Background: Forgiveness is increasingly seen as a resilience factor linked to better mental health. However, its effects may differ based on the type of forgiveness and symptom severity. Prior studies have mostly used mean-based models, which may overlook variation across symptom levels. This study used quantile regression to assess whether dispositional forgivenessâfor self, for others, and by Godâpredicts depression and anxiety at varying levels of symptom severity over time.
Methods: A two-wave longitudinal survey was conducted in a general adult sample in Poland (N = 174), with assessments spaced six months apart. Forgiveness was measured using the Toussaint Forgiveness Scale, including subscales for forgiveness for self, for others, and by God. Depression and anxiety were measured with the PHQ-9 and GAD-7. Quantile regression was used to examine associations at the 25th, 50th, and 75th percentiles of symptom severity, adjusting for baseline scores.
Results: Forgiveness by God significantly predicted lower depression and anxiety at the 75th percentile, indicating greater benefit under high symptom burden. Forgiveness for others was associated with lower depression at both the 50th and 75th percentiles. No significant longitudinal effects were found for forgiveness for self beyond initial correlations. These patterns, revealed through quantile regression, were not evident in traditional linear models, which average effects across the symptom distribution.
Conclusions: Analyzing forgiveness across symptom distributions reveals specific protective patterns. Forgiveness by God and for others may serve as resilience factors, especially under prolonged psychological distress. Forgiveness-based approaches could be accessible, low-cost additions to mental health programs in religiously homogeneous societies.