What do patients learn about psychotropic medications on the web? A natural language processing study.

ABSTRACT:

Background

Low rates of medication adherence remain a major challenge across psychiatry. In part, this likely reflects patient concerns about safety and adverse effects, accurate or otherwise. We therefore sought to characterize online information about common psychiatric medications in terms of positive and negative sentiment.

Methods

We applied a natural language processing tool to score the sentiment expressed in web search results for 51 psychotropic medications across 3 drug classes (antidepressants, antipsychotics, and mood stabilizers), as a means of seeing if articles referencing these medications were generally positive or generally negative in tone. We compared between medications of the same class, and across medication classes.

Results

Across 12,733 web se

SUBMITTER: Hart KL 

PROVIDER: S-EPMC6921244 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature