Objective:

To examine whether general use of generative AI (GenAI) for health information is associated with diabetes-specific GenAI information seeking, and to assess perceived utility, critical literacy, verification behavior, behavioral impact, and trust/risk awareness as potential correlates or indirect pathways.

Approach:

• Design and sample: The context describes a study of 617 adults with diabetes or prediabetes, ages 19–92 years (mean 58.72, SD 13.50).
• Measures and analysis: The study assessed general and diabetes-specific GenAI health-information use and five proposed explanatory dimensions. Analyses adjusted for age, education, diabetes status, technology literacy, non-AI online health-information seeking, and trust in GenAI med…

Key Findings:

• The provided context reports participant characteristics and GenAI use patterns but does not include results for the study hypotheses or statistical associations.
• Type 2 diabetes was the most frequently reported condition (68.4%); 10.7% reported prediabetes.
• Common GenAI information topics included medication or treatment (57.7%), symptoms or diseases (55.4%), and test results or medical reports (54.5%).
• ChatGPT was reported by 68.9% of participants and Google Gemini by 52.2%.

Interpretation:

The supplied material describes the study rationale, methods, and sample characteristics; it does not provide evidence to interpret the hypothesized relationships.

Limitations:

• The provided article context ends during the Methods section and contains no study results.
• The source URL was not provided.

Sources:

• Article context supplied in the prompt