HomeOur World in Data

Depression is complicated and our understanding of the condition has evolved over time

Wallace, E. R., & Gach, J. (Eds.). (2008). History of psychiatry and medical psychology: With an epilogue on psychiatry and the mind-body relation

  • Wallace, E. R., & Gach, J. (Eds.). (2008). History of psychiatry and medical psychology: With an epilogue on psychiatry and the mind-body relation. Springer.Telles-Correia, D., & Marques, J. G. (2015). Melancholia before the twentieth century: fear and sorrow or partial insanity?. Frontiers in Psychology, 6, 81. https://doi.org/10.3389/fpsyg.2015.00081

  • Jansson, Å. (2021). Statistics, Classification, and the Standardisation of Melancholia. In Å. Jansson, From Melancholia to Depression (pp. 123–171). Springer International Publishing. https://doi.org/10.1007/978-3-030-54802-5_5

    See also: Shepherd, A. (2015). Institutionalizing the insane in nineteenth-century England. Routledge.

    York, S. H. (2010). Suicide, lunacy and the asylum in nineteenth-century England (Doctoral dissertation, University of Birmingham).

  • McPherson, S., & Armstrong, D. (2021). Psychometric origins of depression. History of the Human Sciences, 095269512110090. https://doi.org/10.1177/09526951211009085

    Jansson, Å. (2021). Statistics, Classification, and the Standardisation of Melancholia. In Å. Jansson, From Melancholia to Depression (pp. 123–171). Springer International Publishing. https://doi.org/10.1007/978-3-030-54802-5_5

    See also: Shepherd, A. (2015). Institutionalizing the insane in nineteenth-century England. Routledge.York, S. H. (2010). Suicide, lunacy and the asylum in nineteenth-century England (Doctoral dissertation, University of Birmingham).

  • Engstrom, E. J. (2018). Clinical psychiatry in imperial Germany. Cornell University Press.

  • Andrews, J. (1998). Case notes, case histories, and the patient’s experience of insanity at Gartnavel Royal Asylum, Glasgow, in the nineteenth century. Social History of Medicine, 11(2), 255-281.

  • Data from questionnaires and rating scales are used for many purposes. One use is to guide treatment: some guidelines give different recommendations about how patients should be treated depending on how severely they are affected by depression. Another use is to measure levels of depression, which can be used in trials to understand how patients’ symptoms have changed over time.

  • Mars, B., Cornish, R., Heron, J., Boyd, A., Crane, C., Hawton, K., Lewis, G., Tilling, K., Macleod, J., & Gunnell, D. (2016). Using Data Linkage to Investigate Inconsistent Reporting of Self-Harm and Questionnaire Non-Response. Archives of Suicide Research, 20(2), 113–141. https://doi.org/10.1080/13811118.2015.1033121

    Jousilahti, P. (2005). Total and cause specific mortality among participants and non-participants of population based health surveys: A comprehensive follow up of 54 372 Finnish men and women. Journal of Epidemiology & Community Health, 59(4), 310–315. https://doi.org/10.1136/jech.2004.024349Williams, D., & Brick, J. M. (2018). Trends in U.S. Face-To-Face Household Survey Nonresponse and Level of Effort. Journal of Survey Statistics and Methodology, 6(2), 186–211. https://doi.org/10.1093/jssam/smx019

  • People can rate themselves on screening tools, or have a non-professional ask them about their symptoms. These are usually questionnaires. In contrast, diagnostic tools are only used by medical professionals, who tend to use structured interviews to rate people on the symptoms of depression. Screening is usually used as a guide to determine who would benefit from a diagnosis.

  • McPherson, S., & Armstrong, D. (2021). Psychometric origins of depression. History of the Human Sciences, 095269512110090. https://doi.org/10.1177/09526951211009085

  • Price, P., Chiang, I. C. A., & Jhangiani, R. (2014). Research Methods in Psychology. Chapter 5: Psychological measurement. BCcampus, BC Open Textbook Project. https://opentextbc.ca/researchmethods/chapter/reliability-and-validity-of-measurement/ 

    McPherson, S., & Armstrong, D. (2021). Psychometric origins of depression. History of the Human Sciences, 095269512110090. https://doi.org/10.1177/09526951211009085

    Bech, P. (2012). Clinical psychometrics (1. ed). Wiley-Blackwell.

  • Bartholomew, D. J. (1995). Spearman and the origin and development of factor analysis. British Journal of Mathematical and Statistical Psychology, 48(2), 211–220. https://doi.org/10.1111/j.2044-8317.1995.tb01060.x

  • Manea, L., Gilbody, S., & McMillan, D. (2015). A diagnostic meta-analysis of the Patient Health Questionnaire-9 (PHQ-9) algorithm scoring method as a screen for depression. General Hospital Psychiatry, 37(1), 67–75. https://doi.org/10.1016/j.genhosppsych.2014.09.009

  • Tomitaka, S., Kawasaki, Y., Ide, K., Akutagawa, M., Yamada, H., Ono, Y., & Furukawa, T. A. (2018). Distributional patterns of item responses and total scores on the PHQ-9 in the general population: Data from the National Health and Nutrition Examination Survey. BMC Psychiatry, 18(1), 108. https://doi.org/10.1186/s12888-018-1696-9

  • Unlike this PHQ-9, the QIDS-16 questionnaire asks questions related to more specific symptoms of depression (for sleeping problems and movement). For example, while the PHQ-9 lumps together sleeping problems, the QIDS-16 has separate questions related to insomnia and hypersomnia.

  • Stochl, J., Fried, E. I., Fritz, J., Croudace, T. J., Russo, D. A., Knight, C., Jones, P. B., & Perez, J. (2020). On Dimensionality, Measurement Invariance, and Suitability of Sum Scores for the PHQ-9 and the GAD-7. Assessment, 107319112097686. https://doi.org/10.1177/1073191120976863

    Gelaye, B., Williams, M. A., Lemma, S., Deyessa, N., Bahretibeb, Y., Shibre, T., Wondimagegn, D., Lemenhe, A., Fann, J. R., Vander Stoep, A., & Andrew Zhou, X.-H. (2013). Validity of the patient health questionnaire-9 for depression screening and diagnosis in East Africa. Psychiatry Research, 210(2), 653–661. https://doi.org/10.1016/j.psychres.2013.07.015

    Carrozzino, D., Patierno, C., Fava, G. A., & Guidi, J. (2020). The Hamilton Rating Scales for Depression: A Critical Review of Clinimetric Properties of Different Versions. Psychotherapy and Psychosomatics, 89(3), 133–150. https://doi.org/10.1159/000506879.

  • Shafer, A. B. (2006). Meta‐analysis of the factor structures of four depression questionnaires: Beck, CES‐D, Hamilton, and Zung. Journal of clinical psychology, 62(1), 123-146.

  • Ulbricht, C. M., Chrysanthopoulou, S. A., Levin, L., & Lapane, K. L. (2018). The use of latent class analysis for identifying subtypes of depression: A systematic review. Psychiatry Research, 266, 228–246. https://doi.org/10.1016/j.psychres.2018.03.003

    Harald, B., & Gordon, P. (2012). Meta-review of depressive subtyping models. Journal of Affective Disorders, 139(2), 126–140. https://doi.org/10.1016/j.jad.2011.07.015

  • Thase, M. E. (2009). Atypical Depression: Useful Concept, but it’s Time to Revise the DSM-IV Criteria. Neuropsychopharmacology, 34(13), 2633–2641. https://doi.org/10.1038/npp.2009.100

  • Łojko, D., & Rybakowski, J. (2017). Atypical depression: Current perspectives. Neuropsychiatric Disease and Treatment, Volume 13, 2447–2456. https://doi.org/10.2147/NDT.S147317

  • Fried, E. I., van Borkulo, C. D., Epskamp, S., Schoevers, R. A., Tuerlinckx, F., & Borsboom, D. (2016). Measuring depression over time . . . Or not? Lack of unidimensionality and longitudinal measurement invariance in four common rating scales of depression. Psychological Assessment, 28(11), 1354–1367. https://doi.org/10.1037/pas0000275

  • Eaton, W. W., Shao, H., Nestadt, G., Lee, B. H., Bienvenu, O. J., & Zandi, P. (2008). Population-Based Study of First Onset and Chronicity in Major Depressive Disorder. Archives of General Psychiatry, 65(5), 513. https://doi.org/10.1001/archpsyc.65.5.513

  • Eaton, W. W., Shao, H., Nestadt, G., Lee, B. H., Bienvenu, O. J., & Zandi, P. (2008). Population-Based Study of First Onset and Chronicity in Major Depressive Disorder. Archives of General Psychiatry, 65(5), 513. https://doi.org/10.1001/archpsyc.65.5.513

  • Hölzel, L., Härter, M., Reese, C., & Kriston, L. (2011). Risk factors for chronic depression—A systematic review. Journal of Affective Disorders, 129(1–3), 1–13. https://doi.org/10.1016/j.jad.2010.03.025

  • Solmi, M., Radua, J., Olivola, M., Croce, E., Soardo, L., Salazar de Pablo, G., Il Shin, J., Kirkbride, J. B., Jones, P., Kim, J. H., Kim, J. Y., Carvalho, A. F., Seeman, M. V., Correll, C. U., & Fusar-Poli, P. (2021). Age at onset of mental disorders worldwide: Large-scale meta-analysis of 192 epidemiological studies. Molecular Psychiatry. https://doi.org/10.1038/s41380-021-01161-7

  • Bockting, C. L., Hollon, S. D., Jarrett, R. B., Kuyken, W., & Dobson, K. (2015). A lifetime approach to major depressive disorder: the contributions of psychological interventions in preventing relapse and recurrence. Clinical psychology review41, 16-26.

  • All visualizations, data, and code produced by Our World in Data are completely open access under the Creative Commons BY license. You have the permission to use, distribute, and reproduce these in any medium, provided the source and authors are credited.

    The data produced by third parties and made available by Our World in Data is subject to the license terms from the original third-party authors. We will always indicate the original source of the data in our documentation, so you should always check the license of any such third-party data before use and redistribution.