IDEAS home Printed from https://ideas.repec.org/a/sae/socpsy/v71y2025i4p723-737.html

From feeling depressed to getting diagnosed: Determinants of a diagnosis of depression after experiencing symptoms

Author

Listed:
  • Barbara Stacherl
  • Theresa M Entringer

Abstract

Background: Receiving a formal diagnosis for a depressive disorder is a prerequisite for getting treatment, yet the illness inherently complicates care-seeking. Thus, understanding the process from depression symptoms to diagnosis is crucial. Aims: This study aims to disentangle (1) risk factors for depression symptoms from (2) facilitators and barriers to receiving a diagnosis after experiencing depression symptoms. Method: We used data from the German Socio-Economic Panel. Within a sample of 40,238 individuals, we investigated factors predicting depression symptoms, assessed with the SF-12 Mental Component Summary score. Additionally, within a subsample of 3,444 individuals with depression symptoms, we analyzed factors associated with receiving a first-ever diagnosis in the subsequent year. These factors included health status, demographics, socioeconomic characteristics, personality traits, and health infrastructure. Results: Depression symptoms were associated with chronic physical conditions, female gender, middle age, living alone, fewer close friends, being unemployed or not working, lower income, lower agreeableness, conscientiousness, or extraversion, and higher neuroticism. Additionally, poorer overall mental and physical health, female gender, older age, unemployment, and neuroticism were positively associated with receiving a formal diagnosis. Access to general practitioners and psychotherapists was not associated with receiving a formal diagnosis. Conclusions: Our results replicated previous research on risk factors for depression symptoms. Moreover, some risk factors for experiencing symptoms (female gender, middle age, unemployment, and higher neuroticism) subsequently also facilitated receiving a formal depression diagnosis. Thus, this study underscores the importance of considering the chronological sequence in the process from depression symptoms to diagnosis.

Suggested Citation

  • Barbara Stacherl & Theresa M Entringer, 2025. "From feeling depressed to getting diagnosed: Determinants of a diagnosis of depression after experiencing symptoms," International Journal of Social Psychiatry, , vol. 71(4), pages 723-737, June.
    • Handle: RePEc:sae:socpsy:v:71:y:2025:i:4:p:723-737
    DOI: 10.1177/00207640241303038
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/00207640241303038
    Download Restriction: no
    File URL: https://libkey.io/10.1177/00207640241303038?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Goebel, Jan & Grabka, Markus M. & Liebig, Stefan & Kroh, Martin & Richter, David & Schröder, Carsten & Schupp, Jürgen, 2019. "The German Socio-Economic Panel (SOEP)," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 239, pages 345-360.
    2. van Buuren, Stef & Groothuis-Oudshoorn, Karin, 2011. "mice: Multivariate Imputation by Chained Equations in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 45(i03).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sabine Zinn & Michael Bayer, 2021. "Time Spent on School-Related Activities at Home during the Pandemic: A Longitudinal Analysis of Social Group Inequality among Secondary School Students," SOEPpapers on Multidisciplinary Panel Data Research 1132, DIW Berlin, The German Socio-Economic Panel (SOEP).
    2. Katja Möhring & Sabine Zinn & Ulrike Ehrlich, 2023. "Family care during the first COVID-19 lockdown in Germany: longitudinal evidence on consequences for the well-being of caregivers," European Journal of Ageing, Springer, vol. 20(1), pages 1-11, December.
    3. Emily Mena & Katharina Stahlmann & Klaus Telkmann & Gabriele Bolte & on behalf of the AdvanceGender Study Group, 2023. "Intersectionality-Informed Sex/Gender-Sensitivity in Public Health Monitoring and Reporting (PHMR): A Case Study Assessing Stratification on an “Intersectional Gender-Score”," IJERPH, MDPI, vol. 20(3), pages 1-15, January.
    4. Biddle, Louise & Stacherl, Barbara & Heidinger, Ellen, 2025. "Perceived discrimination among migrants in Germany: Does social capital moderate harmful effects on mental health?," Social Science & Medicine, Elsevier, vol. 370(C).
    5. Noémi Kreif & Richard Grieve & Iván Díaz & David Harrison, 2015. "Evaluation of the Effect of a Continuous Treatment: A Machine Learning Approach with an Application to Treatment for Traumatic Brain Injury," Health Economics, John Wiley & Sons, Ltd., vol. 24(9), pages 1213-1228, September.
    6. Simpson, Julija & Albani, Viviana & Kingston, Andrew & Bambra, Clare, 2024. "Closing the life expectancy gap: An ecological study of the factors associated with smaller regional health inequalities in post-reunification Germany," Social Science & Medicine, Elsevier, vol. 362(C).
    7. Abhilash Bandam & Eedris Busari & Chloi Syranidou & Jochen Linssen & Detlef Stolten, 2022. "Classification of Building Types in Germany: A Data-Driven Modeling Approach," Data, MDPI, vol. 7(4), pages 1-23, April.
    8. Boonstra Philip S. & Little Roderick J.A. & West Brady T. & Andridge Rebecca R. & Alvarado-Leiton Fernanda, 2021. "A Simulation Study of Diagnostics for Selection Bias," Journal of Official Statistics, Sciendo, vol. 37(3), pages 751-769, September.
    9. Lin Lin & Rachel L Spreng & Kelly E Seaton & S Moses Dennison & Lindsay C Dahora & Daniel J Schuster & Sheetal Sawant & Peter B Gilbert & Youyi Fong & Neville Kisalu & Andrew J Pollard & Georgia D Tom, 2024. "GeM-LR: Discovering predictive biomarkers for small datasets in vaccine studies," PLOS Computational Biology, Public Library of Science, vol. 20(11), pages 1-23, November.
    10. Rapp, Hannah & Fredrick, Stephanie & Nickerson, Amanda, 2025. "Cyber victimization reports between parents and children: an examination of agreement predictors," Children and Youth Services Review, Elsevier, vol. 177(C).
    11. Christopher J Greenwood & George J Youssef & Primrose Letcher & Jacqui A Macdonald & Lauryn J Hagg & Ann Sanson & Jenn Mcintosh & Delyse M Hutchinson & John W Toumbourou & Matthew Fuller-Tyszkiewicz &, 2020. "A comparison of penalised regression methods for informing the selection of predictive markers," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-14, November.
    12. Liangyuan Hu & Lihua Li, 2022. "Using Tree-Based Machine Learning for Health Studies: Literature Review and Case Series," IJERPH, MDPI, vol. 19(23), pages 1-13, December.
    13. Norah Alyabs & Sy Han Chiou, 2022. "The Missing Indicator Approach for Accelerated Failure Time Model with Covariates Subject to Limits of Detection," Stats, MDPI, vol. 5(2), pages 1-13, May.
    14. Feldkircher, Martin, 2014. "The determinants of vulnerability to the global financial crisis 2008 to 2009: Credit growth and other sources of risk," Journal of International Money and Finance, Elsevier, vol. 43(C), pages 19-49.
    15. Simon Schmidbauer & Maria Becker & Sonja Haug, 2024. "Online Political Participation of Refugees in Germany: Analysis of a Survey in Bavaria," SAGE Open, , vol. 14(4), pages 21582440241, October.
    16. Stella Martin & Kevin Stabenow & Mark Trede, 2024. "Measurement Error in Earnings," CQE Working Papers 10824, Center for Quantitative Economics (CQE), University of Muenster.
    17. repec:plo:pone00:0154450 is not listed on IDEAS
    18. Panarello, Demetrio, 2021. "Economic insecurity, conservatism, and the crisis of environmentalism: 30 years of evidence," Socio-Economic Planning Sciences, Elsevier, vol. 73(C).
    19. Eunsil Seok & Akhgar Ghassabian & Yuyan Wang & Mengling Liu, 2024. "Statistical Methods for Modeling Exposure Variables Subject to Limit of Detection," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 16(2), pages 435-458, July.
    20. König, Johannes & Longmuir, Maximilian, 2025. "Wage risk and portfolio choice: The role of correlated returns," International Review of Financial Analysis, Elsevier, vol. 100(C).
    21. Ida Kubiszewski & Kenneth Mulder & Diane Jarvis & Robert Costanza, 2022. "Toward better measurement of sustainable development and wellbeing: A small number of SDG indicators reliably predict life satisfaction," Sustainable Development, John Wiley & Sons, Ltd., vol. 30(1), pages 139-148, February.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:socpsy:v:71:y:2025:i:4:p:723-737. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.