Knowledge of preconception care and associated factors among maternal health care providers working in urban public health institutions of Eastern Ethiopia
Background: Provision of preconception care is significantly affected by the health care provider’s knowledge of preconception care. In Ethiopia, preconception care is rare, if even available, as part of maternal health care services. Thus, this study aimed to determine the level of knowledge of preconception care and associated factors among health care providers working in public health facilities in Eastern Ethiopia. Methods: A multicenter cross-sectional study was conducted from 1 March to 1 April 2020. A simple random sampling technique was used to select a total of 415 maternal health care providers. We utilized a structured, pretested, and self-administered questionnaire to collect data. Data were entered into EpiData (version 3.1) and exported to STATA (version 16) for analysis. Descriptive statistics and bivariate and multivariate logistic regression analyses were performed. All covariates with a p value ⩽0.20 in bivariate logistic regression were entered into a multivariate logistic regression analysis to control the confounding variables; variables with a p value <0.05 were considered statistically significant. Results: Out of 410 respondents, 247 (60.2%; 95% confidence interval: 55.4–65.1) had good knowledge of preconception care. Having an educational level of Bachelor of Science degree and above (adjusted odds ratio: 6.97, 95% confidence interval: 3.85–12.60), 5 or more years work experience (adjusted odds ratio: 2.60, 95% confidence interval: 1.52–4.49), working in a hospital (adjusted odds ratio: 2.50, 95% confidence interval: 1.25–4.99), reading preconception care guidelines (adjusted odds ratio: 3.06, 95% confidence interval: 1.40–6.68), and training on preconception (adjusted odds ratio: 2.90, 95% confidence interval: 1.37–6.15) were significantly associated with good knowledge of preconception care. Conclusions and Recommendations: Three out of five maternal health care providers in this study had good knowledge of preconception care. Facilitating continuous refreshment training and continuous professional development for health workers, preparing comprehensive preconception care guidelines for health institutions, and reading preconception care guidelines were highly recommended.
The study was conducted in Harar and Dire Dawa, Eastern Ethiopia, from 1 March to 1 April 2020. Harar is the capital city of the Harari region and East Hararghe Zone. Harar is found at a distance of 526 kilometers from the capital city, Addis Ababa. Using the 2007 Ethiopian census projection for 2019/2020, the current estimated total population of the city is 263,656. Among these, 60,667 are reproductive-aged women.29 There are 2 public hospitals, 2 private hospitals, 1 police hospital, 4 health centers, 54 private clinics, and 24 health posts. Roughly 1219 health professionals work in this region.30 Dire Dawa city is one of the two self-administrative cities in Ethiopia, located 515 kilometers east of the capital city, Addis Ababa, and 47 kilometers from Harar town. According to the 2007 Ethiopian census projection for 2019/2020, the current estimated total population of the city is 492,637.29 There are 2 public hospitals, 4 private hospitals, 8 health centers, and 32 health posts regarding the distribution of health facilities. Data from Dire Dawa City Health Bureau (DDCHB) shows 794 health professionals are working in public health institutions in the city.31 Approximately, 2013 health care providers are employed in both study areas. Of which, 570 employees were MHCPs. The study includes only public health institutions found in urban areas in both study areas due to feasibility issues related to COVID-19 pandemic travel restrictions during the study period. An institution-based quantitative cross-sectional study was conducted from 1 March to 1 April 2020. All MHCPs working in public health institutions in Harar and Dire Dawa cities were included in the study. Those MHCPs who were on annual leave and sick leave during the data collection period were excluded from the study. The minimum sample size required for the study was determined by using a single population proportion formula with 0.05 margin of error (d), a 95% confidence interval (CI), a 57% estimated proportion of health care providers with good knowledge of PCC (P) taken from a study done in Hawassa.13 Thus, with adding a 10% non-response rate, a final sample size of 415 participants was used for this study. A simple random sampling technique using computer-generated random numbers was applied to select a total of 415 MHCPs. Employer’s employee registry documents taken from human resources were used as a sampling frame to draw the study unit. All public health institutions in Harar and Dire Dawa cities were included in the study regarding the sampling procedure. After getting the number of MHCPs working in each hospital and health center, the total sample size was proportionally allocated for the selected hospitals and health centers. Subsequently, the sample size given for each institution was earmarked for each profession proportional to the number of health care providers in each discipline. A self-administered structured questionnaire was used for data collection. A validated data collection tool named “Andarg-Ethio PCC-KAP-Questionnaire for HCPs” was adopted from a study done in Hawassa.13 Four BSc Midwives and two BSc Public Health Officers were recruited as data collectors and supervisors for the study. A 2-day training was given on the study’s overall objective, clarity of questionnaire, sampling strategy, ethical considerations, and how to facilitate and supervise the data collection process. Respondents who scored greater than or equal to the 50th percentile of the aggregated knowledge score were categorized as having good PCC knowledge. In contrast, respondents who scored less than the 50th percentile of the aggregated knowledge score were considered poor PCC knowledge.13 Maternal health care providers were categorized as certified obstetricians, gynecologists, general practitioners, internal emergency obstetrical surgeons, nurses, midwives, and public health officers providing (family planning, antenatal care (ANC), Prevention of mother-to-child transmission (PMTCT), abortion, childbirth, postnatal care, and other gynecologic care services for reproductive-aged women up to 1 year after childbirth).20,32 To assure the quality of data, properly designed and validated data collection tools were utilized. A pretest was performed on 5% of the total sample size at Haramaya General Hospital 2 weeks before the actual data collection period to assess the clarity, sequence, consistency, understandability, and time taken to complete the questionnaire. Later on, any ambiguity, complex words, and differences in understanding were revised based on pretest experience. Each questionnaire was coded with a unique identification number. Adequate training was provided to data collectors and supervisors regarding data collection procedures, ethical considerations for the participants, and dangers of data validity, and briefed on each question included in the study. To obtain informed consent and reliable data, a clear explanation of the purpose, procedure, confidentiality, and benefits of the study was given to participants. The principal investigator and supervisors closely supervised and actively reviewed all questionnaires to ensure the completeness and consistency of the information collected, and immediate corrective measures were taken accordingly. Finally, after checking for data completeness and adequately coded with a unique identification number, each questionnaire was entered into the software for analysis. EpiData was utilized for data entry as it has a controlling mechanism for error detection. Two separate data clerks did double data entry to cross check for consistency of data entry. Data were kept in the form of a file in a secure place where no one can access it except the principal investigator. Simple frequencies and cross-tabulation were done to look for missing values and outliers. This was then cross checked by reviewing hard copies of the collected data. The data were exported to STATA (version 16) computer software for analysis. Both descriptive statistics and regression analysis were performed. Descriptive statistical analysis such as cross-tabulation, simple frequencies, measures of central tendency, and measures of variation was computed to summarize and describe the characteristics of study participants. The information was presented using frequencies, summary measures, tables, and figures. MHCP’s comprehensive knowledge of PCC was computed from summing up 18 understanding measuring items. Among the three options given for every 18 questions measuring ability, the correct answer was recoded to “1,” and the wrong options were also recoded to “0.” The maximum possible scores of each MHCP participated in the study were determined by the summation of the recoded 18 knowledge questions. Respondents who scored in the 50th percentile and above were labeled as MHCPs with “good knowledge of PCC,” and those who scored below the 50th percentile were labeled as MHCPs with “poor knowledge of PCC.” For a further description of knowledge level, those who correctly answered >75th percentile were marked as MHCPs with “high knowledge of PCC” and those who scored 50th to 75th percentiles were labeled as MHCPs with “medium knowledge of PCC.” The remaining who scored <50th percentile were marked as MHCPs with “poor knowledge of PCC.” In bivariate analysis, the crude odds ratio (COR) with 95% CI was used to see the association between each independent and dependent variable using binary logistic regression. The result was presented as a COR to show the strength of the association between independent variables and dependent variables. Independent variables with a significance level of p value ⩽0.20 at 95% CI in the bivariable analysis and which fit the model of regression were retained for inclusion into a multivariable logistic regression model to control for the confounders. Multicollinearity was checked to see the linear correlation among the associated independent variables using the variance inflation factor (VIF) and standard error. VIF of >10 or standard error of >2 was considered suggestive of multicollinearity. No multicollinearity was detected during the analysis. Multivariate analysis was conducted using the Enter method inorder to control the confounders. Hosmer–Lemeshow’s goodness-of-fit test was done to check for model fitness. Omnibus test (p < 0.0001) and Hosmer–Lemeshow’s test were found to be significant (p = 0.536), which indicates the model was fitted. Adjusted odds ratio (AOR) with 95% CI was estimated to show the strength of the association between the independent variables and the dependent variable after controlling the effects of confounders. Independent variables with a p value <0.05 and which did not include the null value in the 95% CI were declared as having a statistically significant association with the outcome variable.
The study aimed to determine the level of knowledge of preconception care (PCC) and associated factors among health care providers working in public health facilities in Eastern Ethiopia. This is important because the provision of PCC is significantly affected by the health care provider’s knowledge. In Ethiopia, PCC is rare, if even available, as part of maternal health care services. Therefore, understanding the knowledge level and associated factors can help identify gaps and inform interventions to improve PCC provision.
Highlights:
– Out of 410 respondents, 247 (60.2%) had good knowledge of preconception care.
– Factors significantly associated with good knowledge of preconception care included having an educational level of Bachelor of Science degree and above, 5 or more years of work experience, working in a hospital, reading preconception care guidelines, and receiving training on preconception care.
Recommendations:
– Facilitate continuous refreshment training and continuous professional development for health workers to improve their knowledge of preconception care.
– Prepare comprehensive preconception care guidelines for health institutions to ensure standardized and evidence-based practices.
– Encourage health care providers to read preconception care guidelines to stay updated on best practices.
Key Role Players:
– Ministry of Health: Responsible for developing and implementing policies and guidelines related to preconception care.
– Health Training Institutions: Provide training programs and courses on preconception care for health care providers.
– Health Care Facilities: Implement training programs, provide resources, and support the dissemination of preconception care guidelines.
– Professional Associations: Collaborate with the Ministry of Health to develop training materials and organize workshops on preconception care.
Cost Items:
– Training Programs: Budget for organizing continuous refreshment training and continuous professional development for health workers.
– Guideline Development: Budget for the development and dissemination of comprehensive preconception care guidelines.
– Resource Allocation: Budget for providing necessary resources, such as printed copies of guidelines, to health care facilities.
– Workshops and Conferences: Budget for organizing workshops and conferences on preconception care to promote knowledge sharing and capacity building.
The strength of evidence for this abstract is 7 out of 10. The evidence in the abstract is rated 7 because it provides a detailed description of the study design, sample size, data collection methods, and statistical analysis. However, it does not mention the specific results of the study, such as the prevalence of good knowledge of preconception care among maternal health care providers. To improve the evidence, the abstract should include a summary of the main findings and their implications for practice and policy.
Background: Provision of preconception care is significantly affected by the health care provider’s knowledge of preconception care. In Ethiopia, preconception care is rare, if even available, as part of maternal health care services. Thus, this study aimed to determine the level of knowledge of preconception care and associated factors among health care providers working in public health facilities in Eastern Ethiopia. Methods: A multicenter cross-sectional study was conducted from 1 March to 1 April 2020. A simple random sampling technique was used to select a total of 415 maternal health care providers. We utilized a structured, pretested, and self-administered questionnaire to collect data. Data were entered into EpiData (version 3.1) and exported to STATA (version 16) for analysis. Descriptive statistics and bivariate and multivariate logistic regression analyses were performed. All covariates with a p value ⩽0.20 in bivariate logistic regression were entered into a multivariate logistic regression analysis to control the confounding variables; variables with a p value 75th percentile were marked as MHCPs with “high knowledge of PCC” and those who scored 50th to 75th percentiles were labeled as MHCPs with “medium knowledge of PCC.” The remaining who scored 10 or standard error of >2 was considered suggestive of multicollinearity. No multicollinearity was detected during the analysis. Multivariate analysis was conducted using the Enter method inorder to control the confounders. Hosmer–Lemeshow’s goodness-of-fit test was done to check for model fitness. Omnibus test (p < 0.0001) and Hosmer–Lemeshow’s test were found to be significant (p = 0.536), which indicates the model was fitted. Adjusted odds ratio (AOR) with 95% CI was estimated to show the strength of the association between the independent variables and the dependent variable after controlling the effects of confounders. Independent variables with a p value <0.05 and which did not include the null value in the 95% CI were declared as having a statistically significant association with the outcome variable.
The study titled “Knowledge of preconception care and associated factors among maternal health care providers working in urban public health institutions of Eastern Ethiopia” aimed to determine the level of knowledge of preconception care and associated factors among health care providers in Eastern Ethiopia. The study found that 60.2% of the respondents had good knowledge of preconception care. Factors associated with good knowledge included having an educational level of Bachelor of Science degree and above, 5 or more years of work experience, working in a hospital, reading preconception care guidelines, and receiving training on preconception care.
Based on the study findings, the following recommendations were made:
1. Facilitating continuous refreshment training and continuous professional development for health workers: Providing regular training opportunities for health care providers can help improve their knowledge and understanding of preconception care.
2. Preparing comprehensive preconception care guidelines for health institutions: Developing clear and comprehensive guidelines for preconception care can serve as a reference for health care providers, ensuring that they have access to accurate and up-to-date information.
3. Reading preconception care guidelines: Encouraging health care providers to read and familiarize themselves with preconception care guidelines can enhance their knowledge and understanding of the topic.
Overall, the study highlights the importance of improving knowledge and awareness of preconception care among maternal health care providers in order to enhance access to maternal health services.
AI Innovations Description
The study titled “Knowledge of preconception care and associated factors among maternal health care providers working in urban public health institutions of Eastern Ethiopia” aimed to assess the level of knowledge of preconception care among health care providers and identify factors associated with good knowledge.
The study was conducted in Harar and Dire Dawa, Eastern Ethiopia, from 1 March to 1 April 2020. A total of 415 maternal health care providers working in public health facilities were included in the study. Data was collected using a structured, pretested, and self-administered questionnaire.
The findings of the study revealed that 60.2% of the respondents had good knowledge of preconception care. Factors associated with good knowledge included having an educational level of Bachelor of Science degree and above, 5 or more years of work experience, working in a hospital, reading preconception care guidelines, and receiving training on preconception care.
Based on the study findings, the following recommendations were made:
1. Facilitating continuous refreshment training and continuous professional development for health workers: Providing regular training sessions and opportunities for health care providers to update their knowledge on preconception care can help improve their understanding and implementation of preconception care guidelines.
2. Preparing comprehensive preconception care guidelines for health institutions: Developing and disseminating clear and comprehensive guidelines on preconception care can ensure that health care providers have access to standardized information and protocols for delivering preconception care services.
3. Encouraging health care providers to read preconception care guidelines: Promoting the importance of reading and familiarizing themselves with preconception care guidelines can enhance health care providers’ knowledge and understanding of best practices in preconception care.
In summary, the study highlights the need for continuous training, comprehensive guidelines, and promoting the reading of preconception care guidelines among maternal health care providers to improve access to and quality of maternal health care services in Eastern Ethiopia.
AI Innovations Methodology
Based on the information provided, the study aimed to determine the level of knowledge of preconception care and associated factors among health care providers working in public health facilities in Eastern Ethiopia. The study found that three out of five maternal health care providers had good knowledge of preconception care. Factors such as educational level, work experience, working in a hospital, reading preconception care guidelines, and training on preconception were significantly associated with good knowledge of preconception care.
To improve access to maternal health, here are some potential recommendations based on the study findings:
1. Facilitate continuous refreshment training and continuous professional development for health workers: Providing regular training and educational opportunities for health care providers can help improve their knowledge and skills in preconception care. This can be done through workshops, seminars, online courses, and other training programs.
2. Prepare comprehensive preconception care guidelines for health institutions: Developing and implementing comprehensive guidelines specifically focused on preconception care can help standardize practices and ensure that health care providers have access to up-to-date information and recommendations.
3. Promote reading of preconception care guidelines: Encouraging health care providers to regularly read and stay updated on preconception care guidelines can help improve their knowledge and understanding of best practices in this area.
To simulate the impact of these recommendations on improving access to maternal health, a methodology could include the following steps:
1. Baseline assessment: Conduct a baseline assessment to determine the current level of knowledge and practices related to preconception care among health care providers in the target area.
2. Intervention implementation: Implement the recommended interventions, such as providing training and educational opportunities, developing guidelines, and promoting reading of preconception care guidelines.
3. Post-intervention assessment: After a certain period of time, conduct a follow-up assessment to evaluate the impact of the interventions on the knowledge and practices of health care providers regarding preconception care.
4. Data analysis: Analyze the data collected during the baseline and post-intervention assessments to compare the changes in knowledge and practices. This can be done using statistical methods such as descriptive statistics, bivariate analysis, and multivariate logistic regression analysis.
5. Evaluation and interpretation: Evaluate the results of the data analysis to determine the effectiveness of the interventions in improving access to maternal health. Interpret the findings and identify any areas for further improvement or additional interventions.
6. Recommendations and implementation: Based on the evaluation and interpretation of the results, make recommendations for further actions or interventions to continue improving access to maternal health. Implement the recommended actions and monitor their impact on an ongoing basis.
By following this methodology, it will be possible to assess the impact of the recommended interventions on improving access to maternal health and make evidence-based decisions for future interventions and improvements.
Community Interventions, COVID, Health System and Policy, Maternal Access, Maternal and Child Health, Quality of Care, Sexual and Reproductive Health, Social Determinants, Workforce
Study Countries:
Ethiopia
Study Design:
Case-Control Study, Cross Sectional Study, Grounded Theory