| Literature DB >> 31714110 |
Peter W Smith1, Michael Agbaje, Lerica LeRoux-Pullen, Deborah Van Dyk, Legesse K Debusho, Aminu Shittu, Mohamed M Sirdar, Olubunmi G Fasanmi, Oluwawemimo Adebowale, Folorunso O Fasina.
Abstract
Understanding the knowledge and perceptions of veterinary students of antimicrobial resistance (AMR) as potential future prescribers of antimicrobials may serve as an opportunity to improve stewardship of AMR. Pre-final (n = 42) and final (n = 29) year veterinary students of the University of Pretoria completed questionnaires to determine their knowledge and perceptions of AMR. Of the 71 respondents, mixed practice (48%) and small animal practice (45%) were the most preferred career choices post-graduation, with the field of gross pathology being the least preferred. Over 80% of the respondents believed that veterinary practitioners' misuse of antimicrobials contributes to AMR and a higher percentage (98.6%) believed that farmers' misuse of antimicrobials encourages the development of AMR, in particular, in food animals (60.6%) compared to companion animals (50.7%). Agreement in the ranking of abuse of antimicrobials between pre-final and final year students was fair (36.4%; kappa 0.3), and the most abused antimicrobials in descending order listed by the students were tetracyclines, penicillins, sulphonamides and aminoglycosides. There was wide disparity between training and potential field application, as well as variations in the correct matching of antimicrobials to their respective antibiotic classes. Responses to the clinical application of antimicrobials also varied widely. Despite the apparent teaching of AMR to veterinary students, gaps may exist in the translation of theoretical concepts to clinical applications, hence the need for focused and targeted antimicrobial prescription and stewardship training to bridge these potential identified gaps.Entities:
Keywords: antimicrobials; perception; practice; stewardship; training; undergraduate students
Mesh:
Substances:
Year: 2019 PMID: 31714110 PMCID: PMC6854391 DOI: 10.4102/jsava.v90i0.1765
Source DB: PubMed Journal: J S Afr Vet Assoc ISSN: 1019-9128 Impact factor: 1.474
Descriptive statistics and career choices of pre-final year and final year veterinary students, Faculty of Veterinary Science, University of Pretoria, Onderstepoort, South Africa.
| Variable ( | Category | Number | % | 95% confidence interval |
|---|---|---|---|---|
| Gender | Male | 19 | 26.8 | 16.2; 37.3 |
| Female | 52 | 73.2 | 62.7; 83.8 | |
| Class | Final year | 29 | 40.8 | 29.1; 52.6 |
| Pre-final year | 42 | 59.1 | 47.4; 70.9 | |
| Likely career choice post-graduation | Small animal practice | 32 | 45.1 | 33.8; 56.7 |
| Equine practice | 13 | 18.3 | 10.6; 28.6 | |
| Mixed practice | 34 | 47.9 | 36.5; 59.5 | |
| Feedlot | 6 | 8.5 | 3.5; 16.8 | |
| Dairy | 8 | 11.3 | 5.4; 20.3 | |
| Wildlife | 19 | 26.8 | 17.5; 37.9 | |
| Gross pathology | 0 | 0 | ||
| Pharmaceutical industry | 3 | 4.2 | 1.1; 11.1 | |
| State service | 8 | 11.3 | 5.4; 20.3 | |
| Beef cattle | 15 | 21.1 | 12.8; 31.8 | |
| Sheep and goats | 11 | 15.5 | 8.4; 25.3 | |
| Pig | 7 | 9.9 | 4.4; 18.5 | |
| Poultry | 7 | 9.9 | 4.4; 18.5 | |
| Laboratory medicine or clinical pathology | 2 | 2.8 | 0.5; 9.0 | |
| Exotic pet medicine | 11 | 15.5 | 8.4; 25.3 | |
| Education | 3 | 4.2 | 1.1; 11.1 | |
| Undecided | 6 | 8.5 | 3.5; 16.8 | |
| Other choices | 5 | 7.0 | 2.6; 14.9 | |
| Previous knowledge in the field | No | 64 | 90.1 | 83.0; 97.2 |
| Yes | 7 | 9.9 | 2.8; 17.0 |
, The mean ± standard deviation for number of career choice is 3 ± 2; (Minimum = 1; Median = 2; Maximum = 12; one person made no choice) and the mean ± standard deviation for age of all respondents was 25.2 ± 3.1 years (Minimum = 22; Median = 25; Maximum = 41 years).
, Previous knowledge in the field means the student has done previous studies at post-secondary school levels in pharmacology, biological research, microbiology or pharmacy, which may bias the opinion of the respondent or influence the responses to antimicrobial-related questions.
Perception of antimicrobials of all students who agreed or strongly agreed to the questions.
| Variable | All % ( | Pre-final % ( | Final % ( | |
|---|---|---|---|---|
| Antimicrobial resistance is an increasing global threat to human and animal health | 100.0 | 100.0 | 100.0 | 1.00 |
| The misuse of antimicrobials by veterinary practitioners contributes significantly to antimicrobial resistance | 84.5 | 81.0 | 89.3 | 0.35 |
| The misuse of antimicrobials by farmers contributes significantly to antimicrobial resistance | 98.6 | 97.6 | 100.0 | 0.41 |
| The inappropriate use of antimicrobials in food-producing animals significantly contributes to antimicrobial resistance in human pathogens | 60.6 | 59.5 | 60.7 | 0.92 |
| The inappropriate prescription of antimicrobials by human medical doctors is the main contributor to antimicrobial resistance in human pathogens | 94.4 | 95.2 | 92.9 | 0.68 |
| I have received formal lectures on the rational use of antimicrobials during my undergraduate training | 98.6 | 97.6 | 100.0 | 0.41 |
| My undergraduate training has prepared me well for making informed decisions when choosing an ideal antimicrobial for an individual patient | 76.1 | 73.8 | 78.6 | 0.65 |
| As an individual in practice, I can significantly contribute to preventing an increase in antimicrobial resistance | 84.5 | 85.7 | 85.7 | 1.00 |
| The misuse of antimicrobials was evident in the facilities where I have trained | 23.9 | 11.9 | 39.3 | |
| Governing bodies in Africa are doing enough to help prevent a rise in antimicrobial resistance | 1.4 | 0.0 | 3.6 | 0.22 |
| Educating laypeople on the importance of antimicrobials as controlled scheduled compounds will have a positive effect on decreasing the rise in antimicrobial resistance | 87.3 | 88.1 | 85.7 | 0.77 |
| The use of antimicrobials in the food-producing animal industry (farm animals) contributes more to antimicrobial resistance than their use in companion animals | 50.7 | 38.1 | 67.9 | |
| Banning the use of prophylactic antimicrobials in food-producing animals will have a negative effect on animal welfare | 45.1 | 42.9 | 50.0 | 0.56 |
| Banning the use of prophylactic antimicrobials in food-producing animals will have a positive effect on decreasing the rise in antimicrobial resistance | 56.3 | 52.4 | 60.7 | 0.49 |
| Banning the use of antimicrobials as growth promoters in food-producing animals will have a positive effect on decreasing the rise in antimicrobial resistance | 57.7 | 61.9 | 50.0 | 0.33 |
| Improved use of vaccines, biosecurity measures and hygiene will decrease the need for antimicrobials in the food-producing industry | 95.8 | 95.2 | 96.4 | 0.81 |
| Adhering to meat and milk withdrawal periods will help decrease the rise in antimicrobial resistance in human pathogens | 67.6 | 64.3 | 71.4 | 0.54 |
| Broad-spectrum antimicrobials are ideal to use as first-line antimicrobials | 38.0 | 35.7 | 42.9 | 0.55 |
| Third and fourth generation antimicrobials should only be used as a last resort in treatment | 87.3 | 83.3 | 96.4 | 0.10 |
| Long-acting antimicrobials are more ideal for use in food-producing animals than shorter-acting equivalents | 21.1 | 19.0 | 21.4 | 0.81 |
| Cultures and antibiotic sensitivity testing, for example, antibiograms, should be performed as frequently as possible to guide antimicrobial use | 97.1 | 95.2 | 100.0 | 0.25 |
| Financial constraints of animal owners in Africa disallow the use of cultures and antibiotic sensitivity testing, for example, antibiograms during an infection | 77.5 | 76.2 | 78.6 | 0.82 |
| Drug legislation in Africa is on par with legislation in the rest of the world | 18.3 | 14.3 | 21.4 | 0.44 |
| I am confident that new classes of antimicrobials will be available in the near future to solve current resistance problems | 7.0 | 4.8 | 10.7 | 0.34 |
| The choice of an antimicrobial(s) by a veterinarian should largely be determined based on the cost implications to the farmer | 19.7 | 21.4 | 17.9 | 0.72 |
| I am confident in my ability to choose the ideal antimicrobial agents for a specific patient or group of animals to ensure optimal efficacy and safety | 39.4 | 28.6 | 57.1 |
Note: Data in bold indicate the significant difference between groups.
, Two-sample t-test for proportions was conducted to assess whether there is a significant difference between the responses of pre-final and final year students.
Perceived knowledge of antimicrobials of all participating (pre-final and final year) veterinary students (n = 70), Faculty of Veterinary Science, Onderstepoort.
| Variable | Median score | Mean score ± s.d. (all students) | Confident (%) | Unsure (%) | Vague (%) | No idea (%) | |
|---|---|---|---|---|---|---|---|
| Spectrum, effect, distribution, indications, side effects and contraindications of the most commonly used antimicrobial classes in veterinary medicine, as well as the implication thereof | 2 | 2.0 ± 0.6 | 17.1 | 62.9 | 20.0 | 0.0 | < 0.0001 |
| The difference between time-dependent and concentration-dependent antimicrobials | 1 | 1.5 ± 0.7 | 21.4 | 12.9 | 0.0 | < 0.0001 | |
| Resistance mechanisms | 2 | 2.0 ± 0.9 | 32.9 | 34.3 | 30.0 | 2.8 | < 0.0001 |
| Making a Gram-stain | 1 | 1.7 ± 0.9 | 55.7 | 18.6 | 21.4 | 4.3 | 0.1800 |
| Interpreting antibiograms | 1 | 1.6 ± 0.8 | 21.4 | 12.9 | 2.8 | 0.0020 | |
| Finding reliable sources of information to guide empirical use of antimicrobials | 2 | 1.7 ± 0.8 | 50.0 | 34.3 | 14.3 | 1.4 | 1.0000 |
| Choosing the most ideal route for administering a specific antimicrobial | 1 | 1.6 ± 0.8 | 30.0 | 8.6 | 2.8 | 0.0400 | |
| Choosing the desired time frame for (duration of) therapy | 2 | 1.9 ± 0.9 | 37.1 | 42.9 | 10.0 | 10.0 | 0.0020 |
| Choosing an alternative if my first choice of antimicrobial therapy failed | 2 | 2.0 ± 0.8 | 30.0 | 47.1 | 18.6 | 4.3 | < 0.0001 |
| Designing an integrated treatment protocol for a specific animal with an infection which includes supportive therapy | 2 | 2.1 ± 0.9 | 24.3 | 50.0 | 18.6 | 7.1 | < 0.0001 |
Note: Data in bold indicate significant difference between the confident group and other responses.
The mean score can range from 1 (confident) to 4 (no idea). The closer to 1 a score is, the more confident the students were about their knowledge of the question. The p-value represents the difference between students who were confident of their knowledge of the questions and those who were unsure, vague or had no idea pulled together as a single category.
s.d., standard deviation; No., number.
Ranking of the degree of abuse of antimicrobials based on students’ perceptions, Faculty of Veterinary Science, Onderstepoort.
| Antimicrobials | Ranking of abuse of antimicrobials | ||
|---|---|---|---|
| All ( | Pre-final year ( | Final year ( | |
| Tetracyclines | 1st | 1st | 1st |
| Penicillins | 2nd | 2nd | 2nd |
| Sulphonamides | 3rd | 3rd | 3rd |
| Aminoglycosides | 4th | 6th | 4th |
| Amphenicols | 5th | 5th | 8th |
| Macrolides | 6th | 4th | 6th |
| Quinolones | 7th | 7th | 10th |
| Polypeptides | 8th | 8th | 9th |
| Cephalosporins | 9th | 9th | 5th |
| Combiotics | 10th | 10th | 7th |
| Others | 11th | 11th | 11th |
Note: Spearman (Rho) rank order correlation coefficient (r) = 0.76; p-value < 0.01.
Matching of specific antimicrobials with their class (n = 71).
| Variable | No. of correct responses | Percentage ± s.d. | CI 95% | No. of wrong responses | % |
|---|---|---|---|---|---|
| Beta-lactams | 57 | 80.3 | 69.5; 88.0 | 14 | 19.7 |
| Penicillins | 28 | 39.4 | 28.9; 51.1 | 43 | 60.6 |
| Cephalosporins | 44 | 62.0 | 50.3; 72.4 | 27 | 38.0 |
| Tetracyclines | 60 | 84.5 | 74.2; 91.3 | 11 | 15.5 |
| Aminoglycosides | 67 | 94.4 | 86.0; 98.2 | 4 | 5.6 |
| Macrolides | 27 | 38.0 | 27.6; 49.7 | 44 | 62.0 |
| Amphenicols | 44 | 62.0 | 50.3; 72.4 | 27 | 38.0 |
| Fluoroquinolones | 55 | 77.5 | 66.4; 85.7 | 16 | 22.5 |
| Sulphonamides | 45 | 63.4 | 51.7; 73.7 | 26 | 36.6 |
| Peptide antibiotics | 68 | 95.8 | 87.8; 99.0 | 3 | 4.2 |
Note: Total correct matching score of 69.7% was obtained for all the surveyed students (n = 71). Penicillin and macrolide groups have the two worst matching scores of 39.4% and 38.0%, respectively. A significant majority were able to match peptide antibiotics (95.8%), aminoglycosides (94.4%) and beta-lactams (80.3%) most correctly.
s.d., standard deviation; No., number.
FIGURE 1Specific questions on characteristics of individual antimicrobial agents (n = 71).