Readability of Arabic Medicine Information Leaflets: A Machine Learning Approach

Abstract This paper presents a project that explores the possibility of assessing the readability level of Arabic medicine information leaflets using machine learning techniques. There are a number of popular readability formulas and tools that have been successfully used to assess the readability of health-related information in several languages. However, there is limited work on the readability assessment of health-related information, specifically medicine information leaflets in Arabic. We describe the design of a tool that uses machine learning to assess the readability of medicine information leaflets. We utilize a corpus comprising 1112 medicine information leaflets annotated with three difficulty levels. Based on a study of existing literature, we selected a number of features influencing text difficulty. The tool will help specialized organizations in medicine information leaflets production to produce the leaflets at appropriate level of reading for the majority of leaflets consumers.

[1]  Alastair K Denniston,et al.  Readability assessment of online ophthalmic patient information. , 2013, JAMA ophthalmology.

[2]  George R. Klare,et al.  The measurement of readability , 1963 .

[3]  S. Al-Aqeel.  Evaluation of medication package inserts in Saudi Arabia , 2012, Drug, healthcare and patient safety.

[4]  Lijun Feng,et al.  A Comparison of Features for Automatic Readability Assessment , 2010, COLING.

[5]  Hend Suliman Al-Khalifa,et al.  AUTOMATIC READABILITY MEASUREMENTS OF THE ARABIC TEXT: AN EXPLORATORY STUDY , 2010 .

[6]  George R. Klare,et al.  The measurement of readability: useful information for communicators , 2000, AJCD.

[7]  Udo Kruschwitz,et al.  AraNLP: a Java-based Library for the Processing of Arabic Text , 2014, LREC.

[8]  Alaa M. El-Halees,et al.  Arabic Text Classification Using Maximum Entropy , 2015 .

[9]  S. Bawazir,et al.  Public Attitude toward Drug Technical Package Inserts in Saudi Arabia , 2003 .

[10]  Yiu-Kai Ng,et al.  ReadAid: A Robust and Fully-Automated Readability Assessment Tool , 2011, 2011 IEEE 23rd International Conference on Tools with Artificial Intelligence.

[11]  Lucia Specia,et al.  Readability Assessment for Text Simplification , 2010 .

[12]  Patrik Larsson,et al.  Classification into Readability Levels : Implementation and Evaluation , 2006 .

[13]  Graciela Rosemblat,et al.  Assessing Readability of Consumer Health Information: An Exploratory Study , 2004, MedInfo.

[14]  I. Tleyjeh,et al.  Non prescribed sale of antibiotics in Riyadh, Saudi Arabia: A Cross Sectional Study , 2011, BMC public health.

[15]  Yunli Wang,et al.  Automatic Recognition of Text Difficulty from Consumers Health Information , 2006, 19th IEEE Symposium on Computer-Based Medical Systems (CBMS'06).

[16]  B. Svarstad,et al.  Patient counseling provided in community pharmacies: effects of state regulation, pharmacist age, and busyness. , 2004, Journal of the American Pharmacists Association : JAPhA.

[17]  Shane O'Hanlon,et al.  Readability level of patient information leaflets for older people , 2011, Irish journal of medical science.

[18]  Cédrick Fairon,et al.  An “AI readability” Formula for French as a Foreign Language , 2012, EMNLP.

[19]  S. Alghanim.  Self-medication practice among patients in a public health care system. , 2011, Eastern Mediterranean health journal = La revue de sante de la Mediterranee orientale = al-Majallah al-sihhiyah li-sharq al-mutawassit.

[20]  Gondy Leroy,et al.  A balanced approach to health information evaluation: A vocabulary-based naïve Bayes classifier and readability formulas , 2008 .

[21]  Nello Cristianini,et al.  An Introduction to Support Vector Machines and Other Kernel-based Learning Methods , 2000 .

[22]  Elizabeth Salesky,et al.  A Language-Independent Approach to Automatic Text Difficulty Assessment for Second-Language Learners , 2013, PITR@ACL.

[23]  Nello Cristianini,et al.  An Introduction to Support Vector Machines and Other Kernel-based Learning Methods , 2000 .

[24]  Matthew Dunn,et al.  Health literacy and the Internet: a study on the readability of Australian online health information , 2015, Australian and New Zealand journal of public health.

[25]  Kimberly M. Kelly,et al.  Tools for Assessing Readability and Quality of Health-Related Web Sites , 2009, Journal of Genetic Counseling.