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When “good enough” is no longer enough: Parenting perfectionism, intolerance of uncertainty, and emotion regulation in postnatal depression

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  • Additional Information
    • Contributors:
      Centre Hospitalier Régional Universitaire CHU Lille (CHRU Lille); Laboratoire Sciences Cognitives et Sciences Affectives - UMR 9193 (SCALab); Université de Lille-Centre National de la Recherche Scientifique (CNRS)
    • Publication Information:
      CCSD
      Elsevier
    • Publication Date:
      2025
    • Collection:
      LillOA (HAL Lille Open Archive, Université de Lille)
    • Abstract:
      International audience ; This study addresses the call for psychological research to examine the impact of social expectations and modern parenting paradigms on parents' mental health. We explore parenting perfectionism as a predictor of postnatal depression, with intolerance of uncertainty and emotion regulation difficulties as mediators. Using Partial Least Square Structural Equation Modelling (PLS-SEM) on a sample of 232 mothers, we examined both direct and indirect effects of parenting perfectionism on postnatal depression symptoms, including mediation analysis of emotion regulation difficulties and intolerance of uncertainty. Findings support that parenting perfectionism predicts the risk of postnatal depression through these mediating mechanisms. Limitations of the study include its cross-sectional design and reliance on self-reported measures. Volunteer bias, higher education and employment levels among participants may limit the generalizability of the results. Despite these limitations, this study shows the importance of emotion regulation difficulties and intolerance of uncertainty as key mechanisms by which parenting perfectionism increases the risk of postnatal depression in mothers during the first year postpartum. This study provides novel and actionable targets for the treatment and prevention of postnatal depression and demonstrates how social and cultural contexts of parenthood can be operationalized for psychological inquiry through complex statistical modelling.
    • Accession Number:
      10.1016/j.paid.2024.112910
    • Online Access:
      https://hal.univ-lille.fr/hal-05051898
      https://hal.univ-lille.fr/hal-05051898v1/document
      https://hal.univ-lille.fr/hal-05051898v1/file/Kelly2025.pdf
      https://doi.org/10.1016/j.paid.2024.112910
    • Rights:
      http://creativecommons.org/licenses/by/ ; info:eu-repo/semantics/OpenAccess
    • Accession Number:
      edsbas.EFA60F06