# Development of a questionnaire for assessing the use of ChatGPT in primary and secondary disease prevention

## TL;DR

This paper introduces a validated questionnaire to assess how people use ChatGPT for health prevention, ensuring reliable and adaptable evaluation of AI interactions.

## Contribution

The study presents a novel, validated questionnaire for evaluating ChatGPT's role in health prevention with strong reliability and adaptability.

## Key findings

- The questionnaire showed high test-retest reliability for knowledge, attitude, and behavior items.
- Internal consistency was acceptable with Cronbach's Alpha of 0.771.
- The design allows adaptation for assessing interactions with various conversational AI systems.

## Abstract

Many individuals seek health-related guidance through ChatGPT OpenAI (San Francisco, CA, USA), due to its convenience and perceived reliability, often in place of, or as a supplement to, professional medical advice. This raises concerns about the accuracy of information provided and the potential for misinterpretation. On the other hand, ChatGPT offers a promising avenue for complementing traditional health prevention processes.

This study aimed to develop and validate self-completion questionnaire among adults that evaluates the use of role of ChatGPT in primary and secondary health prevention, to explore the extent to which users utilize ChatGPT for disease prevention and health maintenance.

Questionnaire items were derived from a systematic literature review and comprised demographics, internet-use metrics, and validated items from the Brief Health Literacy Screening Tool. ChatGPT usage was structured into three domains: knowledge, attitudes, and behaviors. Test–retest reliability was quantified by Kendall's tau, and internal consistency by Cronbach's Alpha.

During the validation phase, the questionnaire was administered to a sample of 22 participants (16 female, six male), each of whom completed it twice, resulting in a total of 44 responses. Knowledge items demonstrated significant test–retest stability (Kendall's τ, p < 0.01). For behavior items, seven achieved perfect reliability (τ = 1.00), and five exceeded τ > 0.70. Attitude items similarly showed high stability, with three at τ = 1.00 and three above τ > 0.70. Internal consistency was acceptable (raw Cronbach's α = 0.771).

Our reliability analysis demonstrated that the items of the instrument exhibit good internal consistency, with Cronbach's Alpha values exceeding the commonly accepted threshold for exploratory research. Moreover, the questionnaire's design is inherently model-independent, allowing for its straightforward adaptation to assess user interactions with a variety of conversational artificial intelligence systems beyond ChatGPT.

In conclusion, this study presents an initially validated questionnaire that captures how individuals employ ChatGPT for both primary and secondary disease prevention. The tool addresses key dimensions of artificial intelligence use and enables meaningful comparisons across populations with different social and educational backgrounds.