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Abstract
We conducted two online surveys about antibiotics targeted at the Japanese general population in March 2017 and February 2018. In total, 6,982 participants completed the questionnaire. Factors associated with knowledge of antibiotics, knowledge of antimicrobial resistance (AMR) and appropriate behavioural changes were evaluated by a machine learning approach using DataRobot. Factors strongly associated with three dependent variables in the model were extracted based on permuation importance. We found that the strongest determinant of knowledge of antibiotics and AMR was education level. Knowledge of antibiotics was strongly associated with the frequency of internet use. Exposure to primary information was associated with motivation for appropriate behavioural changes. Improving the availability of primary information would be a beneficial intervention. Individuals lacking higher education and without opportunities to obtain primary information should be considered a target population for effective interventions.
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Details
1 AMR Clinical Reference Center, National Center for Global Health and Medicine, Tokyo, Japan (GRID:grid.45203.30) (ISNI:0000 0004 0489 0290); University of Antwerp, Faculty of Medicine and Health Sciences, Antwerp, Belgium (GRID:grid.5284.b) (ISNI:0000 0001 0790 3681)
2 NTT Data, Tokyo, Japan (GRID:grid.419819.c) (ISNI:0000 0001 2184 8682)
3 DataRobot Japan, Tokyo, Japan (GRID:grid.419819.c)
4 AMR Clinical Reference Center, National Center for Global Health and Medicine, Tokyo, Japan (GRID:grid.45203.30) (ISNI:0000 0004 0489 0290)
5 AMR Clinical Reference Center, National Center for Global Health and Medicine, Tokyo, Japan (GRID:grid.45203.30) (ISNI:0000 0004 0489 0290); Disease Control and Prevention Center, National Center for Global Health and Medicine, Tokyo, Japan (GRID:grid.45203.30) (ISNI:0000 0004 0489 0290)