Using Natural Language Processing to Examine the Uptake, Content, and Readability of Media Coverage of a Pan-Canadian Drug Safety Research Project: Cross-Sectional Observational Study

• Published in: JMIR formative research 2020-01, Vol.4 (1), p.e13296-e13296
• Main Authors: Mohammadhassanzadeh, Hossein, Sketris, Ingrid, Traynor, Robyn, Alexander, Susan, Winquist, Brandace, Stewart, Samuel Alan
• Format: Article
• Language: English
• Subjects: Bibliometrics; Clinical decision making; Consumer health information; Decision making; Internet; Journalism; Journalists; Language; Media coverage; Medical research; Natural language processing; News media; Observational studies; Original Paper; Patients; Pneumonia; Pregnancy; Product safety; Search strategies; Social networks
• ISSN: 2561-326X; 2561-326X
• DOI: 10.2196/13296

Isotretinoin, for treating cystic acne, increases the risk of miscarriage and fetal abnormalities when taken during pregnancy. The Health Canada-approved product monograph for isotretinoin includes pregnancy prevention guidelines. A recent study by the Canadian Network for Observational Drug Effect Studies (CNODES) on the occurrence of pregnancy and pregnancy outcomes during isotretinoin therapy estimated poor adherence to these guidelines. Media uptake of this study was unknown; awareness of this uptake could help improve drug safety communication. The aim of this study was to understand how the media present pharmacoepidemiological research using the CNODES isotretinoin study as a case study. Google News was searched (April 25-May 6, 2016), using a predefined set of terms, for mention of the CNODES study. In total, 26 articles and 3 CNODES publications (original article, press release, and podcast) were identified. The article texts were cleaned (eg, advertisements and links removed), and the podcast was transcribed. A dictionary of 1295 unique words was created using natural language processing (NLP) techniques (term frequency-inverse document frequency, Porter stemming, and stop-word filtering) to identify common words and phrases. Similarity between the articles and reference publications was calculated using Euclidian distance; articles were grouped using hierarchical agglomerative clustering. Nine readability scales were applied to measure text readability based on factors such as number of words, difficult words, syllables, sentence counts, and other textual metrics. The top 5 dictionary words were pregnancy (250 appearances), isotretinoin (220), study (209), drug (201), and women (185). Three distinct clusters were identified: Clusters 2 (5 articles) and 3 (4 articles) were from health-related websites and media, respectively; Cluster 1 (18 articles) contained largely media sources; 2 articles fell outside these clusters. Use of the term isotretinoin versus Accutane (a brand name of isotretinoin), discussion of pregnancy complications, and assignment of responsibility for guideline adherence varied between clusters. For example, the term pregnanc appeared most often in Clusters 1 (14.6 average times per article) and 2 (11.4) and relatively infrequently in Cluster 3 (1.8). Average readability for all articles was high (eg, Flesch-Kincaid, 13; Gunning Fog, 15; SMOG Index, 10; Coleman Liau Index, 15; Linsear Write Index, 13; and Text Standard, 13). R