Given that EM is considered the “gold standard” criterion to compare other adherence measurement methods, data from the current study provides initial evidence on the reliability of a correction factor for parent-reported adherence in a pediatric epilepsy sample. Based on our hypothesis and consistent with the broader adherence literature (Hansen et al., 2009
; Modi et al., 2006
), parent-reported adherence was significantly correlated and inflated relative to EM. Inflated ratings of parent-reported adherence could be due to multiple factors, including social desirability effects, poor memory recall, or individuals recalling global perceptions of adherence rather than specific time frames (e.g., doses missed within the past week) (Quittner et al., 2008
). Although the factors influencing self/parent-reported adherence were not the focus of the current study, given its clinical utility, establishing its reliability is critical to the accurate assessment of adherence in a clinic setting.
The cut-point of 80% has been broadly used to define non-adherence across a variety of pediatric and adult chronic conditions (Rapoff, 1999
); however, it is quite arbitrary (Cramer et al., 2008
) and no studies have examined the validity of this cut-point in pediatric epilepsy. Our data suggest that a cut-point of 90% adherence for parent-report measures has the best sensitivity and specificity compared to 50% or 80% cut-points; however, specificity is still extremely poor at only 28%. Thus, parent-reported adherence that is not corrected for inflation is unhelpful in identifying patients who are non-adherent. One potential reason for this is that caregivers in the current study may have been reluctant to report missing their child’s AED in fear of being judged by the healthcare team. Overall, these data suggest a need to develop self/parent-report measures that normalize non-adherence and allow families to be more comfortable reporting adherence difficulties (Quittner et al., 2008
) or as our study has demonstrated, develop “correction” factors for parent-report.
Given the detrimental impact of non-adherence on both health outcomes (Bassili et al., 2002
; Cramer et al., 2002
; Gopinath et al., 2000
; Jones et al., 2006
; Manjunath et al., 2009
) and unnecessary healthcare costs (Cutler & Everett, 2010
), implementation of EM would be ideal for monitoring adherence in standard clinical practice. EM monitoring has the ability to better identify patients at risk for non-adherence who may benefit from adherence interventions. Although the primary drawback to EM is its high cost, EM is the most reliable adherence tool and routine use may off-set the cost of unnecessary healthcare expenditures that plague the current healthcare system (e.g., unwarranted hospitalizations, emergency room visits). However, in the absence of objective EM adherence data, a self/parent-report adherence measure with a correction factor of 83%, which is consistent with the broader adult adherence literature (Haynes et al., 1980
), could serve as a reliable assessment tool in clinical settings. For example, if a patient reported perfect adherence (i.e., 100%), a clinician could interpret this rate with the correction factor as approximately 83% based on our findings. This technique is particularly helpful if the clinician has other evidence to suggest that self/parent-reported adherence information may be unreliable (e.g., inconsistent reporting of adherence behaviors, zero serum blood levels).
When adherence concerns are suspected by clinicians who routinely assess for AED adherence, clinicians and patients often hesitate to openly discuss non-adherence, as it typically elicits strong reactions on the side of families and healthcare teams. Clinicians may not consider poor adherence when seizures occur or when families present well (i.e., high social desirability) regarding adherence. Lack of communication around adherence can result in unwarranted AED dosage increases or change in AEDs (Koumoutsos et al., 2007
). Open discussion of adherence barriers during clinic visits, along with consistent EM of adherence, when possible, or use of a correction factor for self/parent-reported adherence, may hold promise for improving patient care. Nonetheless, patient perceptions of adherence can serve as a critical point for intervention. For example, families who believe they are highly adherent may benefit from examining their own EM adherence to provide objective data regarding their adherence behaviors. Given the lower rates of adherence identified in the current study, families experiencing adherence challenges may benefit from adherence-promotion interventions (Graves et al., 2010; Kahana et al., 2008
Although this is the first study examining multi-method pediatric AED adherence, several limitations are noted that have direct implications for future research. A primary limitation is that the data only provide a snapshot of adherence during the first 4 months of AED therapy for a restricted age range (i.e., 2–12 years of age). Findings may not generalize for longer-term adherence or for adolescent populations for which adherence appears particularly problematic. Caregivers likely had primary responsibility for administering AEDs in the current study, whereas both the adolescent and caregiver play a role during adolescence. Second, ingestion of the medication is presumed with EM, but not confirmed. Finally, without a well-validated standardized self/parent-reported measure of adherence, we used one ad-hoc question representing caregiver-perceived adherence in the past week. Since the inception of this study, we have developed the Pediatric Epilepsy Medication Self-Management Questionnaire
(Modi et al., 2010
), which has an Adherence to Treatment and Clinic Appointments subscale that could further our understanding of adherence behaviors.
Data from the current study have direct implications for clinical care. Of primary importance is the need to routinely assess AED adherence, as it can have a direct impact on seizure management and healthcare costs (Cutler & Everett, 2010
). Multi-method assessment can yield variable rates of non-adherence and the limitations to each method need to be acknowledged. Although healthcare teams should consider how EM can be integrated into clinical care for their patients, in the interim, self/parent-reported adherence with a correction factor may serve as a useful clinical tool. With routine adherence monitoring, healthcare professionals can proactively identify patients at risk for non-adherence and then refer them for empirically-supported adherence interventions (Graves et al, 2010; Kahana et al., 2008
) that can ultimately improve the health outcomes of children with epilepsy.