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OBJECTIVE: To test models of unidirectional and bidirectional change between treatment adherence and glycemic control in youth with type 1 diabetes. RESEARCH DESIGN AND METHODS: We conducted a 2-year longitudinal, multisite study of 225 youth with type 1 diabetes recruited at the cusp of adolescence (aged 9–11 years) to describe the mutual influences of glycemic control as measured by HbA1c and treatment adherence as measured by blood glucose monitoring frequency (BGMF) during the transition to adolescence. RESULTS: HbA1c increased from 8.2 to 8.6% (P < 0.001) and BGMF decreased from 4.9 to 4.5 checks per day (P < 0.02) during the 2-year period. Changes in the BGMF slope predicted changes in HbA1c. A change (increase) in HbA1c was associated with a change (decrease) in BGMF of 1.26 (P < 0.001) after controlling for covariates. CONCLUSIONS: The magnitude of the effect of declining treatment adherence (BGMF) on glycemic control in young adolescents may be even greater than declines observed among older adolescents. BGMF offers a powerful tool for targeted management of glycemic control for type 1 diabetes during the critical transition to adolescence.

We conducted a survey among 735 parents to determine differences in endorsement of misinformation related to the coronavirus disease pandemic between parents of children in cancer treatment and those with children who had no cancer history. Parents of children with cancer were more likely to believe misinformation than parents of children without cancer.

Despite significant gains in survival rates for pediatric patients and adolescents/young adults (AYA) with chronic illness, patients in this vulnerable age group are also at an increased risk for developing one or more adverse effects related to their disease, treatment, or maladaptive health behaviors. Maladaptive health behaviors ultimately increase the risk for developing adverse effects, including: increased rates of morbidity and mortality, impaired physical functioning, increased fatigue, obesity, increased psychological distress, and poor quality of life. With close attention including participation in preventive and therapeutic health promotion interventions, problematic health behaviors can be mitigated and ultimately prevented over time. It is well known that improved psychological functioning and adaptive coping can result in improved health status. The present paper provides four case examples illustrating various psychological interventions in pediatric chronic illness. As evidenced in the four case examples, pediatric psychologists provide comprehensive interventions for patients with acute and chronic medical conditions through the use of health promotion interventions, adherence and self-management promotion, cognitive behavioral therapy, behavioral therapy, medical coping, parent training, and motivational interviewing. Our case series demonstrates that for the most impactful behavior change to occur, a combination of interventions is often the most effective.

OBJECTIVE: To review interventions with adherence-promoting components and document their impact on glycemic control via meta-analysis. RESEARCH DESIGN AND METHODS: Data from 15 studies that met the following criteria were subjected to meta-analysis: 1) randomized, controlled trial, 2) study sample included youth aged <19 years, 3) youth had type 1 diabetes, 4) study reported results on glycemic control; and 5) study reported use of adherence- or self-management-promoting components. RESULTS: The 15 studies included 997 youth with type 1 diabetes. The mean effect size for pre- to posttreatment change for the intervention versus control group comparison was 0.11 (95% CI -0.01 to 0.23). This is a small effect, demonstrating very modest improvements in glycemic control. However, analysis for the pre- to posttreatment effects for the intervention group alone did show significant variability [Q(14) = 33.11; P < 0.05]. Multicomponent interventions, those that targeted emotional, social, or family processes that facilitate diabetes management, were more potent than interventions just targeting a direct, behavioral process (e.g., increase in blood glucose monitoring frequency). CONCLUSIONS: Interventions that focus on direct, behavioral processes and neglect emotional, social, and family processes are unlikely to have an impact on glycemic control; multicomponent interventions showed more robust effects on A1C. Future clinical research should focus on refining interventions and gathering more efficacy and effectiveness data on health outcomes of the pediatric patients treated with these interventions.

The objective of this study was to test a comprehensive model of biologic (pubertal status), family (communication and conflict), and psychological influences (behavioral autonomy) on diabetes management and glycemic control in a sample of youth ( N  = 226) with type 1 diabetes recruited during late childhood/early adolescence (ages 9–11 years). The study design was a prospective, multisite, multi-method study involving prediction of diabetes management and glycemic control 1 year post-baseline. The primary outcome measures included diabetes management behaviors based on the Diabetes Self-Management Profile (DSMP) administered separately to mothers and youth and glycemic control measured by glycated hemoglobin (HbA1c) obtained by blood samples and analyzed by a central laboratory to ensure standardization. Our hypothesized predictive model received partial support based on structural equation modeling analyses. Family conflict predicted less adequate glycemic control 1 year later ( p  < 0.05). Higher conflict predicted less adequate diabetes management and less adequate glycemic control. More advanced pubertal status also predicted less adequate glycemic control, but behavioral autonomy did not. Family conflict is an important, potentially clinically significant influence on glycemic control that should be considered in primary and secondary prevention in the management of type 1 diabetes in youth.

Not only do racial and ethnic minority children and adolescents with chronic illness experience disparities in health status and health outcomes, they also experience significant healthcare disparities, including differences in healthcare coverage, access to care, and quality of care. It is well known that the interaction between psychosocial functioning, health behaviors and ethnic and racial disparities, ultimately leads to worse health and psychosocial outcomes in pediatric and AYA chronic illness patient populations, including increased rates of morbidity and mortality. Investigating the impact of racial and ethnic factors on health outcomes, and strategies for reducing these disparities, is of the utmost importance, specifically in life-threatening conditions like cancer and sickle cell disease. This commentary underscores the relative importance of identifying factors that could reduce disparities between minority and non-minority populations. This present paper will focus on the dynamic relationships between health disparities, psychosocial factors and health outcomes within pediatric cancer, sickle cell disease and bone marrow transplant populations, and will offer recommendations for healthcare professionals working with these vulnerable patient populations. The primary goal of this commentary is to provide recommendations for enhancing cultural competency and humility for those working with highly vulnerable patient populations.

Previous research suggests that children and adolescents with acute lymphoblastic leukemia (ALL) and lymphoblastic lymphoma (LBL) often have difficulty adhering to complex treatment regimens during the maintenance phase of therapy. Measurement of treatment adherence can be done via objective (e.g., electronic monitoring (EM), pharmacological assays) or subjective methods (patient, parent, or physician reports). This paper provides an illustration of recommended strategies for comparing discrepancies between two objective measures of medication adherence (e.g., behavioral adherence using electronic monitoring versus pharmacological adherence using 6-mercaptopurine (6MP) metabolite data) within a relatively large cohort of pediatric patients with ALL or LBL (N = 139) who had longitudinal data for both measures of medication adherence over a 15-month period. Additionally, individual- and family-level factors such as gender, socioeconomic status, household environment, and dose intensity will be examined to identify possible sources of discrepancies between adherence measures. This information will provide practical advice for physicians, healthcare providers, and psychologists in identifying nonadherence and the caveats therein so patients achieve the best possible health outcomes.

Pediatric patients with acute lymphoblastic leukemia and lymphoblastic lymphoma are prescribed a daily oral chemotherapy medication named 6-mercaptopurine. Adherence to this medication is vital for survival and decreased risk for disease relapse. Adaptive problem-solving strategies are important for adhering to this complex regimen. This manuscript examined ethnic and racial differences in social problem-solving domains (Social Problem-Solving Inventory) among patients aged 7–19 years old who were diagnosed with cancer; and, their caregivers (N = 139). This was a 15-month longitudinal study. We also examined differences in medication adherence based on behavioral adherence measures. Our study found significant differences between minority and non-minority reporters across multiple social problem-solving domains (p < 0.05). However, there were no significant differences observed for medication adherence. Our findings underscore the importance of implementing culturally sensitive interventions in clinical care that could ultimately positively impact health behaviors, interactions with healthcare providers, and long-term health outcomes.

Effective family management of type 1 diabetes in childhood is critical to maintaining optimal glycemic control. The purpose of this study was to provide preliminary evidence for a reduced form of the Diabetes Self - Management Profile (DSMP) using Rasch modeling techniques. The study was a secondary analysis of DSMP data drawn from a previous study on patterns of self-management from 239 preadolescents with type 1 diabetes. Rasch modeling strategies were used to identify the most informative items and then a reduced score composite was correlated with hemoglobin A1c (A1c) and blood glucose monitoring (BGM) frequency. A short form of the DSMP was obtained using seven items that comprised all five subscales of the DSMP. The DSMP Short-Form (DSMP-SF) composite score correlated significantly with child’s HbA1c and BGM frequency. The DSMP-SF may be considered a valid and effective screening interview alternative to the longer, original, DSMP, particularly when attempting to identify high-risk patients.

To test models of unidirectional and bidirectional change between treatment adherence and glycemic control in youth with type 1 diabetes. We conducted a 2-year longitudinal, multisite study of 225 youth with type 1 diabetes recruited at the cusp of adolescence (aged 9-11 years) to describe the mutual influences of glycemic control as measured by HbAsub lc and treatment adherence as measured by blood glucose monitoring frequency (BGMF) during the transition to adolescence. HbAsub 1c increased from 8.2 to 8.6% (P < 0.001) and BGMF decreased from 4.9 to 4.5 checks per day (P < 0.02) during the 2-year period. Changes in the BGMF slope predicted changes in HbAsub 1c. A change (increase) in HbAsub 1c was associated with a change (decrease) in BGMF of 1.26 (P < 0.001) after controlling for covariates. The magnitude of the effect of declining treatment adherence (BGMF) on glycemic control in young adolescents may be even greater than declines observed among older adolescents. BGMF offers a powerful tool for targeted management of glycemic control for type 1 diabetes during the critical transition to adolescence. 20 references