The Cure of Patients with SARS-CoV-2 in China from February 1 to March 31, 2020
Figure 1 shows the changes in the existing diagnosed patients, the cumulative number of cured patients, and the cumulative death toll with SARS-CoV-2 in February and March, 2020 in Hubei Province, China. The cumulative number of cured patients increased exponentially over the previous two months. The cumulative death toll also increased, but not as strongly as the former. The number of existing diagnosed patients, however, had a bell-shaped distribution. An inflection point appeared on February 19. The number of patients diagnosed in Hubei Province had increased geometrically daily until February 19, and the total number of confirmed cases gradually decreased until February 20. It is worth noting that the cumulative number of cured patients on February 29 exceeded the number of existing diagnosed patients, and the gap between them was widening in a trumpet shape.
Participants in the Survey
We received responses from 483 participants; and 126 participants did not complete the questionnaire. Ultimately, we included 357 participants from 4 hospitals, which were all hospitals selected to treat patients with SARS-CoV-2 pneumonia in China (completion rate: 73.91%). A total of 174 participants submitted the questionnaire on the first day (6 April), and 278 participants submitted the questionnaire on the second day (7 April). Only 31 participants submitted the questionnaire on the third day (8 April).
The emergency capacity of medical staff was measured using the EPIQ scale. For simplicity, all three variables were calculated as the means of their respective items (with negative items reverse-coded). In the overall dimension of prevention ability, the sample mean was 5.98 (SD = 1.03). Of all respondents, 5 (1.4%) were considered weak in prevention (score < 3), 90 (25.2%) were considered to have a moderate level of prevention (score: 3-5), and 262 (73.4%) were considered to have strong prevention ability (score > 5). In the overall dimension of preparation ability, the sample mean was 5.11 (SD = 1.22). Of all respondents, 33 (9.2%) were considered weak in preparation (score < 3), 97 (27.2%) were considered to have a moderate level of preparation (score: 3-5), and 206 (57.7%) were considered to have strong preparation ability (score > 5). In the overall dimension of coping ability, the sample mean was 5.54 (SD = 1.07). Of all respondents, 11 (3.1%) were considered weak in coping (score < 3), 100 (28.0%) were considered to have moderate coping ability (score: 3-5), and 246 (68.9%) were considered to have strong coping ability (score > 5).
The self-efficacy level of the medical staff was measured using the GSES scale, and the overall mean of the sample was 3.86 (SD = 0.65). Specifically, 6 (1.7%) were not confident enough to complete the tasks they were assigned (score: 1-2), 85 (23.8%) were considered to have general confidence and could barely complete the tasks they were assigned (score: 3), and 266 (74.5%) were considered relatively confident and could better complete the tasks they were assigned (score: 4-5).
Sociodemographic Variables and Emergency Capacity of Medical Staff
Sociodemographic characteristics are presented in Table 1. The majority of participants were women (85.9%) aged 21 to 30 years (52.7%); they had worked less than 11 years (63.3%), had a bachelor’s degree (59.9%), were clinical nurses (60.5%), and worked in Shaanxi Province (55.2%) and secondary hospitals (89.9%). Nearly half of the respondents were frontline medical staff during the COVID-19 pandemic (43.7%). Male gender was significantly associated with higher scores on the EPIQ preparation ability subscale (B = 0.32, 95% confidence interval (95% CI): 0.00 to 0.64). Age 21 to 30 years was significantly associated with a lower EPIQ preparation ability subscale (B = −0.54, 95% CI: −1.13 to 0.06). Low working-years were significantly associated with lower EPIQ preparation ability subscale scores (B = −0.55, 95% CI: −1.13 to 0.03) and EPIQ coping ability subscale scores (B = −0.44, 95% CI: −0.95 to 0.07). Participants with 11 to 20 working years were significantly associated with lower EPIQ coping ability subscale scores (B = −0.51, 95% CI: −1.06 to 0.05) compared to those who had worked from 31 to 40 years. Participants with a high school degree were significantly associated with lower EPIQ prevention ability subscale scores (B = −2.90, 95% CI: −5.16 to −0.61) than those with a PhD. Clinical nurse status was significantly associated with a lower EPIQ preparation ability subscale (B = −0.45, 95% CI: −0.82 to −0.09). Clinicist status was significantly associated with a lower EPIQ preparation ability subscale (B = −1.62, 95% CI: −2.84 to −0.39) and a lower EPIQ coping ability subscale (B = −1.46, 95% CI: −2.53 to −0.38). The status of frontline medical staff was significantly associated with a higher EPIQ prevention ability subscale (B = 0.33, 95% CI: 0.12 to 0.55), higher EPIQ preparation ability subscale (B = 0.39, 95% CI: 0.14 to 0.64), and higher EPIQ coping ability subscale (B = 0.43, 95% CI: 0.21 to 0.65). Working in Shaanxi Province was significantly associated with a higher EPIQ prevention ability subscale (B = 0.34, 95% CI: 0.08 to 0.60). Working in Hubei Province was significantly associated with a higher EPIQ prevention ability subscale (B = 0.53, 95% CI: 0.21 to 0.85), higher EPIQ preparation ability subscale (B = 0.36, 95% CI: −0.02 to 0.73), and higher EPIQ coping ability subscale (B = 0.32, 95% CI: −0.01 to 0.65). Other sociodemographic variables, such as hospital grade, were not associated with EPIQ subscale scores.
Participation and Emergency Capacity
Table 2 shows the difference between the scores of frontline medical staff and non-frontline medical staff in the three dimensions of emergency capacity. Overall, frontline medical staff scored significantly higher in every dimension than non-frontline medical staff (p < 0.01). For prevention ability, the total score of frontline medical staff (M = 18.51, SD = 2.61) was 1 point higher than that of non-frontline medical staff (M = 17.51, SD = 3.35). For preparation ability, the total score of frontline medical staff (M = 31.96, SD = 6.50) was 2 points higher than that of non-frontline medical staff (M = 29.62, SD = 7.79). For coping ability, the total score of frontline medical staff (M = 161.96, SD = 24.30) was 11 points higher than that of non-frontline medical staff (M = 150.01, SD = 32.60).
Region and Emergency Capacity
Regarding the regions where respondents worked, Table 3 shows a significant difference in the emergency capacity of medical staff between regions. There were differences between the three regions in terms of prevention ability and preparation ability (p < 0.05). In general, the emergency capacity of medical staff in Hubei was higher than that of the other two regions. For prevention ability, the total score of medical staff in Hubei (M = 18.63, SD = 2.30) was 0.5 points higher than that of medical staff in Shaanxi (M = 18.06, SD = 3.09) and 1.5 points higher than that of medical staff in Yunnan (M = 17.04, SD = 3.53). For preparation ability, the total score of medical staff in Hubei (M = 32.67, SD = 5.58) was 2.5 points higher than that of medical staff in Shaanxi (M = 29.89, SD = 8.06) and 2 points higher than that of medical staff in Yunnan (M = 30.52, SD =6.67). For coping ability, the total score of medical staff in Hubei (M = 161.23, SD = 24.39) was 7 points higher than that of medical staff in Shaanxi (M = 154.10, SD = 30.89) and 9 points higher than that of medical staff in Yunnan (M = 152.24, SD = 31.42).
Self-efficacy and Emergency Capacity
Table 4 shows the relationship between the emergency capacity and self-efficacy of medical staff. There was a significant positive correlation between prevention ability and preparation ability (r = 0.598, p < 0.001), a significant positive correlation between prevention ability and coping ability (r = 0.627, p < 0.001), and a significant positive correlation between preparation ability and coping ability (r = 0.761, p < 0.001). There was a significant positive correlation between self-efficacy and prevention ability (r = 0.202, p < 0.001), a significant positive correlation between self-efficacy and preparation ability (r = 0.358, p < 0.001), and a significant positive correlation between self-efficacy and coping ability (r = 0.376, p < 0.001). Figure 2 shows the relationship between medical staff’s self-efficacy and various dimensions of emergency capacity. There was a strong correlation between all dimensions of emergency capacity (r > 0.5, p < 0.001). Medical staff’s self-efficacy was positively correlated with all dimensions of emergency capacity, but not strongly (r < 0.5, p < 0.001).