TABLE 3.
Attitude toward antimicrobial resistance among healthcare professionals, Lusaka.
| Attitude questions antimicrobial resistance can be controlled by | Total (n = 304) | Nurses (n = 100) | Physicians (n = 65) | Pharmacists (n = 58) | Biomedical personnel (n = 80) | a p-value |
|---|---|---|---|---|---|---|
| 1. Updating about local antibiotic resistance patterns | 134 (44.7) | 36 (37.1) | 27 (41.5) | 33 (56.9) | 38 (47.5) | 0.099 |
| 2. Establish national antimicrobial resistance surveillance | 160 (53.2) | 42 (42.9) | 32 (49.2) | 41 (70.7) | 45 (56.3) | 0.007 |
| 3. Develop institutional guideline for antimicrobial use | 146 (48.7) | 46 (46.9) | 32 (49.2) | 33 (56.9) | 35 (44.3) | 0.513 |
| 4. Reduction of antibiotic use for outpatient setting | 58 (19.3) | 23 (23.5) | 12 (18.5) | 6 (10.3) | 17 (21.3) | 0.232 |
| 5. Patient poor adherence promotes antimicrobial resistance | 169 (56.2) | 57 (58.2) | 32 (49.2) | 40 (68.9) | 40 (50.0) | 0.089 |
| 6. Establish hospital infection control committee | 130 (43.3) | 40 (41.2) | 27 (41.5) | 30 (51.7) | 33 (41.3) | 0.569 |
| 7. Establish microbiology diagnostic services | 120 (39.9) | 35 (35.7) | 26 (40.0) | 28 (48.3) | 31 (38.8) | 0.483 |
| 8. Antimicrobial resistance is a worldwide problem | 126 (41.9) | 29 (29.6) | 35 (53.9) | 28 (48.3) | 34 (42.5) | 0.012 |
| 9. Access to current antibiogram | 94 (31.4) | 20 (20.8) | 24 (36.9) | 28 (48.3) | 22 (27.5) | 0.003 |
| 10. Antimicrobial usage policy | 97 (32.3) | 21 (26.7) | 18 (27.7) | 29 (50.0) | 29 (36.3) | 0.002 |
| Overall score (mean ± SD) a | 6.02 ± 1.53 | 5.04 ± 1.66 | 6.12 ± 1.32 | 7.23 ± 1.88 | 6.69 ± 1.74 | 0.001 |
a
All values are mean and Standard Deviation (SD) and p-value from One Way Analysis of Variance (ANOVA). Otherwise, Chi-square tests were used.