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“‘Oh, women always…’. Yeah Image 1.” The mediated construction of medical gaslighting in an Instagram echo chamber

Year: 2026
Type: article
Abstract: The use of the term gaslighting has increased prominently over the last few decades, both as a lay notion and a scholarly framework in the social sciences. Medical gaslighting, however, remains under researched, especially within digitally mediated discourse analysis. This paper addresses this gap by examining the construction of medical gaslighting as mediated discourse, that is, by considering how platform affordances and algorithms alongside user participation shape understandings of medical gaslighting. The study thus responds to calls to investigate how users react to perceived gaslighting on social media as well as how the possible formation of a “good echo chamber” may provide sources of epistemic contestation ( Pohlhaus, 2020 ; Shane et al., 2022 ). To carry out this research, a topical corpus on medical gaslighting was compiled and analysed. The corpus consisted of a National Public Radio post from Instagram, relevant metadata and user-generated comments. The analysis drew insights from mediated discourse analysis, media studies, pragmatics and identity frameworks. The post was qualitatively analysed and a corpus-assisted discourse analysis approach was adopted to examine user-generated comments. Findings reveal how Instagram's algorithms and affordances, together with discourse dynamics mediate the construction of medical gaslighting, which emerged as a socially recognized practice. Further, a largely supportive “good echo chamber” was generated in which strong agreement, epistemic validation and collaboration outweighed dissent, allowing users to contest medical dismissal and repair damaged epistemic identities.
DOI: 10.1016/j.dcm.2026.101045
Language: English
Open Access status: hybrid
Estimated APC paid: $3,770
OpenAlex ID: W7204267724
FWCI: 22.89
Cites: 29
Cited by: 1
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