Frontiers in Psychiatry (May 2023)

Heterogeneity of resilience and the curvilinear relationship between childhood trauma and resilience among people with schizophrenia

  • Weiliang Wang,
  • Weiliang Wang,
  • Jun Zhang,
  • Jun Zhang,
  • Xinzhu Zheng,
  • Xinzhu Zheng,
  • Guohua Li,
  • Yuqiu Zhou

DOI
https://doi.org/10.3389/fpsyt.2023.1082000
Journal volume & issue
Vol. 14

Abstract

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BackgroundAs a group with a high incidence of childhood trauma, the differential characteristics of resilience in schizophrenia and its relationship with childhood trauma are still unclear.MethodsA total of 626 individuals diagnosed with schizophrenia were selected from four psychiatric hospitals in northern China. Childhood trauma and resilience were measured using the Childhood Trauma Questionnaire-short form (CTQ-SF) and Connor–Davidson Resilience Scale (CD-RISC), respectively. Latent profile analysis (LPA) was used to identify the potential classes of resilience. A generalized additive mixed model (GAMM) and restricted cubic spline (RCS) was used to explore and determine the shape of the relationship between childhood trauma and resilience.ResultsModel fits of LPA showed three heterogeneous classes of resilience: moderate resilience levels (n = 312; 49.06%); high resilience levels (n = 171; 26.89%) and low resilience levels (n = 153; 24.06%). Resilience scores fluctuated depending on amount of exposure to childhood trauma. The GAMM results verified the non-linear relationship between resilience and childhood trauma, with an estimated degree of freedom higher than 1 (4.573) and p = 0.003. RCS fitted for ordinary least square (OLS) regression models determined a smooth continuous cubic curve of resilience across childhood trauma levels, and the two turning points of the curve line were 41.04 and 54.74 for childhood trauma.DiscussionOur findings confirm the people-specific differences in the level of resilience in schizophrenia and describe the cubic curvilinear relationship between childhood trauma and resilience, which provides data support for mechanistic research and intervention in related fields.

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