Pediatric Developmental Screening: Understanding and Selecting Screening Instruments

Based on a review of research on developmental screening instruments, provides a manual for selecting and applying tools for screening for both general and specific problems. Includes an interactive questionnaire that links to the recommended instrument

Depressive symptoms and glycemic control in adolescents with type 1 diabetes

OBJECTIVE—To determine whether the association between depressive symptoms and glycemic control is mediated by blood glucose monitoring (BGM). RESEARCH DESIGN AND METHODS—A total of 276 adolescents with type 1 diabetes (mean age ± SD, 15.6 ± 1.4 years) completed a measure of depressive symptoms. Sociodemographic and family characteristics were obtained from caregivers. BGM frequency and glycemic control were obtained at a clinic visit. RESULTS—Separate regression analyses revealed that depressive symptoms were associated with lower BGM frequency (B = −0.03; P = 0.04) and higher A1C (B = 0.03; P = 0.05) and that lower BGM frequency was associated with higher A1C (B = −0.39; P < 0.001). With depressive symptoms and BGM frequency included together, only BGM frequency was associated with A1C and depressive symptoms became nonsignificant (B = 0.02; P = 0.19). The Sobel test was significant (Z = 1.96; P < 0.05) and showed that 38% of the depression-A1C link can be explained by BGM. CONCLUSIONS—BGM is a mediator between depressive symptoms and glycemic control in adolescents with type 1 diabetes

The impact of socio-economic status on health related quality of life for children and adolescents with heart disease

Background: Socioeconomic status (SES) is known to influence children’s health-related quality of life. Many SES indicators assess distinct dimensions of a family’s position rather than measuring the same underlying construct. Many researchers, however, see SES indicators as interchangeable. The primary aim of this study was to determine which measure of SES had the strongest impact on health-related quality of life. Methods: This is a secondary analysis of the Pediatric Cardiac Quality of Life Inventory Validation Study. The SES variables were family income, Hollingshead Index (occupational prestige), and highest parent educational attainment level. Health-related quality of life was measured using the Pediatric Cardiac Quality of Life Inventory. Correlations tested the relationship among the three SES indicators. Regression-based modeling was used to calculate the strength of the association between SES measures and the Pediatric Cardiac Quality of Life Inventory. Results: The correlations among the SES measures were moderately high, with the correlation between the Hollingshead Index and parental education being r = 0.62 (95% CI = 0.56-0.65). There were equally high correlations between family income and the Hollingshead (r = 0.61, 95% CI = 0.57-0.65) and a slightly lower correlation between family income and parental education (r = 0.55, 95% CI = 0.52-0.59). Family income had the highest explanatory value compared to the Hollingshead Index or parental educational attainment, while controlling for sex, race, current cardiac status, and original diagnosis, accounting for 4-5% of the variation in patient and parent Pediatric Cardiac Quality of Life Inventory Total score, respectively, compared to the other SES measures. Conclusion: Family income as an SES measure demonstrated the greatest fidelity with respect to health-related quality of life as measured by the Pediatric Cardiac Quality of Life Inventory across respondent groups and explained more of the variation compared to the Hollingshead Index or highest parental educational attainment

Bullying of extremely low birth weight children: Associated risk factors during adolescence

Preterm children have many risk factors which may increase their susceptibility to being bullied. AIMS: To examine the prevalence of bullying among extremely low birth weight (ELBW, <1kg) and normal birth weight (NBW) adolescents and the associated sociodemographic, physical, and psychosocial risk factors and correlates among the ELBW children

Impact of Surgical Complexity on Health‐Related Quality of Life in Congenital Heart Disease Surgical Survivors

Background: Surgical complexity and related morbidities may affect long‐term patient quality of life (QOL). Aristotle Basic Complexity (ABC) score and Risk Adjustment in Congenital Heart Surgery (RACHS‐1) category stratify the complexity of pediatric cardiac operations. The purpose of this study was to examine the relationship between surgical complexity and QOL and to investigate other demographic and clinical variables that might explain variation in QOL in pediatric cardiac surgical survivors. Methods and Results: Pediatric Cardiac Quality of Life (PCQLI) study participants who had undergone cardiac surgery were included. The PCQLI database provided sample characteristics and QOL scores. Surgical complexity was defined by the highest ABC raw score or RACHS‐1 category. Relationships among surgical complexity and demographic, clinical, and QOL variables were assessed using ordinary least squares regression. A total of 1416 patient–parent pairs were included. Although higher ABC scores and RACHS‐1 categories were associated with lower QOL scores (P<0.005), correlation with QOL scores was poor to fair (r=−0.10 to −0.29) for all groups. Ordinary least squares regression showed weak association with R 2=0.06 to R 2=0.28. After accounting for single‐ventricle anatomy, number of doctor visits, and time since last hospitalization, surgical complexity scores added no additional explanation to the variance in QOL scores. Conclusions: ABC scores and RACHS‐1 categories are useful tools for morbidity and mortality predictions prior to cardiac surgery and quality of care initiatives but are minimally helpful in predicting a child's or adolescent's long‐term QOL scores. Further studies are warranted to determine other predictors of QOL variation