Introduction: The Common Sense Model (CSM) posits that Illness Representations (IRs) are a patient's beliefs and expectations about an illness and that IRs guide health behavior (Leventhal, Brissette, & Leventhal, 2003). This study aimed to examine possible links between youth asthma IRs and disease-related outcomes ( controller medication adherence, asthma control, and lung function) in a sample of black and Latino youth with asthma. Caregiver IRs were also included to examine possible relationships between family-level characteristics and asthma outcomes.
Methods: Black and/or Latino adolescent-caregiver dyads (N=104) were recruited in the Bronx, New York. All children had asthma and a recent controller medication prescription. CSM belief domains were used to guide analyses for associations between asthma IRs and outcomes. For example, a Timeline subscale included beliefs about the expected duration of asthma and whether it is chronic or episodic in nature. Discrepancies between caregiver and child beliefs were also examined ( e.g. discrepancy Timeline IRs ). Measures included: Asthma Illness Representation Scale for Children (C-AIRS); No Symptoms, No Asthma Belief Scale (No Sx); Asthma Control Test (C-ACT and ACT); and the Medication Adherence Report Scale for Asthma (MARS-A). Primary analyses examined relationships between child asthma outcomes with: ( 1) child IRs, (2) caregiver IRs, and (3) child-caregiver discrepancy IRs.
Results: Child participants were balanced in gender (52.9% male) and race/ethnicity (55.8% Latino) with a mean age of 13 years. Caregivers were primarily female (92.3%) with a mean age of 41.5 years. ( 1) Child IRs were not significantly associated with child asthma outcomes. This was true for main effects, moderation analyses, and indirect effects (mediation analyses). (2) Child age moderated the relationship between caregiver IRs and child asthma control on: a) average IRs (F(5, 98) = 10.39,p < .001, R2 = .347), and b) a Timeline subscale (F(4, 99) = 14.02, p < .001, R2 = .362). Surprisingly, these relationships were in the opposite direction of hypotheses. For example, for younger children (b = 0.970) asthma control was worse with caregivers who had professional model IRs ( e.g. asthma is chronic), but better with lay model caregiver IRs (e.g. asthma is acute/episodic). (3) Child-caregiver IR discrepancy was significantly associated with medication adherence (F(3, 99) = 6.04, p = .001, R2 = .155). As expected for families with discrepant beliefs, medication adherence was higher with the combination of caregiver professional/child lay IRs (i.e., caregivers endorsed beliefs aligned more with the professional model compared to children who endorsed IRs more aligned with the lay model). Exploratory analyses showed an interaction between discrepancy Timeline IRs and child age on asthma control(F(6, 96) = 7.22, p < .001, R2 = .311). In younger children (b = - 0.270), asthma control was better for caregiver lay/child professional IRs. This relationship appeared to be reversed in older youth (b = 0.307) with better asthma control for caregiver professional/ child lay IRs.
Discussion: The current analyses do not support a simple, direct link between child asthma beliefs with behaviors (adherence) and/or health outcomes. Significant relationships were only observed within the context of the caregiver-child dyad. Child age was an important factor in the relationship between IR discrepancy and asthma control. The relationship between medication adherence and discrepant beliefs between child and caregiver supports inclusion of both caregiver and child. This may better capture developmental and familial influences ( or social context) when measuring child beliefs, disease management, and health outcomes.