Family health conditions and parental occupational status modify the relationship between pediatric-onset multiple sclerosis and parental health-related quality of life.

BACKGROUND: The health-related quality of life (HRQoL) of children with multiple sclerosis (MS) is mediated by the HRQoL of their parents. Understanding factors that modify the relationship between the child's MS diagnosis and parental HRQoL would inform interventions to improve the HRQoL of both parents and children living with MS. OBJECTIVE: We evaluated whether the association between an MS diagnosis during childhood and parental HRQoL is modified by the presence of a family health condition or low socioeconomic position (SEP). METHODS: Parents of children with MS or the transient illness, monophasic-acquired demyelinating syndromes (monoADS), were enrolled in a prospective Canadian study. Multivariable models evaluated whether the association between a child's MS diagnosis (vs. monoADS) and parental HRQoL was modified by ⩾1 family health conditions or low SEP. RESULTS: Two hundred seven parents and their children with MS (n = 65) or monoADS (n = 142) were included. We found a synergistic effect of an MS diagnosis and a family health condition on parental HRQoL. We also found a synergistic effect of having MS and a low SEP on parental HRQoL. CONCLUSION: Parents of children with MS who have another family health condition or a low SEP are at particularly high risk for low HRQoL.

The health-related quality of life of children with multiple sclerosis is mediated by the health-related quality of life of their parents.

BACKGROUND: We previously found that children with the chronic disease multiple sclerosis (MS) reported lower health-related quality of life (HRQoL) when compared to children who experienced the transient illness termed monophasic acquired demyelinating syndromes (monoADS). Parents of children with MS also reported lower HRQoL. OBJECTIVES: We evaluated whether parental HRQoL mediated the relationship between the diagnosis of MS and the HRQoL of affected children. To ascertain the effect of an MS diagnosis, we compared children with MS to those with monoADS. METHODS: Children were enrolled in a prospective multi-site Canadian study. Random effects models evaluated whether parental HRQoL mediated the relationship between the diagnosis of MS and the HRQoL of affected children, adjusting for child and family characteristics. RESULTS: 207 parent-child dyads (65 MS; 142 monoADS) completed HRQoL questionnaires. When we modeled the child's HRQoL adjusting for covariates, but not the parent's HRQoL, the diagnosis of MS associated with lower HRQoL of the child (p = 0.004). When we added parental HRQOL to the model, the association between the diagnosis of MS and the child's HRQoL diminished (p = 0.13). CONCLUSIONS: Parental HRQoL mediated the relationship between the diagnosis of MS and the HRQoL of affected children, emphasizing the importance of family-centered care.

Examining cognitive speed and accuracy dysfunction in youth and young adults with pediatric-onset multiple sclerosis using a computerized neurocognitive battery.

OBJECTIVE: We evaluated performance on the Penn Computerized Neurocognitive Battery (PCNB), a tool assessing accuracy and response time across four cognitive domains, alongside the Symbol Digit Modalities Test (SDMT), a measure of processing speed commonly used in MS. We determined whether performance decrements are more likely to be detected on measures of accuracy versus response time in pediatric-onset multiple sclerosis (POMS). METHODS: Performance on the SDMT, accuracy on PCNB tests belonging to four domains (executive function, episodic memory, complex cognition, social cognition), and response time on the PCNB were compared for 65 POMS patients (age range: 8-29 years) and 76 healthy controls (HCs) by ANCOVA. Associations between the Overall PCNB score and SDMT were examined for both groups, and their agreement in classifying impairment was assessed using Cohen's kappa. RESULTS: POMS patients (age at testing = 18.3 ± 4.0 years; age at POMS onset = 14.9 ± 2.3 years) demonstrated reduced accuracy relative to HCs on tests of working memory, attention/inhibition, verbal memory, and visuospatial processing, after adjusting for response time (p ≤ .002). Patients demonstrated slower overall response time on the PCNB (p = .003), while group differences on the SDMT did not meet significance (p = .03). Performance on the PCNB and SDMT were correlated (MS: r = 0.43, HC: r = 0.50, both p < .001), however, the degree of agreement for impairment was minimal (k = 0.22, p = .14). CONCLUSION: Specific cognitive deficits exist independently of slowed information processing speed in POMS, and may represent more significant areas of dysfunction. Delineation of accuracy and response time in neuropsychological assessment is important to identify areas of cognitive deficit in POMS. (PsycInfo Database Record (c) 2021 APA, all rights reserved).