RESEARCH OBJECTIVES:
To examine the predictive value of family management and risk/protective factors on quality of life among military children with chronic conditions.
BACKGROUND: Management of children’s chronic conditions significantly impacts families. The family bears the primary burden of caring for a child with a chronic health condition. Families must manage aspects of care such as medication administration, dietary restrictions, exercise, and monitoring procedures, and these aspects may affect the child’s quality of life. “Family management” refers to the daily actions that families implement to manage their child’s chronic condition. As postulated by the Self- and Family Management framework (SFMF), family management describes the daily overall assessments provided and behaviors that a family exhibits to manage the physical, psychological, and social aspects of their child with special health care needs.
The SFMF proposes that risk/protective factors influence family management. Risk/protective factors consist of a variety of factors to include family factors such as parental level of education and family structure. Although studies support the influence of many of the risk/protective factors on family management, no studies examine the influence of parental educational level and family structure on family management of children with chronic conditions. SFMF states family management relates to multiple outcomes, including a child’s health-related quality of life. Available research suggests a theoretical link between family management and a child’s health-related quality of life but no research exists demonstrating such linkage.
Within the context of pediatric chronic conditions, the literature supports the relationship between risk/ protective factors and children’s quality of life. However, no examination of risk/protective factors, such as parental level of education or family structure, along with family management variables regarding their proposed link to quality of life in military children with chronic conditions exists to confirm this relationship.
A contextual factor not yet examined, specifically families managing children with chronic health conditions relates to the military status of the family. In the United States, military families represent a unique subculture with unique challenges now better appreciated given media coverage related to the Iraq and Afghanistan wars. Approximately 280,000 military families include children with special health care needs (CSHCN), these as well as all military families confront multiple challenges including frequent moves, deployments, and separations due to training and schooling. Based on the prevalence of CSHCN within the military family subculture, as well as the potential challenges faced by these families, the influence of risk/protective factors and family management of CSHCN on a child’s quality of life readily justifies examination.
DESIGN AND METHODOLOGY: A descriptive correlational design assessed the relationship between family management, risk/protective factors and pediatric quality of life while controlling for emotional and behavioral difficulties (EBD) using a national cross-sectional survey data base. The United States Department of Health and Human Services (DHHS), Health Resources and Services Administration (HRSA), Maternal and Child Health Bureau (MCHB) sponsored the 2009-2010 NS-CSHCN. The Center for Disease Control (CDC) National Center for Health Statistics (NCHS) State and Local Area integrated Telephone Survey (SLAITS) program conducted the 2009-2010 NS-CSHCN cross-sectional survey of U. S. households. The complex 2009-2010 NS-CSHCN design surveyed U. S. households with at least one resident child (0 to 17 years) with a diagnosis of one or more of twenty chronic disease(s), lasting a minimum of one year at the time of interview. Approximately 40,242 families with a child meeting the criteria completed interviews; identification of sample of military families (n=1,600) resulted from their answering affirmatively to their insurance carrier: Tricare, Champus, or Champ-VA. The variables selected for this secondary data analysis addressed family management, risk/protective factors, and quality of life. For measurement of family management, the selected variables from the secondary data file represent SFMF concepts. The independent variables used to assess family management included the child’s activity limitations, family hours spent per week providing care to the child with the chronic condition, and change of parental employment. The independent risk/protective factor variables included parental education and family structure. Emotional difficulties, activity difficulties, and missed school days comprised the dependent variables that represent quality of life from the database. These variables effectively represent health-related quality of life concepts frequently assessed in children with chronic diseases. G*Power enabled the completion of an a priori power analysis. A sample size of 721 provided sufficient statistical power to calculate and detect a medium size effect. After data cleaning, initial analysis included descriptive statistics consisting of frequency distributions to describe the sample and variables. Multiple imputation and list wise deletion enabled management of missing data. Testing for multi-collinearity among variables and proportional odds for categorical variables occurred using the Pearson Chi-squared associations. Completion of multi-variate logistic regression enabled testing of hypotheses. The 2009-2010 NS-CSHCN data files SPSS codebook functioned as a reference to manage the data set according to provided and recommended study data file usage methods.
RESULTS: Analysis of the outcome variable health-related quality of life, based upon the SFMF model revealed two significant predictors activity limitations and covariates of emotional behavioral conditions. The analysis of military families managing CSHCN produced predictors of the dependent outcome variables that represented health-related quality of life (emotional difficulties, activity difficulties, and missed school days). Finding for strong associated predictors emerged primarily from family management variables (increased activity limitations), and emotional behavioral conditions (ADHD and Depression).
These results demonstrate use of a secondary data base to initially investigate a model representing multiple concepts of family management and health related quality of life for CSHCN among the military populations. The predictors those including aspects of caring for a CSHCN by a family supported this model and this study ultimately identified important information about the complexity associated with representing single variable concepts, along with the strong role of emotional behavioral conditions on health-related quality of life among CSHCN.
CONCLUSION: Analyzing health-related quality of life in CSHCN provides a general measure of a child’s overall functioning in the context of a chronic health condition. Specifically, better understanding the overall impact of families charged with managing pediatric chronic conditions provides greater understanding for healthcare providers, families, society, and policy makers. Expanding a regularly administered national survey to provide a composite of nationwide HRQOL for U. S. CSHCN may provide yet another level of understanding regarding military families managing CSHCN.
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