Comprehension of prescription orders with and without pictograms: tool validation and comparative assessment among a sample of participants from a developing country

BACKGROUND: Medication errors can often occur due to the patient’s inability to comprehend written or verbal medication orders. This study aimed to develop pictograms of selected medication orders and to validate the comprehension of prescription orders index and compare the comprehension scores with and without pictograms. In addition to determine the predictors that could be associated with a better or worse comprehension of prescription orders with pictograms versus that of their written counterparts. METHODS: A cross-sectional study was conducted using a snowball sampling technique. Six pictograms were developed to depict specific medication orders. The comprehension of prescription orders index was constructed and validated. The study then compared the comprehension scores of prescription orders with and without pictograms, and identified the predicting factors score difference. RESULTS: A total of 1848 participants were included in the study. The structure of the comprehension of prescription orders index was validated over a solution of four factors, with an adequate Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy of 0.711 and a significant Bartlett’s test of sphericity (P < 0.001). The construct validity of the index was further confirmed by highly significant correlations between each item and the full index (P < 0.001). The study also found a significant association between the difference in comprehension scores for prescription orders with and without pictograms and several factors, including age, level of education, area of residence, number of children, and smoking status with the difference of comprehension scores (P < 0.001). CONCLUSION: Pictogram-based instructions of medication orders were better understood by the Lebanese population than written instructions, making the incorporation of pictograms in pharmacy practice paramount to optimize medication use by the patient and thus yielding better health outcomes.