Trends in the Diagnostic Prevalence of Mental Disorders, 2012–2022

Using nationwide outpatient claims data for mental health surveillance

Background: Evaluations by the statutory health insurance carriers in Germany have revealed a rising prevalence of diagnoses of mental disorders, at varying levels and to varying extents. For mental health surveillance purposes, we analyzed prevalence trends across health insurance carriers, before and during the COVID-19 pandemic and stratified by diagnosis group, sex and age.

Methods: Nationwide outpatient claims data of all statutorily insured individuals for the years 2012–2022 (N_min = 68.7 million people, N_max = 73.7 million people) were used to determine the diagnostic prevalence of mental disorders (ICD-10 F00–F99 and five selected diagnosis groups), with stratification by sex and age. Changes over time in the spectrum of all documented mental disorders are described.

Results: Over the period 2012–2022, the percentage of people with outpatient diagnoses of mental disorders rose from 33.4% to 37.9% (a relative increase of 13.4%). In the selected diagnosis groups, the trends ranged from –11.6% to +115.8% and were generally steady over time, though stronger or stagnating trends were seen in some groups from 2020 onward. Diagnostic prevalence rose to a greater extent in male (+18.3%) than in female individuals (+10.8%) over the period 2012–2022. The greatest increases (> +15%) were seen among 11- to 17-year-olds and in 60- to 84-year-olds. The composition of the diagnosis spectrum was more stable in adults than in children and adolescents.

Conclusion: Trends in diagnostic prevalence differ across mental disorders and population subgroups and have changed in some diagnosis groups since the COVID-19 pandemic. Contextualizing research is needed for a better understanding of these developments.

The aim of Mental Health Surveillance (MHS) at the Robert Koch Institute in Germany is to continuously and systematically monitor mental health trends in the population (1, 2). For core indicators of the state of health, time series that provide current results and classify these into long-term trends are to be made available. This makes it possible to detect abnormal trends and draw conclusions regarding the need for research or action.

Diagnostic prevalence as an indicator in Mental Health Surveillance

One of the core indicators of population mental health is the frequency of mental disorders (3). The prevalence of these in the adult population was last determined in 2009–2012 by means of a survey conducted by the national health monitoring system based on a clinical interview (4). To supplement this, one can also look at the administrative prevalence, referred to hereinafter as diagnostic prevalence. This reflects the role that diagnoses of mental disorders play in medical and psychotherapeutic treatment, documentation, and billing (5). As shown in comparative studies (6, 7, 8, 9, 10), diagnostic prevalence permits conclusions to be drawn to only a limited extent on the prevalence of disorders in the population—not least since not all patients seek medical or psychotherapeutic help (11), and in many cases, mental disorders are either not recorded or are overdiagnosed by health care professionals (12, 13, 14, e1, e2, e3, e4). Thus, diagnostic prevalence rates are an equivocal indicator of health care provision and use, which is nonetheless frequently used—both internationally (15, 16, 17) and in psychiatry reporting by the German federal states (18, 19). According to expert consensus, nationwide MHS should also report diagnostic prevalence rates, with five diagnostic groups prioritized to date for reporting in adulthood (3).

Trends in the diagnostic prevalence of mental disorders in Germany

Results on trends in the annual diagnostic prevalence of mental disorders in Germany all show significant changes over time, albeit to varying degrees and with different baseline levels. For example, (mostly outpatient) data from individual health insurance carriers show increases in depression, for example from 12 to 16.3% of insured individuals in 2006–2015 (20) and from 11.7 to 12.2% in 2017–2021 (21). For recurrent depression, relative changes of +81.7% were found in 2010–2020 (22). Increases were also reported for the overall group of mental disorders, for example from 21.4% to 30.5% in 2009–2013 (10) and from 32.9% to 39% in 2010–2022 (23). Nationwide outpatient diagnosis data also show similar trends for depression (24, e5) and mental disorders in children and adolescents (25).

Special analyses for the period of the COVID-19 pandemic indicate considerable monthly fluctuations, for example, for anxiety disorders, with increases compared to the same month of the previous year of between +34% in March 2020, but only +2% in May 2020 (26, e6, e7). At the annual level, a slight decline in F diagnoses overall (–0.7%) (27) and a further increase in depression (+1.8%) (22) were observed in the 2019–2020 period.

Since the abovementioned analyses differ in terms of methodology and topic, it has not been possible as yet to draw comprehensive and comparative conclusions regarding multiple diagnostic and population groups over time, which also makes it difficult to classify more recent trends during the period of the pandemic.

Aim of the article

Building on previous works (24, 25), this article uses the nationwide claims data of all individuals insured through German statutory health insurance (SHI) for MHS. For the reporting years 2012–2022, the following questions will be investigated for the overall group of mental disorders as well as for selected diagnosis groups:

• What is the trend in diagnostic prevalence over time?
• Do annual prevalence rates and their trends differaccording to sex and age?
• What percentage of the spectrum of diagnoses in children/adolescents and adults is accounted for by the selected as well as other diagnosis groups?

Methods

Data basis

Nationwide pseudonymized outpatient claims data according to Section 295 of the German Social Code V [SGB V]) of all SHI-insured individuals for the years 2012–2022 who used SHI-authorized medical services (including SHI-authorized psychotherapy) in the respective years were evaluated. This overall population included a total of 68.7 million individuals in 2021 and 73.7 million in 2022. The data include, among other things, outpatient diagnoses according to the German modification of the International Classification of Diseases (ICD-10-GM) (28) as well as information on the age and sex of the individuals.

Case definitions

Mental disorders were investigated based on F00–F99 diagnoses in Chapter V of the ICD-10-GM (referred to hereinafter as F diagnoses). In addition to the overall group (F00–F99), the diagnosis groups agreed upon for MHS in adulthood were considered (3): depression (F32, F33, F34.1), anxiety disorders (F40, F41), posttraumatic stress disorder (F43.1; PTSD), schizophrenia, schizotypal and delusional disorders (F2), as well as mental and behavioral disorders due to psychoactive substance use (F1; referred to hereinafter as substance-related disorders) (3). Only diagnoses coded as “confirmed” were included. In order to also include disorders with a short-term or episodic course, diagnoses were taken into consideration even if they were documented only once a year. In addition, individuals with diagnoses in at least two quarters per year were considered.

Statistical analysis

Prevalence rates were calculated as the percentage of individuals with a relevant diagnosis in the overall population of that year and reported as observed values. To control for annual age and sex differences in the data, prevalence rates were standardized using official statistics from the German Federal Ministry of Health (KM6 statistics) for all SHI-insured individuals in 2012 (29, e8). Analyses were generally performed in relation to the year and were partly stratified by sex and age group. Intra-year fluctuations were shown by means of quarterly analyses. The spectrum of diagnoses was depicted by the percentage of diagnosis groups at the three-digit ICD-code level out of all F diagnoses documented in 2012 and 2022. Analyses were performed using Oracle SQL Developer.

Results

Diagnostic prevalence of mental disorders in 2012–2022

In the 2012–2022 period, the percentage of individuals with outpatient diagnoses of mental disorders rose from 33.4 to 37.9% (Figure 1). In 2022, 27.9 million individuals were documented as having at least one relevant diagnosis, which constitutes an increase by +13.4% or +5.0 million compared to 2012 (Figure 2).

Figure 1

Diagnostic prevalence of mental disorders in 2012 and 2022, overall and for selected diagnosis groups

Figure 2

Relative change in the diagnostic prevalence of mental disorders in 2012–2022, overall and for selected diagnosis groups

Among the selected diagnosis groups, the percentage of people with a diagnosis of depression was the highest over the entire observation period (2012: 12.1%; 2022: 13.9%; +14.7%). In contrast, diagnoses of anxiety disorders (2012: 5.1%; 2022: 6.7%) and substance-related disorders (2012: 5.6%; 2022: 7.5%) were documented less frequently, but increased more markedly over time (+30.7% and +35.3%, respectively). The lowest diagnostic prevalence but strongest growth was seen for PTSD (2012: 0.4%; 2022: 0.9%; +115.8%). The prevalence of schizophrenia, schizotypal and delusional disorders was also low, but showed a downward trend (2012: 1.1%; 2022: 0.9%; –11.6%).

The absolute trends are comparable if one considers only individuals with a documented diagnosis in at least two quarters per year (eTable 1). The percentage of these in the overall group of mental disorders is 22.1% in 2012 and 27.0% in 2022. Individuals with a documented diagnosis in only one quarter account for a smaller percentage of all cases in 2022 (28.8%) compared to 2012 (33.8%).

eTable 1

Diagnostic prevalence of mental disorders in 2012 and 2022 for individuals with documentation of a diagnosis in ≥ 1 quarter per year (M1Q) and documentation of a diagnosis in ≥ 2 quarters per year (M2Q) as well as the share for documentation of a diagnosis in exactly one quarter per year relative to M1Q, overall and for selected diagnosis groups

Over the 11-year observation period, trends were largely constant, whereby annual changes fluctuated and, towards the end, more frequently stagnated (Figure 2). For example, diagnoses of depression and substance-related disorders decreased slightly in 2020. In 2022, the diagnostic prevalence of anxiety disorders also declined, as did that of the overall group of all mental disorders.

Supplementary analyses at the quarterly level show that in 2020–2022, the direction of the trend fluctuated particularly widely within a year (eFigure 1). Quarterly prevalence rates varied multiple times over the entire period. However, more diagnosis groups were affected by pronounced short-term rises and falls in diagnostic prevalence in 2020–2021, with these being comparatively marked and frequent. Here, maximum absolute changes were 1.1 percentage points in the overall group and 0.6 percentage points in the selected diagnosis groups.

If one controls for changes in the age and gender distribution of the 2012–2022 population by standardization, the absolute and relative increases for all mental disorders (+4.5 percentage points and +13.6%, respectively) remain virtually at the level of the observed (raw) values of +4.8 percentage points and +14.5% (Table). Standardization also had only minor effects in the diagnosis groups (eTable 2).

Table

Diagnostic prevalence of mental disorders overall in 2021 and 2022, as observed and standardized as well as by sex and age groups

Differences according to sex and age groups

In the overall group of mental disorders as well as in depression, anxiety disorders, and PTSD, females showed higher diagnostic prevalence rates than did males (Table, eTable 2). For substance-related disorders, the distribution was reversed. Since diagnostic prevalence increased more sharply among males (overall group: +18.3%) than among females (+10.8 %), gender differences were smaller in 2022 than in 2012, with the exception of substance-related disorders.

When comparing age groups, the prevalence rates in the diagnosis groups considered here were almost always lowest in childhood and adolescence. The highest diagnostic prevalence rates were found either in the oldest age groups (overall group of mental disorders, depression, schizophrenia, schizotypal and delusional disorders) or in the middle-aged groups (PTSD, anxiety and substance-related disorders). In 2012–2022, the highest increase of +15% in the overall group of all mental disorders was seen in the 11- to 17-year and the 60- to 84-year age ranges. Age-specific trends differed between diagnosis groups and were largely comparable for both sexes (eFigure 2a–f).

Spectrum of diagnoses in 2012 versus 2022

If one looks at the spectrum of all documented diagnoses of mental disorders in adults, slightly more than half of these belonged to the diagnosis groups selected for MHS (2012: 55.0%; 2022: 56.4%) (Figure 3a, eTable 3a). The composition of the remaining spectrum of diagnoses also remained stable over time and relative percentages barely changed. Alongside the MHS diagnosis groups, somatoform disorders (F45; 2012: 14.8%; 2022: 14.0%) as well as reactions to severe stress and adjustment disorders (F43; 2012: 6.3%; 2022: 7.1%) were most commonly documented.

Figure 3a

Spectrum of diagnoses for all documented mental disorder diagnoses in adults (≥ 18 years) in 2012 versus 2022, percentage of selected MHS diagnosis groups and 10 most common other diagnoses

In the pediatric and adolescent age group, on the other hand, the selected diagnosis groups accounted for only 4.9% (2012) and 6.1% (2022) (Figure 3b, eTable 3b). Here again, the composition of the remaining 10 most common diagnosis groups did not change, but their shares shifted more over time than in adults: The majority of diagnoses related to specific developmental disorders of speech and language (F80; 2012: 24.3%; 2022: 27.4%) and hyperkinetic disorders (F90; 2012: 15.1%; 2022: 10.7%).

Figure 3b

Spectrum of diagnoses for all documented mental disorder diagnoses in children and adolescents (< 18 years) in 2012 versus 2022, percentage of selected MHS diagnosis groups and 10 most common other diagnoses

Discussion

Diagnostic prevalence of mental disorders in 2012–2022

The diagnostic prevalence of mental disorders shows a significant increase at a high level from 33.4% to 37.9% in outpatient care in 2012–2022. Thus, the data for all SHI-insured individuals confirm the trend reported by individual health insurance carriers (10, 23) or show it to be less serious (22). If only people with diagnoses documented in two quarters are taken into account, the increase is at a significantly lower level from 22.1% to 27.0%, but nevertheless comparable.

Accordingly, the trends cannot be explained by a stronger increase in diagnoses that are documented only in one quarter and whose validity is therefore considered as particularly doubtful. Changes in the age and gender structure of the 2012–2022 population are also unable to explain the trends in the diagnostic prevalence of mental disorders. Instead, any interpretation of the trend over time needs to take additional influencing factors into consideration. For example, medical and psychotherapeutic diagnoses of mental disorders rise when, as a result of destigmatization and patient education or a cultural shift in dealing with mental health combined with an expansion in SHI-authorized care (30), more people seek outpatient help (31) and more health professionals are more likely to identify and document mental disorders appropriately—or overdiagnose them (12, 13, 14, e1, e2, e3, e4). At the same time, rising diagnostic prevalence rates can indicate morbidity dynamics in the population, for example, increasing rates of new cases and recurrences or falling mortality.

As a result, the observed trends can be regarded neither as welcome nor as worrying, since any reliable interpretation depends on comprehensive contextualizing evidence in the field of public mental health. However, there is a lack of epidemiological studies in Germany on the trend in the prevalence of mental disorders in the population over the observation period. The currently observed increase in symptoms of depression and anxiety in adults since 2019 and 2021 (32) does not yet appear to have translated into a rise in outpatient diagnostic prevalence, at least not up to 2022. Even in the absence of a clear evaluation, the results presented here are able to draw attention to noteworthy trends, such as those mentioned below, and thus stimulate in-depth research or discussion.

Changes in trends in 2020–2022

Following predominantly consistent trends in the 2012–2019 period, trends became more heterogeneous from 2020 onwards. The annual prevalence rates for 2020–2022 are based on opposing trends in individual quarters; however, these were small compared to the reported monthly fluctuations (26) and did not occur for the first time during the pandemic. At the annual level, there was a marked increase in diagnoses of anxiety disorder in 2020. Looking at 2022, one ultimately sees a stagnating trend for depression as well as anxiety and substance-related disorders and the overall group of mental disorders, despite the catch-up effects of the temporary reduction in the use of relevant psychotherapy and medical specialist groups caused by the pandemic (33). As suggested by other analyses (26, 34, 35), one should also investigate short-term changes in initial diagnoses (diagnostic incidence), which are able to reflect crisis-related dynamics more clearly than prevalent diagnoses.

Differences in trends between diagnosis, gender, and age groups

The comparison of selected diagnosis groups highlights the fact that prevalence trends differ according to the specific disorder. This also applies to the diagnostic incidence of mental disorders in children and adolescents (34). What is striking is the doubling of outpatient PTSD diagnoses and the declining trend observed only for schizophrenia, schizotypal and delusional disorders, which, moreover, were not affected by fluctuations in the 2020–2022 period. It is possible that this also has to do with the immigration of individuals with a higher prevalence of PTSD (for example, due to their experiences of war or flight) (36) or the sometimes presumed reinstitutionalization of people with severe mental disorders (37). The greater increases in diagnostic frequency among men compared to women may be related to the fact that men are becoming ever more active in seeking help as traditional role models fall away (38). Similarly, the age groups showing the strongest growth are predominantly those with a hitherto lower diagnostic prevalence, that is, adolescents, young adults, and individuals aged between 60 and 84 years. In children and adolescents, the increase in initial diagnoses of depressive and anxiety disorders is of considerable significance (34). Classifying the results of subgroups is always extremely complex, since the abovementioned determinants of diagnostic prevalence can vary depending on age, sex, and specific disorder (39).

Spectrum of diagnoses in 2012 versus 2022

The MHS diagnosis groups selected for surveillance in adults account for just over half of all documented diagnoses of mental disorders. A discussion can be had about extending the selection to include common diagnosis groups such as somatoform disorders and reactions to severe stress and adjustment disorders. In children and adolescents, on the other hand, MHS diagnosis groups cover only 5–6% of all documented F diagnoses. Therefore, in order to benefit the surveillance of mental health over the entire lifespan, a selection of relevant mental disorders in childhood and adolescence should also be investigated.

Strengths and limitations

Due to the complete data on which it is based, this study enables reliable statements on the care provided by SHI-authorized health care practitioners to approximately 70 million SHI-insured individuals across all age groups in Germany.

It is not possible to make a direct generalization of the study results to the population as a whole, but this is probably restricted only to a small extent: The data do not include diagnoses from inpatient and selective-contract care or from outpatient treatment in hospital. However, this only explains underreporting if the insured individuals concerned are not additionally treated by SHI-authorized health care practitioners. Furthermore, individuals who do not have SHI (2021: 11.9%) (40) and SHI-insured individuals who do not use outpatient services are excluded, whereby the latter is addressed by standardization according to KM6 statistics (see the Table and eTable 2).

Potential to optimize the analysis strategy lies in the selected case definitions, which could be differentiated, for example, by comparing substance-related disorders for each substance class. Trend analysis methods could enable changes over time to be localized (e9) and evaluated.

Résumé

Analyses of nationwide outpatient claims data show that diagnoses of mental disorders are continuously being documented for more than one in three people and thus significantly shape outpatient diagnostic reality in Germany. In 2012–2022, diagnostic prevalence underwent a marked change, with trends in the period of the pandemic becoming less steady. Trends differed between the mental disorders and population groups considered here. They will also require differentiated surveillance in the future. In order to be able to analyze trends over time, their causes should be examined at various levels, which can be the aim of a comprehensive MHS. For children and adolescents, age-specific surveillance of public health-relevant mental disorders is required. Continuation of the surveillance in the coming years will make it possible to determine whether the recent slowdown of the previously continuous rise can be deemed transient or lasting.

Funding

This article was prepared as part of the the project: “Aufbau einer nationalen Mental Health Surveillance am RKI (MHS)” (Developing National Diabetes Surveillance at the Robert Koch Institute [MHS]). It was funded by the German Federal Ministry of Health (Grant No. ZMI5–2519FSB402). Dr. Lukas Reitzle’s collaboration was as part of the project to develop and continue National Diabetes Surveillance at the Robert Koch Institute funded by the Federal Ministry of Health (Grant Nos.: GE20150323, GE20190305, and 2522DIA700). While the article was being finalized, funding was provided by the German Federal Ministry of Health as part of the project “Verlängerung des Projektes Aufbau einer Nationalen Diabetes-Surveillance mit Erweiterung zu einer NCD-Surveillance ” (Extension of the project Diabetes Surveillance with expansion to an NCD Surveillance) (Grant No.: ZMII2–2523DIA002). The analysis request submitted by the Robert Koch Institute was processed free of charge by the Central Research Institute of Ambulatory Health Care in Germany (Zentralinstitut für die kassenärztliche Versorgung in Deutschland).

Conflict of interest statement
The authors declare that no conflict of interest exists.

Manuscript submitted on 12 July 2023, revised version accepted on 4 March 2024.

Translated from the original German by Christine Rye.

Corresponding author
Dr. rer. medic. Julia Thom
Robert Koch-Institut
Abteilung für Epidemiologie und Gesundheitsmonitoring
General-Pape-Straße 62–66, 12101 Berlin, Germany

Cite this as
Thom J, Jonas B, Reitzle L, Mauz E, Hölling H, Schulz M: Trends in the diagnostic prevalence of mental disorders, 2012–2022—using nationwide outpatient claims data for mental health surveillance.. Dtsch Arztebl Int 2024; 121: 355–62. DOI: 10.3238/arztebl.m2024.0052

References

1. Galea S, Norris FH: Public mental health surveillance and monitoring. In: Norris FH GS, Friedman MJ, Watson PJ, (eds.): Methods for Disaster Mental Health Research. New York: Guilford Press 2006; p. 177–93.

2. Thom J, Walther L, Eicher S, et al.: Mental Health Surveillance am Robert Koch-Institut – Strategien zur Beobachtung der psychischen Gesundheit der Bevölkerung. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz 2023; 66: 379–90

3. Thom J, Mauz E, Peitz D, et al.: Aufbau einer Mental Health Surveillance in Deutschland: Entwicklung von Rahmenkonzept und Indikatorenset; J Health Monit 2021; 6: 36–68.

4. Jacobi F, Hofler M, Siegert J, et al.: Twelve-month prevalence, comorbidity and correlates of mental disorders in Germany: the Mental Health Module of the German Health Interview and Examination Survey for Adults (DEGS1-MH). Int J Methods Psychiatr Res 2014; 23: 304–19

5. Schubert I, Köster I, Küpper-Nybelen J, Ihle P: Versorgungsforschung mit GKV-Routinedaten. Nutzungsmöglichkeiten versichertenbezogener Krankenkassendaten für Fragestellungen der Versorgungsforschung. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz 2008; 51: 1095–105

6. Tannenbaum C, Lexchin J, Tamblyn R, Romans S: Indicators for measuring mental health: towards better surveillance. Healthc Policy 2009; 5: e177–86

7. Grobe TG, Kleine-Budde K, Bramesfeld A, Thom J, Bretschneider J, Hapke U: Prävalenzen von Depressionen bei Erwachsenen – eine vergleichende Analyse bundesweiter Survey- und Routinedaten. Gesundheitswesen 2019; 81: 1011–7

8. Thom J, Bretschneider J, Kraus N, Handerer J, Jacobi F: Versorgungsepidemiologie psychischer Störungen. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz 2019; 2019: 128–39

9. Holbrook JR, Bitsko RH, Danielson ML, Visser SN: Interpreting the prevalence of mental disorders in children: tribulation and triangulation. Health Promot Pract 2017; 18: 5–7

10. Jacobi F, Bretschneider J, Müllender S: Veränderungen und Variationen der Häufigkeit psychischer Störungen in Deutschland. Krankenkassenstatistiken und epidemiologische Befunde. In: Kliner K, Rennert D, Richter M, (eds.): Gesundheit in Regionen – Blickpunkt Psyche BKK Gesundheitsatlas 2015. Berlin: Medizinisch wissenschaftliche Verlagsgesellschaft 2015; p. 63–71.

11. Mack S, Jacobi F, Gerschler A, et al.: Self-reported utilization of mental health services in the adult German population—evidence for unmet needs? Results of the DEGS1-Mental Health Module (DEGS1-MH). Int J Methods Psychiatr Res 2014; 23: 289–303

12. Mitchell AJ, Vaze A, Rao S: Clinical diagnosis of depression in primary care: a meta-analysis. Lancet 2009; 374: 609–19

13. Piontek K, Shedden-Mora MC, Gladigau M, Kuby A, Lowe B: Diagnosis of somatoform disorders in primary care: diagnostic agreement, predictors, and comaprisons with depression and anxiety. BMC Psychiatry 2018; 18: 361

14. Davis KA, Sudlow CL, Hotopf M: Can mental health diagnoses in administrative data be used for research? A systematic review of the accuracy of routinely collected diagnoses. BMC Psychiatry 2016; 16: 263

15. Forslund T, Kosidou K, Wicks S, Dalman C: Trends in psychiatric diagnoses, medications and psychological therapies in a large Swedish region: a population-based study. BMC Psychiatry 2020; 20: 328

16. Tkacz J, Brady BL: Increasing rate of diagnosed childhood mental illness in the United States: Incidence, prevalence and costs. Public Health Pract (Oxf) 2021; 2: 100204

17. World Health Organization: European Health Information Gateway: indicator „prevalence of mental disorders (%)“. www.gateway.euro.who.int/en/indicators/hfa_391–2410-prevalence-of-mental-disorders/#id=19322 (last accessed on 19 December 2023).

18. Blank D, Redel R, Tauscher M, Kuhn J: Mental Health Surveillance auf Länderebene – Psychiatrieberichterstattung in Bayern. J Health Monit 2021; 6: 69–75.

19. Landeszentrum Gesundheit Nordrhein-Westfalen: Gesundheitsberichterstattung. Factsheets zur Gesundheit der Bevölkerung. Depression. www.lzg.nrw.de/ges_bericht/factsheets/psyche/depression/index.html (last accessed on 19 December 2023).

20. Stahmeyer JT, Kuhlmann K, Eberhard S: Die Häufigkeit von Depressionsdiagnosen nach Versichertengruppen im Zeitverlauf – eine Routinedatenanalyse der Jahre 2006–2015. Psychother Psych Med 2019; 69: 72–80

21. Wissenschaftliches Institut der AOK: Gesundheitsatlas Deutschland. Psychische Erkrankungen – Depression. www.gesundheitsatlas-deutschland.de/erkrankung/depressionen?activeValueType=praevalence&activeLayerType=state (last accessed on 19 December 2023).

22. KKH – Kaufmännische Krankenkasse: Corona-Effekt? Starker Anstieg bei Depressionen. www.kkh.de/presse/pressemeldungen/depression (last accessed on 19 December 2023).

23. BARMER Institut für Gesundheitssystemforschung: Personen mit ambulant dokumentierten Diagnosen nach Diagnosekapiteln. www.bifg.de/publikationen/reporte/arztreport/arztreport-ambulante-diagnosen-nach-diagnosekapiteln (last accessed on 19 December 2023).

24. Steffen A, Holstiege J, Akmatov MK, Bätzing J: Zeitliche Trends in der Diagnoseprävalenz depressiver Störungen: eine Analyse auf Basis bundesweiter vertragsärztlicher Abrechnungsdaten der Jahr 2009 bis 2017. Versorgungsatlas-Bericht Nr. 19/05. Berlin: Zentralinstitut für die kassenärztliche Versorgung in Deutschland (Zi); 2019.

25. Steffen A, Akmatov MK, Holstiege J, Bätzing J: Diagnoseprävalenz psychischer Störungen bei Kindern und Jugendlichen in Deutschland: eine Analyse bundesweiter vertragsärztlicher Abrechnungsdaten der Jahre 2009 bis 2017. Versorgungsatlas-Bericht Nr. 18/07. Berlin: Zentralinstitut für die kassenärztliche Versorgung in Deutschland (Zi); 2018.

26. Jacob L, Smith L, Koyanagi A, et al.: Impact of the coronavirus 2019 (COVID-19) pandemic on anxiety diagnosis in general practices in Germany. J Psychiatr Res 2020; 143: 528–33

27. Grobe TG, Braun A, Szecsenyi J: BARMER Arztreport 2022. Berlin: BARMER; 2022.

28. Bundesinstitut für Arzneimittel und Medizinprodukte (BfArM) im Auftrag des Bundesministeriums für Gesundheit (BMG) unter Beteiligung der Arbeitsgruppe ICD des Kuratoriums für Fragen der Klassifikation im Gesundheitswesen (KKG): ICD-10-GM, Version 2022, internationale statistische Klassifikation der Krankheiten und verwandter Gesundheitsprobleme, 10. Revision. 2022. www.bfarm.de/SharedDocs/Downloads/DE/Kodiersysteme/klassifikationen/icd-10-gm/version2022/icd10gm2022syst-pdf_zip.html (last accessed on 19 December 2023).

29. Bundesministerium für Gesundheit (BMG): KM6-Statistik: Mitglieder und mitversicherte Familienangehörige der gesetzlichen Krankenversicherung nach Altersgruppen und Geschlecht, Land, Jahr (Indikator 10.18). In: Ministerium für Gesundheit, Soziale, Frauen und Familie des Landes Nordrhein-Westfalen, (ed.): Indikatorensatz für die Gesundheitsberichterstattung der Länder 2003; p. 696–9.

30. Bramesfeld A: Die Versorgung von Menschen mit psychischen Erkrankungen in Deutschland aus Perspektive des Gesundheits- und Sozialsystems: Aktuelle Entwicklungsbedarfe. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz 2023; 66: 363–70

31. Picco L, Abdin E, Pang S, et al.: Association between recognition and help-seeking preferences and stigma towards people with mental illness. Epidemiol Psychiatr Sci 2018; 27: 84–93

32. Robert Koch-Institut: Dashboard der Mental Health Surveillance. Beobachtung der psychischen Gesundheit der erwachsenen Bevölkerung in Deutschland. https://public.data.rki.de/t/public/views/hf-MHS_Dashboard/Dashboard?%3Aembed=y&%3AisGuestRedirectFromVizportal=y (last accessed on 19 December 2023).

33. Mangiapane S, Kretschmann J, Czihal T, von Stillfried D: Veränderung der vertragsärztlichen Leistungsinanspruchnahme während der COVID-Krise. Tabellarischer Trendreport bis zum 1. Halbjahr 2022. Berlin: Zentralinstitut für die kassenärztliche Versorgung in Deutschland (Zi); 2022.

34. Kohring C, Akmatov MK, Holstiege J, Heuer J, Dammertz L, Bätzing J: Inzidenztrends psychischer sowie Entwicklungs- und Verhaltensstörungen bei Kindern und Jugendlichen in der ambulanten Versorgung – Entwicklungen zwischen 2014 und 2021. Versorgungsatlas-Bericht Nr. 23/05. Berlin: Zentralinstitut für die kassenärztliche Versorgung in Deutschland (Zi); 2023.

35. Bohlken J, Kostev K, Riedel-Heller S, Hoffmann W, Michalowsky B: Effect of the COVID-19 pandemic on stress, anxiety, and depressive disorders in German primary care: a cross-sectional study. J Psychiatr Res 2021; 143: 43–9

36. Blackmore R, Boyle JA, Fazel M, et al.: The prevalence of mental illness in refugees and asylum seekers: a systematic review and meta-analysis. PLoS Med 2020; 17: e1003337

37. Winnie SC, Stefan P: How has the extent of institutional mental healthcare changed in Western Europe? Analysis of data since 1990. BMJ Open 2016; 6: e010188

38. Seidler ZE, Dawes AJ, Rice SM, Oliffe JL, Dhillon HM: The role of masculinity in men‘s help-seeking for depression: a systematic review. Clin Psychol Rev 2016; 49: 106–18

39. Askari MS, Mauro PM, Kaur N, Keyes KM: Age, period, and cohort trends in perceived mental health treatment need and differences by mental health severity in the United States, 2008–2019. Community Ment Health J 2023; 59: 631–40

40. Gesundheitsberichterstattung des Bundes: Versicherungsabdeckung. www.gbe-bund.de:443/gbe/pkg_olap_tables.prc_archiv?p_indnr=814&p_archiv_id=5236125&p_sprache=D (last accessed on 19 December 2023).

e1. Aragones E, Pinol JL, Labad A: The overdiagnosis of depression in non-depressed patients in primary care. Fam Pract 2006; 23: 363–8

e2. Pilars de Pilar M, Abholz HH, Becker N, Sielk M: Was erzählen Hausärzte über ihre Patienten, bei denen sie eine vorliegende Depression nicht diagnostiziert haben? Eine qualitative Studie. Psychiatr Prax 2012; 39: 71–8

e3. Sielk M, Altiner A, Janssen B, Becker N, Pilars M, Abholz HH: Prävalenz und Diagnostik depressiver Störungen in der Allgemeinarztpraxis. Psychiatr Prax 2009; 36: 169–74

e4. Castro-Rodriguez JI, Olariu E, Garnier-Lacueva C, et al.: Diagnostic accuracy and adequacy of treatment of depressive and anxiety disorders: a comparison of primary care and specialized care patients. J Affect Disord 2015; 172: 462–71

e5. Steffen A, Thom J, Jacobi F, Holstiege J, Batzing J: Trends in prevalence of depression in Germany between 2009 and 2017 based on nationwide ambulatory claims data. J Affect Disord 2020; 271: 239–47

e6. Barschkett M, Koletzko B, Spiess CK: COVID-19 associated contact restrictions in Germany: marked decline in children‘s outpatient visits for infectious diseases without increasing visits for mental health disorders. Children (Basel) 2021; 8: 728

e7. Berg G: F-Diagnosen bei 0- bis 20-Jährigen in der ambulanten Behandlung im ersten Jahr der COVID-19-Pandemie. Nervenheilkunde 2022; 41: 335–9

e8. Bundesministerium für Gesundheit (BMG): Statistik über Versicherte, gegliedert nach Status, Alter, Wohnort und Kassenart (Stichtag: 1. Juli des jeweiligen Jahres), Mitgliederstatistik KM6. www.bundesgesundheitsministerium.de/fileadmin/Dateien/3_Downloads/Statistiken/GKV/Mitglieder_Versicherte/KM6_2012_121120.xls (last accessed on 19 December 2023).

e9. Bätzing-Feigenbaum J, Schulz M, Schulz M, Hering R, Miralle JG, Kern WV: Entwicklung des Antibiotikaverbrauchs in der ambulanten vertragsärztlichen Versorgung – Update 2013/2014 mit regionalisierten Trendanalysen für den Zeitraum 2008 bis 2014 und Schwerpunkt zur Verordnung von Cephalosporinen und Fluorchinolonen. Versorgungsatlas-Bericht Nr. 15/15–17. Berlin: Zentralinstitut für die kassenärztliche Versorgung in Deutschland (Zi); 2016.