Friday, September 27, 2002

This presentation is part of : Health Issues of Adolescents

Adaptation in Adolescents with Spina Bifida: Untangling the Outcomes

Kathleen Sawin, DNS, CPNP, FAAN, associate professor, Maternal Child Nursing Department, Virginia Commonwealth University, Richmond, VA, USA, Philip S. Fastenau, PhD, assistant professor, Department of Psychology, School of Science, Indiana University/Purdue University, Indianapolis, Indianapolis, IN, USA, Constance F Buran, DNS, CNS, manager, Rehabilitation Medical Service Area, Riley Hospital for Children, Indianapolis, IN, USA, and Timothy J. Brei, MD, clinical associate professor, Developmental Pediatrics, Indiana University, Indianapolis, IN, USA.

Objective: The Ecological Model of Adaptation in Adolescents with Spina Bifida (SB) has guided our study of adolescents. The model delineates the proposed relationship of spina bifida condition variables, neuropsychological variables, and protective processes (adolescent resilience, family resources and demographic factors) to adaptation outcomes. In this model neuropsychological functioning mediates the impact of the condition variables on outcomes while the protective processes moderate the neuropsychological outcome relationship. The purpose of this analysis was to determine if a single adaptation factor could be supported.

Design: A cross-sectional correlational study.

Variables Studied Together: Six adaptation outcome dimensions are included: quality of life, developmental competence, behavior problems, social competence, functional status, and academic achievement.

Sample, Setting, Years: The sample consisted of 60 adolescents with SB and their parents. Sixty percent of the sample were female, 40% were male. The adolescents ages ranged from 11 to 21 years (M=16.2, SD=2.6) Participants were recruited from a large SB program in a Midwestern state during 1999-2001.

Methods: Structured interviews were conducted either in the home (n=34%) or via phone (n=66%). The following adaptation measures were used: a 47-item SB and adolescent-specific Quality of Life Tool, Harter's Adolescent's Self-Perception Profile, the Child Behavior Checklist (CBCL), the CBCL social competence scale, The WeeFIM and the Adolescent self-Management and Independence Scale (AMIS), the Academic Achievement Scale of the Teacher Report Form (parallel form of the CBCL). ). The Adolescents completed all measures except the CBCL and academic achievement. Parents completed the CBCL and academic achievement was reported by the adolescent's teacher.

Findings: Factor analysis of the measures yielded three factors (functional adaptation, psychosocial adaptation, and academic adaptation) with Eigenvalues of 1.0 or more and factor loadings of .54-.94. The three factors explained 85% of the variance. No significant correlations were found between measures of functional adaptation (functional status and self management) and either psychosocial adaptation (developmental competence, lack of behavior problems, social competence and quality of life) or academic adaptation (academic achievement). The measures of academic achievement were related to the measures of psychosocial adaptation (r=.38-.44). Further, the variables in our model predicting these three factors also varied. The condition variables (level of lesion and hydrocephalus) had high correlations with functional status (r=.60-.71). However, they had no significant relationships with any of the psychosocial or academic adaptation measures. In contrast the neuropsychological variables correlated with all three outcome factors (r=.36 to .50). The adolescent resilience factors demonstrated a clear pattern with decision making and household responsibility correlating significantly with the measures of functional adaptation (r=.39 -.65). Hope, communication efficacy, sexuality beliefs, attitude toward spina bifida, and future expectations were related to psychosocial (r=.32-.62 ) and to academic adaptation (r=.36-.68); however, these variables were not related to functional adaptation. Family resourcefulness reported by teens was modestly related to psychosocial and academic adaptation(r=.29-.32), but family resourcefulness reported by parents had higher correlations to these adaptation outcomes (r=.34-.60). Generally family variables were not significantly correlated to functional adaptation.

Conclusions: The adaptation outcome for adolescents with this chronic condition is not one-dimensional but rather has at least three factors: functional, psychosocial, and academic adaptation. The functional adaptation factor is not significantly correlated with the psychosocial and academic adaptation factors. Although the later two are correlated with each other, the correlations are modest. Furthermore, the correlates of these outcomes vary. Thus, these three outcome domains appear to be fairly independent.

Implications: The current factor analytic findings are based on a small sample, so the results should be considered preliminary. However, it appears that measurement of outcomes in adolescents with this chronic condition, and perhaps in adolescents with other chronic conditions, has three distinct components. The lack of relationship between the outcomes in this work suggests a more complex model is needed to represents the actual adaptation process of these youth. Most frequently in rehabilitation settings interventions are focused on functional adaptation (functional status and self management) with the assumption that, if those are achieved, they will lead to better psychosocial adaptation. Data from this study would challenge those assumptions. Measuring any one component without the others will give an incomplete understanding of adolescent adaptation. Furthermore, neglecting to examine the important unique constellation of predictors for each domain will likely lead to incomplete interventions.

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