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This study used machine learning to examine multiple parenting features assessed across infancy and early childhood as predictors of CU traits and CPs in early adolescence.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"S0033291726103213_sec2\" sec-type=\"methods\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      Data were from the Family Life Project (\n                      <jats:italic>N<\/jats:italic>\n                      \u00a0=\u00a01,292; 49% female, 41% Black, and 28% below the poverty line). Seventy-four parenting predictors were assessed at eight time points between children aged 6\u201390 months using parent-reported questionnaires and observer ratings of videotaped interactions and home visits. CU traits and CPs were assessed via parent-reported questionnaires in preadolescence (12\u201314\u00a0years).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"S0033291726103213_sec3\" sec-type=\"results\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Parenting features explained 8.2% of CU traits variability in preadolescence, with top predictors including early sensitive parenting and later behavior management and scaffolding practices. Prediction of CPs was weaker, with parenting explaining 4.5% of the variability.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"S0033291726103213_sec4\" sec-type=\"conclusions\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Results highlight that disruption in close and sensitive early parent\u2013child relationships is relevant to the development of CU traits. Results from the prediction of CPs indicate a more heterogeneous etiology. Findings support targeting parental sensitivity and behavior management within preventative interventions for CU traits and CPs.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1017\/s0033291726103213","type":"journal-article","created":{"date-parts":[[2026,2,18]],"date-time":"2026-02-18T09:58:38Z","timestamp":1771408718000},"update-policy":"https:\/\/doi.org\/10.1017\/policypage","source":"Crossref","is-referenced-by-count":0,"title":["Using machine learning to identify parenting features prospectively related to callous-unemotional traits from infancy to early adolescence"],"prefix":"10.1017","volume":"56","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1265-5923","authenticated-orcid":false,"given":"Y.","family":"Paz","sequence":"first","affiliation":[{"id":[{"id":"https:\/\/ror.org\/00b30xv10","id-type":"ROR","asserted-by":"publisher"}],"name":"University of 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