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Furthermore, evidence highlighted a tight relationship between attachment style and social cognition abilities, a key PSY behavioral phenotype. The aim of this study is to generate a machine learning algorithm based on the perceived quality of parenting and attachment style-related features to discriminate between PSY and healthy controls (HC) and to investigate its ability to track PSY early stages and risk conditions, as well as its association with social cognition performance.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Perceived maternal and paternal parenting, as well as attachment anxiety and avoidance scores, were trained to separate 71 HC from 34 PSY (20 individuals diagnosed with schizophrenia\u2009+\u200914 diagnosed with bipolar disorder with psychotic manifestations) using support vector classification and repeated nested cross-validation. We then validated this model on independent datasets including individuals at the early stages of disease (ESD, i.e. first episode of psychosis or depression, or at-risk mental state for psychosis) and with familial high risk for PSY (FHR, i.e. having a first-degree relative suffering from psychosis). Then, we performed factorial analyses to test the group x classification rate interaction on emotion perception, social inference and managing of emotions abilities.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The perceived parenting and attachment-based machine learning model discriminated PSY from HC with a Balanced Accuracy (BAC) of 72.2%. Slightly lower classification performance was measured in the ESD sample (HC-ESD BAC\u2009=\u200963.5%), while the model could not discriminate between FHR and HC (BAC\u2009=\u200944.2%). We observed a significant group x classification interaction in PSY and HC from the discovery sample on emotion perception and on the ability to manage emotions (both<jats:italic>p<\/jats:italic>\u2009=\u20090.02). The interaction on managing of emotion abilities was replicated in the ESD and HC validation sample (<jats:italic>p<\/jats:italic>\u2009=\u20090.03).<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>Our results suggest that parenting and attachment-related variables bear significant classification power when applied to both PSY and its early stages and are associated with variability in emotion processing. These variables could therefore be useful in psychosis early recognition programs aimed at softening the psychosis-associated disability.<\/jats:p><\/jats:sec>","DOI":"10.1186\/s40359-021-00552-3","type":"journal-article","created":{"date-parts":[[2021,3,23]],"date-time":"2021-03-23T20:03:05Z","timestamp":1616529785000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Machine learning-based ability to classify psychosis and early stages of disease through parenting and attachment-related variables is associated with social cognition"],"prefix":"10.1186","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7919-7402","authenticated-orcid":false,"given":"Linda A.","family":"Antonucci","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alessandra","family":"Raio","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Giulio","family":"Pergola","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Barbara","family":"Gelao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marco","family":"Papalino","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Antonio","family":"Rampino","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ileana","family":"Andriola","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Giuseppe","family":"Blasi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alessandro","family":"Bertolino","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,3,23]]},"reference":[{"issue":"3","key":"552_CR1","doi-asserted-by":"publisher","first-page":"308","DOI":"10.1002\/wps.20458","volume":"16","author":"D Vancampfort","year":"2017","unstructured":"Vancampfort D, Firth J, Schuch FB, Rosenbaum S, Mugisha J, Hallgren M, Probst M, Ward PB, Gaughran F, De Hert M, et al. 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Informed consent was obtained from all participants included in the study and, in case of minors, also from their parents or caregivers. The study protocol has been approved by the Local Ethic Committee of the Bari University Hospital (study protocol n. 4754). Written informed consent has been obtained by each individual who took part in the study if aged above 18\u00a0years old. In the case of individuals aged below 18\u00a0years old, written informed consent has been obtained by both the participant and his\/her parents.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"AB has received lecture fees from Otsuka, Janssen, Lundbeck, and consultant fees from Biogen. GB has received lecture fees by Janssen and Lundbeck. AR has received travel fees from Lundbeck. All other authors declare no conflicts of interest.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"47"}}