Identifying predictors of resilience at inpatient and 3-month post-spinal cord injury. (January 2016) - Driver, Simon; Warren, Ann Marie; Reynolds, Megan; Agtarap, Stephanie; Hamilton, Rita; Trost, Zina; Monden, Kimberly
Abstract : Objectives: To identify (1) changes in psychosocial factors, (2) relationships between psychosocial factors, and (3) significant predictors of resilience in adults with spinal cord injury (SCI) during inpatient rehabilitation and at 3-month post-discharge. Design: Cross sectional with convenience sample based on inclusion/exclusion criteria. Setting: Inpatient rehabilitation hospital and community-based follow-up. Participants: Individuals with a SCI. Interventions: Not applicable. Outcome measures: Demographic, resilience, self-efficacy for managing a chronic health issue, depression, social roles/activity limitations, and pain. Results: The final sample consisted of 44 respondents (16 women and 28 men). Results of repeated measure analyses of variance indicated no significant changes in variables between inpatient and 3-month follow-up. Bivariate correlations revealed associations between resilience and self-efficacy at inpatient ( r  = 0.54, P < 0.001), and resilience and depression ( r  = −0.69, P < 0.001) and self-efficacy ( r  = 0.67, P < 0.001) at 3-month follow-up. Hierarchical regression analyses a significant model predicting resilience at inpatient stay ( R  = 0.61; adjusted R 2  = 0.24, P = 0.023), and at 3-month follow-up ( R  = 0.83; adjusted R 2  = 0.49, P = 0.022). Self-efficacy was the strongest predictor at inpatient stay ( β  = 0.46, P   =   0.006) and depression was strongest at 3-month follow-up ( β  = −0.80, P = 0.007). Conclusion: Results suggest that although resilience appears to be stable from inpatient to 3-month follow-up, different factors are stronger predictors of resilience across time. Based on current results, an assessment of self-efficacy during inpatient rehabilitation and an identification of depression at 3-month follow-up may be important factors to help identify those at risk of health issues overtime.