{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,29]],"date-time":"2026-10-29T21:07:14Z","timestamp":1793308034756,"version":"4.5.0"},"reference-count":117,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2025,6,1]],"date-time":"2025-06-01T00:00:00Z","timestamp":1748736000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2025,6,1]],"date-time":"2025-06-01T00:00:00Z","timestamp":1748736000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,6,1]],"date-time":"2025-06-01T00:00:00Z","timestamp":1748736000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2025,6,1]],"date-time":"2025-06-01T00:00:00Z","timestamp":1748736000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2025,6,1]],"date-time":"2025-06-01T00:00:00Z","timestamp":1748736000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2025,6,1]],"date-time":"2025-06-01T00:00:00Z","timestamp":1748736000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,6,1]],"date-time":"2025-06-01T00:00:00Z","timestamp":1748736000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100000269","name":"Economic and Social Research Council","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000269","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Journal of Anxiety Disorders"],"published-print":{"date-parts":[[2025,6]]},"DOI":"10.1016\/j.janxdis.2025.103003","type":"journal-article","created":{"date-parts":[[2025,3,11]],"date-time":"2025-03-11T12:13:02Z","timestamp":1741695182000},"page":"103003","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":3,"special_numbering":"C","title":["Using machine learning methods to predict the outcome of psychological therapies for post-traumatic stress disorder: A systematic review"],"prefix":"10.1016","volume":"112","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5336-0363","authenticated-orcid":false,"given":"James","family":"Tait","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stephen","family":"Kellett","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jaime","family":"Delgadillo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"1","key":"10.1016\/j.janxdis.2025.103003_bib1","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1080\/10503307.2020.1808729","article-title":"A scoping review of machine learning in psychotherapy research","volume":"31","author":"Aafjes-van Doorn","year":"2021","journal-title":"Psychotherapy Research"},{"issue":"3","key":"10.1016\/j.janxdis.2025.103003_bib2","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1177\/0011000005285875","article-title":"The meta-analysis of clinical judgment project: Fifty-six years of accumulated research on clinical versus statistical prediction","volume":"34","author":"\u00c6gisd\u00f3ttir","year":"2006","journal-title":"The Counseling Psychologist"},{"key":"10.1016\/j.janxdis.2025.103003_bib3","unstructured":"American Psychological Association(APA). (2017). Clinical practice guideline for the treatment of posttraumatic stress disorder (PTSD) in adults. Author. Retrieved from \u3008https:\/\/www.apa.org\/ptsd-guideline\u3009."},{"issue":"4","key":"10.1016\/j.janxdis.2025.103003_bib4","doi-asserted-by":"crossref","first-page":"344","DOI":"10.1016\/j.carj.2019.06.002","article-title":"Sample-size determination methodologies for machine learning in medical imaging research: A systematic review","volume":"70","author":"Balki","year":"2019","journal-title":"Canadian Association of Radiologists Journal"},{"issue":"1","key":"10.1016\/j.janxdis.2025.103003_bib5","doi-asserted-by":"crossref","DOI":"10.1080\/20008198.2020.1774240","article-title":"A systematic review of factors associated with outcome of psychological treatments for post-traumatic stress disorder","volume":"11","author":"Barawi","year":"2020","journal-title":"European Journal of Psychotraumatology"},{"issue":"12","key":"10.1016\/j.janxdis.2025.103003_bib6","first-page":"2222","article-title":"What is machine learning? A primer for the epidemiologist","volume":"188","author":"Bi","year":"2019","journal-title":"American Journal of Epidemiology"},{"issue":"4","key":"10.1016\/j.janxdis.2025.103003_bib7","doi-asserted-by":"crossref","first-page":"e231","DOI":"10.1016\/S2589-7500(21)00018-2","article-title":"Dynamic prediction of psychological treatment outcomes: Development and validation of a prediction model using routinely collected symptom data","volume":"3","author":"Bone","year":"2021","journal-title":"The Lancet Digital Health"},{"key":"10.1016\/j.janxdis.2025.103003_bib8","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Machine Learning"},{"key":"10.1016\/j.janxdis.2025.103003_bib9","doi-asserted-by":"crossref","DOI":"10.1016\/j.psychres.2020.112779","article-title":"Identifying PTSD symptom typologies: A latent class analysis","volume":"285","author":"Campbell","year":"2020","journal-title":"Psychiatry Research"},{"issue":"15","key":"10.1016\/j.janxdis.2025.103003_bib10","doi-asserted-by":"crossref","first-page":"3646","DOI":"10.1017\/S0033291721000428","article-title":"Dissecting the heterogeneity of posttraumatic stress disorder: Differences in polygenic risk, stress exposures, and course of PTSD subtypes","volume":"52","author":"Campbell-Sills","year":"2022","journal-title":"Psychological Medicine"},{"issue":"2","key":"10.1016\/j.janxdis.2025.103003_bib11","doi-asserted-by":"crossref","first-page":"332","DOI":"10.1017\/S0033291720002032","article-title":"Refining our understanding of depressive states and state transitions in response to cognitive behavioural therapy using latent Markov modelling","volume":"52","author":"Catarino","year":"2022","journal-title":"Psychological Medicine"},{"issue":"1","key":"10.1016\/j.janxdis.2025.103003_bib12","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41398-019-0607-2","article-title":"Recommendations and future directions for supervised machine learning in psychiatry","volume":"9","author":"Cearns","year":"2019","journal-title":"Translational Psychiatry"},{"issue":"2","key":"10.1016\/j.janxdis.2025.103003_bib13","doi-asserted-by":"crossref","first-page":"154","DOI":"10.1002\/wps.20882","article-title":"The promise of machine learning in predicting treatment outcomes in psychiatry","volume":"20","author":"Chekroud","year":"2021","journal-title":"World Psychiatry"},{"issue":"11","key":"10.1016\/j.janxdis.2025.103003_bib14","doi-asserted-by":"crossref","DOI":"10.1016\/j.patter.2022.100602","article-title":"Modern views of machine learning for precision psychiatry","volume":"3","author":"Chen","year":"2022","journal-title":"Patterns"},{"key":"10.1016\/j.janxdis.2025.103003_bib15","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.jclinepi.2019.02.004","article-title":"A systematic review shows no performance benefit of machine learning over logistic regression for clinical prediction models","volume":"110","author":"Christodoulou","year":"2019","journal-title":"Journal of Clinical Epidemiology"},{"key":"10.1016\/j.janxdis.2025.103003_bib16","unstructured":"Cohen, Z.D. (2018). Treatment selection: understanding what works for whom in mental health (Ph.D., University of Pennsylvania). Retrieved from \u3008https:\/\/www.proquest.com\/docview\/2117235776\/abstract\/3CA5132CE7244197PQ\/1\u3009."},{"key":"10.1016\/j.janxdis.2025.103003_bib17","series-title":"Bergin and Garfield\u2019s handbook of psychotherapy and behavior change","first-page":"673","article-title":"Personalized treatment approaches","author":"Cohen","year":"2021"},{"issue":"7","key":"10.1016\/j.janxdis.2025.103003_bib18","doi-asserted-by":"crossref","DOI":"10.1136\/bmjopen-2020-048008","article-title":"Protocol for development of a reporting guideline (TRIPOD-AI) and risk of bias tool (PROBAST-AI) for diagnostic and prognostic prediction model studies based on artificial intelligence","volume":"11","author":"Collins","year":"2021","journal-title":"BMJ Open"},{"key":"10.1016\/j.janxdis.2025.103003_bib19","doi-asserted-by":"crossref","DOI":"10.1136\/bmj-2023-078378","article-title":"TRIPOD+AI statement: Updated guidance for reporting clinical prediction models that use regression or machine learning methods","volume":"385","author":"Collins","year":"2024","journal-title":"BMJ"},{"issue":"1","key":"10.1016\/j.janxdis.2025.103003_bib20","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1186\/s12859-022-04675-1","article-title":"Statistical power for cluster analysis","volume":"23","author":"Dalmaijer","year":"2022","journal-title":"BMC Bioinformatics"},{"issue":"6","key":"10.1016\/j.janxdis.2025.103003_bib21","doi-asserted-by":"crossref","first-page":"541","DOI":"10.1002\/da.22755","article-title":"Individual treatment selection for patients with posttraumatic stress disorder","volume":"35","author":"Deisenhofer","year":"2018","journal-title":"Depression and Anxiety"},{"issue":"1","key":"10.1016\/j.janxdis.2025.103003_bib22","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/10503307.2020.1859638","article-title":"Machine learning: A primer for psychotherapy researchers","volume":"31","author":"Delgadillo","year":"2021","journal-title":"Psychotherapy Research"},{"issue":"2","key":"10.1016\/j.janxdis.2025.103003_bib23","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1001\/jamapsychiatry.2021.3539","article-title":"Stratified care vs stepped care for depression: A cluster randomized clinical trial","volume":"79","author":"Delgadillo","year":"2022","journal-title":"JAMA Psychiatry"},{"key":"10.1016\/j.janxdis.2025.103003_bib24","series-title":"In Reference Module in Neuroscience and Biobehavioral Psychology","article-title":"Artificial intelligence, machine learning and mental health","author":"Delgadillo","year":"2022"},{"issue":"9","key":"10.1016\/j.janxdis.2025.103003_bib25","doi-asserted-by":"crossref","first-page":"889","DOI":"10.1001\/jamapsychiatry.2020.1048","article-title":"A development pathway towards precision mental health care","volume":"77","author":"Delgadillo","year":"2020","journal-title":"JAMA Psychiatry"},{"key":"10.1016\/j.janxdis.2025.103003_bib26","unstructured":"Department of Veterans Affairs and Department of Defense (VA\/DoD). 2017) VA\/DoD clinical practice guideline for the management of posttraumatic stress disorder and acute stress disorder. Author. Retrieved from \u3008https:\/\/www.healthquality.va.gov\/guidelines\/MH\/ptsd\/VADoDPTSDCPGFinal012418.pdf\u3009."},{"key":"10.1016\/j.janxdis.2025.103003_bib27","unstructured":"Department of Veterans Affairs and Department of Defense (VA\/DoD). 2023) VA\/DoD clinical practice guideline for the management of posttraumatic stress disorder and acute stress disorder (Version 4.0). Author. Retrieved from \u3008https:\/\/www.healthquality.va.gov\/guidelines\/MH\/ptsd\/VADoDPTSDCPGFinal012418.pdf\u3009."},{"issue":"2","key":"10.1016\/j.janxdis.2025.103003_bib28","first-page":"71","article-title":"Identifying trajectories and predictors of response to psychotherapy for post-traumatic stress disorder in adults: A systematic review of literature","volume":"65","author":"Dewar","year":"2020","journal-title":"The Canadian Journal of Psychiatry"},{"key":"10.1016\/j.janxdis.2025.103003_bib29","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1146\/annurev-clinpsy-032816-045037","article-title":"Machine learning approaches for clinical psychology and psychiatry","volume":"14","author":"Dwyer","year":"2018","journal-title":"Annual Review of Clinical Psychology"},{"issue":"486","key":"10.1016\/j.janxdis.2025.103003_bib30","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1126\/scitranslmed.aal3236","article-title":"Using fMRI connectivity to define a treatment-resistant form of post-traumatic stress disorder","volume":"11","author":"Etkin","year":"2019","journal-title":"Science Translational Medicine"},{"key":"10.1016\/j.janxdis.2025.103003_bib31","series-title":"Mental health and wellbeing in England: Adult Psychiatric Morbidity Survey 2014","article-title":"Chapter 4: Posttraumatic stress disorder","author":"Fear","year":"2016"},{"issue":"2","key":"10.1016\/j.janxdis.2025.103003_bib32","doi-asserted-by":"crossref","first-page":"172","DOI":"10.1037\/ser0000139","article-title":"Actuarial prediction of psychotherapy retention among Iraq-Afghanistan veterans with posttraumatic stress disorder","volume":"15","author":"Fleming","year":"2018","journal-title":"Psychol Serv"},{"issue":"2","key":"10.1016\/j.janxdis.2025.103003_bib33","doi-asserted-by":"crossref","first-page":"194","DOI":"10.1037\/0022-006X.67.2.194","article-title":"A comparison of exposure therapy, stress inoculation training, and their combination for reducing posttraumatic stress disorder in female assault victims","volume":"67","author":"Foa","year":"1999","journal-title":"Journal of Consulting and Clinical Psychology"},{"issue":"8","key":"10.1016\/j.janxdis.2025.103003_bib34","doi-asserted-by":"crossref","first-page":"531","DOI":"10.1097\/01.nmd.0000082181.79051.83","article-title":"MMPI-2 based subgroups of veterans with combat-related PTSD: differential patterns of symptom change after treatment","volume":"191","author":"Forbes","year":"2003","journal-title":"The Journal of Nervous and Mental Disease"},{"issue":"6","key":"10.1016\/j.janxdis.2025.103003_bib35","doi-asserted-by":"crossref","first-page":"651","DOI":"10.1177\/1745691613504115","article-title":"636,120 ways to have posttraumatic stress disorder","volume":"8","author":"Galatzer-Levy","year":"2013","journal-title":"Perspectives on Psychological Science"},{"issue":"6","key":"10.1016\/j.janxdis.2025.103003_bib36","doi-asserted-by":"crossref","first-page":"968","DOI":"10.1037\/a0030600","article-title":"Manualized therapy for PTSD: Flexing the structure of cognitive processing therapy","volume":"80","author":"Galovski","year":"2012","journal-title":"Journal of Consulting and Clinical Psychology"},{"issue":"2","key":"10.1016\/j.janxdis.2025.103003_bib37","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1037\/ccp0000059","article-title":"Augmenting cognitive processing therapy to improve sleep impairment in PTSD: A randomized controlled trial","volume":"84","author":"Galovski","year":"2016","journal-title":"Journal of Consulting and Clinical Psychology"},{"issue":"6","key":"10.1016\/j.janxdis.2025.103003_bib38","doi-asserted-by":"crossref","first-page":"683","DOI":"10.1080\/10503307.2022.2161432","article-title":"Predicting dropout from psychological treatment using different machine learning algorithms, resampling methods, and sample sizes","volume":"33","author":"Giesemann","year":"2023","journal-title":"Psychotherapy Research"},{"issue":"5","key":"10.1016\/j.janxdis.2025.103003_bib39","article-title":"Machine learning and natural language processing in mental health: Systematic review","volume":"23","author":"Glaz","year":"2021","journal-title":"Journal of Medical Internet Research"},{"key":"10.1016\/j.janxdis.2025.103003_bib40","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1016\/j.cpr.2015.06.008","article-title":"The efficacy of recommended treatments for veterans with PTSD: A metaregression analysis","volume":"40","author":"Haagen","year":"2015","journal-title":"Clinical Psychology Review"},{"key":"10.1016\/j.janxdis.2025.103003_bib41","unstructured":"Haddaway, N.R. (2021). citationchaser: An R package and Shiny app for forward and backward citations chasing in academic searching. \u3008https:\/\/estech.shinyapps.io\/citationchaser\/\u3009."},{"issue":"1","key":"10.1016\/j.janxdis.2025.103003_bib42","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1038\/mp.2016.201","article-title":"Predictive analytics in mental health: Applications, guidelines, challenges and perspectives","volume":"22","author":"Hahn","year":"2017","journal-title":"Molecular Psychiatry"},{"issue":"3","key":"10.1016\/j.janxdis.2025.103003_bib43","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1037\/pst0000231","article-title":"A guide to guidelines for the treatment of posttraumatic stress disorder in adults: An update","volume":"56","author":"Hamblen","year":"2019","journal-title":"Psychotherapy"},{"key":"10.1016\/j.janxdis.2025.103003_bib44","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1016\/j.jpsychires.2022.03.066","article-title":"Who will respond to intensive PTSD treatment? A machine learning approach to predicting response prior to starting treatment","volume":"151","author":"Held","year":"2022","journal-title":"Journal of Psychiatric Research"},{"issue":"1","key":"10.1016\/j.janxdis.2025.103003_bib45","doi-asserted-by":"crossref","DOI":"10.1080\/20008198.2018.1425574","article-title":"Intensive prolonged exposure therapy for chronic PTSD patients following multiple trauma and multiple treatment attempts","volume":"9","author":"Hendriks","year":"2018","journal-title":"European Journal of Psychotraumatology"},{"key":"10.1016\/j.janxdis.2025.103003_bib46","doi-asserted-by":"crossref","DOI":"10.1016\/j.janxdis.2022.102611","article-title":"Is it worth it to personalize the treatment of PTSD? \u2013 A variance-ratio meta-analysis and estimation of treatment effect heterogeneity in RCTs of PTSD","volume":"91","author":"Herzog","year":"2022","journal-title":"Journal of Anxiety Disorders"},{"issue":"4","key":"10.1016\/j.janxdis.2025.103003_bib47","doi-asserted-by":"crossref","first-page":"468","DOI":"10.1080\/10503307.2020.1802081","article-title":"Predictors of outcome during inpatient psychotherapy for posttraumatic stress disorder: A single-treatment, multi-site, practice-based study","volume":"31","author":"Herzog","year":"2021","journal-title":"Psychother Res"},{"issue":"2","key":"10.1016\/j.janxdis.2025.103003_bib48","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1037\/a0038719","article-title":"Combining Seeking Safety with Sertraline for PTSD and alcohol use disorders: A randomized controlled trial","volume":"83","author":"Hien","year":"2015","journal-title":"Journal of Consulting and Clinical Psychology"},{"issue":"19","key":"10.1016\/j.janxdis.2025.103003_bib49","doi-asserted-by":"crossref","DOI":"10.3390\/jcm10194522","article-title":"Personalization of treatment for patients with childhoodabuse-related posttraumatic stress disorder","volume":"10","author":"Hoeboer","year":"2021","journal-title":"Journal of Clinical Medicine"},{"key":"10.1016\/j.janxdis.2025.103003_bib50","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1016\/j.jpsychires.2016.08.018","article-title":"Latent typologies of posttraumatic stress disorder in World Trade Center responders","volume":"83","author":"Horn","year":"2016","journal-title":"Journal of Psychiatric Research"},{"key":"10.1016\/j.janxdis.2025.103003_bib51","unstructured":"International Society for Traumatic Stress Studies (ISTSS). (2018). ISTSS PTSD prevention and treatment guidelines: Methodology and recommendations. Retrieved from \u3008http:\/\/www.istss.org\/getattachment\/TreatingTrauma\/New-ISTSS-Prevention-and-Treatment-Guidelines\/ISTSS_PreventionTreatmentGuidelines_FNL-March-19-2019.pdf.aspx\u3009."},{"key":"10.1016\/j.janxdis.2025.103003_bib52","article-title":"Trauma-focused psychotherapies for post-traumatic stress disorder: A systematic review and network meta-analysis","author":"Jericho","year":"2021","journal-title":"Acta Psychiatrica Scandinavica"},{"issue":"6245","key":"10.1016\/j.janxdis.2025.103003_bib53","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1126\/science.aaa8415","article-title":"Machine learning: Trends, perspectives, and prospects","volume":"349","author":"Jordan","year":"2015","journal-title":"Science"},{"issue":"9","key":"10.1016\/j.janxdis.2025.103003_bib54","doi-asserted-by":"crossref","first-page":"887","DOI":"10.1002\/da.22934","article-title":"Risk factors and comorbidity of ICD-11 PTSD and complex PTSD: Findings from a trauma-exposed population based sample of adults in the United Kingdom","volume":"36","author":"Karatzias","year":"2019","journal-title":"Depression and Anxiety"},{"issue":"4","key":"10.1016\/j.janxdis.2025.103003_bib55","doi-asserted-by":"crossref","first-page":"330","DOI":"10.1002\/da.22731","article-title":"In rape trauma PTSD, patient characteristics indicate which trauma-focused treatment they are most likely to complete","volume":"35","author":"Keefe","year":"2018","journal-title":"Depression and Anxiety"},{"issue":"1","key":"10.1016\/j.janxdis.2025.103003_bib56","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1017\/S2045796016000020","article-title":"Using patient self-reports to study heterogeneity of treatment effects in major depressive disorder","volume":"26","author":"Kessler","year":"2017","journal-title":"Epidemiology and Psychiatric Sciences"},{"issue":"12","key":"10.1016\/j.janxdis.2025.103003_bib57","doi-asserted-by":"crossref","first-page":"1384","DOI":"10.1001\/jamapsychiatry.2021.2500","article-title":"Pragmatic precision psychiatry\u2014A new direction for optimizing treatment selection","volume":"78","author":"Kessler","year":"2021","journal-title":"JAMA Psychiatry"},{"issue":"1","key":"10.1016\/j.janxdis.2025.103003_bib58","doi-asserted-by":"crossref","first-page":"250","DOI":"10.1016\/j.beth.2020.04.015","article-title":"The effect of concurrent depression on PTSD outcomes in trauma-focused psychotherapy: A meta-analysis of randomized controlled trials","volume":"52","author":"Kline","year":"2021","journal-title":"Behavior Therapy"},{"issue":"13","key":"10.1016\/j.janxdis.2025.103003_bib59","doi-asserted-by":"crossref","first-page":"2260","DOI":"10.1017\/S0033291717000708","article-title":"Posttraumatic stress disorder in the World Mental Health Surveys","volume":"47","author":"Koenen","year":"2017","journal-title":"Psychological Medicine"},{"issue":"3\u20134","key":"10.1016\/j.janxdis.2025.103003_bib60","first-page":"114","article-title":"Inpatient treatment of complex PTSD following childhood abuse: effectiveness and predictors of treatment outcome","volume":"69","author":"Kratzer","year":"2019","journal-title":"PPmP Psychotherapie Psychosomatik Medizinische Psychologie"},{"issue":"17","key":"10.1016\/j.janxdis.2025.103003_bib61","doi-asserted-by":"crossref","first-page":"1818","DOI":"10.1001\/jama.2016.16435","article-title":"Confounding by indication in clinical research","volume":"316","author":"Kyriacou","year":"2016","journal-title":"JAMA"},{"key":"10.1016\/j.janxdis.2025.103003_bib62","doi-asserted-by":"crossref","first-page":"519","DOI":"10.1016\/j.jad.2018.08.073","article-title":"Applications of machine learning algorithms to predict therapeutic outcomes in depression: A meta-analysis and systematic review","volume":"241","author":"Lee","year":"2018","journal-title":"Journal of Affective Disorders"},{"issue":"1","key":"10.1016\/j.janxdis.2025.103003_bib63","article-title":"Psychological therapies for post-traumatic stress disorder in adults: Systematic review and meta-analysis","volume":"11","author":"Lewis","year":"2020","journal-title":"European Journal of Psychotraumatology"},{"issue":"1","key":"10.1016\/j.janxdis.2025.103003_bib64","article-title":"Dropout from psychological therapies for post-traumatic stress disorder (PTSD) in adults: Systematic review and meta-analysis","volume":"11","author":"Lewis","year":"2020","journal-title":"European Journal of Psychotraumatology"},{"issue":"10","key":"10.1016\/j.janxdis.2025.103003_bib65","doi-asserted-by":"crossref","first-page":"869","DOI":"10.1037\/ccp0000688","article-title":"Seeing the forest for the trees: Predicting attendance in trials for co-occurring PTSD and substance use disorders with a machine learning approach","volume":"89","author":"L\u00f3pez-Castro","year":"2021","journal-title":"Journal of Consulting and Clinical Psychology"},{"key":"10.1016\/j.janxdis.2025.103003_bib66","doi-asserted-by":"crossref","DOI":"10.1016\/j.brat.2019.103438","article-title":"Towards integrating personalized feedback research into clinical practice: Development of the Trier Treatment Navigator (TTN)","volume":"120","author":"Lutz","year":"2019","journal-title":"Behaviour Research and Therapy"},{"key":"10.1016\/j.janxdis.2025.103003_bib67","doi-asserted-by":"crossref","first-page":"85","DOI":"10.3389\/fpsyt.2017.00085","article-title":"Neural correlates of psychotherapeutic treatment of post-traumatic stress disorder: A systematic literature review","volume":"8","author":"Malejko","year":"2017","journal-title":"Frontiers in Psychiatry"},{"issue":"4","key":"10.1016\/j.janxdis.2025.103003_bib68","doi-asserted-by":"crossref","first-page":"272","DOI":"10.1027\/1016-9040\/a000423","article-title":"ArtificiaL Intelligence and Posttraumatic Stress Disorder (PTSD)","volume":"25","author":"Malgaroli","year":"2021","journal-title":"European Psychologist"},{"key":"10.1016\/j.janxdis.2025.103003_bib69","doi-asserted-by":"crossref","first-page":"127","DOI":"10.2147\/PGPM.S198225","article-title":"Challenges and future prospects of precision medicine in psychiatry","volume":"13","author":"Manchia","year":"2020","journal-title":"Pharmacogenomics and Personalized Medicine"},{"issue":"18","key":"10.1016\/j.janxdis.2025.103003_bib70","doi-asserted-by":"crossref","first-page":"4175","DOI":"10.3390\/jcm10184175","article-title":"Treatment guidelines for PTSD: A systematic review","volume":"10","author":"Martin","year":"2021","journal-title":"Journal of Clinical Medicine"},{"issue":"4","key":"10.1016\/j.janxdis.2025.103003_bib71","doi-asserted-by":"crossref","first-page":"542","DOI":"10.1017\/S0033291720000070","article-title":"Psychological treatments for post-traumatic stress disorder in adults: A network meta-analysis","volume":"50","author":"Mavranezouli","year":"2020","journal-title":"Psychological Medicine"},{"issue":"6","key":"10.1016\/j.janxdis.2025.103003_bib72","doi-asserted-by":"crossref","DOI":"10.1038\/s41380-022-01528-4","article-title":"Clinical prediction models in psychiatry: A systematic review of two decades of progress and challenges","volume":"27","author":"Meehan","year":"2022","journal-title":"Molecular Psychiatry"},{"issue":"9","key":"10.1016\/j.janxdis.2025.103003_bib73","doi-asserted-by":"crossref","first-page":"904","DOI":"10.1001\/jamapsychiatry.2019.0951","article-title":"Comparative efficacy and acceptability of pharmacological, psychotherapeutic, and combination treatments in adults with posttraumatic stress disorder: A network meta-analysis","volume":"76","author":"Merz","year":"2019","journal-title":"JAMA Psychiatry"},{"issue":"10","key":"10.1016\/j.janxdis.2025.103003_bib74","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pmed.1001744","article-title":"Critical appraisal and data extraction for systematic reviews of prediction modelling studies: The CHARMS checklist","volume":"11","author":"Moons","year":"2014","journal-title":"PLoS Medicine"},{"issue":"1","key":"10.1016\/j.janxdis.2025.103003_bib75","doi-asserted-by":"crossref","first-page":"1","DOI":"10.7326\/M18-1377","article-title":"PROBAST: A tool to assess risk of bias and applicability of prediction model studies: Explanation and elaboration","volume":"170","author":"Moons","year":"2019","journal-title":"Annals of Internal Medicine"},{"key":"10.1016\/j.janxdis.2025.103003_bib76","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2022\/2833537","article-title":"Random forests in count data modelling: An analysis of the influence of data features and overdispersion on regression performance","volume":"2022","author":"Mushagalusa","year":"2022","journal-title":"Journal of Probability and Statistics"},{"key":"10.1016\/j.janxdis.2025.103003_bib77","doi-asserted-by":"crossref","first-page":"43","DOI":"10.12703\/P7-43","article-title":"The problem of dropout from \u201cgold standard\u201d PTSD therapies","volume":"7","author":"Najavits","year":"2015","journal-title":"F1000Prime Reports"},{"key":"10.1016\/j.janxdis.2025.103003_bib78","unstructured":"National Institute for Health and Care Excellence (NICE). 2018. Post-traumatic stress disorder (NICE guideline [NG116]). Retrieved from \u3008https:\/\/www.nice.org.uk\/guidance\/ng116\u3009."},{"key":"10.1016\/j.janxdis.2025.103003_bib79","doi-asserted-by":"crossref","DOI":"10.1016\/j.brat.2021.103920","article-title":"Predicting response to cognitive processing therapy for PTSD: a machine-learning approach","volume":"144","author":"Nixon","year":"2021","journal-title":"Behaviour Research and Therapy"},{"issue":"6","key":"10.1016\/j.janxdis.2025.103003_bib80","doi-asserted-by":"crossref","first-page":"642","DOI":"10.1016\/j.cpr.2010.04.008","article-title":"A meta-analysis of the influence of comorbidity on treatment outcome in the anxiety disorders","volume":"30","author":"Olatunji","year":"2010","journal-title":"Clinical Psychology Review"},{"issue":"1","key":"10.1016\/j.janxdis.2025.103003_bib81","doi-asserted-by":"crossref","DOI":"10.1080\/20008198.2020.1851511","article-title":"Effect of Prolonged Exposure, intensified Prolonged Exposure and STAIR+Prolonged Exposure in patients with PTSD related to childhood abuse: A randomized controlled trial","volume":"12","author":"Oprel","year":"2021","journal-title":"European Journal of Psychotraumatology"},{"issue":"1","key":"10.1016\/j.janxdis.2025.103003_bib82","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1016\/j.janxdis.2012.08.004","article-title":"The physical health consequences of PTSD and PTSD symptoms: a meta-analytic review","volume":"27","author":"Pacella","year":"2013","journal-title":"Journal of Anxiety Disorders"},{"key":"10.1016\/j.janxdis.2025.103003_bib83","doi-asserted-by":"crossref","first-page":"n71","DOI":"10.1136\/bmj.n71","article-title":"The PRISMA 2020 statement: an updated guideline for reporting systematic reviews","volume":"372","author":"Page","year":"2021","journal-title":"BMJ"},{"issue":"23","key":"10.1016\/j.janxdis.2025.103003_bib84","doi-asserted-by":"crossref","first-page":"3207","DOI":"10.1002\/sim.8660","article-title":"A general presentation on how to carry out a CHARMS analysis for prognostic multivariate models","volume":"39","author":"Palaz\u00f3n-Bru","year":"2020","journal-title":"Statistics in Medicine"},{"key":"10.1016\/j.janxdis.2025.103003_bib85","unstructured":"Phoenix Australia Centre for Posttraumatic Mental Health. (2021). Australian guidelines for the prevention and treatment of acute stress disorder, posttraumatic stress disorder and complex PTSD. Author. Retrieved from \u3008https:\/\/www.phoenixaustralia.org\/australian-guidelines-for-ptsd\/\u3009."},{"key":"10.1016\/j.janxdis.2025.103003_bib86","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1016\/j.jad.2014.03.024","article-title":"Typologies of posttraumatic stress disorder in the U.S. adult population","volume":"162","author":"Pietrzak","year":"2014","journal-title":"Journal of Affective Disorders"},{"key":"10.1016\/j.janxdis.2025.103003_bib87","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1016\/j.jpsychires.2019.12.001","article-title":"The use of machine learning techniques in trauma-related disorders: A systematic review","volume":"121","author":"Ramos-Lima","year":"2020","journal-title":"Journal of Psychiatric Research"},{"issue":"4","key":"10.1016\/j.janxdis.2025.103003_bib88","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1002\/mhs2.35","article-title":"Neighborhood poverty prospectively predicts PTSD symptoms six-months following trauma exposure","volume":"1","author":"Ravi","year":"2023","journal-title":"Mental Health Science"},{"issue":"4","key":"10.1016\/j.janxdis.2025.103003_bib89","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1891\/0889-8391.15.4.321","article-title":"Cognitive therapy for posttraumatic stress disorder","volume":"15","author":"Resick","year":"2001","journal-title":"Journal of Cognitive Psychotherapy"},{"issue":"2","key":"10.1016\/j.janxdis.2025.103003_bib90","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1037\/0022-006X.76.2.243","article-title":"A randomized clinical trial to dismantle components of cognitive processing therapy for posttraumatic stress disorder in female victims of interpersonal violence","volume":"76","author":"Resick","year":"2008","journal-title":"Journal of Consulting and Clinical Psychology"},{"issue":"4","key":"10.1016\/j.janxdis.2025.103003_bib91","doi-asserted-by":"crossref","first-page":"867","DOI":"10.1037\/0022-006X.70.4.867","article-title":"A comparison of cognitive-processing therapy with prolonged exposure and a waiting condition for the treatment of chronic posttraumatic stress disorder in female rape victims","volume":"70","author":"Resick","year":"2002","journal-title":"Journal of Consulting and Clinical Psychology"},{"key":"10.1016\/j.janxdis.2025.103003_bib92","doi-asserted-by":"crossref","first-page":"m441","DOI":"10.1136\/bmj.m441","article-title":"Calculating the sample size required for developing a clinical prediction model","volume":"368","author":"Riley","year":"2020","journal-title":"BMJ"},{"key":"10.1016\/j.janxdis.2025.103003_bib93","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1016\/j.jclinepi.2020.12.005","article-title":"Penalization and shrinkage methods produced unreliable clinical prediction models especially when sample size was small","volume":"132","author":"Riley","year":"2021","journal-title":"Journal of Clinical Epidemiology"},{"issue":"1","key":"10.1016\/j.janxdis.2025.103003_bib94","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1080\/10503307.2019.1566676","article-title":"The dose-response effect in routinely delivered psychological therapies: A systematic review","volume":"30","author":"Robinson","year":"2020","journal-title":"Psychotherapy Research"},{"issue":"3","key":"10.1016\/j.janxdis.2025.103003_bib95","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1159\/000462977","article-title":"Concurrent treatment with prolonged exposure for co-occurring full or subthreshold posttraumatic stress disorder and substance use disorders: A randomized clinical trial","volume":"86","author":"Ruglass","year":"2017","journal-title":"Psychotherapy and Psychosomatics"},{"issue":"16","key":"10.1016\/j.janxdis.2025.103003_bib96","doi-asserted-by":"crossref","first-page":"2742","DOI":"10.1017\/S0033291721003871","article-title":"Machine learning in the prediction of depression treatment outcomes: A systematic review and meta-analysis","volume":"51","author":"Sajjadian","year":"2021","journal-title":"Psychological Medicine"},{"issue":"8","key":"10.1016\/j.janxdis.2025.103003_bib97","doi-asserted-by":"crossref","first-page":"820","DOI":"10.1001\/jama.297.8.820","article-title":"Cognitive behavioral therapy for posttraumatic stress disorder in women: A randomized controlled trial","volume":"297","author":"Schnurr","year":"2007","journal-title":"Jama"},{"issue":"2","key":"10.1016\/j.janxdis.2025.103003_bib98","doi-asserted-by":"crossref","first-page":"134","DOI":"10.1521\/psyc.2008.71.2.134","article-title":"Nonresponse and dropout rates in outcome studies on PTSD: review and methodological considerations","volume":"71","author":"Schottenbauer","year":"2008","journal-title":"Psychiatry: Interpersonal and Biological Processes"},{"issue":"25","key":"10.1016\/j.janxdis.2025.103003_bib99","doi-asserted-by":"crossref","first-page":"2459","DOI":"10.1056\/NEJMra1612499","article-title":"Post-traumatic stress disorder","volume":"376","author":"Shalev","year":"2017","journal-title":"New England Journal of Medicine"},{"issue":"12","key":"10.1016\/j.janxdis.2025.103003_bib100","doi-asserted-by":"crossref","first-page":"1461","DOI":"10.1001\/jama.286.12.1461","article-title":"Validity of the agency for healthcare research and quality clinical practice guidelineshow quickly do guidelines become outdated?","volume":"286","author":"Shekelle","year":"2001","journal-title":"JAMA"},{"issue":"6","key":"10.1016\/j.janxdis.2025.103003_bib101","doi-asserted-by":"crossref","first-page":"516","DOI":"10.1037\/tra0000038","article-title":"Preferences for trauma treatment: A systematic review of the empirical literature","volume":"7","author":"Simiola","year":"2015","journal-title":"Psychological Trauma Theory, Research, Practice, and Policy"},{"issue":"9","key":"10.1016\/j.janxdis.2025.103003_bib102","doi-asserted-by":"crossref","first-page":"907","DOI":"10.1002\/da.23161","article-title":"Depression subtypes and their response to cognitive behavioral therapy: A latent transition analysis","volume":"38","author":"Simmonds-Buckley","year":"2021","journal-title":"Depression and Anxiety"},{"issue":"5","key":"10.1016\/j.janxdis.2025.103003_bib103","doi-asserted-by":"crossref","first-page":"489","DOI":"10.1001\/jama.2015.8370","article-title":"Psychotherapy for military-related PTSD: A review of randomized clinical trials","volume":"314","author":"Steenkamp","year":"2015","journal-title":"JAMA"},{"key":"10.1016\/j.janxdis.2025.103003_bib104","series-title":"Clinical prediction models: A practical approach to development, validation, and updating","author":"Steyerberg","year":"2019"},{"key":"10.1016\/j.janxdis.2025.103003_bib105","doi-asserted-by":"crossref","DOI":"10.1016\/j.brat.2021.103872","article-title":"A personalized index to inform selection of a trauma-focused or non-trauma-focused treatment for PTSD","volume":"142","author":"Stirman","year":"2021","journal-title":"Behaviour Research and Therapy"},{"issue":"1","key":"10.1016\/j.janxdis.2025.103003_bib106","doi-asserted-by":"crossref","DOI":"10.1080\/20008198.2021.1958471","article-title":"Predicting outcome of daycare cognitive behavioural therapy in a naturalistic sample of patients with PTSD: A machine learning approach","volume":"12","author":"Stuke","year":"2021","journal-title":"European Journal of Psychotraumatology"},{"issue":"1","key":"10.1016\/j.janxdis.2025.103003_bib107","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1037\/pst0000104","article-title":"Treatment refusal and premature termination in psychotherapy, pharmacotherapy, and their combination: A meta-analysis of head-to-head comparisons","volume":"54","author":"Swift","year":"2017","journal-title":"Psychotherapy"},{"issue":"11","key":"10.1016\/j.janxdis.2025.103003_bib108","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0224365","article-title":"Machine learning algorithm validation with a limited sample size","volume":"14","author":"Vabalas","year":"2019","journal-title":"PLOS ONE"},{"issue":"1","key":"10.1016\/j.janxdis.2025.103003_bib109","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1186\/1471-2288-14-137","article-title":"Modern modelling techniques are data hungry: A simulation study for predicting dichotomous endpoints","volume":"14","author":"van der Ploeg","year":"2014","journal-title":"BMC Medical Research Methodology"},{"key":"10.1016\/j.janxdis.2025.103003_bib110","doi-asserted-by":"crossref","DOI":"10.1016\/j.cpr.2022.102193","article-title":"Can we predict who will benefit from cognitive-behavioural therapy? A systematic review and meta-analysis of machine learning studies","author":"Vieira","year":"2022","journal-title":"Clinical Psychology Review"},{"issue":"1","key":"10.1016\/j.janxdis.2025.103003_bib111","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1037\/ccp0000451","article-title":"Personalized prognostic prediction of treatment outcome for depressed patients in a naturalistic psychiatric hospital setting: A comparison of machine learning approaches","volume":"88","author":"Webb","year":"2020","journal-title":"Journal of Consulting and Clinical Psychology"},{"issue":"6","key":"10.1016\/j.janxdis.2025.103003_bib112","doi-asserted-by":"crossref","first-page":"1100","DOI":"10.1177\/1745691617693393","article-title":"Choosing prediction over explanation in psychology: Lessons from machine learning","volume":"12","author":"Yarkoni","year":"2017","journal-title":"Perspectives on Psychological Science"},{"issue":"1","key":"10.1016\/j.janxdis.2025.103003_bib113","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/nrdp.2015.57","article-title":"Post-traumatic stress disorder","volume":"1","author":"Yehuda","year":"2015","journal-title":"Nature Reviews Disease Primers"},{"issue":"4","key":"10.1016\/j.janxdis.2025.103003_bib114","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1038\/s41551-020-00614-8","article-title":"Identification of psychiatric disorder subtypes from functional connectivity patterns in resting-state electroencephalography","volume":"5","author":"Zhang","year":"2021","journal-title":"Nature Biomedical Engineering"},{"issue":"1","key":"10.1016\/j.janxdis.2025.103003_bib115","doi-asserted-by":"crossref","DOI":"10.1038\/s41398-019-0663-7","article-title":"Individual prediction of psychotherapy outcome in posttraumatic stress disorder using neuroimaging data","volume":"9","author":"Zhutovsky","year":"2019","journal-title":"Translational Psychiatry"},{"issue":"7","key":"10.1016\/j.janxdis.2025.103003_bib116","first-page":"688","article-title":"Diagnostic and Predictive Neuroimaging Biomarkers for Posttraumatic Stress Disorder","volume":"5","author":"Zilcha-Mano","year":"2020","journal-title":"Biological Psychiatry: Cognitive Neuroscience and Neuroimaging"},{"issue":"2","key":"10.1016\/j.janxdis.2025.103003_bib117","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1111\/j.1467-9868.2005.00503.x","article-title":"Regularization and variable selection via the elastic net","volume":"67","author":"Zou","year":"2005","journal-title":"Journal of the Royal Statistical Society Series B Statistical Methodology"}],"container-title":["Journal of Anxiety Disorders"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0887618525000398?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0887618525000398?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T03:22:36Z","timestamp":1762312956000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0887618525000398"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6]]},"references-count":117,"alternative-id":["S0887618525000398"],"URL":"https:\/\/doi.org\/10.1016\/j.janxdis.2025.103003","relation":{},"ISSN":["0887-6185"],"issn-type":[{"value":"0887-6185","type":"print"}],"subject":[],"published":{"date-parts":[[2025,6]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Using machine learning methods to predict the outcome of psychological therapies for post-traumatic stress disorder: A systematic review","name":"articletitle","label":"Article Title"},{"value":"Journal of Anxiety Disorders","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.janxdis.2025.103003","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"103003"}}