Childhood Maltreatment, Automatic Negative Thoughts, and Resilience: The Protective Roles of Culture and Genes

Abstract

Resilience, a psychological trait conceptualized as the ability to recover from setbacks, can be weakened by childhood maltreatment, which comprises childhood abuse and childhood neglect. The current study aimed to investigate whether childhood maltreatment could increase automatic negative thoughts (ANT), thus weakening resilience. Furthermore, as psychological characteristics are commonly subject to the moderating effects of cultural context and biology, the study also explored whether and how cultural and genetic factors separately interact with childhood maltreatment to predict resilience. In study 1, the participants comprised 237 American and 347 Chinese individuals; study 2 included 428 genotyped Chinese individuals. We combined regression, mediation, moderation, and machine learning methods to test the mediating effect of ANT on the link between childhood maltreatment and resilience as well as the moderating roles of culture and genetics. Study 1 found that both childhood abuse and childhood neglect increased ANT and thus weakened resilience. In addition, the ANT-mediating effects of childhood neglect were stronger in American than Chinese participants. In Study 2, using the leave-one-out approach, we constructed two separate prediction models based on 22 and 16 important single nucleotide polymorphisms (SNPs), and we found that the interaction between childhood abuse/neglect and polygenic scores based on important SNPs could predict ANT. The mediating effects of ANT on the relationship between childhood abuse/neglect and resilience were significant for participants with low polygenic scores but not for those with high polygenic scores. In conclusion, both the cultural environment and individual genetic makeup moderated the mediating effects of ANT on the association between childhood maltreatment and resilience. These findings indicated the roles of culture and genetics in protecting against the adverse effects of childhood maltreatment on resilience.

Longitudinal Relationship Between Bullying Victimization and Depression Among Left-Behind Children: Roles of Negative Thoughts and Self-Compassion

“…Among them, distal stressors often refer to events, such as violence, and proximal factors usually refer to cognitive processes, self-regulation, etc. Negative thoughts will cause individuals to have negative perceptions and pessimistic interpretations when facing pressure ( Yu et al, 2022 ), which is a typical bad cognitive process. For LBC, both parents leave home all year-round, parental absence contributes to reduced or absent family resources, such as a lack of support and involvement ( Zhao et al, 2015 ).…”

Does losing money truly hurt? The shared neural bases of monetary loss and pain

“…The comparison of activation patterns used three algorithms and consistently showed that the monetary loss network was more similar to the social pain network than to the physical pain network. For individuals, money is not only a physical stimulus but also has rich emotional and social meanings to people, since money can arouse positive or negative emotions (Tang, 1992 ; Yu, Huang, Mao, & Luo, 2022 ), elicit individuals’ internal motivation (Lea & Webley, 2006 ), reduce the harm caused by low self‐esteem (Zhang, 2009 ) and change the norms of interpersonal relationships (Vohs et al, 2008 ; Zaleskiewicz & Gasiorowska, 2016 ). Moreover, this result provided neural evidence of the social resource theory of money, in which money was regarded as a type of social resource, similar to social relationships, which might elicit pain and a sense of security (Zhou et al, 2009 ; Zhou & Gao, 2008 ).…”

The Association between Economic Inequality and Adolescents' Prosocial Behavior: Evidence from Brain Potentials and Genes

“…In specific, I intend to consider the several OXTR SNPs related to prosocial tendency and prosocial behaviors, which were demonstrated significantly in prior studies. For the sake of yielding reliable results, I will adopt a leave-one-out machine learning approach (Yu et al, 2020) to identify valid SNPs, which would interplay with subjective economic inequality to predict adolescents' prosocial behaviors.…”

“…Inspired by Yu et al's (2020) leave-one-out cross-validation, we employed the same approach to calculate polygenic scores (see figure 6). Participants were divided into test set After n iterations, we generated all participants' predicted prosocial behavior scores.…”

“…We further employed a bivariate correlation between the predicted and observed prosocial behavior scores to examine the predictive power of our model. The SNPs were selected as reliable SNPs that were identified in 95% of iterations (Yu et al, 2020).…”