{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,20]],"date-time":"2026-05-20T00:56:52Z","timestamp":1779238612739,"version":"3.51.4"},"reference-count":75,"publisher":"SAGE Publications","issue":"6","license":[{"start":{"date-parts":[[2024,9,9]],"date-time":"2024-09-09T00:00:00Z","timestamp":1725840000000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2024,9,9]],"date-time":"2024-09-09T00:00:00Z","timestamp":1725840000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"DOI":"10.13039\/501100005878","name":"Terveyden Tutkimuksen Toimikunta","doi-asserted-by":"publisher","award":["334057"],"award-info":[{"award-number":["334057"]}],"id":[{"id":"10.13039\/501100005878","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005878","name":"Terveyden Tutkimuksen Toimikunta","doi-asserted-by":"publisher","award":["335901"],"award-info":[{"award-number":["335901"]}],"id":[{"id":"10.13039\/501100005878","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005878","name":"Terveyden Tutkimuksen Toimikunta","doi-asserted-by":"publisher","award":["358138"],"award-info":[{"award-number":["358138"]}],"id":[{"id":"10.13039\/501100005878","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Assessment"],"published-print":{"date-parts":[[2025,9]]},"abstract":"<jats:p>\n                    Unlike depression sum scores, the underlying risk for depression is typically assumed to be normally distributed across the general population. To assess the true empirical shape of depression risk, we created a continuous-valued estimate of the latent depression density, using the Davidian-Curve Item Response Theory (DC-IRT) and the National Health and Nutrition Examination Survey (NHANES) cohorts from 2005 to 2018 (\n                    <jats:italic toggle=\"yes\">n<\/jats:italic>\n                    \u2009=\u200936,244 on the Nine-item Patient Health Questionnaire; PHQ-9). We conducted simulations to investigate the performance of DC-IRT for large samples and realistic items. The method can recover complex latent-risk distributions even when they are not evident from sum scores. However, estimation accuracy for different sample sizes depends on the method of model selection. In addition to full-data analysis, random samples of a few thousand observations were drawn for analysis. The latent shape of depression was left-skewed and bimodal in both investigations, indicating that the latent-normality assumption does not hold for depression.\n                  <\/jats:p>","DOI":"10.1177\/10731911241275327","type":"journal-article","created":{"date-parts":[[2024,9,10]],"date-time":"2024-09-10T09:22:05Z","timestamp":1725960125000},"page":"978-991","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":4,"title":["Non-Gaussian Liability Distribution for Depression in the General Population"],"prefix":"10.1177","volume":"32","author":[{"given":"Anna","family":"Talkkari","sequence":"first","affiliation":[{"name":"Department of Psychology, Faculty of Medicine, University of Helsinki, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8277-3776","authenticated-orcid":false,"given":"Tom H.","family":"Rosenstr\u00f6m","sequence":"additional","affiliation":[{"name":"Department of Psychology, Faculty of Medicine, University of Helsinki, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2024,9,9]]},"reference":[{"key":"e_1_3_2_2_1","doi-asserted-by":"crossref","unstructured":"Ali U. S. Chang H. H. Anderson C. J. (2015). Location indices for ordinal polytomous items based on item response theory. ETS Research Report Series 2015(2) 1\u201313. https:\/\/doi.org\/10.1002\/ets2.12065","DOI":"10.1002\/ets2.12065"},{"key":"e_1_3_2_3_1","doi-asserted-by":"publisher","DOI":"10.1176\/appi.books.9780890425596"},{"key":"e_1_3_2_4_1","doi-asserted-by":"crossref","unstructured":"Ayuso-Mateos J. L. Nuevo R. Verdes E. Naidoo N. Chatterji S. (2010). From depressive symptoms to depressive disorders: The relevance of thresholds. The British Journal of Psychiatry 196(5) 365\u2013371. https:\/\/doi.org\/10.1192\/bjp.bp.109.071191","DOI":"10.1192\/bjp.bp.109.071191"},{"key":"e_1_3_2_5_1","doi-asserted-by":"crossref","unstructured":"Beach S. R. H. Amir N. (2006). Self-reported depression is taxonic. Journal of Psychopathology and Behavioral Assessment 28(3) 169\u2013176. https:\/\/doi.org\/10.1007\/s10862-005-9007-4","DOI":"10.1007\/s10862-005-9007-4"},{"key":"e_1_3_2_6_1","doi-asserted-by":"crossref","unstructured":"Beijers L. Wardenaar K. J. van Loo H. M. Schoevers R. A. (2019). Data-driven biological subtypes of depression: Systematic review of biological approaches to depression subtyping. Molecular Psychiatry 24(6) Article 6. https:\/\/doi.org\/10.1038\/s41380-019-0385-5","DOI":"10.1038\/s41380-019-0385-5"},{"key":"e_1_3_2_7_1","doi-asserted-by":"crossref","unstructured":"Bertha E. A. Bal\u00e1zs J. (2013). Subthreshold depression in adolescence: A systematic review. European Child & Adolescent Psychiatry 22(10) 589\u2013603. https:\/\/doi.org\/10.1007\/s00787-013-0411-0","DOI":"10.1007\/s00787-013-0411-0"},{"key":"e_1_3_2_8_1","doi-asserted-by":"crossref","unstructured":"Bock R. D. Aitkin M. (1981). Marginal maximum likelihood estimation of item parameters: Application of an EM algorithm. Psychometrika 46(4) 443\u2013459. https:\/\/doi.org\/10.1007\/BF02293801","DOI":"10.1007\/BF02293801"},{"key":"e_1_3_2_9_1","doi-asserted-by":"crossref","unstructured":"Bondar J. Caye A. Chekroud A. M. Kieling C. (2020). Symptom clusters in adolescent depression and differential response to treatment: A secondary analysis of the Treatment for Adolescents with Depression Study randomised trial. The Lancet Psychiatry 7(4) 337\u2013343. https:\/\/doi.org\/10.1016\/S2215-0366(20)30060-2","DOI":"10.1016\/S2215-0366(20)30060-2"},{"key":"e_1_3_2_10_1","doi-asserted-by":"crossref","unstructured":"Chalmers R. P. (2012). mirt: A multidimensional item response theory package for the R environment. Journal of Statistical Software 48(6) 1\u201329. https:\/\/doi.org\/doi:10.18637\/jss.v048.i06","DOI":"10.18637\/jss.v048.i06"},{"key":"e_1_3_2_11_1","doi-asserted-by":"crossref","unstructured":"Chen L.-S. Eaton W. W. Gallo J. J. Nestadt G. Crum R. M. (2000). Empirical examination of current depression categories in a population-based study: Symptoms course and risk factors. American Journal of Psychiatry 157(4) 573\u2013580. https:\/\/doi.org\/10.1176\/appi.ajp.157.4.573","DOI":"10.1176\/appi.ajp.157.4.573"},{"key":"e_1_3_2_12_1","unstructured":"Chen T.-C. Clark J. Riddles M. K. Mohadjer L. K. Tala H. I. (2020). National Health and Nutrition Examination Survey 2015\u22122018: Sample design and estimation procedures (No. 184). National Center for Health Statistics. https:\/\/stacks.cdc.gov\/view\/cdc\/88305"},{"key":"e_1_3_2_13_1","unstructured":"Chen T.-C. Parker J. D. Clark J. Shin H.-C. Rammon J. R. Burt V. L. (2018). National Health and Nutrition Examination Survey: Estimation procedures 2011\u20132014 (No. 177). National Center for Health Statistics. https:\/\/stacks.cdc.gov\/view\/cdc\/51180"},{"key":"e_1_3_2_14_1","doi-asserted-by":"crossref","unstructured":"Cuijpers P. Koole S. L. Dijke A. van Roca M. Li J. Reynolds C. F. (2014). Psychotherapy for subclinical depression: Meta-analysis. The British Journal of Psychiatry 205(4) 268\u2013274. https:\/\/doi.org\/10.1192\/bjp.bp.113.138784","DOI":"10.1192\/bjp.bp.113.138784"},{"key":"e_1_3_2_15_1","doi-asserted-by":"crossref","unstructured":"Cuijpers P. Smit F. (2004). Subthreshold depression as a risk indicator for major depressive disorder: A systematic review of prospective studies. Acta Psychiatrica Scandinavica 109(5) 325\u2013331. https:\/\/doi.org\/10.1111\/j.1600-0447.2004.00301.x","DOI":"10.1111\/j.1600-0447.2004.00301.x"},{"key":"e_1_3_2_16_1","doi-asserted-by":"crossref","unstructured":"Davidian M. Gallant A. R. (1993). The nonlinear mixed effects model with a smooth random effects density. Biometrika 80(3) 475\u2013488. https:\/\/doi.org\/10.1093\/biomet\/80.3.475","DOI":"10.1093\/biomet\/80.3.475"},{"key":"e_1_3_2_17_1","doi-asserted-by":"crossref","unstructured":"Dziak J. J. Coffman D. L. Lanza S. T. Li R. Jermiin L. S. (2020). Sensitivity and specificity of information criteria. Briefings in Bioinformatics 21(2) 553\u2013565. https:\/\/doi.org\/10.1093\/bib\/bbz016","DOI":"10.1093\/bib\/bbz016"},{"key":"e_1_3_2_18_1","doi-asserted-by":"crossref","unstructured":"Falconer D. S. (1965). The inheritance of liability to certain diseases estimated from the incidence among relatives. Annals of Human Genetics 29(1) 51\u201376. https:\/\/doi.org\/10.1111\/j.1469-1809.1965.tb00500.x","DOI":"10.1111\/j.1469-1809.1965.tb00500.x"},{"key":"e_1_3_2_19_1","doi-asserted-by":"crossref","unstructured":"Hannan E. J. Quinn B. G. (1979). The determination of the order of an autoregression. Journal of the Royal Statistical Society: Series B (Methodological) 41(2) 190\u2013195. https:\/\/doi.org\/10.1111\/j.2517-6161.1979.tb01072.x","DOI":"10.1111\/j.2517-6161.1979.tb01072.x"},{"key":"e_1_3_2_20_1","doi-asserted-by":"crossref","unstructured":"Haslam N. McGrath M. J. Viechtbauer W. Kuppens P. (2020). Dimensions over categories: A meta-analysis of taxometric research. Psychological Medicine 50(9) 1418\u20131432. https:\/\/doi.org\/10.1017\/S003329172000183X","DOI":"10.1017\/S003329172000183X"},{"key":"e_1_3_2_21_1","doi-asserted-by":"crossref","unstructured":"Haslbeck J. Ryan O. Dablander F. (2023). Multimodality and skewness in emotion time series. Emotion 23(8) 2117\u20132141. https:\/\/doi.org\/10.1037\/emo0001218","DOI":"10.1037\/emo0001218"},{"key":"e_1_3_2_22_1","unstructured":"Hern\u00e1n M. A. Robins J. M. (2020). Causal inference: What if. Chapman & Hall\/CRC. https:\/\/www.hsph.harvard.edu\/miguel-hernan\/causal-inference-book\/"},{"key":"e_1_3_2_23_1","doi-asserted-by":"crossref","unstructured":"Hoorelbeke K. Van den Bergh N. Wichers M. Koster E. H. (2019). Between vulnerability and resilience: A network analysis of fluctuations in cognitive risk and protective factors following remission from depression. Behaviour Research and Therapy 116 1\u20139. https:\/\/doi.org\/10.1016\/j.brat.2019.01.007","DOI":"10.1016\/j.brat.2019.01.007"},{"key":"e_1_3_2_24_1","doi-asserted-by":"crossref","unstructured":"Hosenfeld B. Bos E. H. Wardenaar K. J. Conradi H. J. van der Maas H. L. J. Visser I. de Jonge P. (2015). Major depressive disorder as a nonlinear dynamic system: Bimodality in the frequency distribution of depressive symptoms over time. BMC Psychiatry 15(1) Article 222. https:\/\/doi.org\/10.1186\/s12888-015-0596-5","DOI":"10.1186\/s12888-015-0596-5"},{"key":"e_1_3_2_25_1","doi-asserted-by":"crossref","unstructured":"Hybels C. F. Blazer D. G. Pieper C. F. Landerman L. R. Steffens D. C. (2009). Profiles of depressive symptoms in older adults diagnosed with major depression: Latent cluster analysis. The American Journal of Geriatric Psychiatry 17(5) 387\u2013396. https:\/\/doi.org\/10.1097\/JGP.0b013e31819431ff","DOI":"10.1097\/JGP.0b013e31819431ff"},{"key":"e_1_3_2_26_1","doi-asserted-by":"crossref","unstructured":"Imran A. Tariq S. Kapczinski F. de Azevedo Cardoso T. (2024). Psychological resilience and mood disorders: A systematic review and meta-analysis. Trends in Psychiatry and Psychotherapy 46 e20220524. https:\/\/doi.org\/10.47626\/2237-6089-2022-0524","DOI":"10.47626\/2237-6089-2022-0524"},{"key":"e_1_3_2_27_1","unstructured":"Johnson C. L. Paulose-Ram R. Ogden C. L. Carroll M. D. Kruszan-Moran D. Dohrmann S. M. Curtin L. R. (2013). National health and nutrition examination survey. Analytic guidelines 1999-2010 (No. 161). National Center for Health Statistics. https:\/\/stacks.cdc.gov\/view\/cdc\/21305"},{"key":"e_1_3_2_28_1","doi-asserted-by":"crossref","unstructured":"Kocalevent R.-D. Hinz A. Br\u00e4hler E. (2013). Standardization of the depression screener Patient Health Questionnaire (PHQ-9) in the general population. General Hospital Psychiatry 35(5) 551\u2013555. https:\/\/doi.org\/10.1016\/j.genhosppsych.2013.04.006","DOI":"10.1016\/j.genhosppsych.2013.04.006"},{"key":"e_1_3_2_29_1","doi-asserted-by":"crossref","unstructured":"Kroenke K. Spitzer R. L. Williams J. B. W. (2001). The PHQ-9. Journal of General Internal Medicine 16(9) 606\u2013613. https:\/\/doi.org\/10.1046\/j.1525-1497.2001.016009606.x","DOI":"10.1046\/j.1525-1497.2001.016009606.x"},{"key":"e_1_3_2_30_1","doi-asserted-by":"crossref","unstructured":"Lee Y. Y. Stockings E. A. Harris M. G. Doi S. a. R. Page I. S. Davidson S. K. Barendregt J. J. (2019). The risk of developing major depression among individuals with subthreshold depression: A systematic review and meta-analysis of longitudinal cohort studies. Psychological Medicine 49(1) 92\u2013102. https:\/\/doi.org\/10.1017\/S0033291718000557","DOI":"10.1017\/S0033291718000557"},{"key":"e_1_3_2_31_1","doi-asserted-by":"crossref","unstructured":"Lewinsohn P. M. Solomon A. Seeley J. R. Zeiss A. (2000). Clinical implications of \u201csubthreshold\u201d depressive symptoms. Journal of Abnormal Psychology 109(2) 345\u2013351. https:\/\/doi.org\/10.1037\/0021-843X.109.2.345","DOI":"10.1037\/\/0021-843X.109.2.345"},{"key":"e_1_3_2_32_1","doi-asserted-by":"crossref","unstructured":"Liu R. T. (2016). Taxometric evidence of a dimensional latent structure for depression in an epidemiological sample of children and adolescents. Psychological Medicine 46(6) 1265\u20131275. https:\/\/doi.org\/10.1017\/S0033291715002792","DOI":"10.1017\/S0033291715002792"},{"key":"e_1_3_2_33_1","first-page":"272","volume-title":"Handbook of item response theory modeling: Applications to typical performance assessment","author":"Lucke J. F.","year":"2015","unstructured":"Lucke J. F. (2015). Unipolar item response models. In Reise S. P., Revicki D. A. (Eds.), Handbook of item response theory modeling: Applications to typical performance assessment (pp. 272\u2013284). Taylor & Francis."},{"key":"e_1_3_2_34_1","doi-asserted-by":"crossref","unstructured":"Luque-Fernandez M. A. Schomaker M. Rachet B. Schnitzer M. E. (2018). Targeted maximum likelihood estimation for a binary treatment: A tutorial. Statistics in Medicine 37(16) 2530\u20132546. https:\/\/doi.org\/10.1002\/sim.7628","DOI":"10.1002\/sim.7628"},{"key":"e_1_3_2_35_1","doi-asserted-by":"crossref","unstructured":"Magnus B. E. Liu Y. (2018). A zero-inflated box-cox normal unipolar item response model for measuring constructs of psychopathology. Applied Psychological Measurement 42(7) 571\u2013589. https:\/\/doi.org\/10.1177\/0146621618758291","DOI":"10.1177\/0146621618758291"},{"key":"e_1_3_2_36_1","doi-asserted-by":"crossref","unstructured":"Magnus B. E. Liu Y. (2022). Symptom presence and symptom severity as unique indicators of psychopathology: An application of multidimensional zero-inflated and hurdle graded response models. Educational and Psychological Measurement 82(5) 938\u2013966. https:\/\/doi.org\/10.1177\/00131644211061820","DOI":"10.1177\/00131644211061820"},{"key":"e_1_3_2_37_1","doi-asserted-by":"crossref","unstructured":"Martin A. Rief W. Klaiberg A. Braehler E. (2006). Validity of the Brief Patient Health Questionnaire Mood Scale (PHQ-9) in the general population. General Hospital Psychiatry 28(1) 71\u201377. https:\/\/doi.org\/10.1016\/j.genhosppsych.2005.07.003","DOI":"10.1016\/j.genhosppsych.2005.07.003"},{"key":"e_1_3_2_38_1","doi-asserted-by":"crossref","unstructured":"Moore M. T. Brown T. A. (2012). Are there meaningful differences between major depressive disorder dysthymic disorder and their subthreshold variants? The Journal of Nervous and Mental Disease 200(9) 766\u2013772. https:\/\/doi.org\/10.1097\/NMD.0b013e318266ba3f","DOI":"10.1097\/NMD.0b013e318266ba3f"},{"key":"e_1_3_2_39_1","doi-asserted-by":"crossref","unstructured":"Navrady L. B. Zeng Y. Clarke T. K. Adams M. J. Howard D. M. Deary I. J. McIntosh A. M. (2018). Genetic and environmental contributions to psychological resilience and coping. Wellcome Open Research 3 Article 12. https:\/\/doi.org\/10.12688%2Fwellcomeopenres.13854.1","DOI":"10.12688\/wellcomeopenres.13854.1"},{"key":"e_1_3_2_40_1","doi-asserted-by":"crossref","unstructured":"Plomin R. Haworth C. M. A. Davis O. S. P. (2009). Common disorders are quantitative traits. Nature Reviews Genetics 10(12) Article 12. https:\/\/doi.org\/10.1038\/nrg2670","DOI":"10.1038\/nrg2670"},{"key":"e_1_3_2_41_1","doi-asserted-by":"crossref","unstructured":"Reise S. P. Du H. Wong E. F. Hubbard A. S. Haviland M. G. (2021). Matching IRT models to patient-reported outcomes constructs: The graded response and log-logistic models for scaling depression. Psychometrika 86(3) 800\u2013824. https:\/\/doi.org\/10.1007\/s11336-021-09802-0","DOI":"10.1007\/s11336-021-09802-0"},{"key":"e_1_3_2_42_1","doi-asserted-by":"crossref","unstructured":"Reise S. P. Rodriguez A. (2016). Item response theory and the measurement of psychiatric constructs: Some empirical and conceptual issues and challenges. Psychological Medicine 46(10) 2025\u20132039. https:\/\/doi.org\/10.1017\/S0033291716000520","DOI":"10.1017\/S0033291716000520"},{"key":"e_1_3_2_43_1","doi-asserted-by":"crossref","unstructured":"Robinson J. S. Larson C. L. Cahill S. P. (2014). Relations between resilience positive and negative emotionality and symptoms of anxiety and depression. Psychological Trauma: Theory Research Practice and Policy 6(Suppl. 1) S92\u2013S98. https:\/\/psycnet.apa.org\/doi\/10.1037\/a0033733","DOI":"10.1037\/a0033733"},{"key":"e_1_3_2_44_1","doi-asserted-by":"crossref","unstructured":"Rosenstr\u00f6m T. H. Czajkowski N. O. Solbakken O. A. Saarni S. E. (2023). Direction of dependence analysis for pre-post assessments using non-Gaussian methods: A tutorial. Psychotherapy Research 33(8) 1058\u20131075. https:\/\/doi.org\/10.1080\/10503307.2023.2167526","DOI":"10.1080\/10503307.2023.2167526"},{"key":"e_1_3_2_45_1","doi-asserted-by":"crossref","unstructured":"Rosenstr\u00f6m T. H. Jokela M. Puttonen S. Hintsanen M. Pulkki-R\u00e5back L. Viikari J. S. Raitakari O. T. Keltikangas-J\u00e4rvinen L. (2012). Pairwise measures of causal direction in the epidemiology of sleep problems and depression. PLOS ONE 7(11) Article e50841. https:\/\/doi.org\/10.1371\/journal.pone.0050841","DOI":"10.1371\/journal.pone.0050841"},{"key":"e_1_3_2_46_1","doi-asserted-by":"crossref","unstructured":"Rosenstr\u00f6m T. H. Ritola V. Saarni S. Joffe G. Stenberg J.-H. (2023). Measurement invariant but non-normal treatment responses in guided internet psychotherapies for depressive and generalized anxiety disorders. Assessment 30(3) 618\u2013632. https:\/\/doi.org\/10.1177\/10731911211062500","DOI":"10.1177\/10731911211062500"},{"key":"e_1_3_2_47_1","doi-asserted-by":"crossref","unstructured":"Ruscio J. Brown T. A. Meron Ruscio A. (2009). A taxometric investigation of DSM-IV major depression in a large outpatient sample: Interpretable structural results depend on the mode of assessment. Assessment 16(2) 127\u2013144. https:\/\/doi.org\/10.1177\/1073191108330065","DOI":"10.1177\/1073191108330065"},{"key":"e_1_3_2_48_1","doi-asserted-by":"crossref","unstructured":"Ruscio J. Ruscio A. M. (2000). Informing the continuity controversy: A taxometric analysis of depression. Journal of Abnormal Psychology 109(3) 473\u2013487. https:\/\/doi.org\/10.1037\/0021-843X.109.3.473","DOI":"10.1037\/\/0021-843X.109.3.473"},{"key":"e_1_3_2_49_1","doi-asserted-by":"crossref","unstructured":"Ruscio J. Zimmerman M. McGlinchey J. B. Chelminski I. Young D. (2007). Diagnosing major depressive disorder XI: A taxometric investigation of the structure underlying DSM-IV symptoms. The Journal of Nervous and Mental Disease 195(1) 10. https:\/\/doi.org\/10.1097\/01.nmd.0000252025.12014.c4","DOI":"10.1097\/01.nmd.0000252025.12014.c4"},{"key":"e_1_3_2_50_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4757-2691-6_5"},{"key":"e_1_3_2_51_1","doi-asserted-by":"crossref","unstructured":"Schacht A. Gorwood P. Boyce P. Schaffer A. Picard H. (2014). Depression symptom clusters and their predictive value for treatment outcomes: Results from an individual patient data meta-analysis of duloxetine trials. Journal of Psychiatric Research 53 54\u201361. https:\/\/doi.org\/10.1016\/j.jpsychires.2014.02.001","DOI":"10.1016\/j.jpsychires.2014.02.001"},{"key":"e_1_3_2_52_1","doi-asserted-by":"crossref","unstructured":"Scheffer M. Bockting C. L. Borsboom D. Cools R. Delecroix C. Hartmann J. A. Kendler K. S. van de Leemput I. van der Maas H. L. J. van Nes E. Mattson M. McGorry P. D. Nelson B. (2024a). A dynamical systems view of psychiatric disorders-practical implications: A review. JAMA Psychiatry 81(6) 624\u2013630. https:\/\/doi.org\/10.1001\/jamapsychiatry.2024.0228","DOI":"10.1001\/jamapsychiatry.2024.0228"},{"key":"e_1_3_2_53_1","doi-asserted-by":"crossref","unstructured":"Scheffer M. Bockting C. L. Borsboom D. Cools R. Delecroix C. Hartmann J. A. Kendler K. S. van de Leemput I. van der Maas H. L. J. van Nes E. Mattson M. McGorry P. D. Nelson B. (2024b). A dynamical systems view of psychiatric disorders-theory: A review. JAMA Psychiatry 81(6) 618\u2013623. https:\/\/doi.org\/10.1001\/jamapsychiatry.2024.0215","DOI":"10.1001\/jamapsychiatry.2024.0215"},{"issue":"10","key":"e_1_3_2_54_1","first-page":"2003","article-title":"A linear non-Gaussian acyclic model for causal discovery","volume":"7","author":"Shimizu S.","year":"2006","unstructured":"Shimizu S., Hoyer P. O., Hyvarinen A., Kerminen A. (2006). A linear non-Gaussian acyclic model for causal discovery. Journal of Machine Learning Research, 7(10), 2003\u20132030.","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_2_55_1","doi-asserted-by":"crossref","unstructured":"Solomon A. Ruscio J. Seeley J. R. Lewinsohn P. M. (2006). A taxometric investigation of unipolar depression in a large community sample. Psychological Medicine 36(7) 973\u2013985. https:\/\/doi.org\/10.1017\/S0033291706007689","DOI":"10.1017\/S0033291706007689"},{"key":"e_1_3_2_56_1","doi-asserted-by":"crossref","unstructured":"Tomitaka S. (2020). Patterns of item score and total score distributions on depression rating scales in the general population: Evidence and mechanisms. Heliyon 6(12) E05862. https:\/\/doi.org\/10.1016\/j.heliyon.2020.e05862","DOI":"10.1016\/j.heliyon.2020.e05862"},{"key":"e_1_3_2_57_1","doi-asserted-by":"crossref","unstructured":"Tomitaka S. Kawasaki Y. Furukawa T. (2015). A distribution model of the responses to each depressive symptom item in a general population: A cross-sectional study. BMJ Open 5(9) Article e008599. https:\/\/doi.org\/10.1136\/bmjopen-2015-008599","DOI":"10.1136\/bmjopen-2015-008599"},{"key":"e_1_3_2_58_1","doi-asserted-by":"crossref","unstructured":"Tomitaka S. Kawasaki Y. Ide K. Akutagawa M. Ono Y. Furukawa T. A. (2018). Distribution of item responses and total item scores for the Center for Epidemiologic Studies Depression Scale (CES-D): Data from the Irish Longitudinal Study on Ageing (TILDA). PLOS ONE 13(8) Article e0202607. https:\/\/doi.org\/10.1371\/journal.pone.0202607","DOI":"10.1371\/journal.pone.0202607"},{"key":"e_1_3_2_59_1","doi-asserted-by":"crossref","unstructured":"Tomitaka S. Kawasaki Y. Ide K. Akutagawa M. Ono Y. Furukawa T. A. (2019a). Distribution of psychological distress is stable in recent decades and follows an exponential pattern in the US population. Scientific Reports 9(1) 11982. https:\/\/doi.org\/10.1038\/s41598-019-47322-1","DOI":"10.1038\/s41598-019-47322-1"},{"key":"e_1_3_2_60_1","doi-asserted-by":"crossref","unstructured":"Tomitaka S. Kawasaki Y. Ide K. Akutagawa M. Ono Y. Furukawa T. A. (2019b). Further evidence that item responses on the Kessler Psychological Distress Scale exhibit the characteristic pattern in the general population. Heliyon 5(3) E01387. https:\/\/doi.org\/10.1016\/j.heliyon.2019.e01387","DOI":"10.1016\/j.heliyon.2019.e01387"},{"key":"e_1_3_2_61_1","doi-asserted-by":"crossref","unstructured":"Tomitaka S. Kawasaki Y. Ide K. Akutagawa M. Ono Y. Furukawa T. A. (2019c). Responses to depressive symptom items exhibit a common mathematical pattern across the European populations. Scientific Reports 9(1) Article 1. https:\/\/doi.org\/10.1038\/s41598-019-51499-w","DOI":"10.1038\/s41598-019-51499-w"},{"key":"e_1_3_2_62_1","doi-asserted-by":"crossref","unstructured":"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","DOI":"10.1186\/s12888-018-1696-9"},{"key":"e_1_3_2_63_1","doi-asserted-by":"crossref","unstructured":"Ungar M. Theron L. (2020). Resilience and mental health: How multisystemic processes contribute to positive outcomes. The Lancet Psychiatry 7(5) 441\u2013448. https:\/\/doi.org\/10.1016\/S2215-0366(19)30434-1","DOI":"10.1016\/S2215-0366(19)30434-1"},{"key":"e_1_3_2_64_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4419-9782-1"},{"key":"e_1_3_2_65_1","doi-asserted-by":"crossref","unstructured":"van Loo H. M. de Jonge P. Romeijn J.-W. Kessler R. C. Schoevers R. A. (2012). Data-driven subtypes of major depressive disorder: A systematic review. BMC Medicine 10(1) 156. https:\/\/doi.org\/10.1186\/1741-7015-10-156","DOI":"10.1186\/1741-7015-10-156"},{"key":"e_1_3_2_66_1","doi-asserted-by":"crossref","unstructured":"Verhulst B. Neale M. C. (2021). Best practices for binary and ordinal data analyses. Behavior Genetics 51(3) 204\u2013214. https:\/\/doi.org\/10.1007\/s10519-020-10031-x","DOI":"10.1007\/s10519-020-10031-x"},{"key":"e_1_3_2_67_1","doi-asserted-by":"publisher","DOI":"10.1002\/9781119523024"},{"key":"e_1_3_2_68_1","doi-asserted-by":"crossref","unstructured":"Woods C. M. (2006). Ramsay-curve item response theory (RC-IRT) to detect and correct for nonnormal latent variables. Psychological Methods 11(3) 253\u2013270. https:\/\/doi.org\/10.1037\/1082-989X.11.3.253","DOI":"10.1037\/1082-989X.11.3.253"},{"key":"e_1_3_2_69_1","doi-asserted-by":"crossref","unstructured":"Woods C. M. (2007). Ramsay curve IRT for Likert-type data. Applied Psychological Measurement 31(3) 195\u2013212. https:\/\/doi.org\/10.1177\/0146621606291567","DOI":"10.1177\/0146621606291567"},{"key":"e_1_3_2_70_1","first-page":"60","volume-title":"Handbook of item response theory modeling","author":"Woods C. M.","year":"2015","unstructured":"Woods C. M. (2015). Estimating the latent density in unidimensional IRT to permit non-normality. In Reise S., Revicki D. (Eds.), Handbook of item response theory modeling (pp. 60\u201384). Taylor & Francis."},{"key":"e_1_3_2_71_1","doi-asserted-by":"crossref","unstructured":"Woods C. M. Lin N. (2009). Item response theory with estimation of the latent density using Davidian curves. Applied Psychological Measurement 33(2) 102\u2013117. https:\/\/doi.org\/10.1177\/0146621608319512","DOI":"10.1177\/0146621608319512"},{"key":"e_1_3_2_72_1","doi-asserted-by":"crossref","unstructured":"Zhang D. Davidian M. (2001). Linear mixed models with flexible distributions of random effects for longitudinal data. Biometrics 57(3) 795\u2013802. https:\/\/doi.org\/10.1111\/j.0006-341X.2001.00795.x","DOI":"10.1111\/j.0006-341X.2001.00795.x"},{"key":"e_1_3_2_73_1","doi-asserted-by":"crossref","unstructured":"Zhang J. Yang Y. Ding J. (2023). Information criteria for model selection. WIREs Computational Statistics 15(5) e1607. https:\/\/doi.org\/10.1002\/wics.1607","DOI":"10.1002\/wics.1607"},{"key":"e_1_3_2_74_1","doi-asserted-by":"crossref","unstructured":"Zhang R. Peng X. Song X. Long J. Wang C. Zhang C. Huang R. Lee T. M. C. (2023). The prevalence and risk of developing major depression among individuals with subthreshold depression in the general population. Psychological Medicine 53(8) 3611\u20133620. https:\/\/doi.org\/10.1017\/S0033291722000241","DOI":"10.1017\/S0033291722000241"},{"key":"e_1_3_2_75_1","doi-asserted-by":"crossref","unstructured":"Zhang X. Wang C. Weiss D. J. Tao J. (2021). Bayesian inference for IRT models with non-normal latent trait distributions. Multivariate Behavioral Research 56(5) 703\u2013723. https:\/\/doi.org\/10.1080\/00273171.2020.1776096","DOI":"10.1080\/00273171.2020.1776096"},{"key":"e_1_3_2_76_1","doi-asserted-by":"crossref","unstructured":"Zuithoff N. P. Vergouwe Y. King M. Nazareth I. van Wezep M. J. Moons K. G. Geerlings M. I. (2010). The Patient Health Questionnaire-9 for detection of major depressive disorder in primary care: Consequences of current thresholds in a crosssectional study. BMC Family Practice 11(1) Article 98. https:\/\/doi.org\/10.1186\/1471-2296-11-98","DOI":"10.1186\/1471-2296-11-98"}],"container-title":["Assessment"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/10731911241275327","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/10731911241275327","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/10731911241275327","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T12:12:20Z","timestamp":1777378340000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/10731911241275327"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,9]]},"references-count":75,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2025,9]]}},"alternative-id":["10.1177\/10731911241275327"],"URL":"https:\/\/doi.org\/10.1177\/10731911241275327","relation":{},"ISSN":["1073-1911","1552-3489"],"issn-type":[{"value":"1073-1911","type":"print"},{"value":"1552-3489","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,9,9]]}}}