Objectives: Despite the importance of resilience in well-being and adaptation to the role of caregiver in non-professional caregivers, research on resilience in this population has been scarce and contradictory, and has methodological limitations. The objective of this study was to identify subgroups of caregivers with high levels of resilience based on a series of predictors including sociodemographic variables and variables related to care and personal and social development.Method: 294 non-professional caregivers (89.8% women) with a mean age of 55.3 years (SD = 10.9) were randomly selected. Trained evaluators collected the sociodemographic variables of the person in care and the caregiver and on the care situation, self-esteem, social support, emotional distress and resilience.Results: The Classification Tree Analysis (CTA) showed that self-esteem was the main predictor of high resilience. Additional predictors were: (1) for those with high self-esteem, longer duration of care; (2) for those with low self-esteem, less emotional distress; (3) for those with less emotional distress, shorter duration of care.Conclusion: The results offer guidelines for developing programs to promote high resilience.
Keywords: Predictors; caregivers; classification tree analysis; resilience.