal results, the disorder-specific sections of the Diagnostic Interview for Psychiatric Disorders in Children and Adolescents (Kinder-DIPS; 26, 27) was applied. Pervasiveness and onset of ADHD symptoms and impairment were assessed using the semi-structured “Interviewleitfaden für Externale Störungen” (ILF-EXTERNAL; 25). Furthermore, ADHD rating scales from the DISYPS-III were completed by the child 11 years and older (SBB-ADHS), by the parent (FBB-ADHS / FBB-ADHS-V) and by a teacher or educator (FBB-ADHS / FBB-ADHS-V; 28). The child’s intelligence was assessed using the online version of Raven’s 2 (29). To evaluate executive functions, the child completed an online version of the Continuous Performance Test (CPT; 30). Throughout the entire assessment, the diagnostician rated the behaviour of the child using an observation scale from the DISYPS-III ("Merkmalsausprägungen in der Untersuchungssituation", 28). The overall severity of all psychological symptoms was evaluated with the severity scale of the Clinical Global Impressions Scale (CGI-S; 31). Also, the assessment included a review of school reports and of previous medical reports for symptoms of inattention, hyperactivity, and impulsivity, that were provided by the families and their treatment providers. Whenever possible, pretreatment information was also obtained from treatment providers (e.g., physicians or psychotherapists) by telephone.

Based on all assessed information the diagnostician built a best-estimate judgement on the presence or absence of ADHD according to ICD-10 and DSM-5 criteria. Each assessment was supervised by a psychological and a medical expert. For detailed information on the diagnostic procedure, see Hetzke, Berner (32).

Topics and data processing of the administrative data

Administrative data were provided for 2019 and 2020 by DAK-Gesundheit. The administrative data for the youths contains individual demographic characteristics (date of birth, age in 2020, sex, federal state), inpatient and outpatient health care utilisation (including procedures and diagnoses according to ICD-10-GM-2022, medication prescription, medical aids, non-physician specialist care and rehabilitation services), and information on direct utilisation costs. Data cleaning included verifying quantities and cost data for unreasonable values. If unreasonable data was found, those cases were excluded. This exclusion did not include cost values of 0, which could be related to correction invoices or similar situations. Otherwise, the data was reported without further modifications.

Some external variables were added to the administrative data set, for example a comorbidity index developed by Sun, Bourgeois (33) which summarises 24 conditions. Further, the German Index of Deprivation (GISD; 34) indicating socioeconomic deprivation at the district level (low, medium, high) was added as well as variables containing regional ratios of physicians and psychotherapists (paediatricians, child and adolescent psychiatrists, medical and psychological psychotherapists, general practitioners) per 100,000 inhabitants at district level that were extracted from the register of the Federal Association of SHI Physicians (35). The 2019 data was used to determine incident ADHD (i.e., individual disease-free pre-observation period of at least four quarters).

Only Vandage GmbH had access to the administrative data of the source population and the gross sample for the representativeness, non-responder and cost analyses.

Data-linkage

Finally, the administrative data of the participating families was linked with the survey data and the clinical data on person-level. The data-linkage was implemented using a pseudonym provided by the DAK-Gesundheit.

Response and non-responder analysis

From a total of n = 24,880 invited parents (gross sample), n = 5,919 parents took part in the online survey (see Fig. 1). Thereof, n = 458 participants were excluded from the analyses either because they did not answer the question about their child's ADHD diagnosis or they displayed a completion time of less than 657 seconds (pure reading time) or they had more than 50% missing values or had answered an unsuitable questionnaire due to incorrect entry of their child’s age. Consistency checks after data-linkage led to the exclusion of additional cases because of inconsistent information on age or gender in the administrative and the survey data. This resulted in a net sample of n = 5,461. The response rate according to AAPOR's Standard Definitions, Version 9 (RR3) was 21.5% (36). In total, n = 202 families were clinically examined. Based on the information available, it was not possible for one child to decide whether ADHD according to ICD-10 or DSM-5 was present. Thus, information on clinical ADHD is available for n = 201 children (see Fig. 2).

For non-responder analysis, responders and non-responders of both the online survey and the clinical assessment were compared with regard to sociodemographics, ADHD diagnosis, treatment, and health care utilisation characteristics (Table 2). Children of responders of the online survey were slightly younger, more likely to live in districts with low or medium and less likely to live in districts with high socioeconomic deprivation than those of non-responders. The regional ratios of paediatricians, as well as medical or psychological psychotherapists or child and adolescent psychiatrists at the district level were slightly lower, the proportion of participants living in Western Germany was higher for responders compared to non-responders. Responders were less likely to be ADHD-incident in 2020 and among the incident children, responders utilised less often general practitioners. They received more likely ADHD medication (N06BA04, N06BA09, N06BA02, N06BA12, N06BA21) and behavioural therapy and utilised more frequently child and adolescent psychiatrist or psychotherapist or psychological psychotherapist than non-responders.

Table 2

Non-responder analysis (on the basis of administrative data)
	Online sample						Clinical sample
	Participants^a (n = 5,461)		Non-participants (n = 19,419)				Participants (n = 202)			Non-participants (n = 24,678)
	n (%)	Mean (SD)	n (%)	Mean (SD)	p		n (%)	Mean (SD)		n (%)	Mean (SD)		p
Sociodemographics
Age (in years)	-	11.2 (3.2)	-	11.4 (3.5)	< 0.001	-			10.9 (3.1)	-		11.4 (3.4)	0.011
Boys	4,075 (74.6)	-	14,499 (74.7)	-	0.961	145 (71.8)			-	18,429 (74.7)		-	0.389
Deprivation: low	774 (14.2)	-	2,497 (12.9)	-	< 0.001	26 (12.9)			-	3,245 (13.2)		-	0.919
medium	3,659 (67.0)	-	12,613 (65.0)	-	< 0.001	136 (67.3)			-	16,136 (65.4)		-	0.919
high	983 (18.0)	-	4,166 (21.5)	-	< 0.001	39 (19.3)			-	5,110 (20.7)		-	0.919
Federal state: Western Germany	4,695 (86.0)	-	16,266 (83.8)	-	< 0.001	173 (85.6)			-	20,788 (84.2)		-	0.817
Eastern Germany	721 (13.2)	-	3,010 (15.5)	-	< 0.001	28 (13.9)			-	3,703 (15.0)		-	0.817
Regional ratio of paediatricians	-	9.4 (3.4)	-	9.5 (3.5)	0.004	-			9.1 (3.2)	-		9.5 (3.5)	0.074
of medical or psychological psychotherapists or child and adolescent psychiatrists	-	6.8 (5.6)	-	7.1 (5.7)	0.003	-			6.9 (5.4)	-		7.0 (5.7)	0.722
ADHD diagnosis, treatment and health care utilisation
ADHD-incident in 2020	1,355 (24.8)	-	5,237 (27.0)	-	0.002	46 (22.8)			-	6,546 (26.5)		-	0.741
Incident ADHD diagnosis: general practitioner	285 (5.2)	-	1,317 (6.8)	-	< 0.001	8 (4.0)			-	1,594 (6.5)		-	0.195
Incident ADHD diagnosis: paediatrician	988 (18.1)	-	3,720 (19.2)	-	0.079	32 (15.8)			-	4,676 (19.0)		-	0.302
Incident ADHD diagnosis: child and adolescent psychiatrist or psychotherapist or psychological psychotherapist	624 (11.4)	-	2,078 (10.7)	-	0.134	19 (9.4)			-	2,683 (10.9)		--	0.580
Incident ADHD diagnosis: other	705 (12.9)	-	2,402 (12.4)	-	0.296	27 (13.4)			-	3,080 (12.5)			0.785
ADHD diagnosis: inpatient	335 (6.1)	-	1,246 (6.4)	-	0.470	9 (4.5)			-	1,572 (6.4)		-	0.334
ADHD medication	3,001 (55.0)	-	8,489 (43.7)	-	< 0.001	84 (41.6)			-	11,406 (46.2)		-	0.213
Behavioural therapy	1,620 (29.7)	-	4,952 (25.5)	-	< 0.001	60 (29.7)			-	6,512 (26.4)		-	0.325
Utilisation of child and adolescent psychiatrist or psychotherapist or psychological psychotherapist (yes/no)	3,341 (61.2)	-	10,601 (54.6)	-	< 0.001	112 (55.5)			-	13,830 (56.0)		-	0.921
Utilisation of child and adolescent psychiatrist or psychotherapist or psychological psychotherapist (frequency)	-	3.5 (3.8)	-	2.9 (3.5)	< 0.001	-			3.2 (3.9)	-		3.0 (3.5)	0.465
Number of prescribed medications in 2020	-	4.6 (3.6)	-	4.5 (3.7)	0.207	-			4.7 (3.4)	-		4.5 (3.7)	0.445
Note. Numbers not summing up to total due to missing data.
^a Responders minus excluded subjects due to missing information for ADHD diagnosis, completion time of less than 657 sec, more than 50% missing values, answered unsuitable questionnaire or inconsistency.

Youths participating in the clinical assessment were slightly younger than non-participants (Table 2). There were no other differences between participants and non-participants.

[insert Table 2]

Representativity of the survey and weighting

Children and adolescents insured with DAK-Gesundheit can be regarded as approximately representative of the German child and adolescent population. Comparisons show only slight deviations between eastern Germany (+ 1.9%) and western Germany (-1.9%) (37). To evaluate representativeness with regard to population with an administrative ADHD diagnosis, nationwide data from the Central Institute of Statutory Health Insurance Physicians (Zi) pertaining to outpatient care (here based on the M2Q criterion) available for the years 2015 and 2016 (38) were compared with the INTEGRATE-ADHD gross sample. There were only slight deviations with regard to gender (boys: -1.4% for, girls: +3.1%). Younger subjects, however, were over- and older subjects were underrepresented in the INTEGRATE-ADHD gross sample (5- to 6-year-olds: +5.3% and 7- to 8-year-olds: +13.4%; 11- to 12-year-olds: -7.9%; 13- to 14-year-olds: -12.5%).

In order to adjust for deviations of the online net sample from the gross sample, population weights were calculated normalising the online net sample to the gross sample. The population weights are determined by the inverse probability that a person will participate in the study. People with a low probability of participation represent more people from the population than people with a high probability of participation. To determine the weighting factor, a logistic regression model was fitted, which included variables according to non-responder analysis. The online weights were calculated using the R-packages survey, srvyr und svrep (39).

A weight for the clinical sample was only calculated for subjects for whom a clinical best-estimate judgement was possible (n = 201, see above). The clinical weight represents thus the inverse probability of this judgement multiplied with the weight of the online survey. The probability was predicted through a logistic regression model. To adjust for the oversampling of the ED– group in the clinical sampling procedure, the information whether or not the parents reported an ADHD diagnosis for their child was included in the model. Also, an interaction term between gender and the parental-report was included because the diagnosis was reported more often for boys than for girls. This model was then weighted with the online weight in order to adjust the clinical subsample to the gross sample.

Sample characteristics

Table 3 depicts the sociodemographic characteristics of the online sample and the clinical subsample. The unweighted mean age of children in the online sample was 12.5 years (SD = 3.22), weighted mean age was 12.6 years (SE = 0.05), the range was 2–19 years; 74.6% were male (weighted: 74.1%). The children in the clinical subsample were on average 12.1 years old (SD = 3.04), weighted mean age was 12.4 years (SE = 0.22), the range was 5–19 years; 72.1% were male (weighted: 74.1%). The majority of the parents displayed a medium level of education. In the online sample 6.3% had a migration background (weighted 6.5%), in the clinical subsample 5.0% (weighted 4.8%).

Table 3

Sample characteristics (on the basis of epidemiological and clinical data)
	Online sample			Clinical subsample
	n	%	%_weighted^a	n	%	%_weighted^b
		(95% CI)	(95% CI)		(95% CI)	(95% CI)
Number of participants	5,461			201^c
Age group^d
0–2 years	3	0.1 (0.0-0.2)	0.1 (0.0-0.2)	0	0.0	0.0
3–6 years	167	3.1 (2.6–3.5)	3.5 (3.0–4.0)	10	5.0 (2.7-9.0)	3.7 (1.9–7.1)
7–10 years	1,351	24.7 (23.6–25.9)	24.3 (23.1–25.4)	50	24.9 (19.4–31.4)	22.7 (17.1–29.3)
11–13 years	1,827	33.4 (32.2–34.7)	31.2 (30.0-32.5)	74	36.8 (30.4–43.7)	35.8 (29.1–43.1)
14–17 years	1,770	32.4 (31.2–33.7)	33.4 (32.2–34.8)	60	29.8 (23.9–36.6)	33.5 (26.7–41.2)
18–19 years	343	6.3 (5.7-7.0)	7.5 (6.8–8.3)	7	3.5 (1.7–7.2)	4.3 (2.0-9.1)
Gender
Female	1,386	25.4 (24.2–26.6)	25.9 (24.7–27.1)	56	27.9 (22.1–34.5)	25.9 (20.1–32.7)
Male	4,075	74.6 (73.4–75.8)	74.1 (72.9–75.3)	145	72.1 (65.5–77.9)	74.1 (67.3–79.9)
Parental education (CASMIN)
Low education	560	10.8 (10.0-11.7)	10.4 (9.6–11.3)	14	7.0 (4.2–11.4)	7.5 (4.3–12.6)
Medium education	3,271	63.1 (61.8–64.4)	63.2 (61.9–64.5)	128	63.7 (56.8–70.1)	65.2 (57.8–71.9)
High education	1,355	26.1 (24.9–27.3)	26.4 (25.1–27.6)	59	29.3 (23.4–36.1)	27.3 (21.3–34.4)
Migration background
Migration background (two-sided)	332	6.3 (5.7-7.0)	6.5 (5.9–7.3)	10	5.0 (2.7-9.0)	4.8 (2.5–8.9)
No migration background	4,948	93.7 (93.0-94.3)	93.5 (92.7–94.1)	191	95.0 (91.0-97.3)	95.2 (91.1–97.5)
Note. Numbers not summing up to total due to missing data; CASMIN = Comparative Analysis of Social Mobility in Industrial Nations; CI = Confidence interval.
%_weighted^a = percentage weighted for the online survey; %_weighted^{b =} clinical weight.
^cThe clinical weight was only calculated for subjects for whom a clinical best-estimate judgement was possible (n = 201 out of n = 202). For reasons of comparability, the unweighted percentages were calculated on the basis of 201 persons.
^dage group at the time of the online survey.

[insert Table 3]

On the basis of a large and largely representative sample, the consortium project INTEGRATE-ADHD offers an innovative and − to the best of our knowledge─so far unique synopsis of administrative, epidemiological and clinical data on the diagnosis and health care of children and adolescents with ADHD in Germany. Additionally, the project allows for the examination of treatment satisfaction and direct ADHD-associated health care costs. The joint analysis of this three-dimensional data set makes it possible to pursue the following main goals of this project:

To evaluate administrative and epidemiological ADHD diagnostic data through clinical assessment,
To improve thereby the basis for population-based prevalence estimations of child and adolescent ADHD in Germany,
To gain objectifiable statements about potential over- or misdiagnosis of ADHD,
To identify potential deficits in the diagnostics and health care of children and adolescents with ADHD and their families,
To evaluate treatment satisfaction and the use and potential barriers of relevant health care services.

The results will contribute to the identification of fields of action for health policy and actors in the health care sector. Furthermore, recommendations will be derived for improving the diagnosis and treatment of children and adolescents with ADHD and their families. The results will be made available both to the relevant health policy decision-makers and stakeholders in the health care systems and to the public.

ADHD	Attention-deficit/hyperactivity disorder
ASRS AWMF	ADHD Self-Report Scale Association of the Scientific Medical Societies in Germany
BELLA	Mental health module of KiGGS
CASMIN	Comparative Analysis of Social Mobility in Industrial Nations
CBCL	Child Behavior Checklist
CES-DC	Centre for Epidemiological Studies Depression Scale for Children
CGI-S	Clinical Global Impressions Scale
CPT	Continuous Performance Test
DADYS-Screen	Diagnostic Tool for Affective Dysregulation in Children—Screening Questionnaire
DISYPS	Diagnostic System for Mental Disorders in Childhood and Adolescence
ED+	Youths with epidemiologically parent-reported ADHD diagnosis
ED-	Youths without epidemiologically parent-reported ADHD diagnosis
FBB-ADHS	“Fremdbeurteilungsbogen für Aufmerksamkeitsdefizit-/Hyperaktivitätsstörungen“
GISD	German Index of Deprivation
ICD	International Statistical Classification of Diseases and Related Health Problems
ILF(-EXTERNAL)	“Interviewleitfaden (für Externale Störungen)”
KiGGS	German Health Interview and Examination Survey for Children and Adolescents
Kinder-DIPS	Diagnostic Interview for Psychiatric Disorders in Children and Adolescents
MAS	“Multiaxiales Klassifikationsschema”
PIN	Personal identification number
PROMIS	Patient Reported Outcomes Measurement Information System
SBB-ADHS	“Selbstbeurteilungsbogen für Aufmerksamkeitsdefizit-/Hyperaktivitätsstörungen“
SCARED	Screen for Child Anxiety-Related Emotional Disorders
SDQ	Strengths and Difficulties Questionnaire
SCL-K-9	Short version of the Symptom Checklist
Zi	Central Institute of Statutory Health Insurance Physicians

Consent for publication

Not applicable

Competing Interests

PH lists the following research grants and contracts with organisations and institutions for the past 36 months: German Ministry of Research and Education; European Union; German Parkinson Society; University Hospital Würzburg; German Heart Foundation; Federal Joint Committee (G-BA) within the Innovationfond; German Research Foundation; Bavarian State; German Cancer Aid; Charité - Universitätsmedizin Berlin (within Mondafis; supported by an unrestricted research grant to the Charité from Bayer); University Göttingen (within FIND-AF randomized; supported by an unrestricted research grant to the University Göttingen from Boehringer-Ingelheim); University Hospital Heidelberg (within RASUNOA-prime; supported by an unrestricted research grant to the University Hospital Heidelberg from Bayer, BMS, Boehringer-Ingelheim, Daiichi Sankyo). MR is a board member of the national self-help organisation ADHS Deutschland e.V.All other authors declare that there is no conflict of interest.

Funding

This work was supported by the German Innovation Fund of the German Federal Joint Committee [01VSF19014]. Principal investigator is Robert Schlack. The funder had no role in the design of this study and will not have any role during its execution, analyses, interpretation of the data, or decision to submit results.

Author Contribution

RS, HH, TJ, MR, AK, URS, JuW, WG, AH, PH and CR conceptualized and prepared the study. AKB coordinated the study’s implementation and the field work. RK, MG, JoW, AG, CF and PH developed the sampling procedure, provided statistical support and coordinated the data quality assurance. AKB, LN, RS, MG, AK and URS designed the questionnaire and assessed the online data. LHe, SW, VS, TE, DH, SU, CW, AB, TJ and MR designed the clinical assessment and assessed the clinical data. CR, JuW, LHa, KW and WG provided and managed the administrative data. AKB, LB, RK, JoW, AG and CF, prepared and analysed the data. AKB, LB, LN, RS, LHe, TJ, MG, JuW, LHa, JoW and CF drafted the manuscript, RK, HH, SP, AB, SW, VS, MR, AK, URS, KW, WG, AG, AH, PH and CR revised it critically and provided specific knowledge. AKB, RS, TJ, SW, VS, AK, JuW, KW, JoW and CF made substantial contributions to writing of the final manuscript. All authors read and approved the final manuscript. All authors confirm that they are personal accountable for all aspects of the work and ensure that questions relating to the accuracy or integrity of any part of the work are accurately resolved.

Acknowledgement

The authors would like to thank Julia Wolff and Christoph Schlage from the Department of Epidemiology and Health Monitoring at the Robert Koch Institute for their assistance in conducting the study and preparing the data, as well as Elke Hack and Paula Franz from the Department of Child and Adolescent Psychiatry at the University Hospital Würzburg for their assistance in recruitment and organisation of the clinical assessment. We would also like to thank all participants in the study.

Data Availability

There are access restrictions for the datasets generated and analysed during the current study. The administrative data may not be made publicly accessible. In addition, the use of the administrative data is limited in time.

Data protection, ethics approval and consent to participate

The data protection provisions of the EU General Data Protection Regulation and the German Federal Data Protection Act were strictly adhered to when conducting the study. In addition, the World Medical Association Declaration of Helsinki – Ethical Principles for Medical Research Involving Human Subjects was strictly considered. The study was reviewed and ethically approved by the Ethics Committee of the University of Würzburg (24 March 2021; reference number 249/20) and retrospectively registered with the German Clinical Trials Registry (study number DRKS00028866). The participants were informed about the objectives and content of the study as well as about data protection, and informed consent was obtained from the parents. Children and adolescents aged 14 and older had to give their informed consent for their parents to provide information about them in the online survey. For the clinical assessment, both the parents and children aged 8 years and older gave their written informed consent.

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Competing interest reported. PH lists the following research grants and contracts with organisations and institutions for the past 36 months: German Ministry of Research and Education; European Union; German Parkinson Society; University Hospital Würzburg; German Heart Foundation; Federal Joint Committee (G-BA) within the Innovationfond; German Research Foundation; Bavarian State; German Cancer Aid; Charité - Universitätsmedizin Berlin (within Mondafis; supported by an unrestricted research grant to the Charité from Bayer); University Göttingen (within FIND-AF randomized; supported by an unrestricted research grant to the University Göttingen from Boehringer-Ingelheim); University Hospital Heidelberg (within RASUNOA-prime; supported by an unrestricted research grant to the University Hospital Heidelberg from Bayer, BMS, Boehringer-Ingelheim, Daiichi Sankyo). MR is a board member of the national self-help organisation ADHS Deutschland e.V. All other authors declare that there is no conflict of interest.

The consortium project INTEGRATE-ADHD - Comparison and integration of administrative and epidemiological ADHD diagnostic data by clinical assessment: study description and sample characteristics

Status:

Version 1

Abstract

Background

Methods

Results

Conclusion

Figures

Background

Design and methods

Inclusion criteria and case definitions

Sampling and conduct of the online sample

Sampling and conduct of the clinical subsample

Topics and instruments of the online survey

[insert Table 1]

Topics and instruments of the online clinical assessment

Topics and data processing of the administrative data

Data-linkage

Results

Response and non-responder analysis

[insert Table 2]

Representativity of the survey and weighting

Sample characteristics

[insert Table 3]

Discussion

Conclusion

List of abbrevations

Declarations

Consent for publication

Competing Interests

Funding

Author Contribution

Acknowledgement

Data Availability

Data protection, ethics approval and consent to participate

References

Additional Declarations

Status:

Version 1