UK News Coverage of Diabetes Types and Stigmatizing Language, 2020-2024

A corpus-based discourse analysis of UK mainstream news media from 2020 to 2024 examines language around Type 1 and Type 2 diabetes. The study, authored by Sara Vilar-Lluch, investigates linguistic representation, potential stigma, and alignment with diabetes communication guidelines. The dataset is a 5.5 KB XLS file last updated in April 2026.

Use Cases

• Analyzing trends in medical versus free-will discourse based on the description of prevalent narrative frames.
• Measuring adoption of recommended versus dispreferred language based on the study's focus on communication guidelines.
• Identifying potential sources of misunderstanding based on mentions of generic diabetes references and unrelated condition contexts.

Strengths

• Data is licensed under CC-BY-4.0, permitting broad reuse.
• Focus on a specific 5-year time range (2020-2024) and geography (UK).
• Analysis is grounded in a described corpus-based discourse methodology.

Limitations

• Row count and column-level documentation are unknown, requiring manual inspection after download.
• The dataset is very small at 5.5 KB, indicating limited scope.
• Data may reflect the temporal and source bias inherent to the analyzed UK news media.

Provenance

Source

figshare, authored by Sara Vilar-Lluch.

Collection Method

Corpus-based discourse analysis of mainstream UK news media.

Time Range

2020-2024

Freshness

Last updated 2026-04-30 17:26:14; freshness should be verified.

Geography

United Kingdom