{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T11:21:44Z","timestamp":1785410504003,"version":"3.56.0"},"reference-count":47,"publisher":"Cambridge University Press (CUP)","license":[{"start":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T00:00:00Z","timestamp":1778716800000},"content-version":"unspecified","delay-in-days":133,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100001691","name":"Japan Society for the Promotion of Science","doi-asserted-by":"publisher","award":["17H03589;19K10671;19K10446;18H03107; 18H03062; 19H03860; 21H04856; 19K19439"],"award-info":[{"award-number":["17H03589;19K10671;19K10446;18H03107; 18H03062; 19H03860; 21H04856; 19K19439"]}],"id":[{"id":"10.13039\/501100001691","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100009619","name":"Japan Agency for Medical Research and Development","doi-asserted-by":"publisher","award":["2033648"],"award-info":[{"award-number":["2033648"]}],"id":[{"id":"10.13039\/100009619","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001691","name":"Japan Society for the Promotion of Science","doi-asserted-by":"publisher","award":["25K10835"],"award-info":[{"award-number":["25K10835"]}],"id":[{"id":"10.13039\/501100001691","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001691","name":"Japan Society for the Promotion of Science","doi-asserted-by":"publisher","award":["24K10718"],"award-info":[{"award-number":["24K10718"]}],"id":[{"id":"10.13039\/501100001691","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["cambridge.org"],"crossmark-restriction":true},"short-container-title":["Psychol. Med."],"published-print":{"date-parts":[[2026]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec id=\"S0033291726104590_sec1\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Early prediction of depressive and anxiety disorders is challenging due to substantial heterogeneity in risk pathways. Conventional machine-learning models trained on aggregated populations may obscure subgroup-specific mechanisms and limit interpretability for prevention. We evaluated whether a hybrid unsupervised\u2013supervised framework can identify meaningful subgroups and yield more interpretable risk prediction.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"S0033291726104590_sec2\" sec-type=\"methods\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We analyzed cohort data of 15,897 Japanese adults who completed baseline (August\u2013September 2020) and 6-month follow-up (February\u2013March 2021) surveys and did not screen positive for depressive and anxiety disorders at baseline (K6 score\u00a0&lt;\u00a013). Using 169 baseline demographic, psychosocial, lifestyle, and behavioral variables, we performed hierarchical clustering to derive data-driven subgroups. Within each cluster, we trained Random Forest models to predict incident screened depressive and anxiety disorders at follow-up (K6\u00a0\u2265\u00a013) and interpreted predictors using SHapley Additive exPlanations (SHAP).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"S0033291726104590_sec3\" sec-type=\"results\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The overall 6-month incidence was 6.23%. A five-cluster solution revealed two high-risk subgroups: an older-adult profile with poor quality of life (12.9%) and a working-parent profile characterized by work\u2013family overload (29.8%). Compared with a global model trained on the full sample, the cluster-then-predict framework showed broadly similar overall performance but performed better in the highest-risk subgroup and revealed more differentiated predictor profiles. Loneliness, health-related quality of life, happiness, and personality traits predominated in clusters with moderate adversity, whereas lifestyle disruption (sleep, diet, and irregular routines) characterized the high-risk late-life subgroup and alcohol dependence and work\u2013family burden characterized the high-risk working-parent subgroup.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"S0033291726104590_sec4\" sec-type=\"conclusions\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Addressing risk-factor heterogeneity before prediction may enable more interpretable, context-tailored prevention strategies.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1017\/s0033291726104590","type":"journal-article","created":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T07:47:27Z","timestamp":1778744847000},"update-policy":"https:\/\/doi.org\/10.1017\/policypage","source":"Crossref","is-referenced-by-count":0,"title":["Heterogeneous pathways to depressive and anxiety disorders: A cluster-based predictive study in a nationwide longitudinal cohort"],"prefix":"10.1017","volume":"56","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3189-7397","authenticated-orcid":false,"given":"Chong","family":"Chen","sequence":"first","affiliation":[{"id":[{"id":"https:\/\/ror.org\/03cxys317","id-type":"ROR","asserted-by":"publisher"}],"name":"Yamaguchi University Graduate School of Medicine"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5519-4306","authenticated-orcid":false,"given":"Yoshiyuki","family":"Asai","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/03cxys317","id-type":"ROR","asserted-by":"publisher"}],"name":"Yamaguchi University Graduate School of Medicine"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yasuhiro","family":"Mochizuki","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/00ntfnx83","id-type":"ROR","asserted-by":"publisher"}],"name":"Waseda University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7534-4308","authenticated-orcid":false,"given":"Kosuke","family":"Hagiwara","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/03cxys317","id-type":"ROR","asserted-by":"publisher"}],"name":"Yamaguchi University Graduate School of Medicine"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ryo","family":"Okubo","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/02e16g702","id-type":"ROR","asserted-by":"publisher"}],"name":"Hokkaido University Graduate School of Medicine"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shin","family":"Nakagawa","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/03cxys317","id-type":"ROR","asserted-by":"publisher"}],"name":"Yamaguchi University Graduate School of Medicine"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1050-3125","authenticated-orcid":false,"given":"Takahiro","family":"Tabuchi","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/01dq60k83","id-type":"ROR","asserted-by":"publisher"}],"name":"Tohoku University"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"56","published-online":{"date-parts":[[2026,5,14]]},"reference":[{"key":"S0033291726104590_r39","doi-asserted-by":"publisher","DOI":"10.1016\/j.jad.2023.06.031"},{"key":"S0033291726104590_r43","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.1963.10500845"},{"key":"S0033291726104590_r5","doi-asserted-by":"publisher","DOI":"10.1023\/A:1010933404324"},{"key":"S0033291726104590_r2","doi-asserted-by":"publisher","DOI":"10.1037\/1076-8998.5.2.278"},{"key":"S0033291726104590_r46","doi-asserted-by":"publisher","DOI":"10.1002\/1097-0142(1950)3:1<32::AID-CNCR2820030106>3.0.CO;2-3"},{"key":"S0033291726104590_r30","doi-asserted-by":"crossref","unstructured":"McInnes, L. , Healy, J. , & Melville, J. (2018). UMAP: Uniform manifold approximation and projection for dimension reduction. arXiv preprint arXiv:1802.03426.","DOI":"10.21105\/joss.00861"},{"key":"S0033291726104590_r12","doi-asserted-by":"publisher","DOI":"10.1016\/j.jad.2023.10.091"},{"key":"S0033291726104590_r20","first-page":"627","article-title":"Receiver operating characteristic (ROC) curve analysis for medical diagnostic test evaluation","volume":"4","author":"Hajian-Tilaki","year":"2013","journal-title":"Caspian Journal of Internal Medicine"},{"key":"S0033291726104590_r21","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-84858-7"},{"key":"S0033291726104590_r45","volume-title":"WHO guidelines on mental health at work","year":"2022"},{"key":"S0033291726104590_r3","volume-title":"Diagnostic and statistical manual of mental disorders","year":"1994"},{"key":"S0033291726104590_r18","doi-asserted-by":"publisher","DOI":"10.1002\/mpr.257"},{"key":"S0033291726104590_r13","doi-asserted-by":"publisher","DOI":"10.1111\/gwao.12497"},{"key":"S0033291726104590_r36","doi-asserted-by":"publisher","DOI":"10.1016\/0377-0427(87)90125-7"},{"key":"S0033291726104590_r25","first-page":"46","article-title":"Systematic review and meta-analysis: Anxiety disorders in parents and children\u2019s anxiety","volume":"58","author":"Lawrence","year":"2019","journal-title":"Journal of the American Academy of Child and Adolescent Psychiatry"},{"key":"S0033291726104590_r15","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.1979.4766909"},{"key":"S0033291726104590_r14","doi-asserted-by":"publisher","DOI":"10.1016\/j.cpr.2020.101955"},{"key":"S0033291726104590_r37","doi-asserted-by":"publisher","DOI":"10.1016\/j.euroneuro.2021.07.003"},{"key":"S0033291726104590_r38","doi-asserted-by":"publisher","DOI":"10.1016\/S2468-2667(19)30230-0"},{"key":"S0033291726104590_r42","doi-asserted-by":"publisher","DOI":"10.1016\/j.landig.2025.100916"},{"key":"S0033291726104590_r44","volume-title":"Depression and other common mental disorders: Global Health estimates","year":"2017"},{"key":"S0033291726104590_r28","doi-asserted-by":"publisher","DOI":"10.1038\/s42256-019-0138-9"},{"key":"S0033291726104590_r32","unstructured":"Murtagh, F. , & Legendre, P. (2011). Ward\u2019s hierarchical clustering method: Clustering criterion and agglomerative algorithm. Preprint, arXiv:1111.6285."},{"key":"S0033291726104590_r31","doi-asserted-by":"publisher","DOI":"10.1037\/0033-2909.110.3.406"},{"key":"S0033291726104590_r35","doi-asserted-by":"publisher","DOI":"10.1016\/j.jad.2021.03.028"},{"key":"S0033291726104590_r41","doi-asserted-by":"publisher","DOI":"10.2188\/jea.JE20180116"},{"key":"S0033291726104590_r17","doi-asserted-by":"publisher","DOI":"10.1007\/s00127-016-1278-4"},{"key":"S0033291726104590_r26","doi-asserted-by":"publisher","DOI":"10.1016\/j.jad.2024.04.098"},{"key":"S0033291726104590_r8","first-page":"223","article-title":"Machine learning for precision psychiatry: Opportunities and challenges","volume":"3","author":"Bzdok","year":"2018","journal-title":"Biological Psychiatry: Cognitive Neuroscience and Neuroimaging"},{"key":"S0033291726104590_r29","doi-asserted-by":"publisher","DOI":"10.1176\/appi.ajp.20230574"},{"key":"S0033291726104590_r9","doi-asserted-by":"publisher","DOI":"10.1080\/03610927408827101"},{"key":"S0033291726104590_r11","first-page":"31","article-title":"Early prediction of depression via machine learning","volume":"36","author":"Chen","year":"2025","journal-title":"Japanese Journal of Biological Psychiatry"},{"key":"S0033291726104590_r47","doi-asserted-by":"publisher","DOI":"10.1016\/j.ssresearch.2021.102684"},{"key":"S0033291726104590_r22","doi-asserted-by":"publisher","DOI":"10.1016\/j.jad.2024.10.074"},{"key":"S0033291726104590_r16","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-clinpsy-032816-045037"},{"key":"S0033291726104590_r7","doi-asserted-by":"publisher","DOI":"10.1016\/S0006-3223(02)01410-5"},{"key":"S0033291726104590_r10","doi-asserted-by":"publisher","DOI":"10.1007\/s10802-011-9572-9"},{"key":"S0033291726104590_r24","doi-asserted-by":"publisher","DOI":"10.1001\/archpsyc.60.2.184"},{"key":"S0033291726104590_r4","doi-asserted-by":"publisher","DOI":"10.1017\/S0033291705004411"},{"key":"S0033291726104590_r19","doi-asserted-by":"publisher","DOI":"10.1016\/j.jagp.2017.06.011"},{"key":"S0033291726104590_r40","doi-asserted-by":"publisher","DOI":"10.1002\/9781118653920.ch12"},{"key":"S0033291726104590_r27","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.1982.1056489"},{"key":"S0033291726104590_r34","doi-asserted-by":"publisher","DOI":"10.1186\/1471-244X-9-31"},{"key":"S0033291726104590_r1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330701"},{"key":"S0033291726104590_r33","doi-asserted-by":"publisher","DOI":"10.1016\/j.neulet.2020.134804"},{"key":"S0033291726104590_r6","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(20)30460-8"},{"key":"S0033291726104590_r23","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyt.2021.667592"}],"container-title":["Psychological Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.cambridge.org\/core\/services\/aop-cambridge-core\/content\/view\/S0033291726104590","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T07:47:35Z","timestamp":1778744855000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.cambridge.org\/core\/product\/identifier\/S0033291726104590\/type\/journal_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"references-count":47,"alternative-id":["S0033291726104590"],"URL":"https:\/\/doi.org\/10.1017\/s0033291726104590","relation":{},"ISSN":["0033-2917","1469-8978"],"issn-type":[{"value":"0033-2917","type":"print"},{"value":"1469-8978","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"\u00a9 The Author(s), 2026. Published by Cambridge University Press","name":"copyright","label":"Copyright","group":{"name":"copyright_and_licensing","label":"Copyright and Licensing"}},{"value":"This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http:\/\/creativecommons.org\/licenses\/by\/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.","name":"license","label":"License","group":{"name":"copyright_and_licensing","label":"Copyright and Licensing"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}],"article-number":"e139"}}