| Literature DB >> 29867005 |
Yanhong Hu1, Xiaomin Wang2, Joseph D Tucker3, Paul Little4, Michael Moore5, Keiji Fukuda6, Xudong Zhou7.
Abstract
OBJECTIVE: Inappropriate antibiotic use leads to antibiotic resistance. This has become a serious global crisis, with more multi-drug resistant infections and fewer effective antibiotics available. This study aims to understand knowledge, attitude, and practice (KAP) with respect to antibiotic use for self-limiting illnesses among medical students in China.Entities:
Keywords: antibiotic use; knowledge and attitude; medical students; multicentre
Mesh:
Substances:
Year: 2018 PMID: 29867005 PMCID: PMC6025109 DOI: 10.3390/ijerph15061165
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Questionnaire details were based on knowledge, attitude, and practice (KAP) constructs in the survey among medical students in China in 2015.
| Constructs | Questionnaire |
|---|---|
| Knowledge | 1. Antibiotics are effective for viral infections |
| Attitude | (1) Yes (2) No (3) Unknown/Uncertain |
| Practice | 16.1. What illness/symptoms have you had in the last month? |
Socio-demographic characteristics of university medical students in China in 2015 (n = 1819).
| Characteristics | |
|---|---|
| University (Province) | |
| Nankai University (Tianjin) | 281 (15.5%) |
| Zhejiang University (Zhejiang) | 302 (16.6%) |
| Jilin University (Jilin) | 341 (18.8%) |
| Wuhan University (Hubei) | 303 (16.7%) |
| Lanzhou University (Gansu) | 292 (16.1%) |
| Guizhou University (Guizhou) | 300 (16.5%) |
| Gender | |
| Male | 661 (36.3%) |
| Female | 1158 (63.7%) |
| Age (years) | |
| 16–20 | 717 (39.4%) |
| 21–25 | 980 (53.9%) |
| 26–40 | 122 (6.71%) |
| Education level | |
| Diploma-B. A | 1244 (68.4%) |
| Master–PhD | 575 (31.6%) |
| Study year | |
| Uy1–Uy3/pre clinic | 779 (42.8%) |
| Uy4–Uy8/post clinic | 1040(57.2%) |
| Father’s education | |
| Less than college level | 1341 (73.4%) |
| Above college level | 478 (26.3%) |
| Mother’s education | |
| Less than college level | 1448 (79.6%) |
| Above college level | 3718 (20.4%) |
| Medical background father | |
| Yes | 106 (5.8%) |
| No | 1713 (94.2%) |
| Medical background mother | |
| Yes | 124 (6.8%) |
| No | 1695 (93.2%) |
| Household income/month | |
| < US$1538 | 1565 (86.0%) |
| =/> US$1538 | 254 (14.0%) |
| Hometown | |
| Rural | 916 (50.4%) |
| Urban | 903 (49.6%) |
Antibiotic use behaviour for self-limiting illness symptoms among medical students in China in 2015 (n = 1819).
| Symptoms | Cases ( | SM | SMA | See a Doctor | Antibiotic Prescribed | Injectable Antibiotics | With no Specific Treatment |
|---|---|---|---|---|---|---|---|
| Cold | 363 | 215 (59.2%) | 66 (30.7%) | 61 (16.8%) | 40 (65.6%) | 14 (35.0%) | 87 (24.0%) |
| Fever | 72 | 33 (45.8%) | 11 (33.3%) | 25 (34.7%) | 20 (80.0%) | 8 (40.0%) | 14 (19.4%) |
| Sore throat | 182 | 104 (57.1%) | 36 (34.6%) | 36 (19.8%) | 27 (75.0%) | 11 (40.7%) | 42 (23.1%) |
| Ear pain | 29 | 9 (31.0%) | 5 (55.6%) | 15 (51.7%) | 11 (73.3%) | 4 (36.4%) | 5 (17.2%) |
| Headache | 81 | 47 (58.0%) | 12 (25.5%) | 18 (22.2%) | 14 (77.8%) | 6 (42.9%) | 16 (19.8%) |
| Flu-like illness | 23 | 9 (39.1%) | 5 (55.6%) | 15 (65.2%) | 8 (53.3%) | 4 (50.0%) | 5 (21.7%) |
| Diarrhoea | 95 | 50 (52.6%) | 16 (32.0%) | 17 (17.9%) | 10 (58.8%) | 2 (20.0%) | 28 (29.5%) |
| Suspected pneumonia | 8 | 2 (25.0%) | 1 (50.0%) | 6 (75.0%) | 4 (66.7%) | 1 (25.0%) | 0 (0%) |
| Abdominal pain | 47 | 25 (53.2%) | 4 (16.0%) | 7 (14.9%) | 5 (71.4%) | 1 (20.0%) | 15 (31.9%) |
Note: SM: Self-medication; SMA: Self-medication with antibiotics; Students may have overlapping symptoms; the total number of students who reported having illness in the past month was 529.
Figure 1Self-medication with antibiotics in Chinese medical students in the past month in 2015 (n = 1819).
Determining factors related to antibiotic use behaviours among medical students in China in 2015.
| SM |
| SMA |
| Stock |
| Demand |
| Prophylaxis |
| |
|---|---|---|---|---|---|---|---|---|---|---|
| Universities | 0.001 | 0.082 | 0.010 | 0.006 | 0.001 | |||||
| Lanzhou | 59 (20.2%) | 20 (6.9%) | 191 (65.4%) | 55 (18.8%) | 58 (19.9%) | |||||
| Nankai | 62 (22.1%) | 15 (5.3%) | 201 (71.5%) | 29 (10.3%) | 29 (10.3%) | |||||
| Jilin | 45 (13.2%) | 14 (4.1%) | 215 (63.1%) | 61 (17.9%) | 53 (15.5%) | |||||
| Wuhan | 33 (10.9%) | 9 (3.0%) | 171 (56.4%) | 33 (10.9%) | 33 (10.9%) | |||||
| Zhejiang | 44 (14.6%) | 7 (2.3%) | 192 (63.6%) | 42 (13.9%) | 44 (14.6%) | |||||
| Guizhou | 42 (14.0%) | 12 (4.2%) | 196 (65.3%) | 53 (17.7%) | 62 (20.7%) | |||||
| Age (years) | 0.947 | 0.440 | 0.002 | 0.061 | 0.097 | |||||
| 16–20 | 114 (15.9%) | 35 (4.9%) | 464 (64.7%) | 90 (12.6%) | 125 (17.4%) | |||||
| 21–25 | 153 (15.6%) | 36 (3.7%) | 607 (61.9%) | 163(16.6%) | 140 (14.3%) | |||||
| 26–40 | 18 (14.8%) | 6 (4.9%) | 95 (77.9%) | 20 (16.4%) | 14 (11.5%) | |||||
| Sex | 0.455 | 0.470 | 0.021 | 0.662 | 0.065 | |||||
| Male | 98 (14.8%) | 25 (3.8%) | 401 (60.7%) | 96 (14.5%) | 115 (17.4%) | |||||
| Female | 187 (16.2%) | 52 (4.5%) | 765 (66.1%) | 177 (15.3%) | 164 (14.2%) | |||||
| Study year | 0.327 | 0.654 | 0.412 | 0.001 | 0.101 | |||||
| Uy1–Uy3 | 78 (16.8%) | 20 (2.5%) | 494 (63.4%) | 40 (14.7%) | 147 (18.9%) | |||||
| Uy4–Uy8 | 112 (19.5%) | 38 (3.4%) | 290 (62.4%) | 532 (68.3.%) | 68 (14.1%) | |||||
| Education level | 0.480 | 0.277 | 0.158 | 0.131 | 0.016 | |||||
| Diploma-B. A | 200 (16.1%) | 57 (4.6%) | 784 (63.0%) | 176 (14.2%) | 208 (16.7%) | |||||
| Master/PhD | 85(14.8%) | 20 (3.5%) | 382 (66.4%) | 97 (16.9%) | 71 (12.4%) | |||||
| Father with medical background | 0.042 | 0.081 | 0.036 | 0.558 | 0.111 | |||||
| Yes | 24 (22.6%) | 8 (7.6%) | 78(73.6%) | 18 (16.9%) | 22 (20.8%) | |||||
| No | 261 (15.2%) | 69 (4.0%) | 1088 (63.5%) | 255 (14.9%) | 257 (15.0%) | |||||
| Mother with Medical background | <0.001 | 0.008 | <0.001 | 0.675 | 0.123 | |||||
| Yes | 34 (27.4%) | 11 (8.9%) | 100 (80.7%) | 17(13.7%) | 25 (20.2%) | |||||
| No | 251 (14.8%) | 66 (3.9%) | 1066 (62.9%) | 256 (15.1%) | 254 (15.0%) | |||||
| Father’s education level | <0.001 | 0.020 | <0.001 | 0.192 | 0.919 | |||||
| No college | 177 (13.2%) | 48 (3.6%) | 811 (60.5%) | 210 (15.7%) | 205 (15.3%) | |||||
| College | 108 (22.6%) | 29 (6.1%) | 355 (74.3%) | 63 (13.2%) | 74 (15.5%) | |||||
| Mother’s education level | <0.001 | 0.007 | <0.001 | 0.082 | 0.988 | |||||
| No college | 203 (14.0%) | 52 (3.6%) | 898 (62%) | 228(15.8%) | 222 (15.3%) | |||||
| College | 82 (22.1%) | 25 (6.8%) | 268 (72.2%) | 45 (12.1%) | 57 (15.4%) | |||||
| Household income (Monthly) | 0.014 | 0.015 | 0.383 | 0.177 | 0.040 | |||||
| High | 232 (14.8%) | 59 (3.8%) | 997 (63.7%) | 242 (15.5%) | 251 (16.0%) | |||||
| Low | 53 (20.9%) | 18 (7.1%) | 169 (66.5%) | 31 (12.2%) | 28 (11.0%) | |||||
| Hometown | <0.001 | 0.041 | <0.001 | 0.263 | 0.016 | |||||
| Rural | 108 (11.8%) | 30 (3.3%) | 523 (57.1%) | 146 (15.9%) | 159 (17.4%) | |||||
| Urban | 177 (19.6%) | 47 (5.2%) | 643 (71.2%) | 127 (14.1%) | 120 (13.3%) | |||||
| KAP score | 0.219 | 0.091 | 0.131 | 0.025 | <0.001 | |||||
| 0–7 | 15 (17.7%) | 7 (8.2%) | 49 (57.7%) | 20 (23.5%) | 25 (29.4%) | |||||
| 8–12 | 168 (16.8%) | 45 (4.5%) | 659 (65.9%) | 157 (15.7%) | 169 (16.9%) | |||||
| 13–15 | 102 (13.9%) | 25 (3.4%) | 458 (62.3%) | 96 (13.1%) | 85 (11.6%) |
Notes: SM: self medication; SMA: Self medication with antibiotics; B.A: Bachelor degree/ undergraduate degree; PhD: Doctor of Philosophy; KAP: knowledge, attitude, and practice.
Logistic regression for the characteristics associated with the five behaviour outcomes among medical students in China in 2015.
| SM | Stock | Demand | SMA | Prophylaxis | ||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Factors | aOR (95% CI) |
| aOR (95% CI) |
| aOR (95% CI) |
| aOR (95% CI) |
| aOR (95% CI) |
|
| Sex | ||||||||||
| Female | 1.20 (1.04–1.56) | 0.02 | ||||||||
| Male | ref | |||||||||
| Age | ||||||||||
| 21–30 | 1.50 (1.00–2.20) | 0.049 | ||||||||
| 31–40 | 1.50 (0.75–2.90) | 0.264 | ||||||||
| Father’s educational level | ||||||||||
| Above college | 1.50 (0.99–1.20) | 0.052 | 1.60 (1.10–2.30) | 0.007 | ||||||
| Less college | ref | ref | ||||||||
| Hometown | 1.50 (1.10–2.00) | 0.012 | ||||||||
| Urban | 1.60 (1.20–1.90) | <0.001 | 0.69 (0.50–0.94) | 0.019 | ||||||
| Rural | ref | ref | ref | |||||||
| Mother with medical background | ||||||||||
| No | 0.62 (0.39–0.99) | 0.049 | 0.53 (0.32–0.88) | 0.014 | ||||||
| Yes | ref | ref | ||||||||
| KAP score | ||||||||||
| 8–12 | 0.58 (0.34–0.98) | 0.045 | 0.52 (0.22–1.22) | 0.132 | 0.52 (0.32–0.86) | 0.011 | ||||
| 12–15 | 0.46 (0.26–0.81) | 0.007 | 0.37 (0.15–0.91) | 0.031 | 0.35 (0.21–0.60) | <0.001 | ||||
| 0–7 | ref | ref | ref |
Note: Adjusted for university, age, sex, education level, hometown, household income, study year, parent’s education background, and whether parents with medical background. aOR: adjusted odd ratio. SM: Self-medication, SMA: Self-medication with antibiotics; KAP: knowledge, attitude, and practice.