| Literature DB >> 33224921 |
Diep Ngoc Nguyen1,2, Huong Thi Le3, Phong Khanh Thai4, Xuan Thi Thanh Le3, Men Thi Hoang1,2, Linh Gia Vu5, Toan Thi Thanh Do3, Khanh Nam Do3, Giap Van Vu6,7, Tu Huu Nguyen8, Thanh Tuan Le9, Trung Dinh Tran10, Dat Van Truong11, Cuong Duy Do12, Thu Ha Nguyen3, Dung Tri Phung13, Son Hong Nghiem14, Thuc Thi Minh Vu3, Bach Xuan Tran3,15, Carl A Latkin15, Roger C M Ho16,17, Cyrus S H Ho18.
Abstract
Upon the outbreak of the COVID-19 pandemic, countries worldwide face a critical shortage of human resources in the health sector. Medical students are a potential task force with the capability to support the stretched health sector. This study aims to evaluate their training need for epidemic control in order to employ them effectively. A cross-sectional study was conducted using a web-based survey from December 2019 to February 2020. There were 5,786 observations collected using the snowball sampling technique. Logistic regression was applied to identify factors associated with training participation in epidemic prevention and disaster prevention. Multiple Poisson regression model was constructed to examine factors associated with the number of times they participated in sanitation training and disaster prevention activities in the previous 12 months. Sanitation and health education communication activities had the highest proportion of participants, with 76.5 and 38.4%, followed by examining and treating diseases in the community (13.4%). Those who participated in community activities had a higher number of times to participate in epidemic sanitation training and be involved in disaster prevention. This study informed the need for training programs to prepare medical students for COVID-19 epidemic responses. The training curriculum should include both theoretical approaches and contextual approaches to achieve efficient epidemic control.Entities:
Keywords: COVID-19; epidemic control; infection; medical students; training need
Mesh:
Year: 2020 PMID: 33224921 PMCID: PMC7674483 DOI: 10.3389/fpubh.2020.589331
Source DB: PubMed Journal: Front Public Health ISSN: 2296-2565
Socioeconomic characteristics of medical students.
| Total | 2,019 | 34.9 | 1,189 | 20.6 | 1,198 | 20.7 | 1,380 | 23.9 | 5,786 | 100.0 | |
| Male | 589 | 29.2 | 338 | 28.4 | 320 | 26.7 | 205 | 14.9 | 1,452 | 25.1 | <0.01 |
| Female | 1,429 | 70.8 | 851 | 71.6 | 878 | 73.3 | 1,175 | 85.1 | 4,333 | 74.9 | |
| Urban | 1,782 | 88.8 | 1,039 | 88.1 | 1,056 | 88.6 | 1,161 | 85.1 | 5,038 | 87.7 | 0.01 |
| Rural | 225 | 11.2 | 141 | 12.0 | 136 | 11.4 | 204 | 15.0 | 706 | 12.3 | |
| Single | 1,985 | 98.4 | 1,173 | 98.8 | 1,178 | 98.7 | 1,355 | 98.2 | 5,691 | 98.5 | 0.57 |
| Others | 32 | 1.6 | 14 | 1.2 | 16 | 1.3 | 25 | 1.8 | 87 | 1.5 | |
| Northern | 276 | 14.1 | 495 | 42.9 | 171 | 14.6 | 537 | 39.9 | 1,479 | 26.2 | <0.01 |
| Central | 117 | 6.0 | 58 | 5.0 | 82 | 7.0 | 45 | 3.3 | 302 | 5.4 | |
| South | 1,570 | 80.0 | 601 | 52.1 | 920 | 78.4 | 765 | 56.8 | 3,856 | 68.4 | |
| Yes | 885 | 43.9 | 525 | 44.2 | 455 | 38.1 | 555 | 40.3 | 2,420 | 41.9 | <0.01 |
| No | 1,131 | 56.1 | 663 | 55.8 | 739 | 61.9 | 823 | 59.7 | 3,356 | 58.1 | |
| Under 20 | 602 | 31.8 | 291 | 26.2 | 338 | 29.7 | 610 | 46.9 | 1,841 | 33.8 | <0.01 |
| 20 and above | 1,290 | 68.2 | 821 | 73.8 | 802 | 70.4 | 692 | 53.2 | 3,605 | 66.2 | |
| Age, mean (SD) | 20.8 | (1.9) | 20.7 | (1.5) | 20.6 | (1.6) | 20.1 | (1.8) | 20.6 | (1.7) | <0.01 |
Chi-square test.
Kruskal–Wallis test.
Training and practice for epidemic control among medical students.
| Attend training classes on hygiene in epidemic prevention and disaster prevention | 1,771 | 87.7 | 1,033 | 86.9 | 1,058 | 88.3 | 1,204 | 87.3 | 5,066 | 87.6 | 0.73 |
| Involved in disaster prevention | 1,839 | 91.1 | 1,102 | 92.7 | 1,111 | 92.7 | 1,249 | 90.5 | 5,301 | 91.6 | 0.09 |
| Environmental sanitation | 1,330 | 72.3 | 835 | 75.8 | 917 | 82.5 | 975 | 78.1 | 4,057 | 76.5 | <0.01 |
| Health education communication | 795 | 43.2 | 450 | 40.8 | 355 | 32.0 | 436 | 34.9 | 2,036 | 38.4 | <0.01 |
| Examining and treating diseases in the community | 310 | 16.9 | 135 | 12.3 | 122 | 11.0 | 141 | 11.3 | 708 | 13.4 | <0.01 |
| Mobilize community participation | 206 | 11.2 | 137 | 12.4 | 141 | 12.7 | 125 | 10.0 | 609 | 11.5 | 0.15 |
| Support for life and social security in the locality | 149 | 8.1 | 76 | 6.9 | 103 | 9.3 | 66 | 5.3 | 394 | 7.4 | <0.01 |
| Detect and notify epidemics/natural disasters | 60 | 3.3 | 48 | 4.4 | 29 | 2.6 | 27 | 2.2 | 164 | 3.1 | 0.02 |
| Control and isolate affected areas | 39 | 2.1 | 28 | 2.5 | 25 | 2.3 | 14 | 1.1 | 106 | 2.0 | 0.07 |
| Number of times participating in epidemic sanitation training (per year), mean (SD) | 1.1 | 1.4 | 1.0 | 1.4 | 0.9 | 1.4 | 0.9 | 1.3 | 1.0 | 1.4 | 0.43 |
| Number of times involved in disaster prevention (per year), mean (SD) | 1.3 | 1.0 | 1.2 | 1.0 | 0.9 | 1.0 | 0.9 | 0.8 | 1.1 | 1.0 | 0.01 |
Chi-square test.
Kruskal–Wallis test.
Agreement on the importance of local hygiene and disease prevention measures.
| Early prevention, environmental sanitation, and population health improvement | 744 | 36.9 | 392 | 33.0 | 480 | 40.1 | 494 | 35.8 | 2,110 | 36.5 | <0.01 |
| Mobilization of community participation in disease control | 662 | 32.8 | 365 | 30.7 | 407 | 34.0 | 470 | 34.1 | 1,904 | 32.9 | 0.25 |
| Training on up to date scientific knowledge | 708 | 35.1 | 318 | 26.8 | 410 | 34.2 | 443 | 32.1 | 1,879 | 32.5 | <0.01 |
| Raising awareness on the impacts of climate change | 635 | 31.5 | 317 | 26.7 | 390 | 32.6 | 416 | 30.1 | 1,758 | 30.4 | 0.01 |
| Ensuring adequate budget for disease prevention | 595 | 29.5 | 288 | 24.2 | 387 | 32.3 | 400 | 29.0 | 1,670 | 28.9 | <0.01 |
| Periodic surveillance for infectious diseases | 605 | 30.0 | 297 | 25.0 | 355 | 29.6 | 411 | 29.8 | 1,668 | 28.8 | 0.01 |
| Strengthening health communication and education programs | 571 | 28.3 | 283 | 23.8 | 330 | 27.6 | 395 | 28.6 | 1,579 | 27.3 | 0.02 |
| Development of epidemic forecasts systems to provide early warning | 545 | 27.0 | 274 | 23.0 | 327 | 27.3 | 370 | 26.8 | 1,516 | 26.2 | 0.05 |
| Improvement of interdisciplinary scientific research capacity | 550 | 27.2 | 250 | 21.0 | 323 | 27.0 | 349 | 25.3 | 1,472 | 25.4 | <0.01 |
| Workforce support for preventive medicine sectors | 545 | 27.0 | 243 | 20.4 | 311 | 26.0 | 357 | 25.9 | 1,456 | 25.2 | <0.01 |
| Development of guidelines for disease prevention | 519 | 25.7 | 246 | 20.7 | 303 | 25.3 | 344 | 24.9 | 1,412 | 24.4 | 0.01 |
| Increasing coordination among local actors | 510 | 25.3 | 236 | 19.9 | 275 | 23.0 | 342 | 24.8 | 1,363 | 23.6 | <0.01 |
Kruskal–Wallis test.
Associated factors with training and practice for epidemic control among medical students.
| Gender (female vs. male) | −0.11 | −0.28, 0.06 | −0.06 | −0.11, −0.02 | ||||
| Marital status (living with spouse vs. single) | 0.28 | −0.03, 0.60 | 2.26 | 0.71, 7.23 | ||||
| Age group (20 and above vs. under 20) | −0.13 | −0.26, −0.00 | 1.14 | 0.93, 1.40 | ||||
| Participated in community activities (yes vs. no) | 0.88 | 0.74, 1.03 | 0.22 | 0.09, 0.35 | 1.46 | 1.19, 1.79 | 0.21 | 0.17, 0.24 |
| Central | 0.71 | 0.49, 1.03 | ||||||
| South | 0.83 | 0.68, 1.01 | 1.19 | 0.96, 1.47 | ||||
| General doctor | 1.25 | 0.96, 1.62 | ||||||
| Pharmacist | −0.20 | −0.37, −0.03 | 1.24 | 0.96, 1.60 | ||||
| Others | −0.14 | −0.29, 0.00 | −0.08 | −0.12, −0.04 | ||||
| Development of epidemic forecast systems to provide early warning | −0.04 | −0.10, 0.02 | ||||||
| Ensuring adequate budget for disease prevention | 0.06 | 0.01, 0.11 | ||||||
| Workforce support for preventive medicine sectors | 0.07 | 0.01, 0.13 | ||||||
| Increasing coordination among local actors | 1.86 | 1.42, 2.44 | ||||||
p < 0.01,
p < 0.05,
p < 0.1.
Multivariate logistic regression.
Multivariate Poisson regression.