Participants and procedure
A hierarchical random sampling was used to recruit participants from different regions in China. A total of 4826 Chinese visited the online survey between Feb-2 and Feb-9, 2020. We removed a number of participants because they met one or more of the following exclusion criteria: (1) participants were not willing to participate in the study; (2) participants indicated that they were under 16 years old, a cutting age that parent consent is optional; and (3) participants were inclined to respond to the items in a similar pattern (e.g., chose the same answer across multiple consecutive items or within the whole questionnaire). Finally, 4607 participants were included in the analyses. Participants’ age ranged from 17 to 90 years old (Mean age = 23.71 years old, SD = 7.29). They were from 31 provinces / centrally-governed cities / autonomous regions / special administrative regions, with the sample size ranging from 16 (0.3% of the total sample, Ningxia Hui Autonomous Region) to 1386 (30.1% of the total sample, Guangdong Province). The sample covered a wide range of demographics. Detailed demographics are summarized in Table 1.
The study was reviewed and approved by the Guangzhou University. The whole study was conducted online in compliance with the ethical standards for research outlined in the Ethical Principles of Psychologists and Code of Conduct . Over 200 investigators who majored in psychology voluntarily distributed the online survey link on various internet platforms, including WeChat (the most popular APP for instant message in mainland China), Weibo, QQ, etc. By clicking the hyperlink, participants were directed to an online survey website. An information sheet stating the goal and the procedure of the study was presented to participants on the first page of the survey. If participants checked the “I understood the study and am willing to participate” box at the bottom of the information sheet, they entered the survey and answer the questionnaires. If participants were not willing to participate, they could check the “I understood the study but am not willing to participate” box and then the survey ended. Participation was voluntary and no incentive reward was given. Anonymity was emphasized and no identifiable information was collected. It took participants about 20 minutes to complete the survey.
Emotional and behavioural reactions. Participants’ emotional and behavioural reactions were measured with 18 items. These items cover a number of dimensions, including negative emotion (6 items, anxiety, worry, depressive, panic, lonely, and nervous), positive emotion (3 items, happy, joy, and excited), sleep problems (4 items, insomnia, shallow sleep, have nightmares, and insufficient sleep), aggression (2 items, argue with others and physical fight with others), substance use (2 items, smoking and drinking), and mobile phone use (1 item). Participants were asked to compare the frequencies of the said aspects after the outbreak of the COVID-19 with the ones before the outbreak on a five-point scale (from “1 = much less compared to the days before the outbreak” to “5 = much more compared to the days before the outbreak”). To align with other dimensions, the items for positive emotion were reversely scored. A higher score indicates the COVID-19 causes more negative emotion, sleep problems, aggression, substance use, mobile phone use, and less positive emotion.
Social participation. The Social Participation Scale used in prior research  was adapted to measure participants’ social participation regarding the COVID-19. Participants were asked to indicate how often they participated in different social events related to the COVID-19 since the outbreak of the COVID-19 on a five-point scale (from “0 = never” to “4 = very often). A higher score indicates that participants more actively participated in the social events about the COVID-19. A sample item is “How often do you help improve others’ life quality since the outbreak of the COVID-19?”
Precautionary behaviour. Participants’ precautionary behaviour was measured with 19 items written by authors following the precautionary guideline issued by the Chinese government. Participants were asked to indicate how often they show various precautionary behaviour since the outbreak of the COVID-19 on a five-point scale (from “0 = never” to “4 = very often). A higher score indicates that participants display more precautionary behaviour. Sample items include avoiding travelling to regions affected by the COVID-19, wearing a facemask, regularly changing a facemask, and washing hands.
Knowledge about the COVID-19. Participants’ perceived knowing of various aspects of the COVID-19 (e.g., cause, ways of transmission, symptoms, diagnostic criteria, etc.) was measured with 11 items. Participants indicated how much they know each item on a five-point scale (from “1 = totally not know” to “5 = totally know”). A higher score indicates participants perceived they know more about the COVID-19.
Perceived severity. Participants’ perceived severity about the COVID-19 was measured with 5 items. Participants indicated their perception of how severe is the infection rate, morbidity, mortality, the negative influence on social order and the negative influence on the economics on a five-point scale (from “1 = not severe at all” to “5 = very much severe”). A higher score indicates participants perceived the COVID-19 more severe.
Perceived controllability. Participants’ estimation of how much can the various aspects of the COVID-19 be controlled was measured with 9 items on a five-point scale (from “1 = totally uncontrollable” to “5 = totally controllable”). A higher score indicates participants estimated that the COVID-19 was more controllable. A sample item is “How controllable do you think the cause of the COVID-19 is?”
Demographic variables. We also collected a number of demographic variables of participants, including their biological sex (0 = male, 1 = female), age, education (1 = junior middle school or below, 2 = high school or equivalent, 3 = college, 4 = bachelor degree, 5 = master degree, 6 = doctoral degree), current residential location (referred to province and city/district), their relationship with the COVID-19 (1 = healthy, 2 = other, including suspicious case, diagnosed case, relatives or friends of suspicious/diagnosed case, etc.), the history of chronic physical diseases and psychiatric/psychological disorder (1 = yes, 2 = no), and their current physical health condition (from “1 = very poor” to “5 = very good”).
We analysed the data in SPSS and Mplus 7.0 in several steps, with .05 as the significant level across all analyses. First, we performed the descriptive statistics to capture the centrality and the Cronbach’s alpha of the variables. Second, we conducted correlation analysis to capture the association between participants’ knowledge about the COVID-19, perceived severity, and perceived controllability and emotional and behavioural reactions, social participation, and precautionary behaviour. For the correlation analysis, we applied Cohen’s (1992) standard to determine whether the correlation coefficients were substantial, with r = .01, .03, and .05 representing small, medium, and large effect size . Last, we carried out multi-level regression analysis to examine the associations between the independent variables and the dependent variables, controlling for a number of demographic variables. We applied the multi-level model (MLM) to examine the path model because individual data (level-1) were nested in different provinces (level-2). A maximum likelihood (ML) approach was used as estimator. Since our main interest was to examine the association between the predictors and the outcome variables on level 1, we centred the predictors and the covariates using a centring within cluster approach . The values of RMSEA (< .08), CFI and TLI (> .90) indicate the model fit is acceptable [22, 23].