Bahar KİLİC, Mustafa KARAKAPLAN, Suheyla UNAL

Analysis of posttraumatic embitterment disorders by machine learning: Could sullenness be a predictor of posttraumatic embitterment disorder?

Objective: This study aimed to determine some fundamental factors specific to posttraumatic embitterment disorder (PTED) using deep machine learning (ML) and network analysis techniques. Method: Sociodemographic data form, Buss–Perry Aggression Questionnaire, Brief Symptom Inventory (BSI), PTED Self-Rating Scale (PTED Scale), and list of stressful life events were administered to 557 people who applied to the outpatient anxiety clinic. ML method and network analysis were applied with the 33 most significant variables. Results: PTED was found in urban areas (p=0.006), individual health problems (p=0.029), early separation from their families (p=0.040), previous trauma (p=0.021), describing childhood sexual abuse (p

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