Self-management of chronic pediatric conditions is a formidable challenge for patients, families, and clinicians, with research demonstrating a high prevalence of poor self-management and nonadherence across pediatric conditions. Nevertheless, effective self-management is necessary to maximize treatment efficacy and clinical outcomes and to reduce unnecessary health care utilization and costs. However, this complex behavior is poorly understood as a result of insufficient definitions, reliance on condition-specific and/or adult models of self-management, failure to consider the multitude of factors that influence patient self-management behavior, and lack of synthesis of research, clinical practice, and policy implications. To address this need, we present a comprehensive conceptual model of pediatric self-management that articulates the individual, family, community, and health care system level influences that impact self-management behavior through cognitive, emotional, and social processes. This model further describes the relationship among self-management, adherence, and outcomes at both the patient and system level. Implications for research, clinical practice, and health care policy concerning pediatric chronic care are emphasized with a particular focus on modifiable influences, evidence-based targets for intervention, and the role of clinicians in the provision of self-management support. We anticipate that this unified conceptual approach will equip stakeholders in pediatric health care to (1) develop evidence-based interventions to improve self-management, (2) design programs aimed at preventing the development of poor self-management behaviors, and (3) inform health care policy that will ultimately improve the health and psychosocial outcomes of children with chronic conditions.

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Several recommendations for improving adherence assessment were made. In particular, consideration should be given to the use of innovative technologies that provide a window into the "real time" behaviors of patients and families. Providing written treatment plans, identifying barriers to good adherence, and examining racial and ethnic differences in attitudes, beliefs and behaviors affecting adherence were strongly recommended.

The multi-method measurement approach provided unique information regarding rates of adherence for each disease condition by type of treatment component. Accurately measuring rates of treatment adherence for children with CF is an important step in developing effective interventions to influence these behaviors.

Overall, this study provided evidence that patients and their parents experience specific barriers within the context of their own illness and highlights the need for disease-specific measures and interventions.

ZELLER, MEG H. AND AVANI C. MODI. Predictors of health-related quality of life in obese youth. Obesity. 2006; 14:122-130. Objective: Recent literature has documented the psychosocial consequences of pediatric obesity, including poor health-related quality of life (HRQOL). The present study examines HRQOL and its association with depressive symptoms and perceived social support in African-American and white youth pursuing weight management treatment. Research Methods and Procedures: Study participants were 166 obese youth (mean ϭ 12.7 years, 70% females, 57% African American, mean BMI ϭ 37.0) referred to a pediatric weight management program. Parents of participants completed a demographics form and the parent-proxy Pediatric Quality of Life Inventory (PedsQL). Youth completed the Children's Depression Inventory, PedsQL, and Perceived Social Support Scale for Children. Results: HRQOL scores were quite impaired relative to published norms on healthy youth (p Ͻ 0.001). Approximately 11% of the sample met criteria for clinically significant depressive symptoms. Simultaneous regression analyses revealed that depressive symptoms, perceived social support from classmates, degree of overweight, and socioeconomic status seem to be strong predictors of HRQOL. Discussion: Obesity has a clear impact on HRQOL regardless of respondent (e.g., parent, youth) or racial group. It is likely that assessing and treating depressive symptoms and fostering social support in the context of pediatric intervention have implications for both improved HRQOL and weight management outcomes.

Context Because of epilepsy’s common occurrence, the narrow therapeutic and safety margins of antiepileptic medications, and the recognized complications of medication nonadherence in adults with epilepsy, identifying the rates, patterns, and predictors of nonadherence in children with epilepsy is imperative. The onset and evolution of antiepileptic drug nonadherence in children with newly diagnosed epilepsy remains unknown. Objectives To identify and characterize trajectories of adherence in children with newly diagnosed epilepsy over the first 6 months of therapy and to determine sociodemographic and epilepsy-specific predictors of adherence trajectories. Design, Setting, and Patients Prospective, longitudinal observational study of antiepileptic drug adherence in a consecutive cohort of 124 children (2–12 years old) with newly diagnosed epilepsy at Cincinnati Children’s Hospital Medical Center. Patients were recruited from April 2006 through March 2009, and final data collection occurred in September 2009. Main Outcome Measure Objective adherence measured using electronic monitors. Results Fifty-eight percent of children with newly diagnosed epilepsy demonstrated persistent nonadherence during the first 6 months of therapy. Group-based trajectory models identified 5 differential adherence patterns (Bayesian information criterion=−23611.8): severe early nonadherence (13%; 95% confidence interval [CI], 8%–20%), severe delayed nonadherence (7%; 95% CI, 3%–12%), moderate nonadherence (13%; 95% CI, 8%–20%), mild nonadherence (26%; 95% CI, 19%–34%), and near-perfect adherence (42%; 95% CI, 33%–50%). The adherence pattern of most patients was established by the first month of therapy. Socioeconomic status was the sole predictor of adherence trajectory group status (χ42=19.3 [n = 115]; P < .001; partial r2 = 0.25), with lower socioeconomic status associated with higher nonadherence. Conclusion Five trajectory patterns were identified that captured the spectrum of nonadherence to antiepileptic drugs among children with newly diagnosed epilepsy; the patterns were significantly associated with socioeconomic status.

Controlled study of critical parent and family factors in the obesigenic environment. Obesity. 2007;15:126 -136. Objective: Critical gaps remain in our understanding of the obesigenic family environment. This study examines parent and family characteristics among obese youth presenting for treatment in a clinic setting. Research Methods and Procedures: Families of 78 obese youth (BMI z-score ϭ 2.4; age, 8 to 16 years; 59% girls; 49% African-American) were compared with 71 non-overweight (BMI z-score ϭ Ϫ0.02) demographically matched comparisons. Parents completed measures assessing family demographics, psychological distress (Symptom Checklist 90-Revised), and family functioning both broadly (Family Environment Scale: Conflicted, Support, Control) and at mealtimes (About Your Child's Eating-Revised: Mealtime Challenges, Positive Mealtime Interaction). Height and weight were obtained from all participants. Results: Compared with mothers and fathers of non-overweight youth, parents of obese youth had significantly higher BMIs (p Ͻ 0.001). Mothers of obese youth reported significantly greater psychological distress (p Ͻ 0.01), higher family conflict (p Ͻ 0.05), and more mealtime challenges (p Ͻ 0.01). Less positive family mealtime interactions were reported by both mothers (p Ͻ 0.01) and fathers (p Ͻ 0.05) of obese youth. These group differences did not vary by child sex or race. Logistic regression analyses indicated that maternal distress and mealtime challenges discriminated between obese and non-overweight youth after controlling for maternal BMI. Family conflict was explained, in part, by maternal distress. Discussion: Obese youth who present for treatment in a clinic setting are characterized by psychosocial factors at the parent and family level that differ from non-overweight youth. These data are critical because they identify factors that may be serving as barriers to a family's or youth's ability to implement healthy lifestyle behaviors but that are potentially modifiable.