| Literature DB >> 32468998 |
Lei Huang1,2, Yun Wang1,3, Juan Liu1,3, Pengfei Ye1,3, Bochao Cheng1,3, Huayan Xu1,3, Haibo Qu1,3, Gang Ning1,3.
Abstract
BACKGROUND A growing body of evidence suggests that in the face of life adversity, threats, or other major stressful events, resilience is more conducive to individual adaptation and growth. MATERIAL AND METHODS The Connor-Davidson Resilience Scale and the Chinese Perceived Stress Scale were used to evaluate the resilience and perceived stress of 600 medical staff members from the radiology departments in 32 public hospitals in Sichuan Province, China, respectively. Multiple linear regression was used to analyze factors related to resilience. RESULTS The total resilience score was 65.76±17.26, wherein the toughness dimension score was 33.61±9.52, the strength dimension score was 21.25±5.50, and the optimism dimension score was 10.91±3.15. There was a significant negative correlation between perceived stress and resilience (r=-0.635, P<0.001). According to multivariate analysis, the total perceived stress score (ß=-1.318, P<0.001), gender (ß=-4.738, P<0.001), knowledge of COVID-19 (ß=2.884, P=0.043), knowledge of COVID-19 protective measures (ß=3.260, P=0.042), and availability of adequate protective materials (ß=-1.268, P=0.039) were independent influencing factors for resilience. CONCLUSIONS The resilience level of the medical staff in the radiology departments during the outbreak of COVID-19 was generally low, particularly regarding toughness. More attention should be paid to resilience influence factors such as high perceived stress, female gender, lack of understanding of COVID-19 and protective measures, and lack of protective materials, and targeted interventions should be undertaken to improve the resilience level of the medical staff in the radiology departments during the outbreak of COVID-19.Entities:
Mesh:
Year: 2020 PMID: 32468998 PMCID: PMC7282347 DOI: 10.12659/MSM.925669
Source DB: PubMed Journal: Med Sci Monit ISSN: 1234-1010
Demographic characteristics of participants (N=587).
| Variable | Category | n | % |
|---|---|---|---|
| Gender | Male | 282 | 48.0 |
| Female | 305 | 52.0 | |
| Marital status | Unmarried | 138 | 23.5 |
| Marriage | 439 | 74.8 | |
| Divorced | 10 | 1.7 | |
| Education | Diploma degree | 140 | 23.9 |
| Bachelor degree | 385 | 65.6 | |
| Master’s degree or doctor’s degree | 62 | 10.6 | |
| Job category | Nurse | 119 | 20.3 |
| Technician | 245 | 41.7 | |
| Doctor | 223 | 38.0 | |
| Contact with confirmed/suspected cases at work | Yes | 223 | 38.0 |
| No | 364 | 62.0 | |
| Participant with symptoms | Yes | 34 | 5.8 |
| No | 553 | 94.2 | |
| Family members with symptoms | Yes | 29 | 4.9 |
| No | 558 | 95.1 | |
| Knowledge of COVID-19 | Lack of understanding | 6 | 1.0 |
| Part of understanding | 203 | 34.6 | |
| Significant understanding | 378 | 64.4 | |
| Knowledge of protective measurements | Part of understanding | 169 | 28.8 |
| Significant understanding | 418 | 71.2 | |
| Availability of adequate protective materials | Significant shortage | 77 | 13.1 |
| Partial shortage | 242 | 41.2 | |
| Partial abundance | 157 | 26.7 | |
| Significant abundance | 111 | 18.9 | |
| Knowledge of the psychological hotline | Yes | 395 | 67.3 |
| No | 192 | 32.7 | |
| Whether the participant was concerned about contact with suspected/confirmed cases at work | Yes | 345 | 58.8 |
| No | 242 | 41.2 | |
| Whether the participant was concerned about work-related infections | Yes | 341 | 58.1 |
| No | 246 | 41.9 |
Resilience and the scores for each dimension.
| Variables | Entries | Score ranges | Mean (SD) | Entries mean (SD) |
|---|---|---|---|---|
| Resilience | 25 | 1–100 | 65.76 (17.26) | 2.63 (0.69) |
| Toughness | 13 | 1–52 | 33.61 (9.52) | 2.59 (0.73) |
| Optimism | 4 | 0–16 | 10.91 (3.15) | 2.73 (0.79) |
| Strength | 8 | 0–32 | 21.25 (5.50) | 2.66 (0.69) |
Univariate analyses of the factors associated with resilience (N=587).
| Variable | Category | Mean (SD) | t/F | P |
|---|---|---|---|---|
| Gender | t=5.167 | 0.000 | ||
| Male | 69.51 (17.10) | |||
| Female | 62.30 (16.69) | |||
| Marital status | F=0.034 | 0.966 | ||
| Unmarried | 65.52 (16.39) | |||
| Marriage | 65.86 (17.58) | |||
| Divorced | 64.88 (15.84) | |||
| Education | F=1.369 | 0.255 | ||
| Below the undergraduate | 64.49 (17.92) | |||
| Undergraduate | 65.73 (17.38) | |||
| Master and above | 68.84 (14.64) | |||
| Job category | F=3.647 | 0.027 | ||
| Nurse | 62.16 (18.21) | |||
| Technician | 67.33 (17.77) | |||
| Doctor | 65.97 (15.91) | |||
| Contact with confirmed/suspected cases at work | t=0.217 | 0.828 | ||
| Yes | 65.96 (16.95) | |||
| No | 65.64 (17.46) | |||
| The participant with symptoms | t=−3.125 | 0.002 | ||
| Yes | 56.85 (14.58) | |||
| No | 66.31 (17.27) | |||
| Family members with symptoms | t=−0.552 | 0.581 | ||
| Yes | 64.04 (18.22) | |||
| No | 65.85 (17.22) | |||
| Knowledge of COVID-19 | F=20.534 | 0.001 | ||
| Lack of understanding | 49.43 (12.63) | |||
| Part of understanding | 60.31 (16.41) | |||
| Very understanding | 68.95 (16.91) | |||
| Knowledge of COVID-19 protective measures | t=−6.284 | 0.001 | ||
| Part of understanding | 58.95 (16.10) | |||
| Very understanding | 68.52 (16.96) | |||
| Availability of adequate protective materials | F=3.247 | 0.022 | ||
| Very shortage | 65.39 (19.21) | |||
| Partial shortage | 64.64 (15.85) | |||
| Partial abundance | 64.46 (17.29) | |||
| Very abundance | 70.30 (18.20) | |||
| Knowledge of the psychological hotline | t=3.044 | 0.002 | ||
| Yes | 67.26 (17.36) | |||
| No | 62.68 (16.67) | |||
| Whether the participant was concerned about contact with suspected/confirmed cases at work | t=−2.292 | 0.022 | ||
| Yes | 64.40 (16.94) | |||
| No | 67.71 (17.55) | |||
| Whether the participant was concerned about work-related infections | t=−2.737 | 0.006 | ||
| Yes | 64.12 (16.59) | |||
| No | 68.05 (17.92) |
Hierarchical multiple regression of resilience (N=587).
| Model | B | SE | Beta | P | 95% CI | |
|---|---|---|---|---|---|---|
| Gender | −4.885 | 1.226 | −0.142 | −3.985 | 0.000 | −7.293~−2.478 |
| Participant with symptoms | 3.279 | 2.394 | 0.044 | 1.369 | 0.171 | −1.424~7.982 |
| Knowledge of COVID-19 | 2.849 | 1.425 | 0.083 | 1.999 | 0.046 | 0.049~5.648 |
| Knowledge of COVID-19 protective measures | 3.323 | 1.605 | 0.087 | 2.070 | 0.039 | 0.169~6.476 |
| availability of adequate protective materials | −1.270 | 0.615 | −0.070 | −2.067 | 0.039 | −2.478~−0.063 |
| Knowledge of the psychological hotline | −1.315 | 1.220 | −0.036 | −1.078 | 0.281 | −3.712~1.081 |
| Whether the participant was concerned about contact with suspected/confirmed cases at work | 2.090 | 1.305 | 0.060 | 1.601 | 0.110 | −0.474~4.653 |
| Whether the participant was concerned about work-related infections | −0.005 | 1.276 | 0.000 | −0.004 | 0.997 | −2.512~2.501 |
| The total perceived stress score | −1.318 | 0.078 | −0.581 | −16.900 | 0.000 | −1.475~−1.167 |
| Job category=nurse | 0.676 | 1.630 | 0.016 | 0.415 | 0.679 | −2.526~3.878 |
| Job category=doctor | 0.464 | 1.251 | 0.013 | 0.371 | 0.711 | −1.993~2.920 |
F=38.738, P=0.000, R2=0.426, Adjusted R2=0.415.