Promoting medication compliance in epileptic children: a cross sectional survey

Abstract

Background: Compliance with medication is crucial for the favorable prognosis of children with epilepsy. The objective of this study was to assess the determinants of medication compliance and to construct a predictive model for the risk of non-compliance among pediatric epilepsy patients.

Methods: The study included children diagnosed with epilepsy and treated at our hospital between February 1 and September 30, 2023. We evaluated the demographic characteristics and medication compliance profiles of these patients. The predictive model's performance was assessed using the receiver operating characteristic (ROC) curve to determine its sensitivity and specificity.

Results: A total of 168 children with epilepsy were analyzed. The rate of non-compliance with medication was found to be 32.74% (55 out of 168). Logistic regression identified the educational level of parents (OR = 2.844, 95% CI: 2.182-3.214), monthly household income (OR = 1.945, 95% CI: 1.203-2.422), the number of medications taken (OR = 1.883, 95% CI: 1.314-2.201), and the level of epilepsy knowledge received (OR = 2.517, 95% CI: 1.852-3.009) as significant factors influencing non-compliance (all p < 0.05). A total score threshold of 6 was set for the predictive model. The area under the ROC curve was 0.713 (95% CI: 0.686-0.751), indicating the model's discriminative ability.

Conclusions: The compliance to medication regimens among children with epilepsy is suboptimal and influenced by a multitude of factors. This study has developed a predictive model for medication compliance, which could serve as a valuable tool for clinical assessment and intervention planning regarding medication compliance in pediatric epilepsy patients.

Keywords: Care; Children; Compliance; Epilepsy; Nursing; Treatment.

Fig. 1

The ROC curve on the sensitivity and specificity of developed prediction model