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Data were collected via paper questionnaires assessing youth characteristics and psychological disturbances using Depression, Anxiety and Stress Scale-Short Form (DASS-21) and CT using Childhood Trauma Questionnaire (CTQ). Statistical methods, including the Chi-squared test, Machine Learning (ML) regression and classification models, were used to explore the association of Depression, Anxiety and Stress (DASS) and CT within the data, and model validations were performed for internal stability. The ML models used include Multiple Linear Regression (MLR), Random Forest (RF), Support Vector Machine (SVM), a Deep Neural Network (DNN), and Stochastic Gradient Descent (SGD). The algorithms\u2019 performance was assessed and balanced for more realistic reporting of findings. All CTQ subscales and gender were used in analysis and the importance of the features was compared.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      We find that (19\n                      <jats:italic>.<\/jats:italic>\n                      94%) and (25\n                      <jats:italic>.<\/jats:italic>\n                      68%) of the younger adults experienced moderate and severe CT, respectively. In addition, (59\n                      <jats:italic>.<\/jats:italic>\n                      82%) and (14\n                      <jats:italic>.<\/jats:italic>\n                      8%) experienced moderate and severe DASS, respectively. The MLR is highly significant (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.000), elucidating\n                      <jats:inline-formula>\n                        <jats:tex-math>$${R}^{2}=29\\%$$<\/jats:tex-math>\n                      <\/jats:inline-formula>\n                      variance\n                      <jats:inline-formula>\n                        <jats:tex-math>$${f}^{2}=41\\%)$$<\/jats:tex-math>\n                      <\/jats:inline-formula>\n                      in continuous DASS-CT links, while RF classification attained (71%) Accuracy and (76%) Area Under the ROC Curve (AUC) for severity prediction.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>There are highly significant interrelations between DASS, CT and sex. Younger adults who experienced CT, experience some level of DASS and females exhibit greater sensitivity to DASS. The ML approach proves effective in predicting relationships between DASS, CT, and sex. Bolstered by RF\u2019s 76% AUC for severity stratification, the findings support the practical utility of ML in guiding trauma-informed therapy and early intervention programs.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s40359-026-03997-6","type":"journal-article","created":{"date-parts":[[2026,2,9]],"date-time":"2026-02-09T01:54:09Z","timestamp":1770602049000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Prediction of the relationship between childhood trauma and psychological disturbances among younger adults using machine learning algorithms"],"prefix":"10.1186","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7797-7459","authenticated-orcid":false,"given":"Samira","family":"Salman","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0779-8225","authenticated-orcid":false,"given":"Omayma Abu","family":"Bakr","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2069-7728","authenticated-orcid":false,"given":"Hanaa Ezz","family":"Eldin Prince","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,2,9]]},"reference":[{"key":"3997_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1590\/S1413-81232006000200022","volume-title":"Violence against children","author":"PS Pinheiro","year":"2006","unstructured":"Pinheiro PS. 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