The interaction of family functioning and disease- and treatment-related factors on quality of life for children after cancer.

PURPOSE: Children with cancer experience low quality of life (QOL), yet heterogeneity underscores a need to understand how risk and resilience factors interact. This study evaluated if family functioning relates to QOL differentially depending on diagnosis and treatment intensity. METHODS: Participants included children (ages 8-14) who completed treatment within six months for either brain tumor (BT; n = 42) or non-central nervous system solid tumor (ST; n = 29). Caregivers and children rated QOL and family functioning. Treatment intensity was categorized as low, moderate, or high. Cross-informant moderation models tested hypothesized interactions. RESULTS: Child-reported family functioning significantly interacted with diagnosis and treatment intensity in models of caregiver-reported QOL. More maladaptive family functioning was associated with reduced QOL for children with BT and moderately-intense treatments. CONCLUSIONS: Children with BT and moderate treatment intensities are sensitive to family functioning, highlighting an at-risk group to target for family-level intervention. Future work should evaluate these associations longitudinally.

Social challenges, autism spectrum disorder, and attention deficit/hyperactivity disorder in youth with neurofibromatosis type I.

OBJECTIVE: Youth with neurofibromatosis type I (NF1) demonstrate high rates of Autism Spectrum Disorder (ASD) and Attention Deficit/Hyperactivity Disorder (ADHD), which often have overlapping behaviors. Diagnostic clarity is important to guide services. This study evaluated ASD classification in NF1 using various methods and whether those with ADHD suspicion have more social challenges associated with ASD. METHOD: 34 youth with NF1 (Mage = 10.5 ± 1.6 years), completed ASD assessments that combined direct observation and informant ratings to yield a Clinician Best Estimate (CBE) classification. Caregivers rated ASD-related social challenges using the Social Responsiveness Scale- 2nd Edition (SRS-2). RESULTS: ASD classification varied depending on the method, ranging from 32% using low-threshold SRS-2 cut-scores (T ≥ 60) to under 6% when combining cut scores for diagnostic observational tools and stringent SRS-2 cut-scores (T ≥ 70). 14.7% had a CBE ASD classification. 44% were judged to have autism traits associated with a non-ASD diagnosis. The 52.9% with a suspicion of ADHD had higher SRS-2 scores than those without ADHD, F (7, 26) = 3.45, p < .05, Wilk's lambda = 0.518, partial eta squared = 0.482. CONCLUSIONS: Findings highlight the importance of rigorous diagnostic methodology when evaluating ASD in NF1 to inform the selection of targeted interventions for socialization challenges in NF1.