Knowledge, and attitude as determinants of healthcare professionals’ self-medication practice to antibacterials in Tertiary Care hospitals, North West Ethiopia

Study design, study area and period

A facility-based cross-sectional study design was employed for this research. The study was conducted at Tibebe Ghion Comprehensive Specialized Hospital (TGCSH) and Felege Hiwot Specialized Hospital (FHSH) in Bahir Dar City, Amhara Region, Ethiopia, from September 30, 2023, to February 30, 2024. Bahir Dar, the capital of the Amhara Regional State, is located in the northwest of Ethiopia, approximately 560 km from Addis Ababa, the nation’s capital. The city spans a total area of 120 km², sits at an elevation of 1,800 m above sea level, and is geographically positioned at a latitude of 11.5742° N and a longitude of 37.3614° E. The total population of Bahir Dar is 290,437, comprising 142,068 men and 148,369 women. The city administration is organized into nine sub-cities and has a healthcare infrastructure that includes 10 public health centers, 2 public hospitals, and 2 private health institutions, providing essential health services to the residents of the region.

Source and study population

The source population for this study comprised all healthcare in Tertiary Care Hospitals workers in Bahir Dar City. The study population included staff pharmacists, physicians, nurses, laboratory technologists, and midwives working across various units within two Tertiary Care Hospitals in Bahir Dar City during the study period. All healthcare workers, regardless of their years of work experience, were eligible to participate. However, those on sick leave, absent for other reasons during the data collection period, or unwilling to participate were excluded. A six-month recall period was applied to gather information from all participants, ensuring the reliability of self-reported behaviors and practices.

Sample size determination, sampling procedure

The sample size was determined using the single population proportion formula. Assuming a proportion (p) of 50% to maximize variability, a 95% confidence level (Z = 1.96), a margin of error of 0.05, and accounting for a 10% nonresponse rate, the final calculated sample size was 410.

The study population consisted of 1,326 healthcare workers across the two hospitals, distributed as follows: 298 physicians, 126 pharmacists, 646 nurses, 74 laboratory technologists, and 181 midwives. Proportional allocation was applied to ensure representativeness of the sample, resulting in the following breakdown: 92 physicians, 39 pharmacists, 200 nurses, 23 laboratory technologists, and 56 midwives, totaling 410 participants.

The total numbers of each professional group were based on official records from the two Tertiary Care Hospitals. Participants were selected using a convenience sampling method, which involved recruiting individuals who were readily accessible and willing to participate during the study period.

Validity and reliability

The questionnaire was developed by DGD and CT after an extensive review of literature related to similar studies. A panel consisting of two clinical pharmacy lecturers and a physician critically appraised the data collection tool, evaluating its relevance, accuracy, and appropriateness. Face validity was established by presenting the questionnaire to 20 health workers from the departments of medicine, pharmacy, nursing, midwifery, and medical laboratory technology. Responses from the pretest were excluded from the final analysis.

The internal consistency of the questionnaire was assessed using Cronbach’s alpha, which yielded a satisfactory reliability score (α = 0.75). The questionnaire was structured into seven sections. The first section collected demographic data, including job category, age, gender, and education level. Sections two, three, and four focused on assessing the indications for antibiotic use, types of antibiotics used, and influencing factors, respectively. The sixth section examined healthcare workers’ attitudes toward self-medication, while the seventh evaluated participants’ knowledge of self-medication practices.

Knowledge responses were scored on a scale ranging from 0 to 7. Participants answered knowledge-related items with “Yes,” “No,” or “Do not know.” A score of 1 was assigned for “Yes,” while “No” and “Do not know” were scored as 0. Knowledge levels were categorized as poor for scores of 0–4 and good for scores of 5–7. Attitudes were assessed using a five-point Likert scale, with responses scored as follows: 5 for “Strongly agree,” 4 for “Agree,” 3 for “Uncertain,” 2 for “Disagree,” and 1 for “Strongly disagree. The mean score was used as a benchmark to categorize attitudes as either poor or good. Participants whose scores fell below the mean were classified as having poor attitudes.

Study variables

The dependent variable in this study was the prevalence of self-medication. Independent variables included a range of factors: healthcare workers’ attitudes and knowledge, socio-demographic characteristics (such as age, sex, religion, level of education, income, job category, and work experience), as well as specific parameters related to their attitudes and knowledge on self-medication.

Data collection tools and data collection procedure

Data were collected from the study participants using a pre-tested, structured, self-administered questionnaire adapted from previous research on similar topics^3,5,15,19. The data collection tools were distributed to the participants and subsequently collected by the principal investigator. Verbal consent was obtained from all participants.

Data processing and analysis

Data entry and cleaning were performed using EpiData version 3.1. Before data entry, the data were thoroughly checked for completeness, and any inconsistencies or missing values were addressed. Incomplete questionnaires were excluded from the analysis.

Data analysis was carried out using SPSS version 27.0. Bivariate logistic regression was used to examine the associations between each independent variable and the dependent variable. In the univariate analysis, each factor was assessed for its potential association with the outcome variable, with a p-value of less than 0.2 used as a threshold to select predictors for inclusion in the multivariate analysis. The crude odds ratio (COR) and adjusted odds ratio (AOR) were calculated, and a p-value of less than 0.05 was considered statistically significant.