Aims To explore the status quo and the influencing factors of residents’ knowledge, attitude and practice (KAP) in the prevention and control of coronavirus disease 2019 (COVID‐19), and the difficulties or challenges perceived by residents in their preventive practice. Design An online questionnaire survey. Methods The self‐designed questionnaire was distributed among residents online in February 2020. Descriptive statistics, two independent samples t ‐tests, one‐way analysis of variance, Pearson's correlation analysis, multivariate linear regression and content analysis were performed. Results A total of 919 valid questionnaires were collected. The scoring rates of residents’ KAP were 85.2%, 92.9% and 84.4% respectively. Main factors influencing residents’ knowledge included gender and occupation; while those influencing attitude were occupation, family economic level and knowledge; and those influencing practice included place of residence, occupation, with or without chronic disease, knowledge and attitude. Mass media was the primary approach for people to learn the knowledge and information of COVID‐19. Difficulties or challenges faced were mainly lack of protective equipments, concerns about the risk of prevention and control, impact on daily life, work and study, lack of knowledge and consensus, psychological problems and information problems. Conclusion The attitude of residents towards COVID‐19 prevention and control is generally positive. The knowledge and practice have been popularized to a certain extent, but there are still deviations or deficiencies in residents’ understanding of certain important knowledge and the adoption of relevant preventive measures. Evidence‐based tailored public education initiatives are indicated. Impact Findings of this study add important knowledge about residents’ understanding, attitude, practice and the influencing factors on COVID‐19 prevention and control, which serves as a scientific foundation for optimizing the pandemic public education and decision‐making.

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Online mental health service (OMHS) platforms have contributed significantly to the public’s mental health during the COVID-19 pandemic in China. However, it remains unclear why the public used OMHS platforms for psychological help-seeking (PHS) behavior and how PHS behavior varied across different stages of the COVID-19 pandemic. Based on the ecological PHS behavior data from two OMHS platforms, we extracted population, psychological problems, and influential factors of PHS behavior by text mining and time series analysis methods. Seven top-ranked psychological problems (i.e., depression and anxiety, lack of interest, suicidal tendencies, social phobia, feelings of being worried and afraid, suffering, anger) and seven influential factors (i.e., interpersonal relationships, love, family, work, psychotherapy, personal characteristics, marriage) were found. The online PHS behaviors related to different psychological problems and influential factors remained a growing trend before 2020 and have been increasing significantly due to the COVID-19 outbreak. Four main stages were found during the pandemic according to the changes in the online PHS population: sharp growth, significant decline, slight rebound, and slow decline. This study identified large-scale, spontaneous PHS behaviors among the online public during the COVID-19 pandemic and the various psychological problems and influential factors that varied across different stages of the pandemic, suggesting that the government and health practitioners should adopt effective policies and strategies to prevent and intervene in mental health problems for the online public.

Online lifestyles have been shown to reflect and affect consumers’ preferences across a wide range of online scenarios. In the context of e-commerce, it still remains unclear whether online lifestyles are practically influential in predicting consumers’ purchasing preferences across different product categories, especially considering its potential influence over the widely used personality traits. In this study, we provide the first, to the best of our knowledge, quantitative demonstration of online lifestyles in predicting consumers’ online purchasing preferences in e-commerce by using a data-driven approach. We first construct an online lifestyles lexicon including seven distinct dimensions using text mining approaches based on consumers’ language use behaviors. We then incorporate the lexicon in a typical e-commerce recommender system to predict consumers’ purchasing preferences. Experimental results on Amazon Review Dataset show that online lifestyles and all its subdimensions significantly improve preference predicting performance and outperform the widely used Big Five personality traits as a whole. In addition, product types significantly moderate the influence of online lifestyle on consumer preference. The strong empirical evidence indicates that the big e-commerce consumer data facilitates more specialized market psychographic segmentation, which advances data-driven marketing decision-making.