Cognitive Abilities Moderate the Effect of Disease Severity on Health-Related Quality of Life in Pediatric Sickle Cell Disease

Cognitive Abilities Moderate the Effect of Disease Severity on Health-Related Quality of Life in... Abstract Objective Complications that can arise from sickle cell disease (SCD) have the potential to negatively affect health-related quality of life (HRQL). SCD manifests in varying degrees of severity, but effects on HRQL are not uniform. Cognitive abilities influence HRQL in other pediatric groups, potentially through variability in treatment adherence and psychological coping. This study examined the effect of SCD severity on HRQL and explored cognitive abilities as a moderator of this relationship. Methods A total of 86 children and adolescents with SCD (ages 7–16 years) completed a cognitive assessment (Wechsler Scale of Intelligence for Children, Fifth Edition), and primary caregivers rated their child’s SCD severity and HRQL (PedsQL Sickle Cell Disease Module). A hierarchical linear regression was conducted to evaluate the interactive effect of SCD severity and cognitive functioning on HRQL. Results Caregiver-rated SCD severity predicted HRQL and cognitive abilities interacted with disease severity to influence HRQL. Youth with milder SCD and cognitive abilities in the average range or higher demonstrated significantly better HRQL compared with youth with mild SCD but below average cognitive abilities. Youth with more severe disease appeared to exhibit similarly low levels of HRQL, with only a minimal influence of cognitive abilities. Conclusions Cognitive factors modify the effect of SCD severity on HRQL, particularly among youth with milder forms of SCD. Future studies are warranted to clarify the role of cognitive abilities in determining HRQL. Clinicians should monitor youth with milder forms of SCD and limited cognitive abilities for worsening HRQL and opportunities to provide support around disease self-management. chronic illness, cognitive assessment, hematology, quality of life, sickle cell disease Sickle cell disease (SCD) is a relatively common genetic disorder affecting approximately 100,000 Americans and occurring in roughly one out of every 365 African-American births (Hassell, 2010). Children with SCD are at increased risk for serious medical complications, such as vaso-occlusive pain crises, acute chest syndrome, and cerebral infarction (Bou-Maroun, Meta, Hanba, Campbell, & Yanik, 2018; DeBaun et al., 2012; Fisak, Belkin, von Lehe, & Bansal, 2012; Kawadler, Clayden, Clark, & Kirkham, 2016; Ohene-Frempong et al., 1998). In addition, a significant number of children with SCD experience cognitive difficulties across multiple domains, and the degree of impairment tends to vary according to disease severity (Berkelhammer et al., 2007; Kral, Brown, & Hynd, 2001; Schatz, Schlenz, Reinman, Smith, & Roberts, 2017). Cognitive deficits in pediatric SCD are thought to manifest through several potential pathways, including low socioeconomic status (King et al., 2014; Schatz, Finke, & Roberts, 2004), low hemoglobin and hematocrit (King et al., 2014; Steen et al., 2003), high cerebral blood flow velocity (Ruffieux et al., 2013), high levels of inflammatory cytokines (Andreotti, King, Macy, Compas, & DeBaun, 2015), and cerebral infarction (Schatz, White, Moinuddin, Armstrong, & DeBaun, 2002). These cognitive deficits have widespread implications that can impose a significant burden on children and families as they cope with day-to-day challenges as well as more severe disease-related events (Palermo, Schwartz, Drotar, & McGowan, 2002). Due to the chronicity of SCD, its impact on health-related quality of life (HRQL) has been a focus of research both describing the impact of the disease on patients and families and quantifying the effects of medical and psychosocial interventions to reduce disease burden. Studies have documented that children with SCD experience lower HRQL compared with healthy peers (Dale, Cochran, Roy, Jernigan, & Buchanan, 2011; Panepinto, O'Mahar, DeBaun, Loberiza, & Scott, 2005), and this difference is observed across multiple domains of HRQL, including physical and psychosocial health as well as school functioning (Dale et al., 2011). Disease severity and related complications are central contributors to HRQL in youth with SCD, with symptoms such as pain and fatigue, in particular, being shown to be robust predictors of HRQL (Anderson, Allen, Thornburg, & Bonner, 2015; Barakat, Patterson, Daniel, & Dampier, 2008; Fisak et al., 2012). Cognitive factors may also affect HRQL in youth with chronic illnesses, either directly or indirectly (Clary, Vander Wal, & Titus, 2010; Sherman, Slick, & Eyrl, 2006). A few studies have explored this relationship specifically in SCD, suggesting that neurobehavioral difficulties are associated with impaired HRQL (Allen, Anderson, Rothman, & Bonner, 2017; McClellan, Schatz, Sanchez, & Roberts, 2008; Panepinto et al., 2005). A recent review highlighted the mounting evidence that disease-related cognitive deficits lead to short- and long-term difficulties across multiple domains of psychosocial functioning in youth with chronic illnesses (Compas, Jaser, Reeslund, Patel, & Yarboi, 2017). Research also supports the inverse; strong cognitive abilities appear to serve a protective role for youth with a chronic illness. For example, higher intelligence is associated with decreased mental and behavioral health problems in children with chronic illnesses (Perrin, Ayoub, & Willett, 1993; Ryland, Lundervold, Elgen, & Hysing, 2010; Taylor, Gibson, & Franck, 2008; Thompson et al., 2003). Although cognitive abilities have been hypothesized to influence HRQL through varied pathways, one path with a particularly strong theoretical and empirical basis is treatment adherence. Treatment adherence is an integral component of chronic disease self-management (DiMatteo, Giordani, Lepper, & Croghan, 2002), and although adherence is dependent on multiple factors, some have suggested that cognitive deficits underlie difficulties with adherence (Brock, Brock, & Thiedke, 2011). For example, higher intelligence and executive functioning have been shown to be associated with better treatment adherence across multiple childhood chronic illnesses (Bagner, Williams, Geffken, Silverstein, & Storch, 2007; Gutiérrez-Colina et al., 2016; Malee et al., 2009; McNally, Rohan, Pendley, Delamater, & Drotar, 2010; O'Hara & Holmbeck, 2013). As a result, the effect of a disease on HRQL may partially hinge on cognitive factors and treatment adherence. A central component of HRQL is the functional impact of one’s illness; however, HRQL also encompasses the emotional toll of a disease (Panepinto et al., 2005). Therefore, HRQL may also be influenced by a child or adolescent’s ability to process and emotionally cope with a chronic illness. In studies of youth with chronic illnesses, evidence suggests that cognitive abilities are salient to the development and management of interpersonal relationships and emotion regulation, both of which have implications for broader psychosocial outcomes (Campbell et al., 2009; Compas & Boyer, 2001; Hocking et al., 2011; Zebrack et al., 2004). One recent study involving youth with SCD demonstrated that stronger verbal skills are related to greater utilization of secondary control coping strategies (e.g., acceptance or cognitive reframing), which leads to reduced depressive symptoms (Prussien et al., in press). Functional neuroimaging also supports this link in a pediatric sample, demonstrating that brain activation in the prefrontal cortex is linked to the utilization of adaptive coping strategies (Robinson et al., 2015). In summary, SCD is a chronic illness with the potential to significantly impact HRQL through pain, fatigue, frequent hospitalizations, and activity limitations. Research supports a direct effect of disease severity on HRQL and also implicates cognitive functioning, which can affect treatment adherence and psychological coping, as playing a role in determining HRQL. As such, it may be more challenging for children with limited cognitive resources to manage the potential physical and emotional toll of a chronic illness, thereby resulting in reduced HRQL. It is unclear, though, whether disease severity exerts a uniformly salient influence on HRQL or whether cognitive factors moderate this relationship, potentially weakening the effect of disease severity at higher or lower levels of cognitive functioning. For instance, it may be that for youth with more severe forms of a disease who are faced with especially complex treatment regimens and who endure greater psychosocial disruption, cognitive abilities play a crucial role in determining the degree to which the disease affects HRQL. Conversely, cognitive abilities may be less important in determining HRQL for children with milder presentations of a disease who have less complex treatment regimens to manage and experience fewer threats to psychosocial functioning. The role of cognitive functioning in affecting patient-reported outcomes, including HRQL, is relatively well documented in pediatric samples, but there is limited research describing this relationship specifically in youth with SCD. One recent study has examined the association between cognitive abilities and HRQL in pediatric SCD (Allen et al., 2017). Allen and colleagues (2017) reported that greater impairments in executive functioning, as measured by a parent-report questionnaire, predicted lower quality of life, but it is unclear whether this association applies to all patients with SCD. Informed by these results and others, we sought a conceptually different approach, aiming to explore cognitive abilities as a moderator of the effect of SCD severity on HRQL. Intelligence was used to measure the impact of cognitive abilities on the relationship between SCD severity and HRQL because children with SCD are known to exhibit cognitive deficits across multiple domains, and previous research suggests multiple aspects of cognition have the potential to affect HRQL. We hypothesized that SCD severity would have an inverse main effect on HRQL but that this relationship would vary by cognitive ability. Specifically, we expected that children with severe SCD and higher cognitive functioning would exhibit better HRQL than children with severe SCD and lower cognitive functioning, whereas HRQL among youth with mild SCD would not vary by cognitive ability. This investigation represented an advancement of the literature on pediatric SCD due to its unique focus on improving understanding of how disease severity can impact quality of life differentially as a function of child cognitive abilities. Moreover, we incorporated a well-validated performance-based measure of cognitive functioning in a large sample of youth with SCD to reliably examine the role of cognitive functioning in determining HRQL. Methods Participants Participants were recruited for a cognitive rehabilitation intervention trial open to patients regardless of history of neurologic sequelae or cognitive difficulties. Only data from a baseline assessment completed before any intervention were used. Inclusion criteria included having a diagnosis of SCD (any genotype), being between 7 and 16 years old, English fluency, and having consistent access to electricity (to charge a borrowed electronic device for the intervention). Patients were excluded if they had a visual, motor, auditory, or cognitive impairment that prevented use of a tablet computer during the intervention phase of the study or if there had been a recent (≤30 days) initiation or dose change of a psychostimulant. We approached 238 patients and families to discuss participation in the study. Of those, 66% (n = 158) expressed interest in participating, whereas 33% (n = 80) declined to participate. Although most patients and families were interested in the study, a sizable portion of interested families never enrolled (n = 67; 42%), commonly citing a lack of time to commit to the research. In all, 91 participants (58% of those who expressed interest) enrolled in the study; all participants completed a baseline cognitive assessment, but data were only used from 86 participants, as a small number of caregivers (5%) failed to complete essential study questionnaires, including ratings of SCD severity and proxy reports of child HRQL (described later). Of note, as the present study is a secondary analysis of data collected in the context of a clinical trial, the hypotheses tested were not powered on an a priori basis. Estimates of effect sizes were included to assist in determining clinical significance. Most participants were female (58%), and the mean age of the participants was 10.37 years (SD = 2.91). Caregivers described their children as primarily African, African-American, or Black (93%). Most participants were diagnosed with HbSS (n = 61, 71%), followed by HbSC (n = 18, 21%), HbS/β0 thalassemia (n = 5, 6%), and HbS/β+ thalassemia (n = 2, 2%). Twenty-five (29%) participants had evidence in their medical chart of a history of cerebral infarction. The mean steady-state hemoglobin was 9.35 mg/dL (SD = 1.52). Just over half of the participants (n = 48; 56%) were being prescribed hydroxyurea at the time of enrollment. Only one participant was taking a stimulant at the time of enrollment. In all, 80% of the cognitive assessments were completed in a private consultation room, with the remaining 20% conducted with patients undergoing chronic blood transfusion in a transfusion pod. Caregivers were generally well educated, with most reporting that they had completed at least some college (n = 59; 67%). Procedures The institutional review board at the authors’ institution approved the research protocol before recruitment. Potential patients were recruited during routine hematology clinic visits or appointments for chronic blood transfusion therapy. Medical providers (e.g., hematologists and nurse practitioners) initially screened patients for eligibility and then research staff met with prospective participants to further evaluate eligibility and provide an introduction to the study. Eligible and interested families scheduled a separate enrollment visit, typically arranged to coincide with the patient’s next hematology visit or blood transfusion, where informed consent and assent were obtained. During the enrollment visit, participants completed study questionnaires and a neurocognitive assessment in a private consultation room or in a transfusion pod with appropriate accommodations made to minimize distractions (e.g., sound machine, drawn curtain, and clustered nursing care to reduce interruptions). Neurocognitive assessments were not conducted if a participant was reporting significant pain (i.e., ≥7 on a 0–10 numerical pain scale), had received an opioid before the assessment, or, if the participant was undergoing a blood transfusion, had received an antihistamine. Trained psychometrists and postdoctoral psychology fellows administered neurocognitive tests. Scores were verified by a licensed psychologist, with discrepancies resolved through consultation between two psychologists. Primary caregivers completed a set of questionnaires using REDCap electronic data capture (Harris et al., 2009). Each participating family received $20 in retail gift cards and reimbursement for parking or public transportation. Measures Demographic, Disease, and Treatment Characteristics Caregivers reported on participants’ age, gender, and race/ethnicity, as well as the primary caregiver’s highest level of educational attainment (less than eighth grade, eighth grade, some high school, high school diploma, some college, college degree, or more than a college degree). A chart review was conducted to determine each participant’s sickle cell genotype, whether there was a history of cerebral infarction, and whether participants were currently prescribed hydroxyurea. Hemoglobin values were extracted if labs had been drawn within 45 days (before or after) of the baseline assessment and the chart review did not reveal any acute health problems or treatment changes that might affect labs (i.e., no inpatient admissions within 21 days of blood draw, no blood transfusions within 60 days, and no change in hydroxyurea dosage within 60 days). Disease Severity Caregivers rated the severity of their child’s SCD as either Very Mild, Mild, Moderate, Severe, or Very Severe, and these responses were coded as 1–5, where higher scores reflected more severe disease. This rating served as the primary measure of disease severity and was used as an independent variable in subsequent analyses. To evaluate the validity of caregiver ratings of disease severity, we also collected data on the number of major pain crises a child had experienced and the presence or absence of several SCD-related complications. Specifically, caregivers reported the number of major pain crises (pain that required contact with a doctor) their child had experienced in the past 12 months. To consider the range of indicators of disease severity that could be assessed, caregivers also reported whether their child had a history of silent infarct, overt stroke, acute chest syndrome, abnormal transcranial Doppler ultrasonography, multiple hospitalizations for pain crises (i.e., more than three or four admissions for pain in a single year), avascular necrosis, hospitalization for at least 4 days in a row because of sickle cell pain, and admission to an intensive care unit. Responses (Yes = 1; No = 0) of equal weighting were summed to produce a general composite of disease severity ranging from 0 to 8, where higher scores reflected more severe disease. Caregiver ratings of disease severity were significantly correlated with both pain crises experienced in the past 12 months and the number of SCD-related complications experienced. Specifically, youth with higher ratings of disease severity also had endured more pain crises over the past year (ρ = .36, p < .01). Similarly, children rated as having more severe SCD also had experienced significantly more disease-related complications (ρ = .37, p < .01). The validity of caregiver ratings of child SCD severity was further explored by examining associations with indicators of disease severity extracted from patients’ electronic health records. Following the procedures outlined by Panepinto and colleagues (2013), children were classified as having severe SCD if their health record contained evidence of them meeting one of the following criteria: (1) known history of cerebral infarction, (2) history of a diagnosis of acute chest syndrome, or (3) documentation of three or more hospitalizations for SCD-related pain (e.g., vaso-occlusive crisis, acute chest, or priapism) in the past 3 years. Caregiver ratings of disease severity were significantly correlated with disease severity as measured by chart review (ρ = .27, p = .01). Cognitive Abilities To estimate overall cognitive abilities, participants completed the Wechsler Intelligence Scale for Children, Fifth Edition (WISC-V), which is a widely used and well-validated assessment of intelligence (Wechsler, 2014). The WISC-V normalization sample was stratified across multiple demographic variables, including race/ethnicity, socioeconomic status, and geography. In addition, original validation studies demonstrated the WISC-V possesses adequate convergent and discriminant validity with several other rigorously developed cognitive, academic, and behavioral measures. The Full Scale Intelligence Quotient (IQ) exhibits excellent test–retest reliability at .96. To minimize burden on research participants, we adopted an abbreviated battery, administering primary subtests from the Verbal Comprehension (i.e., ability to reason verbally and express word knowledge), Fluid Reasoning (i.e., ability to discern relationships visually and to apply rules about conceptual relations), Working Memory (i.e., ability to hold and manipulate visual and auditory information in mind), and Processing Speed (i.e., ability to quickly and accurately process visual information) Indices and then calculating a prorated IQ based on six subtests following procedures described in the WISC-V manual (Wechsler, 2014). Trained psychometrists and postdoctoral psychology fellows administered the WISC-V; scoring was verified by a licensed clinical psychologist. The WISC-V was administered electronically using two iPad Air devices. Estimated IQ served as a moderator variable in analyses. Health-Related Quality of Life Participating children completed the Pediatric Quality of Life Inventory Sickle Cell Disease Module (PedsQL SCD Module), and a primary caregiver completed the parent proxy form of the PedsQL SCD Module to assess the extent of SCD-related problems with pain (Pain Hurt), the impact of pain on daily activities (Pain Impact), pain management (Pain Manage), worrying about general medical complications (Worry I), worrying about specific and severe medical complications (Worry II), feeling mad (Emotions), treatments and disease self-management (Treatment), talking to medical providers (Communication I), and talking with others about SCD (Communication II). Examples of items include: “It is hard for him/her to take care of himself/herself when he/she has pain” and “Worrying he/she might have to stay overnight in the hospital.” Respondents reported the degree to which each item had been a problem over the past month using a 0 (“Never”) to 4 (“Almost Always”) rating scale. Items were reversed-scored and transformed to a 0–100 scale using the recommended conversions (i.e., 0 = 100, 1 = 75, 2 = 50, 3 = 25, and 4 = 0). The Total Score was calculated as the mean score of all items answered, with higher scores reflecting better HRQL. Subdomain scores were computed as the mean score of items in the respective scales, following similar score transformations. Although we report HRQL as described by both raters, caregiver reports were the focus of primary statistical analyses. We elected to focus our investigation on caregiver reports of child HRQL due to the superior psychometric properties of the parent proxy form of the PedsQL SCD Module, the desire to preserve consistency in terms of the reporting source for our independent and dependent variables (i.e., disease severity and HRQL, respectively), and well-described concerns (e.g., potential for limited awareness, social desirability, recall bias) with querying children with cognitive deficits about quality of life (Waters et al., 2009). The parent proxy version of the PedsQL SCD Module has been validated in a geographically diverse sample of parents and caregivers of children with SCD (Panepinto et al., 2005, 2013). In the original validation study, child HRQL as measured by the PedsQL SCD Module parent proxy form was significantly lower for children with severe disease compared with those with mild disease (Panepinto et al., 2013). Moreover, parent-reported HRQL was strongly correlated with reports on the PedsQL 4.0 Generic Core Scales and the PedsQL Multidimensional Fatigue Scale. Panepinto and colleagues (2013) reported that internal consistency of the Total Score for the PedsQL SCD Module parent proxy form is excellent at .97; subdomains also demonstrated acceptable internal consistency, with alphas ranging from .83 (Communication I and Communication II) to .97 (Pain Impact). As shown in Table I, we observed similar reliability coefficients in the present sample, with an alpha of .97 for the Total Score and alphas for subdomains ranging from .79 (communication I) to .96 (Pain Impact). The Total Score, as measured by the parent proxy form of the PedsQL SCD Module, was used as the dependent variable in regression analyses. In regard to reliability for the child-report version of the PedsQL SCD Module, Cronbach’s alpha for the Total Score in our sample was good at .93. However, alphas for the subdomains were generally much lower, ranging from .56 (Worry II) to .91 (Pain Impact). Table I. Reliability of the PedsQL SCD Module, Mean Scores, and Differences Between Mild Disease and Moderate to Severe Disease Groups   Total sample (n = 86)   Mild SCD (n = 30)   Mod to Sev SCD (n = 56)   t  PedsQL SCD Module Domain  α  M (SD)  M (SD)  M (SD)  Caregiver-rated HRQL   Total  .97  66.75 (19.20)  77.00 (17.76)  61.25 (17.76)  3.92**   Pain Hurt  .92  73.20 (20.86)  85.09 (16.38)  66.82 (20.30)  4.24**   Pain Impact  .96  53.60 (28.45)  69.33 (27.61)  45.18 (25.33)  4.08**   Pain Manage  .94  60.90 (29.07)  74.58 (23.32)  53.57 (29.36)  3.39**   Worry I  .91  66.57 (27.50)  72.67 (26.61)  63.30 (27.64)  1.52   Worry II  .80  78.34 (27.68)  86.25 (25.29)  74.11 (28.19)  1.97   Emotions  .87  63.95 (28.85)  70.83 (22.58)  60.27 (31.27)  1.63   Treatment  .84  72.67 (20.42)  82.02 (16.92)  67.67 (20.50)  3.28**   Communication I  .79  79.17 (23.56)  83.06 (23.00)  77.08 (23.80)  1.12   Communication II  .86  64.53 (28.90)  67.22 (31.78)  63.10 (27.43)  0.63  Child-rated HRQL   Total  .96  64.79 (20.47)  67.29 (16.95)  63.35 (22.26)  0.93   Pain Hurt  .87  75.51 (21.73)  79.60 (19.78)  73.16 (22.90)  1.34   Pain Impact  .91  55.53 (27.19)  57.86 (23.95)  54.19 (29.00)  0.61   Pain Manage  .80  54.97 (32.86)  58.20 (33.09)  53.13 (32.88)  0.70   Worry I  .87  60.34 (30.98)  60.94 (29.00)  60.00 (32.31)  0.14   Worry II  .56  78.86 (26.56)  83.70 (17.85)  76.39 (29.94)  1.26   Emotions  .76  64.39 (35.90)  70.16 (30.05)  61.14 (38.69)  1.20   Treatment  .82  68.55 (23.66)  74.39 (17.44)  65.26 (26.11)  1.94   Communication I  .80  69.96 (31.53)  65.59 (31.24)  72.42 (31.71)  −0.97   Communication II  .78  50.78 (32.90)  47.85 (31.18)  52.42 (34.01)  −0.62    Total sample (n = 86)   Mild SCD (n = 30)   Mod to Sev SCD (n = 56)   t  PedsQL SCD Module Domain  α  M (SD)  M (SD)  M (SD)  Caregiver-rated HRQL   Total  .97  66.75 (19.20)  77.00 (17.76)  61.25 (17.76)  3.92**   Pain Hurt  .92  73.20 (20.86)  85.09 (16.38)  66.82 (20.30)  4.24**   Pain Impact  .96  53.60 (28.45)  69.33 (27.61)  45.18 (25.33)  4.08**   Pain Manage  .94  60.90 (29.07)  74.58 (23.32)  53.57 (29.36)  3.39**   Worry I  .91  66.57 (27.50)  72.67 (26.61)  63.30 (27.64)  1.52   Worry II  .80  78.34 (27.68)  86.25 (25.29)  74.11 (28.19)  1.97   Emotions  .87  63.95 (28.85)  70.83 (22.58)  60.27 (31.27)  1.63   Treatment  .84  72.67 (20.42)  82.02 (16.92)  67.67 (20.50)  3.28**   Communication I  .79  79.17 (23.56)  83.06 (23.00)  77.08 (23.80)  1.12   Communication II  .86  64.53 (28.90)  67.22 (31.78)  63.10 (27.43)  0.63  Child-rated HRQL   Total  .96  64.79 (20.47)  67.29 (16.95)  63.35 (22.26)  0.93   Pain Hurt  .87  75.51 (21.73)  79.60 (19.78)  73.16 (22.90)  1.34   Pain Impact  .91  55.53 (27.19)  57.86 (23.95)  54.19 (29.00)  0.61   Pain Manage  .80  54.97 (32.86)  58.20 (33.09)  53.13 (32.88)  0.70   Worry I  .87  60.34 (30.98)  60.94 (29.00)  60.00 (32.31)  0.14   Worry II  .56  78.86 (26.56)  83.70 (17.85)  76.39 (29.94)  1.26   Emotions  .76  64.39 (35.90)  70.16 (30.05)  61.14 (38.69)  1.20   Treatment  .82  68.55 (23.66)  74.39 (17.44)  65.26 (26.11)  1.94   Communication I  .80  69.96 (31.53)  65.59 (31.24)  72.42 (31.71)  −0.97   Communication II  .78  50.78 (32.90)  47.85 (31.18)  52.42 (34.01)  −0.62  Note. **p < .01. IQ = Intelligence Quotient; Mod to Sev SCD = moderate to severe sickle cell disease. Table I. Reliability of the PedsQL SCD Module, Mean Scores, and Differences Between Mild Disease and Moderate to Severe Disease Groups   Total sample (n = 86)   Mild SCD (n = 30)   Mod to Sev SCD (n = 56)   t  PedsQL SCD Module Domain  α  M (SD)  M (SD)  M (SD)  Caregiver-rated HRQL   Total  .97  66.75 (19.20)  77.00 (17.76)  61.25 (17.76)  3.92**   Pain Hurt  .92  73.20 (20.86)  85.09 (16.38)  66.82 (20.30)  4.24**   Pain Impact  .96  53.60 (28.45)  69.33 (27.61)  45.18 (25.33)  4.08**   Pain Manage  .94  60.90 (29.07)  74.58 (23.32)  53.57 (29.36)  3.39**   Worry I  .91  66.57 (27.50)  72.67 (26.61)  63.30 (27.64)  1.52   Worry II  .80  78.34 (27.68)  86.25 (25.29)  74.11 (28.19)  1.97   Emotions  .87  63.95 (28.85)  70.83 (22.58)  60.27 (31.27)  1.63   Treatment  .84  72.67 (20.42)  82.02 (16.92)  67.67 (20.50)  3.28**   Communication I  .79  79.17 (23.56)  83.06 (23.00)  77.08 (23.80)  1.12   Communication II  .86  64.53 (28.90)  67.22 (31.78)  63.10 (27.43)  0.63  Child-rated HRQL   Total  .96  64.79 (20.47)  67.29 (16.95)  63.35 (22.26)  0.93   Pain Hurt  .87  75.51 (21.73)  79.60 (19.78)  73.16 (22.90)  1.34   Pain Impact  .91  55.53 (27.19)  57.86 (23.95)  54.19 (29.00)  0.61   Pain Manage  .80  54.97 (32.86)  58.20 (33.09)  53.13 (32.88)  0.70   Worry I  .87  60.34 (30.98)  60.94 (29.00)  60.00 (32.31)  0.14   Worry II  .56  78.86 (26.56)  83.70 (17.85)  76.39 (29.94)  1.26   Emotions  .76  64.39 (35.90)  70.16 (30.05)  61.14 (38.69)  1.20   Treatment  .82  68.55 (23.66)  74.39 (17.44)  65.26 (26.11)  1.94   Communication I  .80  69.96 (31.53)  65.59 (31.24)  72.42 (31.71)  −0.97   Communication II  .78  50.78 (32.90)  47.85 (31.18)  52.42 (34.01)  −0.62    Total sample (n = 86)   Mild SCD (n = 30)   Mod to Sev SCD (n = 56)   t  PedsQL SCD Module Domain  α  M (SD)  M (SD)  M (SD)  Caregiver-rated HRQL   Total  .97  66.75 (19.20)  77.00 (17.76)  61.25 (17.76)  3.92**   Pain Hurt  .92  73.20 (20.86)  85.09 (16.38)  66.82 (20.30)  4.24**   Pain Impact  .96  53.60 (28.45)  69.33 (27.61)  45.18 (25.33)  4.08**   Pain Manage  .94  60.90 (29.07)  74.58 (23.32)  53.57 (29.36)  3.39**   Worry I  .91  66.57 (27.50)  72.67 (26.61)  63.30 (27.64)  1.52   Worry II  .80  78.34 (27.68)  86.25 (25.29)  74.11 (28.19)  1.97   Emotions  .87  63.95 (28.85)  70.83 (22.58)  60.27 (31.27)  1.63   Treatment  .84  72.67 (20.42)  82.02 (16.92)  67.67 (20.50)  3.28**   Communication I  .79  79.17 (23.56)  83.06 (23.00)  77.08 (23.80)  1.12   Communication II  .86  64.53 (28.90)  67.22 (31.78)  63.10 (27.43)  0.63  Child-rated HRQL   Total  .96  64.79 (20.47)  67.29 (16.95)  63.35 (22.26)  0.93   Pain Hurt  .87  75.51 (21.73)  79.60 (19.78)  73.16 (22.90)  1.34   Pain Impact  .91  55.53 (27.19)  57.86 (23.95)  54.19 (29.00)  0.61   Pain Manage  .80  54.97 (32.86)  58.20 (33.09)  53.13 (32.88)  0.70   Worry I  .87  60.34 (30.98)  60.94 (29.00)  60.00 (32.31)  0.14   Worry II  .56  78.86 (26.56)  83.70 (17.85)  76.39 (29.94)  1.26   Emotions  .76  64.39 (35.90)  70.16 (30.05)  61.14 (38.69)  1.20   Treatment  .82  68.55 (23.66)  74.39 (17.44)  65.26 (26.11)  1.94   Communication I  .80  69.96 (31.53)  65.59 (31.24)  72.42 (31.71)  −0.97   Communication II  .78  50.78 (32.90)  47.85 (31.18)  52.42 (34.01)  −0.62  Note. **p < .01. IQ = Intelligence Quotient; Mod to Sev SCD = moderate to severe sickle cell disease. Data Analysis Approach Analyses were initially calculated to examine descriptive qualities of study variables to identify potential outliers and cases of non-normal distribution. We also evaluated the appropriate measure of central tendency for key variables. An independent samples t-test was conducted to examine differences in mean IQ between assessments that were completed in a consultation room and those that were completed in a transfusion pod to ensure that testing environment did not impact performance. Ratings of disease severity were dichotomized, such that ratings of Very Mild or Mild were recoded as “Mild” and ratings of Moderate, Severe, or Very Severe were recoded as “Moderate to Severe.” We conducted this transformation based on likely phenotypic overlap between patients considered to be Very Mild or Mild (i.e., asymptomatic) and patients considered to have Moderate, Severe, or Very Severe disease (i.e., symptomatic). We further verified the clinical relevance of this approach by examining differences between the Mild and Moderate to Severe groups in the average number of pain crises experienced in the past year and the number of disease-related complications ever experienced (described earlier), in comparison with another potentially relevant split (Group 1: Very Mild, Mild, Moderate; Group 2: Severe, Very Severe). The Mild and Moderate to Severe grouping not only produced a more equitable split in terms of sample size (n = 30 and n = 56, respectively) but also revealed greater differences in pain crises and disease-related complications, t(80) = −3.08, p < .01 and t(83) = −3.01, p < .01. This was in contrast to the Very Mild to Moderate and Severe to Very Severe approach to grouping, which produced a larger discrepancy in the number of participants assigned to each group (n = 67 and n = 19, respectively) and somewhat smaller differences between groups in the number of pain crises and disease-related complications experienced, t(80) = −2.40, p = .02 and t(83) = −2.40, p = .02, respectively. We also examined differences between these groups in their ability to discriminate patients with severe SCD as measured by review of their electronic health record. Again, the Mild and Moderate to Severe split better discriminated patients with severe disease compared with the Very Mild to Mild and Severe to Very Severe split (χ2 = 4.52, p = .05 and χ2 = 3.43, p = .06, respectively). Therefore, we elected to adopt the Mild and Moderate to Severe split for subsequent analyses, as it was associated with a more balanced division of the number of participants in each group, and reveal slightly greater differences in other indicators of disease severity. To evaluate whether SCD severity and cognitive abilities interact to influence caregiver ratings of child HRQL above and beyond their individual main effects, a hierarchical multiple regression was calculated. Before creating an interaction term and computing the regression, independent variables were centered to remove nonessential collinearity. In the first step, caregiver-report of child HRQL was regressed on disease severity and IQ, controlling for the effect of parental education. The interaction term (Disease Severity × IQ) was added to the equation in Step 2. To enrich interpretation of moderation results, post hoc analysis with a one-way analysis of variance (ANOVA) was conducted to examine differences in HRQL between four groups: Mild Disease + Normal IQ, Mild Disease + Low IQ, Moderate to Severe Disease + Normal IQ, and Moderate to Severe Disease + Low IQ, with Normal IQ defined as a standard score of 90 or higher as measured by the WISC-V and Low IQ defined as a standard score of 89 or lower. Group differences were further clarified using the Scheffe test for multiple comparisons. Table II. Descriptive Results for Performance on the WISC-V by Membership in Disease Severity and Intelligence Group   Total sample  Mild SCD   Mod to Sev SCD     Total (n = 86)  Total (n = 30)  IQ > 90(n = 18)  IQ < 89(n = 12)  Total (n = 56)  IQ > 90(n = 30)  IQ < 89(n = 26)  WISC-V Index  M (SD)  M (SD)  M (SD)  M (SD)  M (SD)  M (SD)  M (SD)  Range  Range  Range  Range  Range  Range  Range  FSIQ  91.72 (14.27)  95.53 (12.44)  103.56 (9.30)  83.50 (3.34)  89.68 (14.87)  100.90 (8.38)  75.76 (7.35)  61–128  77–122  92–122  77–87  61–128  91–128  61–87  VCI  95.65 (14.15)  98.20 (13.06)  105.11 (11.63)  87.83 (6.74)  94.25 (14.64)  102.71 (10.70)  83.33 (11.53)  59–127  78–127  89–127  78–100  59–124  86–124  59–103  FRI  95.06 (14.45)  97.90 (14.07)  104.67 (13.14)  87.75 (8.24)  93.48 (14.55)  103.10 (8.79)  81.46 (10.90)  55–131  79–131  79–131  79–106  55–121  85–121  55–100  WMI  95.50 (13.45)  98.80 (10.17)  101.61 (10.57)  94.58 (8.24)  93.73 (14.69)  100.48 (10.32)  85.36 (15.16)  55–125  76–125  79–125  76–110  55–120  82–120  55–112  PSI  87.45 (14.59)  91.83 (11.67)  95.28 (10.97)  86.67 (11.16)  85.11 (15.52)  92.32 (11.93)  76.16 (14.95)  45–119  63–119  77–119  63–105  45–119  66–119  45–103    Total sample  Mild SCD   Mod to Sev SCD     Total (n = 86)  Total (n = 30)  IQ > 90(n = 18)  IQ < 89(n = 12)  Total (n = 56)  IQ > 90(n = 30)  IQ < 89(n = 26)  WISC-V Index  M (SD)  M (SD)  M (SD)  M (SD)  M (SD)  M (SD)  M (SD)  Range  Range  Range  Range  Range  Range  Range  FSIQ  91.72 (14.27)  95.53 (12.44)  103.56 (9.30)  83.50 (3.34)  89.68 (14.87)  100.90 (8.38)  75.76 (7.35)  61–128  77–122  92–122  77–87  61–128  91–128  61–87  VCI  95.65 (14.15)  98.20 (13.06)  105.11 (11.63)  87.83 (6.74)  94.25 (14.64)  102.71 (10.70)  83.33 (11.53)  59–127  78–127  89–127  78–100  59–124  86–124  59–103  FRI  95.06 (14.45)  97.90 (14.07)  104.67 (13.14)  87.75 (8.24)  93.48 (14.55)  103.10 (8.79)  81.46 (10.90)  55–131  79–131  79–131  79–106  55–121  85–121  55–100  WMI  95.50 (13.45)  98.80 (10.17)  101.61 (10.57)  94.58 (8.24)  93.73 (14.69)  100.48 (10.32)  85.36 (15.16)  55–125  76–125  79–125  76–110  55–120  82–120  55–112  PSI  87.45 (14.59)  91.83 (11.67)  95.28 (10.97)  86.67 (11.16)  85.11 (15.52)  92.32 (11.93)  76.16 (14.95)  45–119  63–119  77–119  63–105  45–119  66–119  45–103  Note. FSIQ = Full Scale Intelligence Quotient; VCI = Verbal Comprehension Index; FRI = Fluid Reasoning Index; WMI = Working Memory Index; PSI = Processing Speed Index; Mod to Sev SCD = moderate to severe sickle cell disease. Table II. Descriptive Results for Performance on the WISC-V by Membership in Disease Severity and Intelligence Group   Total sample  Mild SCD   Mod to Sev SCD     Total (n = 86)  Total (n = 30)  IQ > 90(n = 18)  IQ < 89(n = 12)  Total (n = 56)  IQ > 90(n = 30)  IQ < 89(n = 26)  WISC-V Index  M (SD)  M (SD)  M (SD)  M (SD)  M (SD)  M (SD)  M (SD)  Range  Range  Range  Range  Range  Range  Range  FSIQ  91.72 (14.27)  95.53 (12.44)  103.56 (9.30)  83.50 (3.34)  89.68 (14.87)  100.90 (8.38)  75.76 (7.35)  61–128  77–122  92–122  77–87  61–128  91–128  61–87  VCI  95.65 (14.15)  98.20 (13.06)  105.11 (11.63)  87.83 (6.74)  94.25 (14.64)  102.71 (10.70)  83.33 (11.53)  59–127  78–127  89–127  78–100  59–124  86–124  59–103  FRI  95.06 (14.45)  97.90 (14.07)  104.67 (13.14)  87.75 (8.24)  93.48 (14.55)  103.10 (8.79)  81.46 (10.90)  55–131  79–131  79–131  79–106  55–121  85–121  55–100  WMI  95.50 (13.45)  98.80 (10.17)  101.61 (10.57)  94.58 (8.24)  93.73 (14.69)  100.48 (10.32)  85.36 (15.16)  55–125  76–125  79–125  76–110  55–120  82–120  55–112  PSI  87.45 (14.59)  91.83 (11.67)  95.28 (10.97)  86.67 (11.16)  85.11 (15.52)  92.32 (11.93)  76.16 (14.95)  45–119  63–119  77–119  63–105  45–119  66–119  45–103    Total sample  Mild SCD   Mod to Sev SCD     Total (n = 86)  Total (n = 30)  IQ > 90(n = 18)  IQ < 89(n = 12)  Total (n = 56)  IQ > 90(n = 30)  IQ < 89(n = 26)  WISC-V Index  M (SD)  M (SD)  M (SD)  M (SD)  M (SD)  M (SD)  M (SD)  Range  Range  Range  Range  Range  Range  Range  FSIQ  91.72 (14.27)  95.53 (12.44)  103.56 (9.30)  83.50 (3.34)  89.68 (14.87)  100.90 (8.38)  75.76 (7.35)  61–128  77–122  92–122  77–87  61–128  91–128  61–87  VCI  95.65 (14.15)  98.20 (13.06)  105.11 (11.63)  87.83 (6.74)  94.25 (14.64)  102.71 (10.70)  83.33 (11.53)  59–127  78–127  89–127  78–100  59–124  86–124  59–103  FRI  95.06 (14.45)  97.90 (14.07)  104.67 (13.14)  87.75 (8.24)  93.48 (14.55)  103.10 (8.79)  81.46 (10.90)  55–131  79–131  79–131  79–106  55–121  85–121  55–100  WMI  95.50 (13.45)  98.80 (10.17)  101.61 (10.57)  94.58 (8.24)  93.73 (14.69)  100.48 (10.32)  85.36 (15.16)  55–125  76–125  79–125  76–110  55–120  82–120  55–112  PSI  87.45 (14.59)  91.83 (11.67)  95.28 (10.97)  86.67 (11.16)  85.11 (15.52)  92.32 (11.93)  76.16 (14.95)  45–119  63–119  77–119  63–105  45–119  66–119  45–103  Note. FSIQ = Full Scale Intelligence Quotient; VCI = Verbal Comprehension Index; FRI = Fluid Reasoning Index; WMI = Working Memory Index; PSI = Processing Speed Index; Mod to Sev SCD = moderate to severe sickle cell disease. Results Descriptive Results The average IQ for the sample was 91.72 (SD = 14.03) and did not differ regardless of whether the testing was conducted in a consultation room or a transfusion pod, t(84) = 1.07, p = .28. When caregivers were asked to rate the severity of their child’s SCD on a scale ranging from 1 to 5, where higher scores indicated more severe disease, the mean rating was 2.76 (SD = 1.04) and the modal rating was a 3, indicating Moderate severity (n = 37; 43%). Thirty caregivers (35%) described their child’s disease as Very Mild or Mild (“Mild”) and 56 (66%) felt their child’s disease should be categorized as Moderate, Severe, or Very Severe (“Moderate to Severe”). As shown in Table II, children whose parents rated them as having Moderate to Severe SCD obtained lower Full Scale IQ scores on the WISC-V (M = 89.68, SD = 14.87) than children whose parents rated them as having Mild disease (M = 95.53, SD = 12.44); though, this difference was not statistically significant, t(84) = 1.84, p = .07. Of note, as one would expect, there was similar variability in IQ across levels of disease severity. In regard to performance on WISC-V index scores, the two groups only differed on the Processing Speed Index, with children with Moderate to Severe disease scoring significantly lower (M = 85.11, SD = 15.52) than children with Mild disease (M = 91.83, SD = 11.67), t(86) = 2.08, p = .04. Table III. Hierarchical Multiple Regression Testing Moderation of Effect of Disease Severity on Caregiver-Rated Child Health-Related Quality of Life Model  b  SE  β  R2  ΔR2  Step 1        .316  .316**   (Intercept)  76.78  7.15         Parental education  −1.90  1.34  −.13       Disease severity  −9.60**  1.80  −.52       IQ  0.12  0.13  .09      Step 2        .351  .035*   (Intercept)  75.58  7.03         Parental education  −1.91  1.31  −.13       Disease severity  −9.42**  1.76  −.51       IQ  0.15  0.13  .11       Disease severity × IQ  −0.24*  0.12  −.19      Model  b  SE  β  R2  ΔR2  Step 1        .316  .316**   (Intercept)  76.78  7.15         Parental education  −1.90  1.34  −.13       Disease severity  −9.60**  1.80  −.52       IQ  0.12  0.13  .09      Step 2        .351  .035*   (Intercept)  75.58  7.03         Parental education  −1.91  1.31  −.13       Disease severity  −9.42**  1.76  −.51       IQ  0.15  0.13  .11       Disease severity × IQ  −0.24*  0.12  −.19      Note. *p < .05. **p < .01. IQ = Intelligence Quotient. Table III. Hierarchical Multiple Regression Testing Moderation of Effect of Disease Severity on Caregiver-Rated Child Health-Related Quality of Life Model  b  SE  β  R2  ΔR2  Step 1        .316  .316**   (Intercept)  76.78  7.15         Parental education  −1.90  1.34  −.13       Disease severity  −9.60**  1.80  −.52       IQ  0.12  0.13  .09      Step 2        .351  .035*   (Intercept)  75.58  7.03         Parental education  −1.91  1.31  −.13       Disease severity  −9.42**  1.76  −.51       IQ  0.15  0.13  .11       Disease severity × IQ  −0.24*  0.12  −.19      Model  b  SE  β  R2  ΔR2  Step 1        .316  .316**   (Intercept)  76.78  7.15         Parental education  −1.90  1.34  −.13       Disease severity  −9.60**  1.80  −.52       IQ  0.12  0.13  .09      Step 2        .351  .035*   (Intercept)  75.58  7.03         Parental education  −1.91  1.31  −.13       Disease severity  −9.42**  1.76  −.51       IQ  0.15  0.13  .11       Disease severity × IQ  −0.24*  0.12  −.19      Note. *p < .05. **p < .01. IQ = Intelligence Quotient. The mean total score reported by caregivers on the parent proxy form of the PedsQL SCD Module was 66.75 (SD = 19.20), which is consistent with previous reports (Panepinto et al., 2013). Gender, age, and parental education were unrelated to caregiver ratings of child HRQL, t(84) = −.25, p = .80; r = −.03, p = .79; and r = −.10, p = .38, respectively. Caregivers who rated their child’s disease as Moderate to Severe described their child’s HRQL as significantly lower than caregivers who rated their child’s disease as Mild (Table I). Moderation Results The model used in the first step of the hierarchical multiple regression accounted for 32% of the variance in caregiver-rated HRQL (p < .01) (Table III). Disease severity significantly predicted caregiver-rated HRQL (b = −9.60, p < .01), whereas IQ did not significantly influence caregiver-rated HRQL (b = 0.12, p = .38). Specifically, more severe ratings of disease were related to worse caregiver-rated HRQL. When the interaction term was added to the equation in Step 2, the model predicted an additional 4% of variance in caregiver-rated HRQL (p = .04). The interaction between disease severity and IQ significantly predicted HRQL (b = −.24, p = .04). Results supported both a main effect of caregiver-rated SCD severity on caregiver reports of child HRQL and a joint effect of disease severity and IQ on caregiver reports of HRQL. Figure 1 illustrates the interaction effect observed using dichotomized variables for disease severity (Mild or Moderate to Severe) and cognitive abilities (IQ ≥ 90 or IQ ≤ 89). At more severe levels of disease severity, HRQL decreased; however, the effect of disease severity on HRQL was not uniform, as cognitive abilities exerted a stronger influence on HRQL among youth with SCD with Mild disease, compared with those with Moderate to Severe Disease. Youth with Moderate to Severe SCD exhibited similarly low HRQL regardless of IQ. The mean HRQL was higher among youth with Mild SCD, but it was particularly higher for youth who also had an IQ in the Average range or higher. We also examined this interaction analysis using child-reported HRQL as the dependent variable in the regression model; however, the model did not predict significant variance in child-reported HRQL (R2 = .08, p= .08) and no interaction effects were evident (ΔR2 = .01, p = .30; b = .15, p = .30). Figure 1. View largeDownload slide Cognitive abilities moderate the influence of SCD severity on caregiver-rated child HRQL. Figure 1. View largeDownload slide Cognitive abilities moderate the influence of SCD severity on caregiver-rated child HRQL. Post Hoc Analysis In a post hoc analysis, we examined differences in HRQL between the Mild Disease + Normal IQ, Mild Disease + Low IQ, Moderate to Severe Disease + Normal IQ, and Moderate to Severe Disease + Low IQ groups (Table IV). HRQL significantly varied by group classification, F(3, 85) = 8.94, p < .01]. Comparisons using the Scheffe test showed that the mean HRQL for the Mild Disease + Normal IQ group was significantly higher than the mean HRQL for the Mild Disease + Low IQ (p = .03), Moderate to Severe Disease + Normal IQ (p < .01), and Moderate to Severe Disease + Low IQ (p < .01) groups. Significant differences were also observed between groups on the Pain Hurt (p < .01), Pain Impact (p < .01), Pain Manage (p < .01), Treatment (p < .01), and Communication I (p = .03) and II (p = .01) subdomains of the PedsQL SCD Module. Table IV. Results of a One-Way ANOVA Testing for Variability in Caregiver-Rated Child Health-Related Quality of Life by Membership in Disease Severity and Intelligence Group PedsQL SCD Module Domain  Mild SCDIQ ≥ 90(n = 18)  Mild SCDIQ ≤ 89(n = 12)  Mod to Sev SCDIQ ≥ 90(n = 30)  Mod to Sev SCDIQ ≤ 89(n = 26)  F    M (SD)  M (SD)  M (SD)  M (SD)    Caregiver-rated HRQL   Total  84.92 (12.43)  65.12 (18.33)  62.23 (18.80)  60.13 (16.78)  8.94**   Pain Hurt  90.28 (10.53)  77.31 (20.65)  66.48 (17.76)  67.21 (23.25)  7.24**   Pain Impact  79.17 (19.63)  54.58 (31.91)  45.25 (27.26)  45.10 (23.45)  8.12**   Pain Manage  81.94 (18.80)  63.54 (25.81)  55.83 (30.39)  50.96 (28.49)  5.16**   Worry I  80.28 (23.85)  61.25 (27.40)  63.17 (27.05)  63.46 (28.84)  1.97   Worry II  93.06 (16.17)  76.04 (33.05)  75.83 (24.33)  72.12 (32.46)  2.35   Emotions  78.47 (18.09)  59.38 (24.50)  60.42 (30.81)  60.10 (32.41)  1.99   Treatment  88.69 (11.57)  72.02 (19.13)  71.19 (18.85)  63.60 (21.92)  6.52**   Communication I  91.20 (15.78)  70.83 (27.18)  81.11 (22.52)  72.44 (24.81)  3.05*   Communication II  81.48 (19.92)  45.83 (34.91)  61.11 (30.35)  65.38 (24.00)  4.34**  PedsQL SCD Module Domain  Mild SCDIQ ≥ 90(n = 18)  Mild SCDIQ ≤ 89(n = 12)  Mod to Sev SCDIQ ≥ 90(n = 30)  Mod to Sev SCDIQ ≤ 89(n = 26)  F    M (SD)  M (SD)  M (SD)  M (SD)    Caregiver-rated HRQL   Total  84.92 (12.43)  65.12 (18.33)  62.23 (18.80)  60.13 (16.78)  8.94**   Pain Hurt  90.28 (10.53)  77.31 (20.65)  66.48 (17.76)  67.21 (23.25)  7.24**   Pain Impact  79.17 (19.63)  54.58 (31.91)  45.25 (27.26)  45.10 (23.45)  8.12**   Pain Manage  81.94 (18.80)  63.54 (25.81)  55.83 (30.39)  50.96 (28.49)  5.16**   Worry I  80.28 (23.85)  61.25 (27.40)  63.17 (27.05)  63.46 (28.84)  1.97   Worry II  93.06 (16.17)  76.04 (33.05)  75.83 (24.33)  72.12 (32.46)  2.35   Emotions  78.47 (18.09)  59.38 (24.50)  60.42 (30.81)  60.10 (32.41)  1.99   Treatment  88.69 (11.57)  72.02 (19.13)  71.19 (18.85)  63.60 (21.92)  6.52**   Communication I  91.20 (15.78)  70.83 (27.18)  81.11 (22.52)  72.44 (24.81)  3.05*   Communication II  81.48 (19.92)  45.83 (34.91)  61.11 (30.35)  65.38 (24.00)  4.34**  Note. *p < .05. **p < .01. IQ = Intelligence Quotient; Mod to Sev SCD = moderate to severe sickle cell disease. Table IV. Results of a One-Way ANOVA Testing for Variability in Caregiver-Rated Child Health-Related Quality of Life by Membership in Disease Severity and Intelligence Group PedsQL SCD Module Domain  Mild SCDIQ ≥ 90(n = 18)  Mild SCDIQ ≤ 89(n = 12)  Mod to Sev SCDIQ ≥ 90(n = 30)  Mod to Sev SCDIQ ≤ 89(n = 26)  F    M (SD)  M (SD)  M (SD)  M (SD)    Caregiver-rated HRQL   Total  84.92 (12.43)  65.12 (18.33)  62.23 (18.80)  60.13 (16.78)  8.94**   Pain Hurt  90.28 (10.53)  77.31 (20.65)  66.48 (17.76)  67.21 (23.25)  7.24**   Pain Impact  79.17 (19.63)  54.58 (31.91)  45.25 (27.26)  45.10 (23.45)  8.12**   Pain Manage  81.94 (18.80)  63.54 (25.81)  55.83 (30.39)  50.96 (28.49)  5.16**   Worry I  80.28 (23.85)  61.25 (27.40)  63.17 (27.05)  63.46 (28.84)  1.97   Worry II  93.06 (16.17)  76.04 (33.05)  75.83 (24.33)  72.12 (32.46)  2.35   Emotions  78.47 (18.09)  59.38 (24.50)  60.42 (30.81)  60.10 (32.41)  1.99   Treatment  88.69 (11.57)  72.02 (19.13)  71.19 (18.85)  63.60 (21.92)  6.52**   Communication I  91.20 (15.78)  70.83 (27.18)  81.11 (22.52)  72.44 (24.81)  3.05*   Communication II  81.48 (19.92)  45.83 (34.91)  61.11 (30.35)  65.38 (24.00)  4.34**  PedsQL SCD Module Domain  Mild SCDIQ ≥ 90(n = 18)  Mild SCDIQ ≤ 89(n = 12)  Mod to Sev SCDIQ ≥ 90(n = 30)  Mod to Sev SCDIQ ≤ 89(n = 26)  F    M (SD)  M (SD)  M (SD)  M (SD)    Caregiver-rated HRQL   Total  84.92 (12.43)  65.12 (18.33)  62.23 (18.80)  60.13 (16.78)  8.94**   Pain Hurt  90.28 (10.53)  77.31 (20.65)  66.48 (17.76)  67.21 (23.25)  7.24**   Pain Impact  79.17 (19.63)  54.58 (31.91)  45.25 (27.26)  45.10 (23.45)  8.12**   Pain Manage  81.94 (18.80)  63.54 (25.81)  55.83 (30.39)  50.96 (28.49)  5.16**   Worry I  80.28 (23.85)  61.25 (27.40)  63.17 (27.05)  63.46 (28.84)  1.97   Worry II  93.06 (16.17)  76.04 (33.05)  75.83 (24.33)  72.12 (32.46)  2.35   Emotions  78.47 (18.09)  59.38 (24.50)  60.42 (30.81)  60.10 (32.41)  1.99   Treatment  88.69 (11.57)  72.02 (19.13)  71.19 (18.85)  63.60 (21.92)  6.52**   Communication I  91.20 (15.78)  70.83 (27.18)  81.11 (22.52)  72.44 (24.81)  3.05*   Communication II  81.48 (19.92)  45.83 (34.91)  61.11 (30.35)  65.38 (24.00)  4.34**  Note. *p < .05. **p < .01. IQ = Intelligence Quotient; Mod to Sev SCD = moderate to severe sickle cell disease. Discussion We present results from an investigation of caregiver reports of HRQL in children and adolescents with SCD that demonstrates an effect of caregiver-rated disease severity on HRQL, which is moderated by intelligence. As hypothesized, higher ratings of SCD severity significantly predicted lower ratings of HRQL. Contrary to our hypothesis, however, the interactive effect of disease severity and cognitive abilities was such that IQ magnified differences in HRQL among youth with Mild SCD but had little effect on the relationship between disease severity and HRQL among youth with Moderate to Severe SCD. Participants with Mild SCD and an IQ in the Average range or higher exhibited the highest HRQL, though differences between groups primarily centered on pain- and treatment-related subdomains of HRQL rather than psychosocial subdomains. Of note, these relationships were not observed when child-reported HRQL was added to the model as the dependent variable, possibly suggesting that caregivers and children prioritize different events when forming their perceptions of disease burden. Consistent with previous studies, our data suggest that disease severity is associated with caregiver-reported child HRQL, such that as caregivers rated youth as having more severe SCD, they also described their child’s HRQL as lower (Anderson et al., 2015; Barakat et al., 2008; Fisak et al., 2012). This relationship was expected, given previous reports and our initial finding that caregiver ratings of more severe disease were associated with more pain crises in the past 12 months and a greater number of SCD-related complications (e.g., acute chest syndrome, abnormal transcranial Doppler ultrasonography, or silent infarct). It is likely that children with more severe presentations of SCD are at greatest risk for experiencing pain-related burden, activity disruption, and disease-related psychosocial problems. Children with less severe SCD generally seemed to endure a minimal impact on SCD-specific HRQL; however, we also observed that this association varied by cognitive ability. Results supported the hypothesis that cognitive functioning moderates the relationship between SCD severity and HRQL, with SCD severity differentially impacting HRQL depending on cognitive abilities. The interaction term predicted an additional 4% of unique variance in HRQL after controlling for the direct effects of disease severity and IQ. This finding represents a statistically significant effect and, although relatively small, helps to clarify previously unexplained variance in HRQL that could inform assessment and treatment of certain patients. We expected that youth with more severe SCD and a higher IQ would demonstrate significantly better HRQL compared with youth with severe SCD and a lower IQ. We also posited that youth with milder SCD would exhibit relatively high HRQL, with cognitive functioning exerting a minimal influence. Contrary to these expectations, IQ played a more salient role in determining HRQL among youth with Mild SCD compared with those with Moderate to Severe SCD. We initially thought that cognitive abilities would have greater importance in discriminating between youth with severe SCD with high or low HRQL because these youth often have more complex treatment regimens to manage and greater potential for psychosocial distress. Based on our review of the literature, we suspected that patients with higher cognitive abilities would be better equipped to manage certain aspects of their treatment and cope with their disease, thereby buffering the effect of the increased burdens that accompany severe forms of SCD. Instead, cognitive abilities were more salient to determining HRQL among those with less severe SCD and played only a minimal role in youth with more severe SCD. Although this finding needs to be interpreted with caution, one possible explanation is that more severe SCD presentations impose burdens and impairments that may be difficult to mitigate through the use of cognitive strategies alone to enhance treatment adherence or psychological coping. Children with more severe SCD may be exposed to added disease complications (e.g., vasculopathy, silent infarct or stroke, avascular necrosis, or frequent pain crises) with far-reaching effects, possibly leading to additional medical visits (e.g., chronic blood transfusions or visits to the emergency department) or causing academic disruptions, interpersonal and intrafamilial problems, or significant worries about one’s health and future. In these cases, it appears that strong cognitive abilities may not directly compensate for the additional threats severe SCD poses to HRQL. Although our data do not support a direct relationship between intelligence and HRQL in youth with severe SCD, it remains possible that cognitive factors play a role, but perhaps with youth with severe SCD and specific cognitive profiles (e.g., high executive functioning) or other characteristics not measured in this study (e.g., supportive home environment). Future studies should further explore how cognitive abilities modulate health outcomes and quality of life in youth with severe SCD so that interventions to support this vulnerable subgroup can be best tailored. In contrast, cognitive functioning moderated the effect of mild SCD on HRQL, with youth with mild SCD and an average or higher IQ exhibiting significantly higher HRQL than youth with mild SCD and a below average IQ. It seems that youth with mild SCD are not equally spared negative effects of the disease on HRQL, but rather it is those with sufficient cognitive abilities who are protected. We suspected that cognitive abilities could play a role in moderating the effect of SCD severity on HRQL through either enhanced treatment adherence or capacity to cope and adjust to disease-related challenges. As we did not directly assess treatment adherence or coping, we conducted post hoc analyses to examine differences between the Mild SCD + Normal IQ and Mild SCD + Low IQ groups on subdomains of the PedsQL SCD Module. The Mild SCD + Normal IQ group exhibited higher HRQL across all subdomains but differences were only significant for physical symptom and treatment-related subdomains: Pain Hurt, Pain Impact, Pain Manage, Treatment, and Communication I and II. Differences between the Mild SCD + Normal IQ and Mild SCD + Low IQ groups on emotion-related subdomains (Worry I, Worry II, and Emotions) were not significant. This finding suggests high cognitive functioning primarily influences HRQL in youth with milder forms of SCD through effects on disease (e.g., reduced pain and reduced impact of pain on activities) and treatment factors (e.g., enhanced self-management and communication with medical providers). This may reflect the generally straightforward and predictable nature of treatment for children and adolescents with milder forms of SCD, which commonly involves taking one or two daily medications (e.g., hydroxyurea), avoiding triggers of vaso-occlusive crises, and completing recommended screenings for worsening disease (National Heart, Lung, and Blood Institute, 2014). Youth who carefully manage these aspects of their treatment likely experience fewer disease-related complications on average; however, even youth with mild SCD who do not adhere to recommended medications or repeatedly expose themselves to known triggers may experience heightened disease burden. Relatedly, these initial results imply that coping and emotion regulation are not salient pathways through which cognitive abilities moderate the impact of mild SCD on HRQL. Given the established association between weaker cognitive skills and coping difficulties, it was surprising that indicators of coping and emotion regulation were not moderated by cognitive functioning in our sample. Even so, the Communication I and II subscales were significantly predicted by the combination of disease and cognitive factors. Items on the Communication subscales generally ask respondents to indicate the extent to which they feel that others (either medical team members or individuals at large) understand them and the burdens of their disease. Results indicate that caregivers of children with mild disease and lower intellectual functioning have greater concerns that their children feel poorly understood in this regard, both in comparison with those with more severe disease at any cognitive skill level, but especially with those with mild disease and average cognitive abilities. It may be that children with milder SCD and lower cognitive functioning are less effective in communicating to others when they are experiencing pain, discomfort, or other disease-related symptoms, particularly when those symptoms are not obvious to others. However, there is also recent evidence that verbal comprehension skills are associated with secondary control coping in children with SCD (Prussien et al., in press). Specifically, better verbal abilities are associated with better use of coping strategies intended to adapt to a stressor, such as using distraction, positive thinking, or cognitive reappraisal—all approaches that may rely on active “self-talk.” Therefore, it could be that children with weaker cognitive skills in the context of mild disease can adequately regulate emotional responses to disease-related stressors, but are less adept both at secondary control coping and in talking about their disease burden in a way that can be readily understood by others. In contrast, children experiencing symptoms in the context of more severe disease may not have to rely on well-developed verbal skills to communicate their symptoms, as caregivers may be more attuned to, and familiar with, the frequent physical complications of SCD in that child. However, these paths remain unclear and need to be directly and prospectively studied before drawing conclusions regarding the underlying explanation for the role of cognitive functioning in determining HRQL among youth with mild SCD. This study is limited in several ways, including potential sampling bias, reliance on caregiver ratings of disease severity, an assumption that disease severity is static, failure to assess more specific cognitive functions that could better explain observed effects, and absence of direct measurement of pathways through which cognitive functioning affects HRQL. First, as data were derived from a cognitive rehabilitation intervention trial, it is possible that participating patients and caregivers were more interested in enrolling if they had cognitive or academic concerns, thereby biasing the sample and limiting generalizability. However, many families denied cognitive or academic concerns during recruitment but still elected to enroll. Moreover, cognitive abilities were intact for a substantial portion of the sample. Another limitation was that our use of caregivers’ ratings of their child’s SCD severity assumes caregivers are able to accurately assess disease severity and possess similar metrics for estimating severity. We attempted to mitigate the latter concern by applying descriptive labels to the scale and allowing for gradation as caregivers estimated severity by choosing between five choices. Although it is difficult to determine whether caregiver ratings of SCD severity accurately reflect the severity of a child’s disease, there is no universally accepted measure of SCD severity to which our caregiver ratings could be compared. We did, however, attempt to validate these ratings, demonstrating that caregiver perceptions of disease severity were significantly and positively correlated with the number of caregiver-reported pain crises experienced in the last 12 months, the number of caregiver-reported SCD-related complications endured, and disease severity as measured by chart review (i.e., history of cerebral infarction, history of acute chest syndrome, or history of three or more hospitalizations for SCD-related pain in the past 3 years). In the absence of a gold standard for measuring SCD severity, it will be important for future studies to incorporate multiple measures of severity spanning patient, caregiver, and physician reports; documentation of disease complications and healthcare utilization; and biomarkers of severity (e.g., hemoglobin or reticulocytes). Our cross-sectional design also limits interpretations of the findings because it imposed an assumption that SCD severity is fixed, when it actually can vary according to various factors. Future studies should examine SCD severity at multiple time points and explore whether the interactive relationship with cognitive ability that we observed is preserved despite fluctuations in disease severity over time. We relied on IQ as a broad measure of cognitive ability but, given evidence that differences in disease self-management may have partially explained the effect of cognitive abilities, future research should aim to develop a more nuanced understanding of the cognitive factors that affect the relationship between disease severity and HRQL. Although caregiver educational attainment did not significantly affect HRQL in our model, it is possible that other unmeasured socioeconomic or familial factors common among youth with mild disease and normal intelligence played a role in buffering the impact of their disease on HRQL. Finally, we were able to make inferences about the reasons why variability in cognitive functioning led to discrepant HRQL outcomes in youth with mild SCD by examining differences on the PedsQL SCD Module subdomains in post hoc analyses; however, these paths need to be directly assessed. For example, future investigations should explicitly measure adherence to treatment regimens and coping to determine whether either explains the protective nature of high cognitive functioning on HRQL in youth with mild SCD. In summary, results from this study demonstrated that caregiver-rated SCD severity predicts HRQL and this relationship varies by child IQ. Our data suggested that, for youth with more severe forms of SCD, cognitive abilities have a limited role in determining HRQL. However, HRQL in youth with milder forms of SCD does depend on cognitive abilities, with youth with mild SCD and low cognitive abilities exhibiting significantly lower HRQL compared with those with similarly mild disease, but normal or high cognitive abilities. These findings have important clinical implications with regard to identifying an often overlooked subgroup. Children and adolescents perceived to have mild SCD may be followed less closely and assumed to have few limitations imposed on their daily lives. However, our results indicate that youth with mild SCD and low cognitive abilities exhibit low HRQL—similar to youth with more severe SCD. Clinically, providers should monitor disease-related burden across multiple domains of functioning, particularly with youth with SCD who are thought to have milder forms of the disease and, therefore, may be less commonly screened for psychosocial difficulties. Routine cognitive assessment of youth with mild SCD could offer useful information to assist in stratifying patients based on risk for disrupted HRQL and introducing supportive, targeted interventions efficiently. Funding This work was supported by Grant # 2013141 from the Doris Duke Charitable Foundation. Conflicts of interest: None declared. References Allen T. M., Anderson L. M., Rothman J. A., Bonner M. J. ( 2017). 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Psychological outcomes in long-term survivors of childhood brain cancer: A report from the childhood cancer survivor study. J Clin Oncol , 22, 999– 1006. doi: 10.1200/JCO.2004.06.148 Google Scholar CrossRef Search ADS   © The Author(s) 2018. Published by Oxford University Press on behalf of the Society of Pediatric Psychology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Pediatric Psychology Oxford University Press

Cognitive Abilities Moderate the Effect of Disease Severity on Health-Related Quality of Life in Pediatric Sickle Cell Disease

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© The Author(s) 2018. Published by Oxford University Press on behalf of the Society of Pediatric Psychology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com
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10.1093/jpepsy/jsy019
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Abstract

Abstract Objective Complications that can arise from sickle cell disease (SCD) have the potential to negatively affect health-related quality of life (HRQL). SCD manifests in varying degrees of severity, but effects on HRQL are not uniform. Cognitive abilities influence HRQL in other pediatric groups, potentially through variability in treatment adherence and psychological coping. This study examined the effect of SCD severity on HRQL and explored cognitive abilities as a moderator of this relationship. Methods A total of 86 children and adolescents with SCD (ages 7–16 years) completed a cognitive assessment (Wechsler Scale of Intelligence for Children, Fifth Edition), and primary caregivers rated their child’s SCD severity and HRQL (PedsQL Sickle Cell Disease Module). A hierarchical linear regression was conducted to evaluate the interactive effect of SCD severity and cognitive functioning on HRQL. Results Caregiver-rated SCD severity predicted HRQL and cognitive abilities interacted with disease severity to influence HRQL. Youth with milder SCD and cognitive abilities in the average range or higher demonstrated significantly better HRQL compared with youth with mild SCD but below average cognitive abilities. Youth with more severe disease appeared to exhibit similarly low levels of HRQL, with only a minimal influence of cognitive abilities. Conclusions Cognitive factors modify the effect of SCD severity on HRQL, particularly among youth with milder forms of SCD. Future studies are warranted to clarify the role of cognitive abilities in determining HRQL. Clinicians should monitor youth with milder forms of SCD and limited cognitive abilities for worsening HRQL and opportunities to provide support around disease self-management. chronic illness, cognitive assessment, hematology, quality of life, sickle cell disease Sickle cell disease (SCD) is a relatively common genetic disorder affecting approximately 100,000 Americans and occurring in roughly one out of every 365 African-American births (Hassell, 2010). Children with SCD are at increased risk for serious medical complications, such as vaso-occlusive pain crises, acute chest syndrome, and cerebral infarction (Bou-Maroun, Meta, Hanba, Campbell, & Yanik, 2018; DeBaun et al., 2012; Fisak, Belkin, von Lehe, & Bansal, 2012; Kawadler, Clayden, Clark, & Kirkham, 2016; Ohene-Frempong et al., 1998). In addition, a significant number of children with SCD experience cognitive difficulties across multiple domains, and the degree of impairment tends to vary according to disease severity (Berkelhammer et al., 2007; Kral, Brown, & Hynd, 2001; Schatz, Schlenz, Reinman, Smith, & Roberts, 2017). Cognitive deficits in pediatric SCD are thought to manifest through several potential pathways, including low socioeconomic status (King et al., 2014; Schatz, Finke, & Roberts, 2004), low hemoglobin and hematocrit (King et al., 2014; Steen et al., 2003), high cerebral blood flow velocity (Ruffieux et al., 2013), high levels of inflammatory cytokines (Andreotti, King, Macy, Compas, & DeBaun, 2015), and cerebral infarction (Schatz, White, Moinuddin, Armstrong, & DeBaun, 2002). These cognitive deficits have widespread implications that can impose a significant burden on children and families as they cope with day-to-day challenges as well as more severe disease-related events (Palermo, Schwartz, Drotar, & McGowan, 2002). Due to the chronicity of SCD, its impact on health-related quality of life (HRQL) has been a focus of research both describing the impact of the disease on patients and families and quantifying the effects of medical and psychosocial interventions to reduce disease burden. Studies have documented that children with SCD experience lower HRQL compared with healthy peers (Dale, Cochran, Roy, Jernigan, & Buchanan, 2011; Panepinto, O'Mahar, DeBaun, Loberiza, & Scott, 2005), and this difference is observed across multiple domains of HRQL, including physical and psychosocial health as well as school functioning (Dale et al., 2011). Disease severity and related complications are central contributors to HRQL in youth with SCD, with symptoms such as pain and fatigue, in particular, being shown to be robust predictors of HRQL (Anderson, Allen, Thornburg, & Bonner, 2015; Barakat, Patterson, Daniel, & Dampier, 2008; Fisak et al., 2012). Cognitive factors may also affect HRQL in youth with chronic illnesses, either directly or indirectly (Clary, Vander Wal, & Titus, 2010; Sherman, Slick, & Eyrl, 2006). A few studies have explored this relationship specifically in SCD, suggesting that neurobehavioral difficulties are associated with impaired HRQL (Allen, Anderson, Rothman, & Bonner, 2017; McClellan, Schatz, Sanchez, & Roberts, 2008; Panepinto et al., 2005). A recent review highlighted the mounting evidence that disease-related cognitive deficits lead to short- and long-term difficulties across multiple domains of psychosocial functioning in youth with chronic illnesses (Compas, Jaser, Reeslund, Patel, & Yarboi, 2017). Research also supports the inverse; strong cognitive abilities appear to serve a protective role for youth with a chronic illness. For example, higher intelligence is associated with decreased mental and behavioral health problems in children with chronic illnesses (Perrin, Ayoub, & Willett, 1993; Ryland, Lundervold, Elgen, & Hysing, 2010; Taylor, Gibson, & Franck, 2008; Thompson et al., 2003). Although cognitive abilities have been hypothesized to influence HRQL through varied pathways, one path with a particularly strong theoretical and empirical basis is treatment adherence. Treatment adherence is an integral component of chronic disease self-management (DiMatteo, Giordani, Lepper, & Croghan, 2002), and although adherence is dependent on multiple factors, some have suggested that cognitive deficits underlie difficulties with adherence (Brock, Brock, & Thiedke, 2011). For example, higher intelligence and executive functioning have been shown to be associated with better treatment adherence across multiple childhood chronic illnesses (Bagner, Williams, Geffken, Silverstein, & Storch, 2007; Gutiérrez-Colina et al., 2016; Malee et al., 2009; McNally, Rohan, Pendley, Delamater, & Drotar, 2010; O'Hara & Holmbeck, 2013). As a result, the effect of a disease on HRQL may partially hinge on cognitive factors and treatment adherence. A central component of HRQL is the functional impact of one’s illness; however, HRQL also encompasses the emotional toll of a disease (Panepinto et al., 2005). Therefore, HRQL may also be influenced by a child or adolescent’s ability to process and emotionally cope with a chronic illness. In studies of youth with chronic illnesses, evidence suggests that cognitive abilities are salient to the development and management of interpersonal relationships and emotion regulation, both of which have implications for broader psychosocial outcomes (Campbell et al., 2009; Compas & Boyer, 2001; Hocking et al., 2011; Zebrack et al., 2004). One recent study involving youth with SCD demonstrated that stronger verbal skills are related to greater utilization of secondary control coping strategies (e.g., acceptance or cognitive reframing), which leads to reduced depressive symptoms (Prussien et al., in press). Functional neuroimaging also supports this link in a pediatric sample, demonstrating that brain activation in the prefrontal cortex is linked to the utilization of adaptive coping strategies (Robinson et al., 2015). In summary, SCD is a chronic illness with the potential to significantly impact HRQL through pain, fatigue, frequent hospitalizations, and activity limitations. Research supports a direct effect of disease severity on HRQL and also implicates cognitive functioning, which can affect treatment adherence and psychological coping, as playing a role in determining HRQL. As such, it may be more challenging for children with limited cognitive resources to manage the potential physical and emotional toll of a chronic illness, thereby resulting in reduced HRQL. It is unclear, though, whether disease severity exerts a uniformly salient influence on HRQL or whether cognitive factors moderate this relationship, potentially weakening the effect of disease severity at higher or lower levels of cognitive functioning. For instance, it may be that for youth with more severe forms of a disease who are faced with especially complex treatment regimens and who endure greater psychosocial disruption, cognitive abilities play a crucial role in determining the degree to which the disease affects HRQL. Conversely, cognitive abilities may be less important in determining HRQL for children with milder presentations of a disease who have less complex treatment regimens to manage and experience fewer threats to psychosocial functioning. The role of cognitive functioning in affecting patient-reported outcomes, including HRQL, is relatively well documented in pediatric samples, but there is limited research describing this relationship specifically in youth with SCD. One recent study has examined the association between cognitive abilities and HRQL in pediatric SCD (Allen et al., 2017). Allen and colleagues (2017) reported that greater impairments in executive functioning, as measured by a parent-report questionnaire, predicted lower quality of life, but it is unclear whether this association applies to all patients with SCD. Informed by these results and others, we sought a conceptually different approach, aiming to explore cognitive abilities as a moderator of the effect of SCD severity on HRQL. Intelligence was used to measure the impact of cognitive abilities on the relationship between SCD severity and HRQL because children with SCD are known to exhibit cognitive deficits across multiple domains, and previous research suggests multiple aspects of cognition have the potential to affect HRQL. We hypothesized that SCD severity would have an inverse main effect on HRQL but that this relationship would vary by cognitive ability. Specifically, we expected that children with severe SCD and higher cognitive functioning would exhibit better HRQL than children with severe SCD and lower cognitive functioning, whereas HRQL among youth with mild SCD would not vary by cognitive ability. This investigation represented an advancement of the literature on pediatric SCD due to its unique focus on improving understanding of how disease severity can impact quality of life differentially as a function of child cognitive abilities. Moreover, we incorporated a well-validated performance-based measure of cognitive functioning in a large sample of youth with SCD to reliably examine the role of cognitive functioning in determining HRQL. Methods Participants Participants were recruited for a cognitive rehabilitation intervention trial open to patients regardless of history of neurologic sequelae or cognitive difficulties. Only data from a baseline assessment completed before any intervention were used. Inclusion criteria included having a diagnosis of SCD (any genotype), being between 7 and 16 years old, English fluency, and having consistent access to electricity (to charge a borrowed electronic device for the intervention). Patients were excluded if they had a visual, motor, auditory, or cognitive impairment that prevented use of a tablet computer during the intervention phase of the study or if there had been a recent (≤30 days) initiation or dose change of a psychostimulant. We approached 238 patients and families to discuss participation in the study. Of those, 66% (n = 158) expressed interest in participating, whereas 33% (n = 80) declined to participate. Although most patients and families were interested in the study, a sizable portion of interested families never enrolled (n = 67; 42%), commonly citing a lack of time to commit to the research. In all, 91 participants (58% of those who expressed interest) enrolled in the study; all participants completed a baseline cognitive assessment, but data were only used from 86 participants, as a small number of caregivers (5%) failed to complete essential study questionnaires, including ratings of SCD severity and proxy reports of child HRQL (described later). Of note, as the present study is a secondary analysis of data collected in the context of a clinical trial, the hypotheses tested were not powered on an a priori basis. Estimates of effect sizes were included to assist in determining clinical significance. Most participants were female (58%), and the mean age of the participants was 10.37 years (SD = 2.91). Caregivers described their children as primarily African, African-American, or Black (93%). Most participants were diagnosed with HbSS (n = 61, 71%), followed by HbSC (n = 18, 21%), HbS/β0 thalassemia (n = 5, 6%), and HbS/β+ thalassemia (n = 2, 2%). Twenty-five (29%) participants had evidence in their medical chart of a history of cerebral infarction. The mean steady-state hemoglobin was 9.35 mg/dL (SD = 1.52). Just over half of the participants (n = 48; 56%) were being prescribed hydroxyurea at the time of enrollment. Only one participant was taking a stimulant at the time of enrollment. In all, 80% of the cognitive assessments were completed in a private consultation room, with the remaining 20% conducted with patients undergoing chronic blood transfusion in a transfusion pod. Caregivers were generally well educated, with most reporting that they had completed at least some college (n = 59; 67%). Procedures The institutional review board at the authors’ institution approved the research protocol before recruitment. Potential patients were recruited during routine hematology clinic visits or appointments for chronic blood transfusion therapy. Medical providers (e.g., hematologists and nurse practitioners) initially screened patients for eligibility and then research staff met with prospective participants to further evaluate eligibility and provide an introduction to the study. Eligible and interested families scheduled a separate enrollment visit, typically arranged to coincide with the patient’s next hematology visit or blood transfusion, where informed consent and assent were obtained. During the enrollment visit, participants completed study questionnaires and a neurocognitive assessment in a private consultation room or in a transfusion pod with appropriate accommodations made to minimize distractions (e.g., sound machine, drawn curtain, and clustered nursing care to reduce interruptions). Neurocognitive assessments were not conducted if a participant was reporting significant pain (i.e., ≥7 on a 0–10 numerical pain scale), had received an opioid before the assessment, or, if the participant was undergoing a blood transfusion, had received an antihistamine. Trained psychometrists and postdoctoral psychology fellows administered neurocognitive tests. Scores were verified by a licensed psychologist, with discrepancies resolved through consultation between two psychologists. Primary caregivers completed a set of questionnaires using REDCap electronic data capture (Harris et al., 2009). Each participating family received $20 in retail gift cards and reimbursement for parking or public transportation. Measures Demographic, Disease, and Treatment Characteristics Caregivers reported on participants’ age, gender, and race/ethnicity, as well as the primary caregiver’s highest level of educational attainment (less than eighth grade, eighth grade, some high school, high school diploma, some college, college degree, or more than a college degree). A chart review was conducted to determine each participant’s sickle cell genotype, whether there was a history of cerebral infarction, and whether participants were currently prescribed hydroxyurea. Hemoglobin values were extracted if labs had been drawn within 45 days (before or after) of the baseline assessment and the chart review did not reveal any acute health problems or treatment changes that might affect labs (i.e., no inpatient admissions within 21 days of blood draw, no blood transfusions within 60 days, and no change in hydroxyurea dosage within 60 days). Disease Severity Caregivers rated the severity of their child’s SCD as either Very Mild, Mild, Moderate, Severe, or Very Severe, and these responses were coded as 1–5, where higher scores reflected more severe disease. This rating served as the primary measure of disease severity and was used as an independent variable in subsequent analyses. To evaluate the validity of caregiver ratings of disease severity, we also collected data on the number of major pain crises a child had experienced and the presence or absence of several SCD-related complications. Specifically, caregivers reported the number of major pain crises (pain that required contact with a doctor) their child had experienced in the past 12 months. To consider the range of indicators of disease severity that could be assessed, caregivers also reported whether their child had a history of silent infarct, overt stroke, acute chest syndrome, abnormal transcranial Doppler ultrasonography, multiple hospitalizations for pain crises (i.e., more than three or four admissions for pain in a single year), avascular necrosis, hospitalization for at least 4 days in a row because of sickle cell pain, and admission to an intensive care unit. Responses (Yes = 1; No = 0) of equal weighting were summed to produce a general composite of disease severity ranging from 0 to 8, where higher scores reflected more severe disease. Caregiver ratings of disease severity were significantly correlated with both pain crises experienced in the past 12 months and the number of SCD-related complications experienced. Specifically, youth with higher ratings of disease severity also had endured more pain crises over the past year (ρ = .36, p < .01). Similarly, children rated as having more severe SCD also had experienced significantly more disease-related complications (ρ = .37, p < .01). The validity of caregiver ratings of child SCD severity was further explored by examining associations with indicators of disease severity extracted from patients’ electronic health records. Following the procedures outlined by Panepinto and colleagues (2013), children were classified as having severe SCD if their health record contained evidence of them meeting one of the following criteria: (1) known history of cerebral infarction, (2) history of a diagnosis of acute chest syndrome, or (3) documentation of three or more hospitalizations for SCD-related pain (e.g., vaso-occlusive crisis, acute chest, or priapism) in the past 3 years. Caregiver ratings of disease severity were significantly correlated with disease severity as measured by chart review (ρ = .27, p = .01). Cognitive Abilities To estimate overall cognitive abilities, participants completed the Wechsler Intelligence Scale for Children, Fifth Edition (WISC-V), which is a widely used and well-validated assessment of intelligence (Wechsler, 2014). The WISC-V normalization sample was stratified across multiple demographic variables, including race/ethnicity, socioeconomic status, and geography. In addition, original validation studies demonstrated the WISC-V possesses adequate convergent and discriminant validity with several other rigorously developed cognitive, academic, and behavioral measures. The Full Scale Intelligence Quotient (IQ) exhibits excellent test–retest reliability at .96. To minimize burden on research participants, we adopted an abbreviated battery, administering primary subtests from the Verbal Comprehension (i.e., ability to reason verbally and express word knowledge), Fluid Reasoning (i.e., ability to discern relationships visually and to apply rules about conceptual relations), Working Memory (i.e., ability to hold and manipulate visual and auditory information in mind), and Processing Speed (i.e., ability to quickly and accurately process visual information) Indices and then calculating a prorated IQ based on six subtests following procedures described in the WISC-V manual (Wechsler, 2014). Trained psychometrists and postdoctoral psychology fellows administered the WISC-V; scoring was verified by a licensed clinical psychologist. The WISC-V was administered electronically using two iPad Air devices. Estimated IQ served as a moderator variable in analyses. Health-Related Quality of Life Participating children completed the Pediatric Quality of Life Inventory Sickle Cell Disease Module (PedsQL SCD Module), and a primary caregiver completed the parent proxy form of the PedsQL SCD Module to assess the extent of SCD-related problems with pain (Pain Hurt), the impact of pain on daily activities (Pain Impact), pain management (Pain Manage), worrying about general medical complications (Worry I), worrying about specific and severe medical complications (Worry II), feeling mad (Emotions), treatments and disease self-management (Treatment), talking to medical providers (Communication I), and talking with others about SCD (Communication II). Examples of items include: “It is hard for him/her to take care of himself/herself when he/she has pain” and “Worrying he/she might have to stay overnight in the hospital.” Respondents reported the degree to which each item had been a problem over the past month using a 0 (“Never”) to 4 (“Almost Always”) rating scale. Items were reversed-scored and transformed to a 0–100 scale using the recommended conversions (i.e., 0 = 100, 1 = 75, 2 = 50, 3 = 25, and 4 = 0). The Total Score was calculated as the mean score of all items answered, with higher scores reflecting better HRQL. Subdomain scores were computed as the mean score of items in the respective scales, following similar score transformations. Although we report HRQL as described by both raters, caregiver reports were the focus of primary statistical analyses. We elected to focus our investigation on caregiver reports of child HRQL due to the superior psychometric properties of the parent proxy form of the PedsQL SCD Module, the desire to preserve consistency in terms of the reporting source for our independent and dependent variables (i.e., disease severity and HRQL, respectively), and well-described concerns (e.g., potential for limited awareness, social desirability, recall bias) with querying children with cognitive deficits about quality of life (Waters et al., 2009). The parent proxy version of the PedsQL SCD Module has been validated in a geographically diverse sample of parents and caregivers of children with SCD (Panepinto et al., 2005, 2013). In the original validation study, child HRQL as measured by the PedsQL SCD Module parent proxy form was significantly lower for children with severe disease compared with those with mild disease (Panepinto et al., 2013). Moreover, parent-reported HRQL was strongly correlated with reports on the PedsQL 4.0 Generic Core Scales and the PedsQL Multidimensional Fatigue Scale. Panepinto and colleagues (2013) reported that internal consistency of the Total Score for the PedsQL SCD Module parent proxy form is excellent at .97; subdomains also demonstrated acceptable internal consistency, with alphas ranging from .83 (Communication I and Communication II) to .97 (Pain Impact). As shown in Table I, we observed similar reliability coefficients in the present sample, with an alpha of .97 for the Total Score and alphas for subdomains ranging from .79 (communication I) to .96 (Pain Impact). The Total Score, as measured by the parent proxy form of the PedsQL SCD Module, was used as the dependent variable in regression analyses. In regard to reliability for the child-report version of the PedsQL SCD Module, Cronbach’s alpha for the Total Score in our sample was good at .93. However, alphas for the subdomains were generally much lower, ranging from .56 (Worry II) to .91 (Pain Impact). Table I. Reliability of the PedsQL SCD Module, Mean Scores, and Differences Between Mild Disease and Moderate to Severe Disease Groups   Total sample (n = 86)   Mild SCD (n = 30)   Mod to Sev SCD (n = 56)   t  PedsQL SCD Module Domain  α  M (SD)  M (SD)  M (SD)  Caregiver-rated HRQL   Total  .97  66.75 (19.20)  77.00 (17.76)  61.25 (17.76)  3.92**   Pain Hurt  .92  73.20 (20.86)  85.09 (16.38)  66.82 (20.30)  4.24**   Pain Impact  .96  53.60 (28.45)  69.33 (27.61)  45.18 (25.33)  4.08**   Pain Manage  .94  60.90 (29.07)  74.58 (23.32)  53.57 (29.36)  3.39**   Worry I  .91  66.57 (27.50)  72.67 (26.61)  63.30 (27.64)  1.52   Worry II  .80  78.34 (27.68)  86.25 (25.29)  74.11 (28.19)  1.97   Emotions  .87  63.95 (28.85)  70.83 (22.58)  60.27 (31.27)  1.63   Treatment  .84  72.67 (20.42)  82.02 (16.92)  67.67 (20.50)  3.28**   Communication I  .79  79.17 (23.56)  83.06 (23.00)  77.08 (23.80)  1.12   Communication II  .86  64.53 (28.90)  67.22 (31.78)  63.10 (27.43)  0.63  Child-rated HRQL   Total  .96  64.79 (20.47)  67.29 (16.95)  63.35 (22.26)  0.93   Pain Hurt  .87  75.51 (21.73)  79.60 (19.78)  73.16 (22.90)  1.34   Pain Impact  .91  55.53 (27.19)  57.86 (23.95)  54.19 (29.00)  0.61   Pain Manage  .80  54.97 (32.86)  58.20 (33.09)  53.13 (32.88)  0.70   Worry I  .87  60.34 (30.98)  60.94 (29.00)  60.00 (32.31)  0.14   Worry II  .56  78.86 (26.56)  83.70 (17.85)  76.39 (29.94)  1.26   Emotions  .76  64.39 (35.90)  70.16 (30.05)  61.14 (38.69)  1.20   Treatment  .82  68.55 (23.66)  74.39 (17.44)  65.26 (26.11)  1.94   Communication I  .80  69.96 (31.53)  65.59 (31.24)  72.42 (31.71)  −0.97   Communication II  .78  50.78 (32.90)  47.85 (31.18)  52.42 (34.01)  −0.62    Total sample (n = 86)   Mild SCD (n = 30)   Mod to Sev SCD (n = 56)   t  PedsQL SCD Module Domain  α  M (SD)  M (SD)  M (SD)  Caregiver-rated HRQL   Total  .97  66.75 (19.20)  77.00 (17.76)  61.25 (17.76)  3.92**   Pain Hurt  .92  73.20 (20.86)  85.09 (16.38)  66.82 (20.30)  4.24**   Pain Impact  .96  53.60 (28.45)  69.33 (27.61)  45.18 (25.33)  4.08**   Pain Manage  .94  60.90 (29.07)  74.58 (23.32)  53.57 (29.36)  3.39**   Worry I  .91  66.57 (27.50)  72.67 (26.61)  63.30 (27.64)  1.52   Worry II  .80  78.34 (27.68)  86.25 (25.29)  74.11 (28.19)  1.97   Emotions  .87  63.95 (28.85)  70.83 (22.58)  60.27 (31.27)  1.63   Treatment  .84  72.67 (20.42)  82.02 (16.92)  67.67 (20.50)  3.28**   Communication I  .79  79.17 (23.56)  83.06 (23.00)  77.08 (23.80)  1.12   Communication II  .86  64.53 (28.90)  67.22 (31.78)  63.10 (27.43)  0.63  Child-rated HRQL   Total  .96  64.79 (20.47)  67.29 (16.95)  63.35 (22.26)  0.93   Pain Hurt  .87  75.51 (21.73)  79.60 (19.78)  73.16 (22.90)  1.34   Pain Impact  .91  55.53 (27.19)  57.86 (23.95)  54.19 (29.00)  0.61   Pain Manage  .80  54.97 (32.86)  58.20 (33.09)  53.13 (32.88)  0.70   Worry I  .87  60.34 (30.98)  60.94 (29.00)  60.00 (32.31)  0.14   Worry II  .56  78.86 (26.56)  83.70 (17.85)  76.39 (29.94)  1.26   Emotions  .76  64.39 (35.90)  70.16 (30.05)  61.14 (38.69)  1.20   Treatment  .82  68.55 (23.66)  74.39 (17.44)  65.26 (26.11)  1.94   Communication I  .80  69.96 (31.53)  65.59 (31.24)  72.42 (31.71)  −0.97   Communication II  .78  50.78 (32.90)  47.85 (31.18)  52.42 (34.01)  −0.62  Note. **p < .01. IQ = Intelligence Quotient; Mod to Sev SCD = moderate to severe sickle cell disease. Table I. Reliability of the PedsQL SCD Module, Mean Scores, and Differences Between Mild Disease and Moderate to Severe Disease Groups   Total sample (n = 86)   Mild SCD (n = 30)   Mod to Sev SCD (n = 56)   t  PedsQL SCD Module Domain  α  M (SD)  M (SD)  M (SD)  Caregiver-rated HRQL   Total  .97  66.75 (19.20)  77.00 (17.76)  61.25 (17.76)  3.92**   Pain Hurt  .92  73.20 (20.86)  85.09 (16.38)  66.82 (20.30)  4.24**   Pain Impact  .96  53.60 (28.45)  69.33 (27.61)  45.18 (25.33)  4.08**   Pain Manage  .94  60.90 (29.07)  74.58 (23.32)  53.57 (29.36)  3.39**   Worry I  .91  66.57 (27.50)  72.67 (26.61)  63.30 (27.64)  1.52   Worry II  .80  78.34 (27.68)  86.25 (25.29)  74.11 (28.19)  1.97   Emotions  .87  63.95 (28.85)  70.83 (22.58)  60.27 (31.27)  1.63   Treatment  .84  72.67 (20.42)  82.02 (16.92)  67.67 (20.50)  3.28**   Communication I  .79  79.17 (23.56)  83.06 (23.00)  77.08 (23.80)  1.12   Communication II  .86  64.53 (28.90)  67.22 (31.78)  63.10 (27.43)  0.63  Child-rated HRQL   Total  .96  64.79 (20.47)  67.29 (16.95)  63.35 (22.26)  0.93   Pain Hurt  .87  75.51 (21.73)  79.60 (19.78)  73.16 (22.90)  1.34   Pain Impact  .91  55.53 (27.19)  57.86 (23.95)  54.19 (29.00)  0.61   Pain Manage  .80  54.97 (32.86)  58.20 (33.09)  53.13 (32.88)  0.70   Worry I  .87  60.34 (30.98)  60.94 (29.00)  60.00 (32.31)  0.14   Worry II  .56  78.86 (26.56)  83.70 (17.85)  76.39 (29.94)  1.26   Emotions  .76  64.39 (35.90)  70.16 (30.05)  61.14 (38.69)  1.20   Treatment  .82  68.55 (23.66)  74.39 (17.44)  65.26 (26.11)  1.94   Communication I  .80  69.96 (31.53)  65.59 (31.24)  72.42 (31.71)  −0.97   Communication II  .78  50.78 (32.90)  47.85 (31.18)  52.42 (34.01)  −0.62    Total sample (n = 86)   Mild SCD (n = 30)   Mod to Sev SCD (n = 56)   t  PedsQL SCD Module Domain  α  M (SD)  M (SD)  M (SD)  Caregiver-rated HRQL   Total  .97  66.75 (19.20)  77.00 (17.76)  61.25 (17.76)  3.92**   Pain Hurt  .92  73.20 (20.86)  85.09 (16.38)  66.82 (20.30)  4.24**   Pain Impact  .96  53.60 (28.45)  69.33 (27.61)  45.18 (25.33)  4.08**   Pain Manage  .94  60.90 (29.07)  74.58 (23.32)  53.57 (29.36)  3.39**   Worry I  .91  66.57 (27.50)  72.67 (26.61)  63.30 (27.64)  1.52   Worry II  .80  78.34 (27.68)  86.25 (25.29)  74.11 (28.19)  1.97   Emotions  .87  63.95 (28.85)  70.83 (22.58)  60.27 (31.27)  1.63   Treatment  .84  72.67 (20.42)  82.02 (16.92)  67.67 (20.50)  3.28**   Communication I  .79  79.17 (23.56)  83.06 (23.00)  77.08 (23.80)  1.12   Communication II  .86  64.53 (28.90)  67.22 (31.78)  63.10 (27.43)  0.63  Child-rated HRQL   Total  .96  64.79 (20.47)  67.29 (16.95)  63.35 (22.26)  0.93   Pain Hurt  .87  75.51 (21.73)  79.60 (19.78)  73.16 (22.90)  1.34   Pain Impact  .91  55.53 (27.19)  57.86 (23.95)  54.19 (29.00)  0.61   Pain Manage  .80  54.97 (32.86)  58.20 (33.09)  53.13 (32.88)  0.70   Worry I  .87  60.34 (30.98)  60.94 (29.00)  60.00 (32.31)  0.14   Worry II  .56  78.86 (26.56)  83.70 (17.85)  76.39 (29.94)  1.26   Emotions  .76  64.39 (35.90)  70.16 (30.05)  61.14 (38.69)  1.20   Treatment  .82  68.55 (23.66)  74.39 (17.44)  65.26 (26.11)  1.94   Communication I  .80  69.96 (31.53)  65.59 (31.24)  72.42 (31.71)  −0.97   Communication II  .78  50.78 (32.90)  47.85 (31.18)  52.42 (34.01)  −0.62  Note. **p < .01. IQ = Intelligence Quotient; Mod to Sev SCD = moderate to severe sickle cell disease. Data Analysis Approach Analyses were initially calculated to examine descriptive qualities of study variables to identify potential outliers and cases of non-normal distribution. We also evaluated the appropriate measure of central tendency for key variables. An independent samples t-test was conducted to examine differences in mean IQ between assessments that were completed in a consultation room and those that were completed in a transfusion pod to ensure that testing environment did not impact performance. Ratings of disease severity were dichotomized, such that ratings of Very Mild or Mild were recoded as “Mild” and ratings of Moderate, Severe, or Very Severe were recoded as “Moderate to Severe.” We conducted this transformation based on likely phenotypic overlap between patients considered to be Very Mild or Mild (i.e., asymptomatic) and patients considered to have Moderate, Severe, or Very Severe disease (i.e., symptomatic). We further verified the clinical relevance of this approach by examining differences between the Mild and Moderate to Severe groups in the average number of pain crises experienced in the past year and the number of disease-related complications ever experienced (described earlier), in comparison with another potentially relevant split (Group 1: Very Mild, Mild, Moderate; Group 2: Severe, Very Severe). The Mild and Moderate to Severe grouping not only produced a more equitable split in terms of sample size (n = 30 and n = 56, respectively) but also revealed greater differences in pain crises and disease-related complications, t(80) = −3.08, p < .01 and t(83) = −3.01, p < .01. This was in contrast to the Very Mild to Moderate and Severe to Very Severe approach to grouping, which produced a larger discrepancy in the number of participants assigned to each group (n = 67 and n = 19, respectively) and somewhat smaller differences between groups in the number of pain crises and disease-related complications experienced, t(80) = −2.40, p = .02 and t(83) = −2.40, p = .02, respectively. We also examined differences between these groups in their ability to discriminate patients with severe SCD as measured by review of their electronic health record. Again, the Mild and Moderate to Severe split better discriminated patients with severe disease compared with the Very Mild to Mild and Severe to Very Severe split (χ2 = 4.52, p = .05 and χ2 = 3.43, p = .06, respectively). Therefore, we elected to adopt the Mild and Moderate to Severe split for subsequent analyses, as it was associated with a more balanced division of the number of participants in each group, and reveal slightly greater differences in other indicators of disease severity. To evaluate whether SCD severity and cognitive abilities interact to influence caregiver ratings of child HRQL above and beyond their individual main effects, a hierarchical multiple regression was calculated. Before creating an interaction term and computing the regression, independent variables were centered to remove nonessential collinearity. In the first step, caregiver-report of child HRQL was regressed on disease severity and IQ, controlling for the effect of parental education. The interaction term (Disease Severity × IQ) was added to the equation in Step 2. To enrich interpretation of moderation results, post hoc analysis with a one-way analysis of variance (ANOVA) was conducted to examine differences in HRQL between four groups: Mild Disease + Normal IQ, Mild Disease + Low IQ, Moderate to Severe Disease + Normal IQ, and Moderate to Severe Disease + Low IQ, with Normal IQ defined as a standard score of 90 or higher as measured by the WISC-V and Low IQ defined as a standard score of 89 or lower. Group differences were further clarified using the Scheffe test for multiple comparisons. Table II. Descriptive Results for Performance on the WISC-V by Membership in Disease Severity and Intelligence Group   Total sample  Mild SCD   Mod to Sev SCD     Total (n = 86)  Total (n = 30)  IQ > 90(n = 18)  IQ < 89(n = 12)  Total (n = 56)  IQ > 90(n = 30)  IQ < 89(n = 26)  WISC-V Index  M (SD)  M (SD)  M (SD)  M (SD)  M (SD)  M (SD)  M (SD)  Range  Range  Range  Range  Range  Range  Range  FSIQ  91.72 (14.27)  95.53 (12.44)  103.56 (9.30)  83.50 (3.34)  89.68 (14.87)  100.90 (8.38)  75.76 (7.35)  61–128  77–122  92–122  77–87  61–128  91–128  61–87  VCI  95.65 (14.15)  98.20 (13.06)  105.11 (11.63)  87.83 (6.74)  94.25 (14.64)  102.71 (10.70)  83.33 (11.53)  59–127  78–127  89–127  78–100  59–124  86–124  59–103  FRI  95.06 (14.45)  97.90 (14.07)  104.67 (13.14)  87.75 (8.24)  93.48 (14.55)  103.10 (8.79)  81.46 (10.90)  55–131  79–131  79–131  79–106  55–121  85–121  55–100  WMI  95.50 (13.45)  98.80 (10.17)  101.61 (10.57)  94.58 (8.24)  93.73 (14.69)  100.48 (10.32)  85.36 (15.16)  55–125  76–125  79–125  76–110  55–120  82–120  55–112  PSI  87.45 (14.59)  91.83 (11.67)  95.28 (10.97)  86.67 (11.16)  85.11 (15.52)  92.32 (11.93)  76.16 (14.95)  45–119  63–119  77–119  63–105  45–119  66–119  45–103    Total sample  Mild SCD   Mod to Sev SCD     Total (n = 86)  Total (n = 30)  IQ > 90(n = 18)  IQ < 89(n = 12)  Total (n = 56)  IQ > 90(n = 30)  IQ < 89(n = 26)  WISC-V Index  M (SD)  M (SD)  M (SD)  M (SD)  M (SD)  M (SD)  M (SD)  Range  Range  Range  Range  Range  Range  Range  FSIQ  91.72 (14.27)  95.53 (12.44)  103.56 (9.30)  83.50 (3.34)  89.68 (14.87)  100.90 (8.38)  75.76 (7.35)  61–128  77–122  92–122  77–87  61–128  91–128  61–87  VCI  95.65 (14.15)  98.20 (13.06)  105.11 (11.63)  87.83 (6.74)  94.25 (14.64)  102.71 (10.70)  83.33 (11.53)  59–127  78–127  89–127  78–100  59–124  86–124  59–103  FRI  95.06 (14.45)  97.90 (14.07)  104.67 (13.14)  87.75 (8.24)  93.48 (14.55)  103.10 (8.79)  81.46 (10.90)  55–131  79–131  79–131  79–106  55–121  85–121  55–100  WMI  95.50 (13.45)  98.80 (10.17)  101.61 (10.57)  94.58 (8.24)  93.73 (14.69)  100.48 (10.32)  85.36 (15.16)  55–125  76–125  79–125  76–110  55–120  82–120  55–112  PSI  87.45 (14.59)  91.83 (11.67)  95.28 (10.97)  86.67 (11.16)  85.11 (15.52)  92.32 (11.93)  76.16 (14.95)  45–119  63–119  77–119  63–105  45–119  66–119  45–103  Note. FSIQ = Full Scale Intelligence Quotient; VCI = Verbal Comprehension Index; FRI = Fluid Reasoning Index; WMI = Working Memory Index; PSI = Processing Speed Index; Mod to Sev SCD = moderate to severe sickle cell disease. Table II. Descriptive Results for Performance on the WISC-V by Membership in Disease Severity and Intelligence Group   Total sample  Mild SCD   Mod to Sev SCD     Total (n = 86)  Total (n = 30)  IQ > 90(n = 18)  IQ < 89(n = 12)  Total (n = 56)  IQ > 90(n = 30)  IQ < 89(n = 26)  WISC-V Index  M (SD)  M (SD)  M (SD)  M (SD)  M (SD)  M (SD)  M (SD)  Range  Range  Range  Range  Range  Range  Range  FSIQ  91.72 (14.27)  95.53 (12.44)  103.56 (9.30)  83.50 (3.34)  89.68 (14.87)  100.90 (8.38)  75.76 (7.35)  61–128  77–122  92–122  77–87  61–128  91–128  61–87  VCI  95.65 (14.15)  98.20 (13.06)  105.11 (11.63)  87.83 (6.74)  94.25 (14.64)  102.71 (10.70)  83.33 (11.53)  59–127  78–127  89–127  78–100  59–124  86–124  59–103  FRI  95.06 (14.45)  97.90 (14.07)  104.67 (13.14)  87.75 (8.24)  93.48 (14.55)  103.10 (8.79)  81.46 (10.90)  55–131  79–131  79–131  79–106  55–121  85–121  55–100  WMI  95.50 (13.45)  98.80 (10.17)  101.61 (10.57)  94.58 (8.24)  93.73 (14.69)  100.48 (10.32)  85.36 (15.16)  55–125  76–125  79–125  76–110  55–120  82–120  55–112  PSI  87.45 (14.59)  91.83 (11.67)  95.28 (10.97)  86.67 (11.16)  85.11 (15.52)  92.32 (11.93)  76.16 (14.95)  45–119  63–119  77–119  63–105  45–119  66–119  45–103    Total sample  Mild SCD   Mod to Sev SCD     Total (n = 86)  Total (n = 30)  IQ > 90(n = 18)  IQ < 89(n = 12)  Total (n = 56)  IQ > 90(n = 30)  IQ < 89(n = 26)  WISC-V Index  M (SD)  M (SD)  M (SD)  M (SD)  M (SD)  M (SD)  M (SD)  Range  Range  Range  Range  Range  Range  Range  FSIQ  91.72 (14.27)  95.53 (12.44)  103.56 (9.30)  83.50 (3.34)  89.68 (14.87)  100.90 (8.38)  75.76 (7.35)  61–128  77–122  92–122  77–87  61–128  91–128  61–87  VCI  95.65 (14.15)  98.20 (13.06)  105.11 (11.63)  87.83 (6.74)  94.25 (14.64)  102.71 (10.70)  83.33 (11.53)  59–127  78–127  89–127  78–100  59–124  86–124  59–103  FRI  95.06 (14.45)  97.90 (14.07)  104.67 (13.14)  87.75 (8.24)  93.48 (14.55)  103.10 (8.79)  81.46 (10.90)  55–131  79–131  79–131  79–106  55–121  85–121  55–100  WMI  95.50 (13.45)  98.80 (10.17)  101.61 (10.57)  94.58 (8.24)  93.73 (14.69)  100.48 (10.32)  85.36 (15.16)  55–125  76–125  79–125  76–110  55–120  82–120  55–112  PSI  87.45 (14.59)  91.83 (11.67)  95.28 (10.97)  86.67 (11.16)  85.11 (15.52)  92.32 (11.93)  76.16 (14.95)  45–119  63–119  77–119  63–105  45–119  66–119  45–103  Note. FSIQ = Full Scale Intelligence Quotient; VCI = Verbal Comprehension Index; FRI = Fluid Reasoning Index; WMI = Working Memory Index; PSI = Processing Speed Index; Mod to Sev SCD = moderate to severe sickle cell disease. Results Descriptive Results The average IQ for the sample was 91.72 (SD = 14.03) and did not differ regardless of whether the testing was conducted in a consultation room or a transfusion pod, t(84) = 1.07, p = .28. When caregivers were asked to rate the severity of their child’s SCD on a scale ranging from 1 to 5, where higher scores indicated more severe disease, the mean rating was 2.76 (SD = 1.04) and the modal rating was a 3, indicating Moderate severity (n = 37; 43%). Thirty caregivers (35%) described their child’s disease as Very Mild or Mild (“Mild”) and 56 (66%) felt their child’s disease should be categorized as Moderate, Severe, or Very Severe (“Moderate to Severe”). As shown in Table II, children whose parents rated them as having Moderate to Severe SCD obtained lower Full Scale IQ scores on the WISC-V (M = 89.68, SD = 14.87) than children whose parents rated them as having Mild disease (M = 95.53, SD = 12.44); though, this difference was not statistically significant, t(84) = 1.84, p = .07. Of note, as one would expect, there was similar variability in IQ across levels of disease severity. In regard to performance on WISC-V index scores, the two groups only differed on the Processing Speed Index, with children with Moderate to Severe disease scoring significantly lower (M = 85.11, SD = 15.52) than children with Mild disease (M = 91.83, SD = 11.67), t(86) = 2.08, p = .04. Table III. Hierarchical Multiple Regression Testing Moderation of Effect of Disease Severity on Caregiver-Rated Child Health-Related Quality of Life Model  b  SE  β  R2  ΔR2  Step 1        .316  .316**   (Intercept)  76.78  7.15         Parental education  −1.90  1.34  −.13       Disease severity  −9.60**  1.80  −.52       IQ  0.12  0.13  .09      Step 2        .351  .035*   (Intercept)  75.58  7.03         Parental education  −1.91  1.31  −.13       Disease severity  −9.42**  1.76  −.51       IQ  0.15  0.13  .11       Disease severity × IQ  −0.24*  0.12  −.19      Model  b  SE  β  R2  ΔR2  Step 1        .316  .316**   (Intercept)  76.78  7.15         Parental education  −1.90  1.34  −.13       Disease severity  −9.60**  1.80  −.52       IQ  0.12  0.13  .09      Step 2        .351  .035*   (Intercept)  75.58  7.03         Parental education  −1.91  1.31  −.13       Disease severity  −9.42**  1.76  −.51       IQ  0.15  0.13  .11       Disease severity × IQ  −0.24*  0.12  −.19      Note. *p < .05. **p < .01. IQ = Intelligence Quotient. Table III. Hierarchical Multiple Regression Testing Moderation of Effect of Disease Severity on Caregiver-Rated Child Health-Related Quality of Life Model  b  SE  β  R2  ΔR2  Step 1        .316  .316**   (Intercept)  76.78  7.15         Parental education  −1.90  1.34  −.13       Disease severity  −9.60**  1.80  −.52       IQ  0.12  0.13  .09      Step 2        .351  .035*   (Intercept)  75.58  7.03         Parental education  −1.91  1.31  −.13       Disease severity  −9.42**  1.76  −.51       IQ  0.15  0.13  .11       Disease severity × IQ  −0.24*  0.12  −.19      Model  b  SE  β  R2  ΔR2  Step 1        .316  .316**   (Intercept)  76.78  7.15         Parental education  −1.90  1.34  −.13       Disease severity  −9.60**  1.80  −.52       IQ  0.12  0.13  .09      Step 2        .351  .035*   (Intercept)  75.58  7.03         Parental education  −1.91  1.31  −.13       Disease severity  −9.42**  1.76  −.51       IQ  0.15  0.13  .11       Disease severity × IQ  −0.24*  0.12  −.19      Note. *p < .05. **p < .01. IQ = Intelligence Quotient. The mean total score reported by caregivers on the parent proxy form of the PedsQL SCD Module was 66.75 (SD = 19.20), which is consistent with previous reports (Panepinto et al., 2013). Gender, age, and parental education were unrelated to caregiver ratings of child HRQL, t(84) = −.25, p = .80; r = −.03, p = .79; and r = −.10, p = .38, respectively. Caregivers who rated their child’s disease as Moderate to Severe described their child’s HRQL as significantly lower than caregivers who rated their child’s disease as Mild (Table I). Moderation Results The model used in the first step of the hierarchical multiple regression accounted for 32% of the variance in caregiver-rated HRQL (p < .01) (Table III). Disease severity significantly predicted caregiver-rated HRQL (b = −9.60, p < .01), whereas IQ did not significantly influence caregiver-rated HRQL (b = 0.12, p = .38). Specifically, more severe ratings of disease were related to worse caregiver-rated HRQL. When the interaction term was added to the equation in Step 2, the model predicted an additional 4% of variance in caregiver-rated HRQL (p = .04). The interaction between disease severity and IQ significantly predicted HRQL (b = −.24, p = .04). Results supported both a main effect of caregiver-rated SCD severity on caregiver reports of child HRQL and a joint effect of disease severity and IQ on caregiver reports of HRQL. Figure 1 illustrates the interaction effect observed using dichotomized variables for disease severity (Mild or Moderate to Severe) and cognitive abilities (IQ ≥ 90 or IQ ≤ 89). At more severe levels of disease severity, HRQL decreased; however, the effect of disease severity on HRQL was not uniform, as cognitive abilities exerted a stronger influence on HRQL among youth with SCD with Mild disease, compared with those with Moderate to Severe Disease. Youth with Moderate to Severe SCD exhibited similarly low HRQL regardless of IQ. The mean HRQL was higher among youth with Mild SCD, but it was particularly higher for youth who also had an IQ in the Average range or higher. We also examined this interaction analysis using child-reported HRQL as the dependent variable in the regression model; however, the model did not predict significant variance in child-reported HRQL (R2 = .08, p= .08) and no interaction effects were evident (ΔR2 = .01, p = .30; b = .15, p = .30). Figure 1. View largeDownload slide Cognitive abilities moderate the influence of SCD severity on caregiver-rated child HRQL. Figure 1. View largeDownload slide Cognitive abilities moderate the influence of SCD severity on caregiver-rated child HRQL. Post Hoc Analysis In a post hoc analysis, we examined differences in HRQL between the Mild Disease + Normal IQ, Mild Disease + Low IQ, Moderate to Severe Disease + Normal IQ, and Moderate to Severe Disease + Low IQ groups (Table IV). HRQL significantly varied by group classification, F(3, 85) = 8.94, p < .01]. Comparisons using the Scheffe test showed that the mean HRQL for the Mild Disease + Normal IQ group was significantly higher than the mean HRQL for the Mild Disease + Low IQ (p = .03), Moderate to Severe Disease + Normal IQ (p < .01), and Moderate to Severe Disease + Low IQ (p < .01) groups. Significant differences were also observed between groups on the Pain Hurt (p < .01), Pain Impact (p < .01), Pain Manage (p < .01), Treatment (p < .01), and Communication I (p = .03) and II (p = .01) subdomains of the PedsQL SCD Module. Table IV. Results of a One-Way ANOVA Testing for Variability in Caregiver-Rated Child Health-Related Quality of Life by Membership in Disease Severity and Intelligence Group PedsQL SCD Module Domain  Mild SCDIQ ≥ 90(n = 18)  Mild SCDIQ ≤ 89(n = 12)  Mod to Sev SCDIQ ≥ 90(n = 30)  Mod to Sev SCDIQ ≤ 89(n = 26)  F    M (SD)  M (SD)  M (SD)  M (SD)    Caregiver-rated HRQL   Total  84.92 (12.43)  65.12 (18.33)  62.23 (18.80)  60.13 (16.78)  8.94**   Pain Hurt  90.28 (10.53)  77.31 (20.65)  66.48 (17.76)  67.21 (23.25)  7.24**   Pain Impact  79.17 (19.63)  54.58 (31.91)  45.25 (27.26)  45.10 (23.45)  8.12**   Pain Manage  81.94 (18.80)  63.54 (25.81)  55.83 (30.39)  50.96 (28.49)  5.16**   Worry I  80.28 (23.85)  61.25 (27.40)  63.17 (27.05)  63.46 (28.84)  1.97   Worry II  93.06 (16.17)  76.04 (33.05)  75.83 (24.33)  72.12 (32.46)  2.35   Emotions  78.47 (18.09)  59.38 (24.50)  60.42 (30.81)  60.10 (32.41)  1.99   Treatment  88.69 (11.57)  72.02 (19.13)  71.19 (18.85)  63.60 (21.92)  6.52**   Communication I  91.20 (15.78)  70.83 (27.18)  81.11 (22.52)  72.44 (24.81)  3.05*   Communication II  81.48 (19.92)  45.83 (34.91)  61.11 (30.35)  65.38 (24.00)  4.34**  PedsQL SCD Module Domain  Mild SCDIQ ≥ 90(n = 18)  Mild SCDIQ ≤ 89(n = 12)  Mod to Sev SCDIQ ≥ 90(n = 30)  Mod to Sev SCDIQ ≤ 89(n = 26)  F    M (SD)  M (SD)  M (SD)  M (SD)    Caregiver-rated HRQL   Total  84.92 (12.43)  65.12 (18.33)  62.23 (18.80)  60.13 (16.78)  8.94**   Pain Hurt  90.28 (10.53)  77.31 (20.65)  66.48 (17.76)  67.21 (23.25)  7.24**   Pain Impact  79.17 (19.63)  54.58 (31.91)  45.25 (27.26)  45.10 (23.45)  8.12**   Pain Manage  81.94 (18.80)  63.54 (25.81)  55.83 (30.39)  50.96 (28.49)  5.16**   Worry I  80.28 (23.85)  61.25 (27.40)  63.17 (27.05)  63.46 (28.84)  1.97   Worry II  93.06 (16.17)  76.04 (33.05)  75.83 (24.33)  72.12 (32.46)  2.35   Emotions  78.47 (18.09)  59.38 (24.50)  60.42 (30.81)  60.10 (32.41)  1.99   Treatment  88.69 (11.57)  72.02 (19.13)  71.19 (18.85)  63.60 (21.92)  6.52**   Communication I  91.20 (15.78)  70.83 (27.18)  81.11 (22.52)  72.44 (24.81)  3.05*   Communication II  81.48 (19.92)  45.83 (34.91)  61.11 (30.35)  65.38 (24.00)  4.34**  Note. *p < .05. **p < .01. IQ = Intelligence Quotient; Mod to Sev SCD = moderate to severe sickle cell disease. Table IV. Results of a One-Way ANOVA Testing for Variability in Caregiver-Rated Child Health-Related Quality of Life by Membership in Disease Severity and Intelligence Group PedsQL SCD Module Domain  Mild SCDIQ ≥ 90(n = 18)  Mild SCDIQ ≤ 89(n = 12)  Mod to Sev SCDIQ ≥ 90(n = 30)  Mod to Sev SCDIQ ≤ 89(n = 26)  F    M (SD)  M (SD)  M (SD)  M (SD)    Caregiver-rated HRQL   Total  84.92 (12.43)  65.12 (18.33)  62.23 (18.80)  60.13 (16.78)  8.94**   Pain Hurt  90.28 (10.53)  77.31 (20.65)  66.48 (17.76)  67.21 (23.25)  7.24**   Pain Impact  79.17 (19.63)  54.58 (31.91)  45.25 (27.26)  45.10 (23.45)  8.12**   Pain Manage  81.94 (18.80)  63.54 (25.81)  55.83 (30.39)  50.96 (28.49)  5.16**   Worry I  80.28 (23.85)  61.25 (27.40)  63.17 (27.05)  63.46 (28.84)  1.97   Worry II  93.06 (16.17)  76.04 (33.05)  75.83 (24.33)  72.12 (32.46)  2.35   Emotions  78.47 (18.09)  59.38 (24.50)  60.42 (30.81)  60.10 (32.41)  1.99   Treatment  88.69 (11.57)  72.02 (19.13)  71.19 (18.85)  63.60 (21.92)  6.52**   Communication I  91.20 (15.78)  70.83 (27.18)  81.11 (22.52)  72.44 (24.81)  3.05*   Communication II  81.48 (19.92)  45.83 (34.91)  61.11 (30.35)  65.38 (24.00)  4.34**  PedsQL SCD Module Domain  Mild SCDIQ ≥ 90(n = 18)  Mild SCDIQ ≤ 89(n = 12)  Mod to Sev SCDIQ ≥ 90(n = 30)  Mod to Sev SCDIQ ≤ 89(n = 26)  F    M (SD)  M (SD)  M (SD)  M (SD)    Caregiver-rated HRQL   Total  84.92 (12.43)  65.12 (18.33)  62.23 (18.80)  60.13 (16.78)  8.94**   Pain Hurt  90.28 (10.53)  77.31 (20.65)  66.48 (17.76)  67.21 (23.25)  7.24**   Pain Impact  79.17 (19.63)  54.58 (31.91)  45.25 (27.26)  45.10 (23.45)  8.12**   Pain Manage  81.94 (18.80)  63.54 (25.81)  55.83 (30.39)  50.96 (28.49)  5.16**   Worry I  80.28 (23.85)  61.25 (27.40)  63.17 (27.05)  63.46 (28.84)  1.97   Worry II  93.06 (16.17)  76.04 (33.05)  75.83 (24.33)  72.12 (32.46)  2.35   Emotions  78.47 (18.09)  59.38 (24.50)  60.42 (30.81)  60.10 (32.41)  1.99   Treatment  88.69 (11.57)  72.02 (19.13)  71.19 (18.85)  63.60 (21.92)  6.52**   Communication I  91.20 (15.78)  70.83 (27.18)  81.11 (22.52)  72.44 (24.81)  3.05*   Communication II  81.48 (19.92)  45.83 (34.91)  61.11 (30.35)  65.38 (24.00)  4.34**  Note. *p < .05. **p < .01. IQ = Intelligence Quotient; Mod to Sev SCD = moderate to severe sickle cell disease. Discussion We present results from an investigation of caregiver reports of HRQL in children and adolescents with SCD that demonstrates an effect of caregiver-rated disease severity on HRQL, which is moderated by intelligence. As hypothesized, higher ratings of SCD severity significantly predicted lower ratings of HRQL. Contrary to our hypothesis, however, the interactive effect of disease severity and cognitive abilities was such that IQ magnified differences in HRQL among youth with Mild SCD but had little effect on the relationship between disease severity and HRQL among youth with Moderate to Severe SCD. Participants with Mild SCD and an IQ in the Average range or higher exhibited the highest HRQL, though differences between groups primarily centered on pain- and treatment-related subdomains of HRQL rather than psychosocial subdomains. Of note, these relationships were not observed when child-reported HRQL was added to the model as the dependent variable, possibly suggesting that caregivers and children prioritize different events when forming their perceptions of disease burden. Consistent with previous studies, our data suggest that disease severity is associated with caregiver-reported child HRQL, such that as caregivers rated youth as having more severe SCD, they also described their child’s HRQL as lower (Anderson et al., 2015; Barakat et al., 2008; Fisak et al., 2012). This relationship was expected, given previous reports and our initial finding that caregiver ratings of more severe disease were associated with more pain crises in the past 12 months and a greater number of SCD-related complications (e.g., acute chest syndrome, abnormal transcranial Doppler ultrasonography, or silent infarct). It is likely that children with more severe presentations of SCD are at greatest risk for experiencing pain-related burden, activity disruption, and disease-related psychosocial problems. Children with less severe SCD generally seemed to endure a minimal impact on SCD-specific HRQL; however, we also observed that this association varied by cognitive ability. Results supported the hypothesis that cognitive functioning moderates the relationship between SCD severity and HRQL, with SCD severity differentially impacting HRQL depending on cognitive abilities. The interaction term predicted an additional 4% of unique variance in HRQL after controlling for the direct effects of disease severity and IQ. This finding represents a statistically significant effect and, although relatively small, helps to clarify previously unexplained variance in HRQL that could inform assessment and treatment of certain patients. We expected that youth with more severe SCD and a higher IQ would demonstrate significantly better HRQL compared with youth with severe SCD and a lower IQ. We also posited that youth with milder SCD would exhibit relatively high HRQL, with cognitive functioning exerting a minimal influence. Contrary to these expectations, IQ played a more salient role in determining HRQL among youth with Mild SCD compared with those with Moderate to Severe SCD. We initially thought that cognitive abilities would have greater importance in discriminating between youth with severe SCD with high or low HRQL because these youth often have more complex treatment regimens to manage and greater potential for psychosocial distress. Based on our review of the literature, we suspected that patients with higher cognitive abilities would be better equipped to manage certain aspects of their treatment and cope with their disease, thereby buffering the effect of the increased burdens that accompany severe forms of SCD. Instead, cognitive abilities were more salient to determining HRQL among those with less severe SCD and played only a minimal role in youth with more severe SCD. Although this finding needs to be interpreted with caution, one possible explanation is that more severe SCD presentations impose burdens and impairments that may be difficult to mitigate through the use of cognitive strategies alone to enhance treatment adherence or psychological coping. Children with more severe SCD may be exposed to added disease complications (e.g., vasculopathy, silent infarct or stroke, avascular necrosis, or frequent pain crises) with far-reaching effects, possibly leading to additional medical visits (e.g., chronic blood transfusions or visits to the emergency department) or causing academic disruptions, interpersonal and intrafamilial problems, or significant worries about one’s health and future. In these cases, it appears that strong cognitive abilities may not directly compensate for the additional threats severe SCD poses to HRQL. Although our data do not support a direct relationship between intelligence and HRQL in youth with severe SCD, it remains possible that cognitive factors play a role, but perhaps with youth with severe SCD and specific cognitive profiles (e.g., high executive functioning) or other characteristics not measured in this study (e.g., supportive home environment). Future studies should further explore how cognitive abilities modulate health outcomes and quality of life in youth with severe SCD so that interventions to support this vulnerable subgroup can be best tailored. In contrast, cognitive functioning moderated the effect of mild SCD on HRQL, with youth with mild SCD and an average or higher IQ exhibiting significantly higher HRQL than youth with mild SCD and a below average IQ. It seems that youth with mild SCD are not equally spared negative effects of the disease on HRQL, but rather it is those with sufficient cognitive abilities who are protected. We suspected that cognitive abilities could play a role in moderating the effect of SCD severity on HRQL through either enhanced treatment adherence or capacity to cope and adjust to disease-related challenges. As we did not directly assess treatment adherence or coping, we conducted post hoc analyses to examine differences between the Mild SCD + Normal IQ and Mild SCD + Low IQ groups on subdomains of the PedsQL SCD Module. The Mild SCD + Normal IQ group exhibited higher HRQL across all subdomains but differences were only significant for physical symptom and treatment-related subdomains: Pain Hurt, Pain Impact, Pain Manage, Treatment, and Communication I and II. Differences between the Mild SCD + Normal IQ and Mild SCD + Low IQ groups on emotion-related subdomains (Worry I, Worry II, and Emotions) were not significant. This finding suggests high cognitive functioning primarily influences HRQL in youth with milder forms of SCD through effects on disease (e.g., reduced pain and reduced impact of pain on activities) and treatment factors (e.g., enhanced self-management and communication with medical providers). This may reflect the generally straightforward and predictable nature of treatment for children and adolescents with milder forms of SCD, which commonly involves taking one or two daily medications (e.g., hydroxyurea), avoiding triggers of vaso-occlusive crises, and completing recommended screenings for worsening disease (National Heart, Lung, and Blood Institute, 2014). Youth who carefully manage these aspects of their treatment likely experience fewer disease-related complications on average; however, even youth with mild SCD who do not adhere to recommended medications or repeatedly expose themselves to known triggers may experience heightened disease burden. Relatedly, these initial results imply that coping and emotion regulation are not salient pathways through which cognitive abilities moderate the impact of mild SCD on HRQL. Given the established association between weaker cognitive skills and coping difficulties, it was surprising that indicators of coping and emotion regulation were not moderated by cognitive functioning in our sample. Even so, the Communication I and II subscales were significantly predicted by the combination of disease and cognitive factors. Items on the Communication subscales generally ask respondents to indicate the extent to which they feel that others (either medical team members or individuals at large) understand them and the burdens of their disease. Results indicate that caregivers of children with mild disease and lower intellectual functioning have greater concerns that their children feel poorly understood in this regard, both in comparison with those with more severe disease at any cognitive skill level, but especially with those with mild disease and average cognitive abilities. It may be that children with milder SCD and lower cognitive functioning are less effective in communicating to others when they are experiencing pain, discomfort, or other disease-related symptoms, particularly when those symptoms are not obvious to others. However, there is also recent evidence that verbal comprehension skills are associated with secondary control coping in children with SCD (Prussien et al., in press). Specifically, better verbal abilities are associated with better use of coping strategies intended to adapt to a stressor, such as using distraction, positive thinking, or cognitive reappraisal—all approaches that may rely on active “self-talk.” Therefore, it could be that children with weaker cognitive skills in the context of mild disease can adequately regulate emotional responses to disease-related stressors, but are less adept both at secondary control coping and in talking about their disease burden in a way that can be readily understood by others. In contrast, children experiencing symptoms in the context of more severe disease may not have to rely on well-developed verbal skills to communicate their symptoms, as caregivers may be more attuned to, and familiar with, the frequent physical complications of SCD in that child. However, these paths remain unclear and need to be directly and prospectively studied before drawing conclusions regarding the underlying explanation for the role of cognitive functioning in determining HRQL among youth with mild SCD. This study is limited in several ways, including potential sampling bias, reliance on caregiver ratings of disease severity, an assumption that disease severity is static, failure to assess more specific cognitive functions that could better explain observed effects, and absence of direct measurement of pathways through which cognitive functioning affects HRQL. First, as data were derived from a cognitive rehabilitation intervention trial, it is possible that participating patients and caregivers were more interested in enrolling if they had cognitive or academic concerns, thereby biasing the sample and limiting generalizability. However, many families denied cognitive or academic concerns during recruitment but still elected to enroll. Moreover, cognitive abilities were intact for a substantial portion of the sample. Another limitation was that our use of caregivers’ ratings of their child’s SCD severity assumes caregivers are able to accurately assess disease severity and possess similar metrics for estimating severity. We attempted to mitigate the latter concern by applying descriptive labels to the scale and allowing for gradation as caregivers estimated severity by choosing between five choices. Although it is difficult to determine whether caregiver ratings of SCD severity accurately reflect the severity of a child’s disease, there is no universally accepted measure of SCD severity to which our caregiver ratings could be compared. We did, however, attempt to validate these ratings, demonstrating that caregiver perceptions of disease severity were significantly and positively correlated with the number of caregiver-reported pain crises experienced in the last 12 months, the number of caregiver-reported SCD-related complications endured, and disease severity as measured by chart review (i.e., history of cerebral infarction, history of acute chest syndrome, or history of three or more hospitalizations for SCD-related pain in the past 3 years). In the absence of a gold standard for measuring SCD severity, it will be important for future studies to incorporate multiple measures of severity spanning patient, caregiver, and physician reports; documentation of disease complications and healthcare utilization; and biomarkers of severity (e.g., hemoglobin or reticulocytes). Our cross-sectional design also limits interpretations of the findings because it imposed an assumption that SCD severity is fixed, when it actually can vary according to various factors. Future studies should examine SCD severity at multiple time points and explore whether the interactive relationship with cognitive ability that we observed is preserved despite fluctuations in disease severity over time. We relied on IQ as a broad measure of cognitive ability but, given evidence that differences in disease self-management may have partially explained the effect of cognitive abilities, future research should aim to develop a more nuanced understanding of the cognitive factors that affect the relationship between disease severity and HRQL. Although caregiver educational attainment did not significantly affect HRQL in our model, it is possible that other unmeasured socioeconomic or familial factors common among youth with mild disease and normal intelligence played a role in buffering the impact of their disease on HRQL. Finally, we were able to make inferences about the reasons why variability in cognitive functioning led to discrepant HRQL outcomes in youth with mild SCD by examining differences on the PedsQL SCD Module subdomains in post hoc analyses; however, these paths need to be directly assessed. For example, future investigations should explicitly measure adherence to treatment regimens and coping to determine whether either explains the protective nature of high cognitive functioning on HRQL in youth with mild SCD. In summary, results from this study demonstrated that caregiver-rated SCD severity predicts HRQL and this relationship varies by child IQ. Our data suggested that, for youth with more severe forms of SCD, cognitive abilities have a limited role in determining HRQL. However, HRQL in youth with milder forms of SCD does depend on cognitive abilities, with youth with mild SCD and low cognitive abilities exhibiting significantly lower HRQL compared with those with similarly mild disease, but normal or high cognitive abilities. These findings have important clinical implications with regard to identifying an often overlooked subgroup. Children and adolescents perceived to have mild SCD may be followed less closely and assumed to have few limitations imposed on their daily lives. However, our results indicate that youth with mild SCD and low cognitive abilities exhibit low HRQL—similar to youth with more severe SCD. Clinically, providers should monitor disease-related burden across multiple domains of functioning, particularly with youth with SCD who are thought to have milder forms of the disease and, therefore, may be less commonly screened for psychosocial difficulties. Routine cognitive assessment of youth with mild SCD could offer useful information to assist in stratifying patients based on risk for disrupted HRQL and introducing supportive, targeted interventions efficiently. Funding This work was supported by Grant # 2013141 from the Doris Duke Charitable Foundation. Conflicts of interest: None declared. References Allen T. M., Anderson L. M., Rothman J. A., Bonner M. J. ( 2017). 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Journal of Pediatric PsychologyOxford University Press

Published: Apr 6, 2018

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