3.1. 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 the cured, and the cumulative death toll with SARS-CoV-2 in February and March, 2020 in Hubei province, China. The cumulative number of the cured had been increasing exponentially over the past two months. The number of the cumulative death toll had also been increasing, but not as strongly as the former. The number of the existing diagnosed patients, however, was in a bell-shaped distribution. An inflection point appeared on February 19. The number of the patients diagnosed in Hubei province had increased geometrically daily by February 19. Until February 20, the total number of the confirmed cases was gradually decreasing. It is worth noting that the cumulative number of the cured on February 29 exceeded the number of the existing diagnosed patients, and the gap between them was widening in a trumpet shape.
3.2. Participants in the Survey
We received responses from 483 participants, and 126 participants did not complete the questionnaire. In the end, we included 357 participants from 4 hospitals, which were all the selected hospitals 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 by using the EPIQ scale. For simplicity, all the 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); 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 people (27.2%) were considered to have a moderate level of preparation (score: 3-5); 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); 246 (68.9%) were considered to have strong coping ability (score > 5).
The self-efficacy level of the medical staff was measured by 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 with (score: 1-2); 85 (23.8%) were considered general confidence and could barely complete the tasks they were assigned with (score: 3); 266 (74.5%) were considered to be relatively confident and could better complete the tasks they were assigned with (score: 4-5).
3.3. 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%); had worked under 11 years (63.3%), with a bachelor’s degree (59.9%), as clinical nurse (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 Pandemic of COVID-19 (43.7%). Male gender was significantly associated with higher scores in the EPIQ preparation ability subscale (B = 0.32, 95% Confidence Interval (95% CI): 0.00 to 0.64). Ages of 21 to 30 years were significantly associated with 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), EPIQ coping ability subscale (B = −0.44, 95% CI: −0.95 to 0.07); and those 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) as compared to those who have worked from 31 to 40 years. Those with high school degree were significantly associated with lower EPIQ prevention ability subscale scores (B = −2.90, 95% CI: −5.16 to −0.61) as compared to those with a PhD. Clinical nurse status was significantly associated with lower EPIQ preparation ability subscale (B = −0.45, 95% CI: −0.82 to −0.09). Clinicist status was significantly associated with lower EPIQ preparation ability subscale (B = −1.62, 95% CI: −2.84 to −0.39) and 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 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). The status of Shaanxi province was significantly associated with higher EPIQ prevention ability subscale (B = 0.34, 95% CI: 0.08 to 0.60). The status of Hubei province was significantly associated with 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.
Table 1. Association between demographic variables and emergency capacities of medical staff during the fight against COVID-19
Variable
|
N (%)
|
Prevention ability
|
Preparation ability
|
Coping ability
|
R-Squared (R2)
|
Adjusted R-Squared (AR2)
|
Beta (95% Confidence Interval) or B (95% CI)
|
R2
|
AR2
|
B (95% CI)
|
R2
|
AR2
|
B (95% CI)
|
Gender
|
|
|
|
|
|
|
|
|
|
|
Male
|
68(19.1)
|
0.002
|
−0.001
|
0.12 (−0.15 to 0.40)
|
0.011
|
0.008
|
0.32** (0.00 to 0.64)
|
0.006
|
0.003
|
0.20 (−0.08 to 0.48)
|
Female
|
289(85.9)
|
Reference
|
Reference
|
Reference
|
Age (Years)
|
|
|
|
|
|
|
|
|
|
|
(under 21)
|
4(1.1)
|
0.044
|
0.033
|
0.04 (−1.07 to 1.15)
|
0.034
|
0.023
|
0.09 (−1.23 to 1.41)
|
0.009
|
−0.003
|
0.05(−1.12 to 1.21)
|
(21 − 30)
|
188(52.7)
|
−0.47 (−0.98 to 0.03)
|
−0.54* (−1.13 to 0.06)
|
−0.33 (−0.86 to 0.20)
|
(31 − 40)
|
91(25.5)
|
−0.30 (−0.83 to 0.22)
|
−0.26 (−0.88 to 0.37)
|
−0.29 (−0.84 to 0.27)
|
(41 − 50)
|
57(16.0)
|
0.10 (−0.45 to 0.65)
|
0.02 (−0.63 to 0.68)
|
−0.12 (−0.70 to 0.45)
|
(51 − 60)
|
17(4.7)
|
Reference
|
Reference
|
Reference
|
Working years
|
|
|
|
|
|
|
|
|
|
|
(under 11)
|
226(63.3)
|
0.039
|
0.031
|
−0.40 (−0.89 to 0.09)
|
0.025
|
0.017
|
−0.55* (−1.13 to 0.03)
|
0.016
|
0.007
|
−0.44* (−0.95 to 0.07)
|
(11 − 20)
|
64(17.9)
|
−0.44 (−0.97 to 0.09)
|
−0.51 (−1.14 to 0.13)
|
−0.51* (−1.06 to 0.05)
|
(21 − 30)
|
49(13.7)
|
0.15 (−0.40 to 0.70)
|
−0.07 (−0.73 to 0.59)
|
−0.76 (−0.76 to 0.39)
|
(31 − 41)
|
18(5.1)
|
Reference
|
Reference
|
Reference
|
Educational attainment
|
|
|
|
|
|
|
|
|
|
|
Upper secondary school
|
3(0.8)
|
0.063
|
0.053
|
−2.9** (−5.16 to −0.61)
|
0.023
|
0.012
|
−1.61 (−4.37 to 1.15)
|
0.027
|
0.016
|
−1.29 (−3.69 to 1.11)
|
Associate degree
|
130(36.5)
|
−1.24 (−3.22 to 0.73)
|
−0.20 (−2.60 to 2.20)
|
0.10 (−1.99 to 2.19)
|
Bachelor degree
|
214(59.9)
|
−0.87 (−2.84 to 1.11)
|
0.05 (−2.35 to 2.44)
|
0.31 (−1.77 to 2.40)
|
Master degree
|
9(2.5)
|
−0.70 (−2.78 to 1.37)
|
0.01 (−2.52 to 2.52)
|
0.32 (−1.87 to 2.51)
|
Doctorate
|
1(0.3)
|
Reference
|
Reference
|
Reference
|
*** p<0.01, ** p<0.05, * p<0.1
Table 1. Continued.
Variable
|
N (%)
|
Prevention ability
|
Preparation ability
|
Coping ability
|
R2
|
AR2
|
B (95% CI)
|
R2
|
AR2
|
B (95% CI)
|
R2
|
AR2
|
B (95% CI)
|
Position
|
|
|
|
|
|
|
|
|
|
|
Clinician
|
85(23.8)
|
0.019
|
0.011
|
0.13 (−0.23 to 0.48)
|
0.043
|
0.035
|
−0.03 (−0.44 to 0.39)
|
0.034
|
0.025
|
0.22 (−0.14 to 0.59)
|
Clinical nurse
|
216(60.5)
|
−0.20 (−0.51 to 0.11)
|
−0.45 ** (−0.82 to −0.09)
|
−0.06 (−0.38 to 0.26)
|
Clinicist
|
4(1.1)
|
−0.08 (−1.12 to 0.97)
|
−1.62** (−2.84 to −0.39)
|
−1.46*** (−2.53 to −0.38)
|
Others
|
52(14.6)
|
Reference
|
Reference
|
Reference
|
Are you a member of frontline medical staff in COVID-19 Pandemic?
|
Yes
|
156(43.7)
|
0.026
|
0.023
|
0.33*** (0.12 to 0.55)
|
0.025
|
0.022
|
0.39*** (0.14 to 0.64)
|
0.040
|
0.037
|
0.43*** (0.21 to 0.65)
|
No
|
201(56.3)
|
Reference
|
Reference
|
Reference
|
Region
|
|
|
|
|
|
|
|
|
|
|
Shaanxi province
|
197(55.2)
|
0.031
|
0.026
|
0.34** (0.08 to 0.60)
|
0.023
|
0.017
|
−0.11 (−0.42 to 0.21)
|
0.012
|
0.006
|
0.07 (−0.21 to 0.34)
|
Hubei province
|
78(21.9)
|
0.53*** (0.21 to 0.85)
|
0.36* (−0.02 to 0.73)
|
0.32* (−0.01 to 0.65)
|
Yunnan province
|
82(22.9)
|
Reference
|
Reference
|
Reference
|
Hospital grade
|
|
|
|
|
|
|
|
|
|
|
Tertiary hospital
|
29(8.1)
|
0.009
|
0.003
|
−0.19 (−1.04 to 0.66)
|
0.005
|
−0.001
|
−0.01 (−1.02 to 1.01)
|
0.007
|
0.001
|
−0.03 (−0.91 to 0.85)
|
Secondary hospital
|
321(89.9)
|
0.16 (−0.61 to 0.93)
|
0.28 (−0.64 to 1.20)
|
0.27 (−0.53 to 1.07)
|
Others
|
7(3.0)
|
Reference
|
Reference
|
Reference
|
3.4. 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 the 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 the 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 the 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).
Table 2. Relationship between the emergency capacity and participation of medical staff in the Pandemic prevention
Dimension
|
Frontline medical staff of Pandemic prevention (n = 156)
|
Not frontline medical staff of Pandemic prevention (n = 201)
|
F
|
P-value
|
Prevention ability
|
18.51 ± 2.61
|
17.51 ± 3.35
|
9.44
|
0.0023
|
Preparation ability
|
31.96 ± 6.50
|
29.62 ± 7.79
|
9.14
|
0.0027
|
Coping ability
|
161.96 ± 24.30
|
150.01 ± 32.60
|
14.65
|
0.0002
|
3.5. Region and Emergency Capacity
Regarding the regions where respondents worked in, Table 3 also 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 the prevention ability, the total score of medical staff in Hubei (M = 18.63, SD = 2.30) was 0.5 point 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 the 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 the 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).
Table 3. Relationship between the emergency capacity and the region of medical staff
Dimension
|
Shaanxi province (n = 197)
|
Hubei province (n = 78)
|
Yunnan province (n = 82)
|
F
|
P-value
|
Prevention ability
|
18.06 ± 3.09
|
18.63 ± 2.30
|
17.04 ± 3.53
|
5.74
|
0.0035
|
Preparation ability
|
29.89 ± 8.06
|
32.67 ± 5.58
|
30.52 ± 6.67
|
4.08
|
0.0178
|
Coping ability
|
154.10 ± 30.89
|
161.23 ± 24.39
|
152.24 ± 31.42
|
2.15
|
0.1186
|
3.6. Self-efficacy and Emergency Capacity
Table 4 shows the relationship between 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); there was a significant positive correlation between prevention ability and coping ability (r = 0.627, p < 0.001); and there was 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).
Table 4. Correlation between emergency capacity and self-efficacy of medical staff
|
Prevention ability
|
Preparation ability
|
Coping ability
|
Self-efficacy
|
Prevention ability
|
1.0000
|
|
|
|
Preparation ability
|
0.5981*
|
1.0000
|
|
|
|
0.0000
|
|
1.0000
|
|
Coping ability
|
0.6266*
|
0.7608*
|
|
|
|
0.0000
|
0.0000
|
|
|
Self-efficacy
|
0.2017*
|
0.3576*
|
0.3759*
|
1.0000
|
|
0.0001
|
0.0000
|
0.0000
|
|
* shows the significance at the 0.05 level