Knowledge, Attitude, and Prevention Practice of Cosmetology Students toward Covid-19 Infectious Disease

Purpose: This study aimed to confirm the knowledge on COVID-19 and hygiene behavior of cosmetology students and identify factors affecting mental health.Methods: In the analysis, SPSS/WIN program was used. Univariate analysis was used for knowledge COVID-19, preventive behavior, and mental health, and stepwise multiple regression was used for factors affecting mental health.Results: The factors affecting the mental health of cosmetology students were identified as knowledge related to COVID-19, subjective health perception, and part-time job.Conclusion: In this study, 34.9% and 36.2% of the borderline and severe groups of anxiety and depression respectively, which are subfactors of the mental health of cosmetology students, were identified. In future studies, it is considered necessary to expand sample and the influencing factors.

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Discrete Emotions Response after Purchase Cosmetics of Millennial Consumers: Evaluation of Satisfaction/Normal/Dissatisfaction Attributes Using Text Mining Techniques

Song¹,

Cho²,

Yim³

2022

Asian J Beauty Cosmetol

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Purpose: This study aimed to analyze the similarities and differences between each area using wordcloud analysis and semantic network analysis, which are text mining techniques. Further, confirmatory factor analysis will be conducted by crawling for word-of-mouth information on attribute reviews as satisfied, normal, or dissatisfied after purchases that are subjectively given by millennial generations.Methods: The R program version 4.1.2 was used as a big data collection and analysis tool, and text mining analysis was performed through preprocessing and stopword processing on the collected data. Further, using LISREL 8.80 we conducted confirmatory factor analysis on these results.Results: Wordcloud analysis revealed that the terms “skin,” “products,” and “skin” ranked first in the evaluation area of “satisfied,” “normal,” and “dissatisfied,” respectively. Additionally, using confirmatory factor analysis, the correlation between the three latent variables of satisfaction, normal, and dissatisfaction was differentiated.Conclusion: The similarities and differences between the domains obtained through wordcloud and semantic network analyses and derived by classifying individual emotional responses of millennial consumers in social media into satisfied, normal, and dissatisfied domains are considered very meaningful. The keywords derived with high centrality in the semantic network for each domain is then refined and introduced as an observation variable for confirmatory factor analysis in accordance with the purpose of the study; this is helpful in research development for causal analysis in the future.

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Knowledge, Attitude, and Prevention Practice of Cosmetology Students toward Covid-19 Infectious Disease

Cited by 5 publications

References 7 publications

Awareness on New Infectious Diseases and Ethical Awareness by Optometrists during COVID-19 Pandemic

Awareness on New Infectious Diseases and Ethical Awareness by Optometrists during COVID-19 Pandemic

Effect of Knowledge on COVID-19 and Hygiene Behavior on the Mental Health of Cosmetology Students

Discrete Emotions Response after Purchase Cosmetics of Millennial Consumers: Evaluation of Satisfaction/Normal/Dissatisfaction Attributes Using Text Mining Techniques

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