| Literature DB >> 29980174 |
Mohammed Assen Seid1, Mohammed Seid Hussen2.
Abstract
BACKGROUND: Globally, antimicrobial resistance (AMR) is a complex public problem, which is mainly fuelled by inappropriate use of antimicrobials. Rational use of antimicrobials is the main strategy for the prevention of AMR, which can be achieved by changing the prescribers' behavior and knowledge. Hence, this study aimed to assess knowledge and attitude of paramedical students regarding antimicrobial resistance, which helps to rationalize the use of antimicrobials.Entities:
Keywords: Antimicrobial resistance; Ethiopia; Knowledge; Paramedical students
Mesh:
Substances:
Year: 2018 PMID: 29980174 PMCID: PMC6035414 DOI: 10.1186/s12879-018-3199-1
Source DB: PubMed Journal: BMC Infect Dis ISSN: 1471-2334 Impact factor: 3.090
Characteristics of study participants in College of Medicine and Health Sciences, University of Gondar, North West Ethiopia, 2016 (n = 323)
| Variables | Frequency | Percent |
|---|---|---|
| Sex | ||
| Male | 202 | 62.5 |
| Female | 121 | 37.5 |
| Department | ||
| Midwifery | 101 | 31.3 |
| Health Officer | 83 | 25.7 |
| Nursing | 75 | 23.2 |
| Pharmacy | 41 | 12.7 |
| Optometry | 23 | 7.1 |
Participants’ knowledge about antimicrobial resistances among paramedical health science students at University of Gondar, North West Ethiopia, 2016 (n = 323)
| Items | Correct | Incorrect |
|---|---|---|
| General knowledge about antibiotics | ||
| 1. Does inappropriate use of antibiotics put your patients at risk? | 319(98.8%) | 4(1.2%) |
| 2. Does the frequent use of antibiotics will decrease its efficacy? | 266(82.4%) | 57(16.6%) |
| 3. Do antibiotics speed up the recovery of common cold and flu? | 113(35%) | 210(65%) |
| 4. Do antibiotics kill both viruses and bacteria? | 233(72.1%) | 90(27.9%) |
| 5. Which of these do you think may promote the inappropriate use of antimicrobials? | ||
| Poor counseling of patients | 180(55.7%) | 143(43.3%) |
| Poor skills and knowledge of prescribers | 183(56.7%) | 140(43.3%) |
| Patient Self medication | 113(35%) | 210(65%) |
| Inadequate supervision | 82(25.4%) | 241(74.6%) |
| 6. Which of these factors may influence the decision to start antimicrobial therapy? | ||
| Patient’s clinical condition | 170(52.6%) | 153(47.4%) |
| Positive microbiological results in symptomatic patients | 201(62.2%) | 122(37.8%) |
| 7. Which of the following do you think are the consequences of antimicrobials overuse? | ||
| Antimicrobial resistance | 181(56%) | 142(44%) |
| Adverse drug reactions and medication errors | 193(59.8%) | 130(40.2%) |
| Better patient outcome | 315(97.5%) | 8(2.5%) |
| 8. Which of the following promote antimicrobial resistances? | ||
| Inappropriate prescribing habits of antibiotics | 163(50.5%) | 160(49.5%) |
| Lack of effective diagnostics tools to diagnose bacterial infections | 171(52.9%) | 152(47.1%) |
| Patients self-medication | 202(62.5%) | 121(37.%) |
| Spread of bacteria in healthcare settings due to poor hygiene practices | 62(19.2%) | 261(80.8%) |
| 9. Which of the following are appropriate strategies to control antimicrobial resistance? | ||
| Targeting antimicrobial therapy to likely pathogens | 149(46.1%) | 174(53.9%) |
| Changing the attitudes of prescribers and patients | 165(51.1%) | 158(48.9%) |
| Obtaining local antimicrobial resistance profile | 63(19.5%) | 260(80.5%) |
| Consulting with infectious diseases experts | 112(34.7%) | 211(65.3%) |
| Overall level of knowledge | Frequency (%) | |
| Good | 39(12.1) | |
| Moderate | 107(33.1) | |
| Poor | 177(54.8) | |
Fig. 1Participants’ source of information about antimicrobial resistance at University of Gondar, North West Ethiopia, 2016 (n = 323)
Participants’attitude towards antimicrobial resistances among paramedical health science students at University of Gondar, North West Ethiopia, 2016 (n = 323)
| Items | Response | ||
|---|---|---|---|
| Agree | Neutral | Disagree | |
| 1. Antimicrobial resistance will affect you and your family’s health. | 293(90.7%) | 19(5.9%) | 11(3.4%) |
| 2. It is necessary to give more education for final year students about antimicrobial resistance. | 307(95.0%) | 8(2.5%) | 8(2.5%) |
| 3. Inappropriate use of antimicrobials causes antimicrobial resistance. | 304(94.1) | 9(2.8%) | 10(3.1%) |
| 4. Poor infection control practices by healthcare professionals will cause the spread of antimicrobial resistance. | 299(92.6%) | 9(2.8%) | 15(4.6%) |
| 5. Final year students should get special training on the appropriate prescribing of antimicrobials before exit. | 310(96.0%) | 4(1.2%) | 9(2.8%) |
| 6. You have to follow the recommendations of your hospital antimicrobial guidelines in the future. | 233(72.1%) | 75(23.2%) | 15(4.6%) |
| 7. Currently, antimicrobial resistance is a major problem in the world as well as in Ethiopia. | 228(70.6%) | 26 (8.0%) | 69(21.4%) |
| 8. Antibiotic prescribing should be more closely controlled. | 289(89.5%) | 10(3.1%) | 24(7.4%) |
| 9. Dispensing antibiotics without prescription should be more closely controlled. | 272(84.2%) | 19(5.9) | 32(9.9%) |
| 10. People’s socioeconomic status has an effect on the risk of being affected by antibiotic resistance. | 249(77.1%) | 29(9.0%) | 45(13.9%) |
| 11. The consequences of antibiotic resistance will affect your future work as a health professional when caring for patients with bacterial infections. | 282(87.3%) | 8(2.5%) | 33(10.2%) |
| 12. Students can contribute to the work being done to control antimicrobial resistances. | 284(87.9%) | 21(6.5) | 18 (5.6%) |
| Overall level of attitude | Positive | Neutral | Negative |
| 311(96.3%) | 10(3.1%) | 2(0.6%) | |
Kruskal Wallis test to compare the participants’ knowledge and attitude score variation across their department at University of Gondar, North West Ethiopia, 2016 (n = 323)
| Knowledge and attitude score classified by Department | |||||||
|---|---|---|---|---|---|---|---|
| Department | Frequency | Median (range) | Mean rank (R) | df | Test value (H) | ||
| Knowledge Score | Pharmacy | 41 | 11(5–19) | 167 | 4 | 36.48 | < 0.0001 |
| Nursing | 75 | 9(6–16) | 124 | ||||
| Health officer | 83 | 13(4–20) | 209 | ||||
| Optometry | 23 | 12(6–19) | 167 | ||||
| Midwifery | 101 | 10(5–12) | 149 | ||||
| Attitude Score | Pharmacy | 41 | 35(30–36) | 180 | 4 | 17.049 | 0.002 |
| Nursing | 75 | 34(28–36) | 163 | ||||
| Health officer | 83 | 34(29–36) | 188 | ||||
| Optometry | 23 | 34(20–36) | 132 | ||||
| Midwifery | 101 | 34(21–36) | 139 | ||||
| Total | 323 | ||||||
The difference is significant at α =0.05(i.e. χ2=9.488)
Kruskal Wallis H test for comparison of the participants’ attitude score by their level of knowledge at University of Gondar, North West Ethiopia, 2016 (n = 323)
| Attitude score classified by Participants’ their level of knowledge | |||||||
|---|---|---|---|---|---|---|---|
| Knowledge | Frequency | Mean score | Mean rank(R) | df | Test value(H) | ||
| Attitude Score | Good | 39 | 35 | 212.4 | 2 | 32.9 | < 0.0001 |
| Moderate | 107 | 34.3 | 186.2 | ||||
| Poor | 177 | 32.7 | 136.3 | ||||
| Total | 323 | ||||||
The difference is significant at α =0.05(i.e. χ2 = 9.488)