Research Letter: Characterizing spin in psychiatric clinical research literature using large language models.

ABSTRACT:

Importance

Spin is a common form of biased reporting that misrepresents study results in publications as more positive than an objective assessment would indicate, but its prevalence in psychiatric journals is unknown.

Objective

To apply a large language model to characterize the extent to which original reports of pharmacologic and non-pharmacologic interventions in psychiatric journals reflect spin.

Design

We identified abstracts from studies published between 2013 and 2023 in 3 high-impact psychiatric journals describing randomized trials or meta-analyses of interventions.

Main outcome and measure

Presence or absence of spin estimated by a large language model (GPT4-turbo, turbo-2024-04-09), validated using gold standard abstracts with and without spin.

R

SUBMITTER: Perlis RH 

PROVIDER: S-EPMC11245075 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature