Internationally, women continue to report health inequities that are increasingly being framed as medical misogyny, yet the linguistic mechanisms underpinning them remain understudied. To examine the discourse through which women's healthcare experiences are publicly framed and interpreted as medical misogyny. A 37,327-word corpus was constructed and analysed using established corpus-assisted discourse study approaches. The software 'AntConc' was used to identify frequent and collocated words. Concordance line analysis identified four discursive patterns operating across the genres represented within the corpus. Four discursive patterns were identified: (1) professional authority and normalisation, (2) epistemic struggle, (3) communicative asymmetry, and (4) psychiatric containment. These patterns were realised through linguistic strategies such as normalising formulations, categorical exclusion, unidirectional "telling", and pathologising attributions. Understanding how language may undermine women's credibility, and how diagnostic uncertainty may be gendered, is important nursing knowledge. As social agents and clinical communicators, nurses are positioned to recognise and interrupt these discursive patterns. Reflexive documentation practices, and advocacy within multidisciplinary teams, may support more equitable clinical encounters and help address gendered barriers in healthcare. Reporting followed the COREQ checklist. This study reveals linguistic patterns of medical misogyny in news media, equipping nurses with discursive awareness to better recognise and interrupt epistemic exclusion through reflexive documentation and advocacy. Such efforts may support more equitable care and gender-informed clinical practice. Women face inequitable and sometimes dismissive treatment in healthcare, increasingly identified as medical misogyny. News stories shape how the public understands this issue but less is known about the specific language used to describe it. This study examines how media represent women's healthcare experiences as medical misogyny.The authors built a 37,327-word collection of texts from a media article and analysed it using a downloadable software package. This computer tool helped the authors find frequent words and associated patterns. Looking closely at example lines, the authors have identified four key ways gender bias may appear in language.The authors found four patterns: (1) doctors asserting authority and calling women's symptoms “normal,” (2) women struggling to be believed, (3) one-way communication where women aren't heard, and (4) labelling women's distress as psychiatric problems.These language patterns undermine women's credibility and make diagnostic uncertainty seem like “women's issues.” Nurses can spot these patterns in conversations and media. By documenting carefully and speaking up in teams, nurses help support more equitable care. This research gives nurses tools to challenge bias and contribute to more equitable healthcare practices.
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