| Literature DB >> 35022953 |
Ogochukwu Chinedum Okoye1, Oluseyi Ademola Adejumo2, Abimbola Olubukunola Opadeyi3, Cynthia Roli Madubuko4, Maureen Ntaji5, Kenechukwu Chukwuemeka Okonkwo6, Imuetinyan Rashidat Edeki4, Uchechukwu Oby Agboje1, Oladimeji Emmanuel Alli6, John Oghenevwirhe Ohaju-Obodo1.
Abstract
Background The exposure of health care professionals (HCP) to patients with coronavirus disease-2019 (COVID-19) in the course of performing their professional duties may expose them to contracting the virus. This may likely increase their tendency to self-medicate for prevention or treatment of perceived infection. Aim This study determined the prevalence of COVID-19 related self-medication and its determinants among HCPs in three tertiary hospitals in Southern Nigeria. Method This was a cross-sectional study that enrolled 669 adult HCPs from three tertiary hospitals in three Southern Nigerian States using a non-probability convenience sampling method. A structured self-administered questionnaire was used for data collection. Data entry and analysis were done using IBM SPSS version 22. Results The mean age of the respondents was 35.6 ± 8.7 years. Two hundred and forty-three respondents (36.3%) reported having practiced COVID-19 related self-medication. The commonly used medications were ivermectin, azithromycin, vitamin C, chloroquine and zinc. Factors associated with self-medication were older age (p = < 0.0001), being pharmacist (p = 0.03), higher income (p = < 0.0001), previous COVID-19 testing (p < 0.001). Predictors of self medication were > 44 years (Adjusted Odd Ratio[AOR]:2.77,95% Confidence Interval [CI]: 1.62-4.75, p = < 0.0001), previous COVID-19 testing (AOR = 2.68, 95% CI: 1.82-3.94, p = < 0.0001). Conclusion About one-third of HCPs practiced COVID-19 related self-medication. HCPs that are often assumed to be health literate may not necessarily practice safe health behavior. Regular health education of the HCPs on implications of self-medications is highly recommended. There should also be formulation and effective implementation of policies that regulate purchase of medications.Entities:
Keywords: COVID-19; Health care professionals; Nigeria; Self-medication
Mesh:
Year: 2022 PMID: 35022953 PMCID: PMC8754192 DOI: 10.1007/s11096-021-01374-4
Source DB: PubMed Journal: Int J Clin Pharm
Demographic and characteristics of respondents
| Centres | A | B | C | Total | ||||
|---|---|---|---|---|---|---|---|---|
| % | % | % | % | |||||
| Male | 97 | 41.3 | 127 | 41.9 | 40 | 40.0 | 264 | 41.4 |
| Female | 138 | 58.7 | 176 | 58.1 | 60 | 60.0 | 374 | 58.6 |
| Total | 235 | 100.0 | 303 | 100.0 | 100 | 100.0 | 638 | 100.0 |
| 20–29 | 66 | 29.1 | 76 | 25.4 | 27 | 39.1 | 169 | 28.4 |
| 30–39 | 88 | 38.8 | 134 | 44.8 | 30 | 43.5 | 252 | 42.4 |
| 40–49 | 42 | 18.5 | 67 | 22.4 | 9 | 13.0 | 118 | 19.8 |
| 50–59 | 30 | 13.2 | 21 | 7.0 | 3 | 4.3 | 54 | 9.1 |
| ≥ 60 | 1 | 0.4 | 1 | 0.3 | 0 | 0.0 | 2 | 0.3 |
| Total | 226 | 100.0 | 299 | 100.0 | 69 | 100.0 | 595 | 100.0 |
| Mean ± SD | 36.3 ± 9.5 | 35.6 ± 8.4 | 33.0 ± 7.4 | 35.6 ± 8.7 | ||||
| Never married | 92 | 39.5 | 100 | 33.0 | 61 | 46.9 | 253 | 38.0 |
| Currently married | 128 | 54.9 | 192 | 63.4 | 67 | 51.5 | 387 | 58.1 |
| Domestic partner | 1 | 0.4 | 1 | 0.3 | 2 | 1.5 | 4 | 0.6 |
| Separated | 3 | 1.3 | 4 | 1.3 | 0 | 0.0 | 7 | 11 |
| Divorced | 0 | 0.0 | 2 | 0.7 | 0 | 0.0 | 2 | 0.3 |
| Widowed | 9 | 3.9 | 4 | 1.3 | 0 | 00 | 13 | 2.0 |
| Total | 233 | 100.0 | 303 | 100.0 | 130 | 100.0 | 666 | 100.0 |
| None | 0 | 0.0 | 0 | 0.0 | 1 | 0.8 | 1 | 0.1 |
| Primary | 6 | 2.6 | 0 | 0.0 | 0 | 0.0 | 2 | 2.6 |
| Secondary | 4 | 1.7 | 6 | 2.0 | 0 | 0.0 | 10 | 1.5 |
| Tertiary | 225 | 95.7 | 297 | 98.0 | 129 | 99.2 | 651 | 97.5 |
| Total | 235 | 100.0 | 303 | 100.0 | 130 | 100.0 | 664 | 100.0 |
| Doctor | 104 | 44.3 | 113 | 37.3 | 71 | 55.9 | 288 | 55.9 |
| Nurse | 61 | 26.0 | 121 | 39.9 | 47 | 37.0 | 229 | 37.0 |
| Pharm | 17 | 7.2 | 9 | 3.0 | 0 | 0.0 | 26 | 0.0 |
| MLS | 8 | 3.4 | 14 | 4.6 | 2 | 1.6 | 24 | 1.6 |
| Health assistant | 12 | 5.1 | 9 | 3.0 | 6 | 4.7 | 27 | 4.7 |
| Records officers | 0 | 0.0 | 13 | 4.3 | 0 | 0.0 | 13 | 0.0 |
| Others** | 33 | 14.0 | 24 | 7.9 | 1 | 0.8 | 58 | 0.8 |
| Total | 235 | 100.0 | 303 | 100.0 | 127 | 100.0 | 665 | 100.0 |
| < 600,000 | 23 | 10.0 | 9 | 3.0 | 16 | 14.4 | 48 | 7.4 |
| 600,000–1.19 M | 55 | 23.8 | 67 | 22.1 | 25 | 22.5 | 147 | 22.8 |
| 1.20–2.39 M | 94 | 40.7 | 101 | 33.3 | 38 | 34.2 | 233 | 36.1 |
| 2.40–5.99 M | 43 | 18.6 | 75 | 24.8 | 29 | 26.1 | 147 | 22.8 |
| 6-12 M | 16 | 6.9 | 47 | 15.5 | 1 | 0.9 | 64 | 9.9 |
| > 12 M | 0 | 0.0 | 4 | 1.3 | 2 | 1.8 | 6 | 0.9 |
| Total | 231 | 100.0 | 303 | 100.0 | 111 | 100.0 | 645 | 100.0 |
M = Million |MLS = Medical Laboratory Scientist | Pharm = Pharmacist |Others** = Dietician, Engineer, Dentist, Medical Laboratory Technician, Pharm Tech, Physiotherapist, Psychologist, Social worker
Self-medication for COVID-19 among the HCPs
| Parameter | Frequency ( | Percentage (%) |
|---|---|---|
| Yes | 243 | 36.3 |
| No | 423 | 63.2 |
| No response | 3 | 0.5 |
| Total | 669 | 100.0 |
| Zinc Sulphate | 5 | 2.0 |
| Vitamin C | 18 | 7.4 |
| Chloroquine | 14 | 5.7 |
| Azithromycin | 22 | 9.1 |
| Ivermectin | 23 | 9.5 |
| No response | 161 | 66.2 |
| Total | 243 | 100.0 |
| Reason for taking medication* | ||
| Symptoms of COVID | 52 | 21.3 |
| Definite exposure to a patient diagnosed with COVID | 76 | 31.2 |
| Probable exposure to a patientdiagnosed with COVID | 37 | 15.2 |
| Prophylaxis against contracting COVID-19 | 111 | 45.6 |
| Psychological assurance | 17 | 6.9 |
| No reason | 9 | 3.7 |
| Was taking the medication beneficial? | ||
| Yes | 199 | 81.9 |
| No | 31 | 12.8 |
| No response | 13 | 5.3 |
| Total | 243 | 100.0 |
*Multiple responses
Socio-demographic factors affecting self medication for COVID-19
| Self-medication | No Self-medication | Total | Test statistics | |||||
|---|---|---|---|---|---|---|---|---|
| % | % | % | ||||||
| Male | 94 | 40.0 | 167 | 42.3 | 261 | 41.4 | 0.315 | 0.574 |
| Female | 141 | 60.0 | 228 | 57.7 | 369 | 58.6 | ||
| TOTAL | 235 | 100.0 | 395 | 100.0 | 630 | 100.0 | ||
| 20–29 | 52 | 22.7 | 116 | 32.0 | 168 | 28.4 | 25.855 | < 0.0001 |
| 30–39 | 84 | 36.7 | 167 | 46.0 | 251 | 42.4 | ||
| 40–49 | 64 | 27.9 | 53 | 14.6 | 117 | 19.8 | ||
| 50–59 | 27 | 11.8 | 27 | 7.4 | 54 | 9.1 | ||
| ≥ 60 | 2 | 0.9 | 0 | 0.0 | 2 | 0.3 | ||
| 229 | 100.0 | 363 | 100.0 | 592 | 100.0 | |||
| Never married | 70 | 28.9 | 175 | 42.4 | 245 | 37.4 | 14.680 | 0.012 |
| Currently married | 159 | 65.7 | 225 | 54.5 | 384 | 58.6 | ||
| Domestic partner | 2 | 0.8 | 2 | 0.5 | 4 | 0.6 | ||
| Separated | 5 | 2.1 | 2 | 0.5 | 7 | 1.1 | ||
| Divorced | 1 | 0.4 | 1 | 0.2 | 2 | 0.3 | ||
| Widowed | 5 | 2.1 | 8 | 1.9 | 13 | 2.0 | ||
| 242 | 100.0 | 413 | 100.0 | 655 | 100.0 | |||
| None | 0 | 0.0 | 1 | 0.2 | 1 | 0.2 | 4.849 | 0.183 |
| Primary | 1 | 0.4 | 5 | 1.2 | 6 | 0.9 | ||
| Secondary | 1 | 0.4 | 9 | 2.2 | 10 | 1.5 | ||
| Tertiary | 240 | 99.2 | 400 | 96.4 | 640 | 97.4 | ||
| 242 | 100.0 | 415 | 100.0 | 657 | 100.0 | |||
| Doctor | 94 | 38.7 | 185 | 44.9 | 279 | 42.7 | 32.585 | 0.037 |
| Nurse | 96 | 39.5 | 131 | 31.8 | 227 | 34.7 | ||
| Pharmacist | 13 | 5.4 | 13 | 3.2 | 26 | 4.0 | ||
| MLSǂ | 7 | 2.9 | 17 | 4.1 | 24 | 3.7 | ||
| Health assistant | 4 | 1.6 | 23 | 5.7 | 27 | 4.1 | ||
| Record officers | 4 | 1.6 | 9 | 2.2 | 13 | 2.0 | ||
| Others** | 25 | 10.3 | 33 | 8.1 | 58 | 8.8 | ||
| 243 | 100.0 | 411 | 100.0 | 654 | 100.0 | |||
| 0–3 | 106 | 44.0 | 158 | 40.0 | 264 | 41.5 | 1.573 | 0.455 |
| 4–6 | 120 | 49.8 | 204 | 51.6 | 324 | 50.9 | ||
| 7 or more | 15 | 6.2 | 33 | 8.4 | 48 | 7.5 | ||
| 241 | 100.0 | 395 | 100.0 | 636 | 100.0 | |||
| < 600,000 | 8 | 3.4 | 37 | 9.3 | 45 | 7.1 | 30.691 | < 0.0001 |
| 600,000–1.19 M | 51 | 21.7 | 95 | 23.8 | 146 | 23.0 | ||
| 1.2 M–2.39 M | 78 | 33.2 | 150 | 37.5 | 228 | 35.9 | ||
| 2.4 M–5.99 M | 54 | 23.0 | 92 | 23.0 | 146 | 23.0 | ||
| 6.0 M–11.9 M | 42 | 17.9 | 22 | 5.5 | 64 | 10.1 | ||
| > 12 M | 2 | 0.9 | 4 | 1.0 | 6 | 0.9 | ||
| 235 | 100.0 | 400 | 100.0 | 635 | 100.0 | |||
χ2 = Pearson Chi-Square test. | t = Student’s T-test | P-value = Probability value | P = Probability value of statistical significance | M = Million |MLS = Medical Laboratory Scientist | Others** = Dietician, Engineer, Dentist, Medical Laboratory Technician, Pharm Tech, Physiotherapist, Psychologist, Social worker
Behavioural and clinical characteristics and COVID-19 self medication
| Self-medication | No Self-medication | TOTAL | χ2 | |||||
|---|---|---|---|---|---|---|---|---|
| % | % | % | ||||||
| Yes | 239 | 98.8 | 405 | 98.1 | 644 | 98.3 | 0.449 | 0.503 |
| No | 3 | 1.2 | 8 | 1.9 | 11 | 1.7 | ||
| Total | 242 | 100.0 | 413 | 100.0 | 655 | 100.0 | ||
| Yes | 135 | 55.6 | 160 | 38.6 | 295 | 44.8 | 17.911 | < 0.0001 |
| No | 108 | 44.4 | 255 | 61.4 | 363 | 55.2 | ||
| Total | 243 | 100.0 | 415 | 100.0 | 658 | 100.0 | ||
| Yes | 92 | 38.2 | 139 | 36.7 | 231 | 37.3 | 0.142 | 0.707 |
| No | 149 | 61.8 | 240 | 63.3 | 389 | 62.7 | ||
| Total | 241 | 100.0 | 379 | 100.0 | 620 | 100.0 | ||
| Yes | 33 | 13.7 | 31 | 7.5 | 64 | 9.8 | 6.510 | *0.039 |
| No | 208 | 86.3 | 380 | 92.5 | 588 | 90.2 | ||
| Total | 241 | 100.0 | 411 | 100.0 | 652 | 100.0 | ||
| Yes | 9 | 3.8 | 2 | 0.5 | 11 | 1.7 | 10.934 | *0.004 |
| No | 230 | 96.2 | 410 | 99.5 | 640 | 98.3 | ||
| Total | 239 | 100.0 | 412 | 100.0 | 651 | 100.0 | ||
χ2 = Pearson Chi-Square test. | P-value = Probability value |
Independent risk factors of COVID-19 self-medication
| Parameters | B | Std. error | AOR | 95% C.I | ||
|---|---|---|---|---|---|---|
| Lower | Upper | |||||
| Male | − 0.193 | 0.217 | 0.373 | 0.82 | 0.54 | 1.26 |
| Female (Ref) | ||||||
| > 44 | 1.019 | 0.275 | < 0.0001* | 2.77 | 1.62 | 4.75 |
| ≤ 44 (Ref) | ||||||
| Not married | − 0.302 | 0.206 | 0.143 | 0.74 | 0.49 | 1.11 |
| Currently married (Ref) | ||||||
| Doctor | − 0.225 | 0.308 | 0.464 | 0.79 | 0.44 | 1.46 |
| Nurse | − 0.040 | 0.320 | 0.900 | 0.96 | 0.51 | 1.80 |
| Pharmacist | 0.282 | 0.509 | 0.579 | 1.33 | 0.49 | 3.59 |
| MLSǂ | − 0.411 | 0.560 | 0.463 | 0.66 | 0.22 | 1.99 |
| Others** (Ref) | ||||||
| < 600,000 | − 0.898 | 0.466 | 0.054 | 0.41 | 0.16 | 1.01 |
| > 600,000 (Ref) | ||||||
| Yes | 0.453 | 0.682 | 0.506 | 1.57 | 0.41 | 5.99 |
| No (Ref) | ||||||
| Yes | 0.988 | 0.196 | < 0.0001* | 2.68 | 1.82 | 3.94 |
| No (Ref) | ||||||
| Yes | − 0.428 | 1.041 | 0.681 | 0.65 | 0.08 | 5.01 |
| No (Ref) | ||||||
| Yes | 0.073 | 1.521 | 0.962 | 1.07 | 0.05 | 21.18 |
| No (Ref) | ||||||
B = Unstandardized beta (B) | SE = Standard Error | P-value = Probability value | * = Probability value of statistical significance | OR = adjusted Odd Ratio