Youth Resilience Assessment
As a follow-up to RAW-A, the authors began an investigation of the level of resilience among adolescents and college students. This population is still in the process of developing as human beings and by assessing their level of resilience at this earlier age, strategies could be designed to build their resilience. Thus, they created the Youth Resilience Assessment.
Development of the Youth Resilience Assessment
Again, one of the primary findings in Werner’s research into resilience as it applies to children and adolescents suggested that individuals who had someone who believed in them were more likely to flourish through adversity. The importance of this finding–that an individual feels a strong connection to others in the environment–cannot be overstated. Therefore, the resilience attributes of the RAW-A needed to be adapted. The development of the assessment started with 19 attributes and 79 items (4 or 5 items for each attribute) to accommodate these findings. The challenge was to determine which attributes and items in the assessment most closely reflected the concept of resilience.
Reliability
The assessment was administered to 79 eighth grade students at a private school in the northern Chicago suburbs. Thus, the assessment items that had the greatest internal consistency were identified. This would assure valid and reliable responses to the assessment. The analysis revealed 40 items and 12 attributes with reliability coefficients and variance levels listed below.
Domain reliability was examined using Cronbach’s alpha (a reliability coefficient statistic). All domains exceeded the traditional threshold of .70. The coefficient reliabilities were as follows: Self domain alpha = 0.78; Others domain alpha = 0.86; Environment domain alpha = 0.81. All alphas indicated high reliability.
Reliability scores for the attributes were strong (greater than .70) with the majority of attributes having scores of .78 or higher. This validation study and the analyses performed identified 12 constructs (attributes) with strong factor loadings and internal consistency. These were then aggregated into the three domains, as described below.
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