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Child-To-Parent Violence: Which Parenting Style Is More Protective? A Study with Spanish Adolescents.

Cristian Suárez-RelinqueGonzalo Del Moral ArroyoCeleste León MorenoJuan Evaristo Callejas Jerónimo
Published in: International journal of environmental research and public health (2019)
The link between parenting style and violent behavior during adolescence has become a relevant topic of research over the last few years. In order to deepen the understanding of this relationship, the aim of the present study was to examine what type of parenting style (authoritative, indulgent, authoritarian, and neglectful) is more protective against child-to-parent violence (CPV). A total of 2112 adolescents of both sexes participated in this study (50.2% men and 49.8% women), aged between 12 and 18 years (M = 14. 72, SD = 1.55). A multivariate factorial design (MANOVA, 4 × 2 × 3) was applied using parenting style, sex, and age group (12-14, 15-16, and 17-18 years) as independent variables and dimensions of CPV (physical and verbal aggression against the mother and father) as dependent variables. As shown in the results, the lowest scores on all the dimensions of CPV examined corresponded to the adolescents from indulgent families. Further, two interaction effects were observed between parenting style and age in verbal aggression against the mother and verbal aggression against the father. Regarding these effects, the adolescents from indulgent families obtained the lowest scores in two of the three age groups analyzed (12-14 years and 15-16 years). In the 17-18 years group, adolescents from authoritative families obtained similar but lower values than those coming from families with an indulgent style of parenting. These findings suggest that indulgent style is the most protective parenting style against CPV and also highlight the importance of affective warmth, emotional nurturance, and support giving in preventing CPV.
Keyphrases
  • young adults
  • physical activity
  • mental health
  • working memory
  • depressive symptoms
  • data analysis