[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-121109-en":3,"doc-seo-121109-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},121109,8796095461564,"Liam","https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d",8,"Research & Report","Predicting remission following CBT for childhood anxiety disorders - a machine learning approach","Identification of predictors of treatment response is critical for improving outcomes for children with anxiety disorders. Machine learning enables detection of factor combinations that can strengthen risk prediction models. In a sample of 2,114 anxious youth aged 5–18, demographic, clinical, parental, and treatment variables measured pre-, post-, and at follow-up were used to predict anxiety-disorder remission. Model performance was comparable (AUC 0.67–0.69).","Psychological Medicine  \n[cambridge.org/psm](cambridge.org/psm)  \nOriginal Article  \n*These two authors contributed equally to this work.  \nCite this article: Bertie L-A et al (2024) . Predicting remission following CBT for childhood anxiety disorders: a machine learning approach. Psychological Medicine 1–11. [https://doi.org/10.1017/](https://doi.org/10.1017/)[ ](https://doi.org/10.1017/)S0033291724002654  \nReceived: 15 March 2024  \nRevised: 22 August 2024  \nAccepted: 30 September 2024  \nKeywords:  \nchildhood anxiety; cognitive behavior therapy; machine learning; risk prediction  \nCorresponding author:  \nJennifer L. Hudson;  \nEmail: [jennie.hudson@blackdog.org.au](jennie.hudson@blackdog.org.au)  \n© The Author(s), 2024 . Published by Cambridge University Press. This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence ([http://creativecommons.org/licenses/by/4.0/](http://creativecommons.org/licenses/by/4.0/)), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.  \nPredicting remission following CBT for childhood anxiety disorders: a machine learning approach  \nLizel-Antoinette Bertie1,2, * , Juan C. Quiroz3,4, * , Shlomo Berkovsky4 , Kristian Arendt5 , Susan Bögels6 , Jonathan R. I. Coleman7 , Peter Cooper8, Cathy Creswell8,9 , Thalia C. Eley7 , Catharina Hartman10,  \nKrister Fjermestadt11, Tina In-Albon12 , Kristen Lavallee13, Kathryn J. Lester14 , Heidi J. Lyneham15, Carla E. Marin16 , Anna McKinnon15,  \nLauren F. McLellan15 , Richard Meiser-Stedman17 , Maaike Nauta10 , Ronald M. Rapee15 , Silvia Schneider18 , Carolyn Schniering15 ,  \nWendy K. Silverman16 , Mikael Thastum5 , Kerstin Thirlwall8, Polly Waite8,9 , Gro Janne Wergeland19 , Viviana Wuthrich15  and Jennifer L. Hudson1,2   \n1Black Dog Institute, University of New South Wales, Sydney, NSW, Australia; 2School of Psychology, UNSW, Sydney, Australia; 3Center for Big Data Research, UNSW, Sydney, Australia; 4Centre for Health Informatics, Australian Institute of Health Innovation, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, Australia; 5Department of Psychology, University of Aarhus, Denmark; 6Research Institute Child Development and Education, University of Amsterdam, the Netherlands; 7Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, & King’s College London, UK; 8School of Psychology and Clinical Language Sciences, University of Reading, UK; 9Departments of Psychiatry and Experimental Psychology, University of Oxford, UK; 10Department of Psychiatry, University Medical Centre Groningen, University of Groningen, the Netherlands; 11Department of Psychology, University of Oslo, Norway; 12Clinical Child and Adolescent Psychology and Psychotherapy, Department of Psychology, University of KoblenzLandau, Landau, Germany; 13Institute of Psychology, University of Basel, Switzerland; 14School of Psychology, University of Sussex, UK; 15Department of Psychological Sciences, Centre for Emotional Health, Macquarie University, Sydney, NSW, Australia; 16Yale University, Child Study Center, New Haven, CT, USA; 17MRC Cognition and Brian Sciences Unit, Cambridge, UK; 18Mental Health Research and Treatment Center, Ruhr-Universtät Bochum, Germany and 19Department of Clinical Medicine, Faculty of Medicine, University of Bergen, Norway  \nAbstract  \nBackground. The identification of predictors of treatment response is crucial for improving treatment outcome for children with anxiety disorders. Machine learning methods provide opportunities to identify combinations of factors that contribute to risk prediction models. Methods. A machine learning approach was applied to predict anxiety disorder remission in a large sample of 2114 anxious youth (5–18 years) . Potential predictors included demographic, clinical, parental, and treatment variables with data obtained pre-treatment, post-treatment, and at le","cbCaihdRAVxQZWbi","https://ap.wps.com/l/cbCaihdRAVxQZWbi","pdf",612523,1,11,"English","en",105,"# Abstract\n# Background\n# Methods\n# Results\n# Conclusions\n# Introduction","[{\"question\":\"What is the study trying to predict after CBT for childhood anxiety disorders?\",\"answer\":\"The study predicts remission of anxiety disorders after cognitive behavior therapy (CBT), including remission across all anxiety disorders and remission of the primary anxiety disorder.\"},{\"question\":\"How was the machine learning approach applied in the study?\",\"answer\":\"Machine learning models used predictors drawn from demographic, clinical, parental, and treatment variables collected before treatment, after treatment, and at follow-up, in a sample of 2,114 youths aged 5–18.\"},{\"question\":\"Which kinds of factors were associated with a higher likelihood of non-remission at therapy completion?\",\"answer\":\"Older age, multiple anxiety disorders, comorbid depression and externalising disorders, receiving group treatment, therapy by a more experienced therapist, and higher parent anxiety/depression symptoms were linked to still meeting criteria at completion.\"}]","Predicting remission following CBT for childhood anxiety disorders - a machine learning approach | PDF",1785733778,28,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"predicting-remission-following-cbt-for-childhood-anxiety-disorders-a-machine-learning-approach","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/predicting-remission-following-cbt-for-childhood-anxiety-disorders-a-machine-learning-approach/121109/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-03",true,{"@type":65,"interactionType":66,"userInteractionCount":20},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What is the study trying to predict after CBT for childhood anxiety disorders?","Question",{"text":75,"@type":76},"The study predicts remission of anxiety disorders after cognitive behavior therapy (CBT), including remission across all anxiety disorders and remission of the primary anxiety disorder.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How was the machine learning approach applied in the study?",{"text":80,"@type":76},"Machine learning models used predictors drawn from demographic, clinical, parental, and treatment variables collected before treatment, after treatment, and at follow-up, in a sample of 2,114 youths aged 5–18.",{"name":82,"@type":73,"acceptedAnswer":83},"Which kinds of factors were associated with a higher likelihood of non-remission at therapy completion?",{"text":84,"@type":76},"Older age, multiple anxiety disorders, comorbid depression and externalising disorders, receiving group treatment, therapy by a more experienced therapist, and higher parent anxiety/depression symptoms were linked to still meeting criteria at completion.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]