Using explainable machine learning to investigate the relationship between childhood maltreatment, positive psychological traits, and CPTSD symptoms
Background: The functional impairment resulting from CPTSD symptoms is enduring and far-reaching. Existing research has found that CPTSD symptoms are closely associated with childhood maltreatment; however, researchers debate whether CPTSD symptoms are predominantly influenced by a specific type of...
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Taylor & Francis Group
2025-12-01
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| Series: | European Journal of Psychotraumatology |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/20008066.2025.2455800 |
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| author | Xiaoxiao Zhou Zongbao Liang Guangzhen Zhang |
| author_facet | Xiaoxiao Zhou Zongbao Liang Guangzhen Zhang |
| author_sort | Xiaoxiao Zhou |
| collection | DOAJ |
| description | Background: The functional impairment resulting from CPTSD symptoms is enduring and far-reaching. Existing research has found that CPTSD symptoms are closely associated with childhood maltreatment; however, researchers debate whether CPTSD symptoms are predominantly influenced by a specific type of childhood maltreatment or the combined influence of multiple maltreatment types.Objective: (1) Examines the impact of childhood maltreatment on CPTSD symptoms, specifically exploring whether specific types of maltreatment or the cumulative exposure to multiple types of maltreatment play a predominant role. (2) Investigates the role of positive psychological traits in this relationship, assessing whether these traits serve as protective factors or are outcomes of the negative psychological consequences of maltreatment.Methods: A sample of 1894 adolescents (Mage = 13.88; SD = 1.00) from a chronically impoverished rural area in China completed the International Trauma Questionnaire – Child and Adolescent Version for CPTSD symptoms, the Childhood Trauma Questionnaire – Short Form for childhood maltreatment types. Positive psychological traits, including mindfulness, self-compassion, and gratitude, were measured using the Mindful Attention Awareness Scale (MAAS), the Self-Compassion Scale – Short Form, and the Gratitude Questionnaire. We addressed the research question using explainable machine learning methods, with SHAP enhancing model interpretability.Results: The findings indicate that emotional abuse is the most effective predictor of CPTSD symptoms, with individuals who experienced emotional abuse showing higher rates of other forms of maltreatment. Among positive psychological traits, mindfulness contributes the most, followed by self-compassion, while gratitude shows no significant association with CPTSD symptoms. Additionally, individuals with poor positive psychological traits are more likely to have experienced maltreatment, whereas those with higher positive traits are less exposed to abuse.Conclusions: Emotional abuse and low levels of positive psychological traits are strongly associated with CPTSD symptoms in adolescents from impoverished areas, with positive traits showing limited buffering effects against maltreatment. |
| format | Article |
| id | doaj-art-93f3da3ac9c44dde9c0f338e24a7abb2 |
| institution | OA Journals |
| issn | 2000-8066 |
| language | English |
| publishDate | 2025-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | European Journal of Psychotraumatology |
| spelling | doaj-art-93f3da3ac9c44dde9c0f338e24a7abb22025-08-20T02:38:10ZengTaylor & Francis GroupEuropean Journal of Psychotraumatology2000-80662025-12-0116110.1080/20008066.2025.2455800Using explainable machine learning to investigate the relationship between childhood maltreatment, positive psychological traits, and CPTSD symptomsXiaoxiao Zhou0Zongbao Liang1Guangzhen Zhang2Department of Medical Humanities, School of Humanities, Southeast University, Nanjing, People’s Republic of ChinaKey Laboratory of Child Development and Learning Science, School of Biological Science & Medical Engineering, Southeast University, Nanjing, People’s Republic of ChinaKey Laboratory of Child Development and Learning Science, School of Biological Science & Medical Engineering, Southeast University, Nanjing, People’s Republic of ChinaBackground: The functional impairment resulting from CPTSD symptoms is enduring and far-reaching. Existing research has found that CPTSD symptoms are closely associated with childhood maltreatment; however, researchers debate whether CPTSD symptoms are predominantly influenced by a specific type of childhood maltreatment or the combined influence of multiple maltreatment types.Objective: (1) Examines the impact of childhood maltreatment on CPTSD symptoms, specifically exploring whether specific types of maltreatment or the cumulative exposure to multiple types of maltreatment play a predominant role. (2) Investigates the role of positive psychological traits in this relationship, assessing whether these traits serve as protective factors or are outcomes of the negative psychological consequences of maltreatment.Methods: A sample of 1894 adolescents (Mage = 13.88; SD = 1.00) from a chronically impoverished rural area in China completed the International Trauma Questionnaire – Child and Adolescent Version for CPTSD symptoms, the Childhood Trauma Questionnaire – Short Form for childhood maltreatment types. Positive psychological traits, including mindfulness, self-compassion, and gratitude, were measured using the Mindful Attention Awareness Scale (MAAS), the Self-Compassion Scale – Short Form, and the Gratitude Questionnaire. We addressed the research question using explainable machine learning methods, with SHAP enhancing model interpretability.Results: The findings indicate that emotional abuse is the most effective predictor of CPTSD symptoms, with individuals who experienced emotional abuse showing higher rates of other forms of maltreatment. Among positive psychological traits, mindfulness contributes the most, followed by self-compassion, while gratitude shows no significant association with CPTSD symptoms. Additionally, individuals with poor positive psychological traits are more likely to have experienced maltreatment, whereas those with higher positive traits are less exposed to abuse.Conclusions: Emotional abuse and low levels of positive psychological traits are strongly associated with CPTSD symptoms in adolescents from impoverished areas, with positive traits showing limited buffering effects against maltreatment.https://www.tandfonline.com/doi/10.1080/20008066.2025.2455800Explainable machine learningSHAPCPTSDchildhood maltreatmentpositive psychological traitsTEPTC |
| spellingShingle | Xiaoxiao Zhou Zongbao Liang Guangzhen Zhang Using explainable machine learning to investigate the relationship between childhood maltreatment, positive psychological traits, and CPTSD symptoms European Journal of Psychotraumatology Explainable machine learning SHAP CPTSD childhood maltreatment positive psychological traits TEPTC |
| title | Using explainable machine learning to investigate the relationship between childhood maltreatment, positive psychological traits, and CPTSD symptoms |
| title_full | Using explainable machine learning to investigate the relationship between childhood maltreatment, positive psychological traits, and CPTSD symptoms |
| title_fullStr | Using explainable machine learning to investigate the relationship between childhood maltreatment, positive psychological traits, and CPTSD symptoms |
| title_full_unstemmed | Using explainable machine learning to investigate the relationship between childhood maltreatment, positive psychological traits, and CPTSD symptoms |
| title_short | Using explainable machine learning to investigate the relationship between childhood maltreatment, positive psychological traits, and CPTSD symptoms |
| title_sort | using explainable machine learning to investigate the relationship between childhood maltreatment positive psychological traits and cptsd symptoms |
| topic | Explainable machine learning SHAP CPTSD childhood maltreatment positive psychological traits TEPTC |
| url | https://www.tandfonline.com/doi/10.1080/20008066.2025.2455800 |
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