A proposed method for quality evaluation of COVID-19 reusable face mask.

During the time of COVID-19, the use of face masks has become an essential control and prevention measure. The wide usage of disposable face masks has presented a great challenge to governments to face the impact of plastic waste on humans health and the environment. The quality of reusable face masks was assessed in previous research based on general measures such as the fabric, size fit, arrival time, price, and convenience, and based on more-specific measures related to the number of layers and the included filters. However, as the quality of reusable face masks includes several other dimensions, the general measures cannot be enough to ensure a comprehensive evaluation of these products during the COVID-19 outbreak. Nowadays, however, digital social media has provided venues and convenient tools for users to share their opinions, preferences, and experiences on the quality of reusable face masks. Considering reusable face masks, several types have been launched on online platforms to meet the increasing demand during COVID-19. The main goal of this study is to investigate how reusable face masks can be evaluated through online customers' reviews. This study proposes a combination of qualitative (text mining) and quantitative (survey-based analysis) approaches to provide the researchers with a method of data analysis to inspect the most influential quality factors for the evaluation of reusable face masks. We performed a literature review on the previous works and also collected online customers' reviews from Amazon.com to find the quality factors of reusable face masks. The review of previous literature on reusable face masks and the result of online reviews analysis indicated that several factors impact customers' experiences, including filteration efficiency, fabric quality, breathability, design, functionality, environmental impact, comfort, easy to use, easy to clean, economic impact, donning/doffing, quality of seal, vision, communication and safety protection. The presented framework can be complementary to the existing evaluation research methods, which use the strengths of one method to overcome the shortcomings of the other. [ABSTRACT FROM AUTHOR]