{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T12:33:58Z","timestamp":1791462838016,"version":"4.3.4"},"reference-count":81,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Public Health Surveill"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec sec-type=\"background\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Scalable and accurate screening tools are critical for public mental health strategies, especially in low- and middle-income countries (LMICs). While the Generalized Anxiety Disorder Scale (GAD-7) and Patient Health Questionnaire (PHQ-9) are widely used, their full application in large-scale programs can pose feasibility challenges. By contrast, shorter versions like GAD-2 and PHQ-2 reduce burdens but fail to capture symptom diversity.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"objective\">\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This study aimed to optimize screening for anxiety and depression severity using classification and regression tree (CART) models, identifying concise and high-performing decision rules based on the GAD-7 and PHQ-9 items, and to test their reproducibility in 5 independent datasets.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"methods\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      A cross-sectional, nonprobabilistic study was conducted with 20,585 Brazilian adults from all 27 states and more than 3,000 cities, collected using digital outreach. Anxiety and depression symptoms were assessed using the GAD-7 and PHQ-9. CART models were trained and tested on bootstrapped samples (70% training, 30% testing), totaling 45,000 trees per scale. Each model used combinations of scale items and sociodemographic predictors. Robustness was evaluated via 10-fold cross-validation and evaluation across 3 hyperparameter configurations (\n                      <jats:italic>minsplit<\/jats:italic>\n                      and\n                      <jats:italic>minbucket<\/jats:italic>\n                      =500, 1000, 2000). Performance metrics included accuracy, sensitivity, specificity, precision, F1-score, and area under the curve (AUC).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"results\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The CART models produced concise, high-performing decision rules\u2014using only 2 items for the GAD-7 and 3 for the PHQ-9. No sociodemographic variable appeared in the final classification paths. For GAD-7, the models achieved an accuracy of 86.1% for minimal or mild severity and 85.1% for severe cases, with both categories showing AUC values above 0.900. By contrast, the moderate severity class had lower performance, with accuracy around 51% and an AUC of 0.728. For PHQ-9, the models achieved 81.7% accuracy for minimal or mild cases and 78.8% for severe cases, with AUCs again exceeding 0.900 for the extreme classes; the moderate or moderately severe class showed 66.9% accuracy and an AUC of 0.776. The most frequently repeated rules included the following: \u201cGAD2&lt;2 and GAD4&lt;2\u201d for identifying minimal or mild anxiety and \u201cGAD2\u22652 and GAD4=3\u201d for severe anxiety; for depression, \u201cPHQ2&lt;2and PHQ4&lt;2\u201d for minimal or mild cases and \u201cPHQ2\u22652 and PHQ8\u22652\u201d for severe cases. These rule-based models demonstrated stable performance across thousands of bootstrapped replications and showed reproducibility in 5 independent datasets through external validation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"conclusions\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>CART models enabled simplified, symptom-specific pathways for stratifying anxiety and depression severity with high precision and minimal item burden. These rule-based shortcuts offer an efficient alternative to fixed short forms (eg, GAD-2, PHQ-2) by preserving symptom diversity and severity discrimination. The findings support and lay the groundwork for adaptive, cost-effective screening and intervention models, especially in resource-limited settings and LMICs.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.2196\/72591","type":"journal-article","created":{"date-parts":[[2025,9,30]],"date-time":"2025-09-30T20:41:51Z","timestamp":1759264911000},"page":"e72591-e72591","source":"Crossref","is-referenced-by-count":7,"title":["Severity Classification of Anxiety and Depression Using Generalized Anxiety Disorder Scale and Patient Health Questionnaire: National Cross-Sectional Study Applying Classification and Regression Tree Models"],"prefix":"10.2196","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7348-6297","authenticated-orcid":false,"given":"Andre","family":"Faro","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0275-3578","authenticated-orcid":false,"given":"Julian","family":"Tejada","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8292-0510","authenticated-orcid":false,"given":"Wael","family":"Al-Delaimy","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1010","published-online":{"date-parts":[[2025,9,30]]},"reference":[{"issue":"2","key":"R1","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1016\/S2215-0366(21)00395-3","article-title":"Global, regional, and national burden of 12 mental disorders in 204 countries and territories, 1990\u20132019: a systematic analysis for the Global Burden of Disease Study 2019","volume":"9","author":"GBD","journal-title":"Lancet Psychiatry"},{"issue":"10402","key":"R2","doi-asserted-by":"publisher","first-page":"656","DOI":"10.1016\/S0140-6736(23)00918-2","article-title":"Transforming mental health systems globally: principles and policy recommendations","volume":"402","author":"Patel","journal-title":"Lancet"},{"issue":"7","key":"R3","doi-asserted-by":"publisher","first-page":"537","DOI":"10.1016\/S2215-0366(23)00113-X","article-title":"Mental health in Europe during the COVID-19 pandemic: a systematic review","volume":"10","author":"Ahmed","journal-title":"Lancet Psychiatry"},{"issue":"9","key":"R4","doi-asserted-by":"publisher","first-page":"8435","DOI":"10.1007\/s12144-022-02913-6","article-title":"Mental health among the general population and healthcare workers during the COVID-19 pandemic: A meta-analysis of well-being and psychological distress prevalence","volume":"43","author":"Blasco-Belled","journal-title":"Curr Psychol"},{"issue":"suppl 1","key":"R5","doi-asserted-by":"publisher","first-page":"2457","DOI":"10.1590\/1413-81232020256.1.10932020","article-title":"Impact of COVID-19 on mental health in a low and middle-income country","volume":"25","author":"Castro-de-Araujo","journal-title":"Cien Saude Colet"},{"issue":"10312","key":"R6","doi-asserted-by":"publisher","first-page":"1700","DOI":"10.1016\/S0140-6736(21)02143-7","article-title":"Global prevalence and burden of depressive and anxiety disorders in 204 countries and territories in 2020 due to the COVID-19 pandemic","volume":"398","author":"Santomauro","journal-title":"The Lancet"},{"issue":"6","key":"R7","doi-asserted-by":"publisher","first-page":"535","DOI":"10.1016\/S2215-0366(21)00025-0","article-title":"COVID-19 mental health impact and responses in low-income and middle-income countries: reimagining global mental health","volume":"8","author":"Kola","journal-title":"Lancet Psychiatry"},{"issue":"7","key":"R8","doi-asserted-by":"publisher","first-page":"301","DOI":"10.1007\/s11920-023-01426-8","article-title":"Global mental health: where we are and where we are going","volume":"25","author":"Moitra","journal-title":"Curr Psychiatry Rep"},{"key":"R9","doi-asserted-by":"publisher","DOI":"10.1016\/j.eclinm.2022.101675","article-title":"Quantifying the global burden of mental disorders and their economic value","volume":"54","author":"Arias","journal-title":"EClinicalMedicine"},{"key":"R10","doi-asserted-by":"crossref","unstructured":"Pringle B Williams M Collins PY . 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