JMIR Publications

ABSTRACT

Background:

Direct-to-consumer (DTC) pharmaceutical advertising allots billions annually in the U.S., yet social media discourse of it remains underexamined.

Objective:

To see what user-generated topics are discussed for the biggest budgeted DTC pharmaceutical drugs and what uses and gratifications and agenda-setting themes emerged.

Methods:

This social listening study employs Brandwatch to analyze Twitter conversations (August 2021—August 2023) surrounding top-budgeted DTC brands. A dataset of 44,700 mentions from 26,800 unique authors was analyzed for content, sentiment, and thematic relevance using uses gratifications and agenda-setting frameworks.

Results:

Four dominant themes emerged: (1) patient experiences/testimonials, (2) drug pricing/insurance concerns, (3) pharmaceutical news, and (4) advertising commentary. The content shows a range of potentially agenda-setting topics, including the pharmaceutical companies, their DTC drugs, patient experiences, costs, insurance, and advertising commentary. Twitter/X is serving as a forum for pharmaceutical companies, their constituents, and social media health influencers to discuss topics related to top-spending DTC drugs. The uses and gratifications we found included information, entertainment, economic benefits, and social benefits, information being the most prevalent.

Conclusions:

Our study is an important glimpse into what is being discussed on Twitter/X by, with, and about pharmaceutical drugs that spend billions on advertising each year (Fierce Pharma, 2022). Although more tweets were neutral than positive or negative, the overall sentiment of the top terms was negative. The predominance of negative sentiment in our findings suggests that many social media users express apprehensions or criticisms about these drugs, highlighting the need for improved communication, transparency, and engagement strategies. Further implications are also discussed surrounding public policy and industry practice. Suggested future research directions include NodeXL network analysis and qualitative inquiry into user motivations.