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See next page for additional authors  \nLet us know how access to this document benefits you  \nGeneral rights  \nAll content in PEARL is protected by copyright law. Author manuscripts are made available in accordance with publisher policies. Please cite only the published version using the details provided on the item record or document. In the absence of an open licence (e.g. Creative Commons), permissions for further reuse of content should be sought from the publisher or author.  \nTake down policy  \nIf you believe that this document breaches copyright please contact the library providing details, and we will remove access to the work immediately and investigate your claim.  \nFollow this and additional works at: [https://pearl.plymouth.ac.uk/psy-research](https://pearl.plymouth.ac.uk/psy-research)  \nRecommended Citation  \nJornkokgoud, K., Baggio, T., Faysal, M., Bakiaj, R., Wongupparaj, P., Job, R., & Grecucci, A. (2023)'Predicting narcissistic personality traits from brain and psychological features: A supervised machine learning approach', Social Neuroscience, 18(5), pp. 257-270. Available at: [https://doi.org/10.1080/](https://doi.org/10.1080/)[ ](https://doi.org/10.1080/)17470919.2023.2242094  \nThis Article is brought to you for free and open access by the Faculty of Health at PEARL. It has been accepted for inclusion in School of Psychology by an authorized administrator of PEARL. For more information, please contact [openresearch@plymouth.ac.uk](openresearch@plymouth.ac.uk).  \nAuthors  \nKhanitin Jornkokgoud, Teresa Baggio, Md Faysal, Richard Bakiaj, Peera Wongupparaj, Remo Job, and Alessandro Grecucci  \nThis article is available at PEARL: [https://pearl.plymouth.ac.uk/psy-research/749](https://pearl.plymouth.ac.uk/psy-research/749)  \nPEARL  \nPredicting narcissistic personality traits from brain and psychological features  \nJornkokgoud, Khanitin; Baggio, Teresa; Faysal, Md; Bakiaj, Richard; Wongupparaj, Peera; Job, Remo; Grecucci, Alessandro  \nPublished in:  \nSocial Neuroscience  \nDOI:  \n10.1080/17470919.2023.2242094  \nPublication date:  \n2023  \nDocument version:  \nPublisher's PDF, also known as Version of record  \nLink:  \nLink to publication in PEARL  \nCitation for published version (APA):  \nJornkokgoud, K. , Baggio, T. , Faysal, M. , Bakiaj, R. , Wongupparaj, P. , Job, R. , & Grecucci, A.(2023) . Predicting narcissistic personality traits from brain and psychological features: A supervised machine learning approach. Social Neuroscience , 18(5), 257-270. [https://doi.org/10.1080/17470919.2023.2242094](https://doi.org/10.1080/17470919.2023.2242094)  \nAll content in PEARL is protected by copyright law. Author manuscripts are made available in accordance with publisher policies. Wherever possible please cite the published version using the details provided on the item record or document. In the absence of an open licence (e.g. Creative Commons), permissions for further reuse of content  \nshould be sought from the publisher or author.  \nDownload date: 28. Oct. 2024  \nSocial Neuroscience  \nISSN: (Print) (Online) Journal [homepage: ](homepage: www.tandfonline.com/journals/psns20)[www.tandfonline.com/journals/psns20](homepage: www.tandfonline.com/journals/psns20)  \nPredicting narcissistic personality traits from brain and psychological features: A supervised machine learning approach  \nKhanitin Jornkokgoud, Teresa Baggio, Md Faysal, Richard Bakiaj, Peera Wongupparaj, Remo Job & Alessandro Grecucci  \nTo cite this article: Khanitin Jornkokgoud, Teresa Baggio, Md Faysal, Richard Bakiaj, Peera Wongupparaj, Remo Job & Alessandro Grecucci (2023) Predicting narcissistic pers","cbCaijAY1eVYaBFR","https://ap.wps.com/l/cbCaijAY1eVYaBFR","pdf",2453669,18,"English","# Abstract\n## Background and motivation\n## Methodological limitations in prior studies\n## Study aim and predictive modeling approach","[{\"question\":\"Why are findings about narcissism’s neural correlates inconsistent in earlier studies?\",\"answer\":\"Earlier research often suffers from methodological limitations, including small sample sizes and dependence on mass univariate methods, which can yield inconsistent results.\"},{\"question\":\"What is the primary goal of this study?\",\"answer\":\"The study aims to overcome prior methodological limitations by building a predictive model that integrates brain and psychological features.\"},{\"question\":\"How does the study improve over previous approaches to studying narcissism?\",\"answer\":\"It uses supervised machine learning to develop a predictive model rather than relying on mass univariate analyses, which helps address data and modeling constraints.\"}]","Predicting narcissistic personality traits from brain and psychological features - A supervised machine learning approach | PDF",45]