Introduction:
Conducting effective web surveys while ensuring representation of diverse demographics has become increasingly challenging. Traditional web survey platforms may not fully capture certain populations, such as those without internet access or the elderly. To address this, a hybrid approach, using both web and paper surveys, has emerged as a promising solution. However, the manual processes involved in merging paper and web data can be time-consuming and tedious. We aim to showcase how advanced AI technologies on the Chisquares scientific platform have revolutionized the integration of paper and web surveys, drastically reducing the time and effort required.

Material and Methods:
The Chisquares platform uses Optical Character Recognition (OCR) technology to extract data from scanned paper questionnaires. The extracted data is then seamlessly combined with web-collected data from the same survey. Sequential numbering is employed to accurately match the paper and web versions of the questionnaires. This ensures precise data extraction and tracking of printed survey copies. The Chisquares platform offers automatic and project-specific assignment of serial numbers to avoid repetition within a project.

Results:
The Chisquares platform offers two key functionalities for web surveys: (1) Directly uploading a word document-based questionnaire to the survey environment, saving time and effort. (2) Allowing participants to complete a paper-based questionnaire that can be automatically extracted using OCR technology.

Conclusions:
Chisquares utilizes innovative AI technologies to streamline the process of conducting hybrid web-paper surveys, making data collection easier and more reliable. The platform holds great promise for researchers and public health practitioners, showcasing the potential of cutting-edge technologies in enhancing survey methodologies and making a meaningful impact.