UK News Coverage of Diabetes Types for Stigma and Discourse Analysis, 2020-2024

News articles from mainstream UK media between 2020 and 2024, compiled to analyze linguistic representation of Type 1 and Type 2 diabetes. The corpus, created by Sara Vilar-Lluch, examines how reporting may promote misunderstandings and stigma, and assesses alignment with diabetes communication guidelines. The dataset was last updated on April 30, 2026.

Use Cases

• Analyze trends in medical versus free will discourse around diabetes based on the linguistic features described.
• Identify the presence or omission of social determinants of health in news reporting based on the study's focus.
• Measure adoption of recommended versus dispreferred language in diabetes communication based on the guideline analysis mentioned.
• Examine potential for misunderstanding from generic references to diabetes or co-mentions with unrelated conditions based on the description.

Strengths

• Explicit temporal coverage from 2020 to 2024.
• Clear research focus on diabetes stigma and communication guidelines.
• Published under a permissive CC-BY-4.0 license.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is very small at 5.5 KB, indicating limited scope.

Provenance

Source

Mainstream UK news media.

Collection Method

Corpus-based approach to discourse analysis, as described in the study.

Time Range

2020-2024

Freshness

Last updated 2026-04-30 17:26:13; freshness should be verified.

Geography

United Kingdom