Xiaoyan Liu1, Qian Zhang2, Meng Yu3, Wei Xu1. 1. Faculty of Psychology, Beijing Normal University, Beijing, China. 2. Department of Psychology, University of Leeds, Leeds, UK. 3. Guangdong Provincial Key Laboratory of Social Cognitive Neuroscience and Mental Health, Department of Psychology, Sun Yat-Sen University, Guangzhou, China.
Abstract
OBJECTIVE: The aim of this study was to identify the patterns of posttraumatic responses among breast cancer (BC) patients, to explore the variables associated with these patterns, and to compare anxiety and depression on various posttraumatic response patterns. METHODS: A questionnaire survey was conducted with a sample of 612 BC patients who were currently undergoing treatment. The questionnaire package included Posttraumatic Stress Disorder Symptom Scale (PSS), Posttraumatic Growth Inventory (PTGI), Network of Relationships Inventory, Generalized Anxiety Disorder-7 (GAD-7), and Patient Health Questionnaire-9 (PHQ-9). Modeling was performed using a latent profile analysis (LPA) to explore patterns of posttraumatic responses among BC patients. RESULTS: Based on the fitting indicators of LPA, three-class patterns model of posttraumatic responses was optimal. Resisting group (34.6%): patients reported mild posttraumatic stress symptoms (PTSS) and mild posttraumatic growth (PTG). Growth group (47.4%): patients showed mild PTSS and high PTG. Struggling group (18.0%): patients showed high PTSS and high PTG. BC patients with lower income were more likely to belong to Resisting group and Struggling group. BC patients with high levels of social support were more likely to belong to Growth group. Patients in Struggling group had the highest levels of anxiety and depression. CONCLUSIONS: This study showed that there was heterogeneity in posttraumatic response patterns of BC patients. The results provided theoretical base guiding the development of health care schemes and psychological interventions for patients, suggesting the necessity of differentiated health care for BC patients with different posttraumatic response patterns.
OBJECTIVE: The aim of this study was to identify the patterns of posttraumatic responses among breast cancer (BC) patients, to explore the variables associated with these patterns, and to compare anxiety and depression on various posttraumatic response patterns. METHODS: A questionnaire survey was conducted with a sample of 612 BCpatients who were currently undergoing treatment. The questionnaire package included Posttraumatic Stress Disorder Symptom Scale (PSS), Posttraumatic Growth Inventory (PTGI), Network of Relationships Inventory, Generalized Anxiety Disorder-7 (GAD-7), and Patient Health Questionnaire-9 (PHQ-9). Modeling was performed using a latent profile analysis (LPA) to explore patterns of posttraumatic responses among BCpatients. RESULTS: Based on the fitting indicators of LPA, three-class patterns model of posttraumatic responses was optimal. Resisting group (34.6%): patients reported mild posttraumatic stress symptoms (PTSS) and mild posttraumatic growth (PTG). Growth group (47.4%): patients showed mild PTSS and high PTG. Struggling group (18.0%): patients showed high PTSS and high PTG. BCpatients with lower income were more likely to belong to Resisting group and Struggling group. BCpatients with high levels of social support were more likely to belong to Growth group. Patients in Struggling group had the highest levels of anxiety and depression. CONCLUSIONS: This study showed that there was heterogeneity in posttraumatic response patterns of BCpatients. The results provided theoretical base guiding the development of health care schemes and psychological interventions for patients, suggesting the necessity of differentiated health care for BCpatients with different posttraumatic response patterns.
Authors: Justyna Michalczyk; Joanna Dmochowska; Anna Aftyka; Joanna Milanowska Journal: Int J Environ Res Public Health Date: 2022-05-27 Impact factor: 4.614
Authors: Benson Wu; Wassim Tarraf; Douglas M Wallace; Ariana M Stickel; Neil Schneiderman; Susan Redline; Sanjay R Patel; Linda C Gallo; Yasmin Mossavar-Rahmani; Martha L Daviglus; Phyllis C Zee; Gregory A Talavera; Daniela Sotres-Alvarez; Hector M González; Alberto Ramos Journal: PLoS One Date: 2022-04-04 Impact factor: 3.752