Study of the User Behaviour Caused by Automatic Recommendation Systems Call to Action

Georgy Kopanitsa, Sergey Kovalchuk, Sergey Kovalchuk

2022

Abstract

Diagnostics accuracy and usability of symptom checkers have been researched in several studies. Their ability to set a correct diagnosis especially in the urgent cases is questionable. There is one aspect of symptom checkers that has not been deeply studied yet. It is their ability to motivate patients to follow up after receiving a direct recommendation and to decrease a load on the health care professionals. The goal of this research is to study how patients behave after receiving a recommendation from a symptom checker and motivation of this behaviour. We studied how patients react on the symptom checker recommendations and the motivation behind this behaviour. In total we invited 3615 patients to have a symptom checker screening; 2374 of them agreed to run a symptom checker screening; 867 of them agreed to participate in the study. The proportion of the patients who agreed to have a symptom checker screening. So, we can clearly see that symptom checker screening doesn’t result in a significant decrease of the load on healthcare professionals. This is supported by the quantitative study results. The patients emphasized the ease of use of the tool and clearness of the recommendations it gives. However, they perceived it as rather a second opinion tool or a tool that helps to prepare to the doctor’s visit.

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Paper Citation


in Harvard Style

Kopanitsa G. and Kovalchuk S. (2022). Study of the User Behaviour Caused by Automatic Recommendation Systems Call to Action. In Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2022) - Volume 5: HEALTHINF; ISBN 978-989-758-552-4, SciTePress, pages 499-503. DOI: 10.5220/0010840000003123


in Bibtex Style

@conference{healthinf22,
author={Georgy Kopanitsa and Sergey Kovalchuk},
title={Study of the User Behaviour Caused by Automatic Recommendation Systems Call to Action},
booktitle={Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2022) - Volume 5: HEALTHINF},
year={2022},
pages={499-503},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010840000003123},
isbn={978-989-758-552-4},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2022) - Volume 5: HEALTHINF
TI - Study of the User Behaviour Caused by Automatic Recommendation Systems Call to Action
SN - 978-989-758-552-4
AU - Kopanitsa G.
AU - Kovalchuk S.
PY - 2022
SP - 499
EP - 503
DO - 10.5220/0010840000003123
PB - SciTePress