{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,10]],"date-time":"2026-10-10T04:49:23Z","timestamp":1791607763044,"version":"4.3.4"},"reference-count":44,"publisher":"Wiley","license":[{"start":{"date-parts":[[2026,10,9]],"date-time":"2026-10-09T00:00:00Z","timestamp":1791504000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,10,9]],"date-time":"2026-10-09T00:00:00Z","timestamp":1791504000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JCPP Advances"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Correct psychiatric diagnoses represent a prerequisite for the efficacy of treatment, especially during adolescence, a critical period for the onset of mental health disorders. Diagnoses can evolve over time, influenced by factors such as changes in symptoms, treatment effects, and comorbidities. The transition from Child and Adolescent Mental Health Services (CAMHS) to Adult Mental Health Services (AMHS) presents challenges due to differences in diagnostic criteria and treatment approaches. This study explores whether and how psychiatric diagnoses change during this transition, aiming to examine the prevalence and composition of primary diagnoses and identify predictors of diagnostic change.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>From the MILESTONE project total sample, 770 participants aged 17\u201319 with available diagnoses and clinical data were included and assessed at four\u2010time points. We categorised participants into 10 diagnostic groups based on shared clinical features. Statistical analysis included multilevel logistic regression to examine diagnosis changes, with a Sankey plot to visualise transitions.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Clinically, anxiety\/trauma disorders (25.1%) were the most common at baseline, followed by depression\/bipolar (21.3%) and attention deficit hyperactivity disorder (15.6%). Most diagnoses remained stable over time, with showing high stability; depression\/bipolar showed moderate stability (80.7%), while schizophrenia spectrum disorders and substance use disorders exhibited nearly perfect consistency (100% and 85.7%, respectively). Multilevel logistic regression revealed that higher externalising scores (OR\u00a0=\u00a02.90;\n                      <jats:italic>p<\/jats:italic>\n                      \u00a0=\u00a00.045) was a predictor of diagnostic change, while being assessed by a psychiatrist (\n                      <jats:italic>p<\/jats:italic>\n                      \u00a0=\u00a00.037) was an index of diagnostic stability over time.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>This study highlights the diagnostic stability of most psychiatric conditions during the transition from CAMHS to AMHS. Given the complexity of adolescent mental health, accurate and continuous assessment is crucial. Understanding the evolving nature of psychiatric symptoms during adolescence will improve diagnostic accuracy and inform better interventions, fostering long\u2010term mental health outcomes.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/jcv2.70174","type":"journal-article","created":{"date-parts":[[2026,10,10]],"date-time":"2026-10-10T04:14:58Z","timestamp":1791605698000},"source":"Crossref","is-referenced-by-count":0,"title":["Diagnostic variability of mental disorders in adolescence: A longitudinal study across transition boundary age"],"prefix":"10.1002","author":[{"given":"Marta","family":"Magno","sequence":"first","affiliation":[{"name":"Unit of Epidemiological Psychiatry and Digital Mental Health IRCCS Istituto Fatebenefratelli  Brescia Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Donato","family":"Martella","sequence":"additional","affiliation":[{"name":"Unit of Epidemiological Psychiatry and Digital Mental Health IRCCS Istituto Fatebenefratelli  Brescia Italy"},{"name":"Department of Statistics and Quantitative Methods University of Milano\u2010Bicocca  Milano Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Silvia","family":"Leone","sequence":"additional","affiliation":[{"name":"Unit of Epidemiological Psychiatry and Digital Mental Health IRCCS Istituto Fatebenefratelli  Brescia Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Adriana","family":"Pastore","sequence":"additional","affiliation":[{"name":"Unit of Adolescent Psychiatric Emergency Policlinico Hospital  Bari Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cosmo","family":"Strozza","sequence":"additional","affiliation":[{"name":"Interdisciplinary Centre on Population Dynamics University of Southern Denmark  Odense Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Elisa","family":"Caselani","sequence":"additional","affiliation":[{"name":"Unit of Epidemiological 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