Background
Resilience is broadly defined as the ability to maintain or regain functioning in the face of adversity. Recent work to harmonise the quantification and definition of resilience quantifies resilience as the residual variance in psychosocial functioning that remains after accounting for adversity exposure. However, there have been no published studies that have formally investigated the validity of this approach. Considering this, we examine the construct and predictive validity of the residuals approach using participants from the Avon Longitudinal Study of Parents and Children (ALSPAC), a multigenerational, longitudinal cohort study.
Methods
We regressed exposures of adolescent adversity on adolescent psychopathology scores using the Strength and Difficulties Questionnaire and obtained the residual variance. We investigated construct validity by analysing whether previously identified demographic and resilience factors significantly predicted resilience. Predictive validity of resilience was investigated by comparing the predictive power of resilience with other determinants of psychosocial functioning on two developmental outcomes: depressive symptoms at 18 years, measured by the Short Moods and Feelings Questionnaire, and NEET (Not in Employment, Education or Training) status at 17 and 23 years. The associations between depressive symptoms at 18, resilience, ACEs and covariates were tested using multiple linear regression. NEET status at 17 and 23 were run as separate binary multiple logistic regression models to test associations with resilience and known demographics previously associated with NEET status.
Results
Seven previously identified protective factors, including self-esteem, positive sibling relationship, temperament, and positive perception of school, significantly predicted resilience to adolescent psychopathology, thus providing strong construct validity. Resilience significantly predicted a reduction in depressive symptoms at 18 years, and significantly decreased the likelihood of having NEET status at both 17 years and 23 years, even after taking into account early childhood adversity and other risk factors. None of the socioeconomic factors were significantly associated with resilience.
Conclusions
Our study demonstrates that the residuals method of operationalising resilience has good construct and predictive validity yet recommend replication studies. It has the potential to advance research into the mechanisms and modifiability of resilience.
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