Health systems’ preparedness to provide post-abortion care: assessment of health facilities in Burkina Faso, Kenya and Nigeria

BMC Health Services Research, Volume 22, No. 1, Year 2022

Interpretation

Background: In many parts of sub-Saharan Africa, access to abortion is legally restricted, which partly contributes to high incidence of unsafe abortion. This may result in unsafe abortion-related complications that demand long hospital stays, treatment and attendance by skilled health providers. There is however, limited knowledge on the capacity of public health facilities to deliver post-abortion care (PAC), and the spread of PAC services in these settings. We describe and discuss the preparedness and capacity of public health facilities to deliver complete and quality PAC services in Burkina Faso, Kenya and Nigeria. Methods: A cross-sectional survey of primary, secondary and tertiary-level public health facilities was conducted between November 2018 and February 2019 in the three countries. Data on signal functions (including information on essential equipment and supplies, staffing and training among others) for measuring the ability of health facilities to provide post-abortion services were collected and analyzed. Results: Across the three countries, fewer primary health facilities (ranging from 6.3–12.1% in Kenya and Burkina Faso) had the capacity to deliver on all components of basic PAC services. Approximately one-third (26–43%) of referral facilities across Burkina Faso, Kenya and Nigeria could provide comprehensive PAC services. Lack of trained staff, absence of necessary equipment and lack of PAC commodities and supplies were a main reason for inability to deliver specific PAC services (such as surgical procedures for abortion complications, blood transfusion and post-PAC contraceptive counselling). Further, the lack of capacity to refer acute PAC cases to higher-level facilities was identified as a key weakness in provision of post-abortion care services. Conclusions: Our findings reveal considerable gaps and weaknesses in the delivery of basic and comprehensive PAC within the three countries, linked to both the legal and policy contexts for abortion as well as broad health system challenges in the countries. There is a need for increased investments by governments to strengthen the capacity of primary, secondary and tertiary public health facilities to deliver quality PAC services, in order to increase access to PAC and avert preventable maternal mortalities. This was a multi-country study to assess the preparedness of public health facilities to deliver PAC services in Burkina Faso, Kenya and Nigeria. The three countries offer both similar and dissimilar contexts for investigating the quality of PAC. For instance, abortion is largely restricted across the three countries, and they all report high incidences of unsafe abortion [8, 10, 11]. These settings offer worthy contexts to examine the preparedness of their health facilities to provide PAC services. A cross-sectional survey was conducted among a representative sample of primary, secondary and tertiary health facilities in the aforementioned countries. Health systems across the three countries are organized according to hierarchical levels. Health facility levels are generally categorized as primary, secondary and tertiary-levels. Primary health facilities are the first point of contact for the majority of community members’ health needs, and include community facilities, dispensaries and clinics. In Kenya, primary-level facilities handle the Kenya Essential Package for Health (KEPH), which encompass activities related to health promotion, preventive care, and curative services. Secondary facilities are mainly sub-regional and regional and serve as referral facilities for the primary-level facilities. They undertake curative and rehabilitative care and address a limited extent of preventive care and health promotion. Tertiary facilities are mainly national referral and teaching hospitals. All health facilities capable of conducting normal deliveries were included in our sample frame. Data was collected in facilities over a 30-day period between November 2018 and February 2019. A two stage stratified sampling procedure was used in each country, that is, a) the highest sub-national administrative units (i.e. counties in Kenya, states in Nigeria and regions in Burkina Faso), and b) the levels of health facilities. The sub-national levels represented by “counties”, “states” and “regions”, denote the geopolitical zone below national and above district levels. At the first stage, in each country, a random sample of six regions, counties or states was drawn, and excluding the administrative unit hosting the national capital regions – i.e. Centre in Burkina, Nairobi in Kenya, and Abuja – Federal Capital Territory (FCT) in Nigeria. Thereafter, the capital regions were added to the regions purposely to make seven regions/counties/states in each country. The selected administrative units included, Burkina Faso (seven regions from the 13: Boucle du Mouhoun, Cascades, Centre, Centre-Ouest, Centre-sud, Haut-Bassins, and Nord); Kenya (seven counties from 47: Garissa, Kajiado, Kiambu, Laikipia, Mandera, Migori, and Nairobi); Nigeria (seven states from 36: namely Anambra, Bauchi, Cross-River, Edo, Federal Capital Territory, Kano and Kogi. At the second stage, the researchers obtained from government records updated master lists of all public health facilities in the different sub-national units. Burkina Faso and Nigeria’s list were updated up to July 2018 while Kenya was updated in February 2018. A requisite sample of facilities in each country was determined using a formula for known populations and known proportion estimates by: ∆ = z√ ((p (1-p))/n). To solve for n we made it the subject: n=zΔ2p1-p, and assumed a confidence interval of 95%, with z as 1.96, and ∆ as 0.05. In all cases, the known estimate p represented the proportion of facilities capable of providing PAC contraceptive counseling, which was the lowest measure for quality of PAC in Kenya (19.4%) and Nigeria (16%) [22, 35]. Because we did not find any recent estimate in Burkina Faso, we used the 50% proxy in order to generate the maximum sample size possible. These calculations yielded the number of facilities required for each country, and upon accounting for a response rate of approximately 93%, the estimated sample size of facilities was determined as follows: 414 in Burkina Faso, 259 in Kenya, and 223 in Nigeria. The total sample size of health facilities was allocated to each of the seven sub-national units in each country depending on the population of eligible facilities in a specific region/county or state. Therefore, health facilities were randomly selected within each sub-national level with all tertiary health facilities included and a sample of primary and secondary health facilities. Eligible facilities were those that could provide normal delivery services, were publicly owned (government owned) and operational at the time of survey. As such, we excluded some specialized facilities including mental and spinal hospitals as well as military and prison hospitals known not to offer services to the public. Our focus on public health facilities is because government investments in health services primarily go to these facilities. During the survey, some facilities were dropped and replaced with similar facilities within the same locality, due to insecurity and travel inaccessibility. In addition, sampled facilities that declined to participate in the study were replaced with similar facilities from the sampling frame, which had been identified a priori. Trained field workers visited each eligible facility and administered the signal functions questionnaire which had been adopted from previous versions [36, 37]. The questionnaire was further refined to the contexts following extensive discussions with experienced obstetricians and gynecologists in each country. The questionnaires captured details on availability of key equipment, supplies and commodities, staffing and staff training, facility operation hours and ability to perform various sexual and reproductive health services (Supplementary file 1). Uniform tools were used across all countries. However, some aspects were adapted to fit in national standards (e.g. facilities categorizations). We asked the providers whether they were currently providing the listed services (Table 1). Whenever the provider indicated that a particular service was currently unavailable, the next sets of questions probed for the reasons why the service is not available. In response, the providers listed all possible reasons why the service was unavailable at that time. The tools were pre-tested to enhance conceptual clarity and logical flow. At large referral hospitals, respondents were the head of the obstetrics and gynecology department, or a key obstetrician gynecologist working in the facility. However, at lower level facilities, a nurse, a midwife or another health worker who was knowledgeable on PAC services provided in the facility was interviewed. The quantitative data were collected using tablets and hosted on the SurveyCTO platform. Completed and verified data were uploaded unto the APHRC cloud server for safe storage. Spot-checks were performed on 5% of the sample by the lead for each country. Description of signal functions for basic and comprehensive PAC services Source: Owolabi et al., (2019) [23] aHealth facilities reported whether they were providing the service bHealth facilities indicated availability of drugs or equipment, and also indicated the validity or functionality of the given item cThis was premised on availability of staff capable of conducting caesarean sections (would also capable of doing normal deliveries) Using the Ministry of Health master list of health facilities in Burkina Faso, Kenya and Nigeria, and the sampling frame of public facilities, we constructed facility-levels weights accounting for the sample design and adjusting for stratification by regions/counties/states, and facility non-response, as well as applying a finite population correction. The statistical analysis was conducted in Stata version 15.0 [38]. We therefore use weighted data to describe the capacity of health facilities to deliver PAC services. We drew from the Owolabi et al. (2019) approach and constructed composite or aggregate indicators of signal functions to provide basic and comprehensive PAC using a signal functions approach [23]. By calculating the availability of specific health interventions that are key to PAC—i.e., the signal functions—we measure the capacity for, and quality of, PAC from a health systems perspective. We do this by summating or combining sets of indicators that constitute the two delineated levels of care – basic and comprehensive PAC, that roughly correspond to care that should be provided at both the primary level and at the referral level hospitals respectively (Table (Table1).1). A key departure from the Owolabi approach is that under basic PAC indicators, we excluded the ability to communicate with referral facilities. This was mainly because this variable was not captured in our data collection tool and was proxied with having an established referral pathway between different health facilities. We also explored another level of analysis, again adopted from the Owolabi paper [23], which included developing case scenarios by excluding some PAC signal functions to have a less restrictive criterion at various stages. At first, we analyzed all PAC signal functions for each facility levels. Secondly, we excluded the availability of staff capable of conducting normal deliveries, thirdly, we excluded – staff with delivery capabilities; having a referral capacity; availability of short and long-acting, or permanent family planning methods. At the fourth stage, we examined PAC capability by excluding the ability of a facility to conduct referrals (through having a vehicle fueled). “Capacity” or “preparedness” was conceptualized as the ability of health facilities to deliver services based on signal function indicators [37]. Proportions of facilities capable of delivering basic and comprehensive PAC were generated.

AI Digest

Study Justification:

– Access to safe abortion is legally restricted in many parts of sub-Saharan Africa, leading to high incidences of unsafe abortion.
– Limited knowledge exists on the capacity of public health facilities to provide post-abortion care (PAC) and the spread of PAC services in these settings.
– This study aims to assess the preparedness and capacity of public health facilities in Burkina Faso, Kenya, and Nigeria to deliver complete and quality PAC services.

Highlights:

– The study conducted a cross-sectional survey of primary, secondary, and tertiary-level public health facilities in the three countries.
– Data on signal functions, including essential equipment and supplies, staffing, and training, were collected and analyzed.
– Findings revealed significant gaps and weaknesses in the delivery of basic and comprehensive PAC services in all three countries.
– Lack of trained staff, absence of necessary equipment, and lack of PAC commodities and supplies were identified as key barriers to delivering specific PAC services.
– The study highlights the need for increased investments by governments to strengthen the capacity of public health facilities to provide quality PAC services.

Recommendations:

– Governments should invest in strengthening the capacity of primary, secondary, and tertiary public health facilities to deliver quality PAC services.
– Efforts should be made to train and retain skilled health providers in PAC services.
– Adequate provision of essential equipment, supplies, and commodities for PAC should be ensured.
– Improved referral systems and transportation for acute PAC cases should be established.
– Policies and laws related to abortion should be reviewed and revised to ensure safe and accessible abortion services.

Key Role Players:

– Government health ministries and departments
– Public health facility administrators and managers
– Health providers specializing in obstetrics and gynecology
– Training institutions for health professionals
– Non-governmental organizations (NGOs) working in reproductive health

Cost Items for Planning Recommendations:

– Training programs for health providers
– Procurement of essential equipment, supplies, and commodities
– Infrastructure improvements in health facilities
– Development and implementation of referral systems
– Awareness campaigns and community engagement activities
– Monitoring and evaluation of PAC services
Please note that the cost items provided are general categories and not actual cost estimates. Actual costs will vary based on the specific context and requirements of each country.

Strength of Evidence

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is strong, but there are some areas for improvement. The study design is cross-sectional, which limits the ability to establish causality. Additionally, the abstract does not provide information on the sample size or representativeness of the facilities surveyed. To improve the evidence, future studies could consider using a longitudinal design to assess changes over time and ensure a representative sample of health facilities. Additionally, providing more details on the methodology, such as the sampling strategy and response rate, would enhance the transparency and reliability of the findings.

Abstract

This was a multi-country study to assess the preparedness of public health facilities to deliver PAC services in Burkina Faso, Kenya and Nigeria. The three countries offer both similar and dissimilar contexts for investigating the quality of PAC. For instance, abortion is largely restricted across the three countries, and they all report high incidences of unsafe abortion [8, 10, 11]. These settings offer worthy contexts to examine the preparedness of their health facilities to provide PAC services. A cross-sectional survey was conducted among a representative sample of primary, secondary and tertiary health facilities in the aforementioned countries. Health systems across the three countries are organized according to hierarchical levels. Health facility levels are generally categorized as primary, secondary and tertiary-levels. Primary health facilities are the first point of contact for the majority of community members’ health needs, and include community facilities, dispensaries and clinics. In Kenya, primary-level facilities handle the Kenya Essential Package for Health (KEPH), which encompass activities related to health promotion, preventive care, and curative services. Secondary facilities are mainly sub-regional and regional and serve as referral facilities for the primary-level facilities. They undertake curative and rehabilitative care and address a limited extent of preventive care and health promotion. Tertiary facilities are mainly national referral and teaching hospitals. All health facilities capable of conducting normal deliveries were included in our sample frame. Data was collected in facilities over a 30-day period between November 2018 and February 2019. A two stage stratified sampling procedure was used in each country, that is, a) the highest sub-national administrative units (i.e. counties in Kenya, states in Nigeria and regions in Burkina Faso), and b) the levels of health facilities. The sub-national levels represented by “counties”, “states” and “regions”, denote the geopolitical zone below national and above district levels. At the first stage, in each country, a random sample of six regions, counties or states was drawn, and excluding the administrative unit hosting the national capital regions – i.e. Centre in Burkina, Nairobi in Kenya, and Abuja – Federal Capital Territory (FCT) in Nigeria. Thereafter, the capital regions were added to the regions purposely to make seven regions/counties/states in each country. The selected administrative units included, Burkina Faso (seven regions from the 13: Boucle du Mouhoun, Cascades, Centre, Centre-Ouest, Centre-sud, Haut-Bassins, and Nord); Kenya (seven counties from 47: Garissa, Kajiado, Kiambu, Laikipia, Mandera, Migori, and Nairobi); Nigeria (seven states from 36: namely Anambra, Bauchi, Cross-River, Edo, Federal Capital Territory, Kano and Kogi. At the second stage, the researchers obtained from government records updated master lists of all public health facilities in the different sub-national units. Burkina Faso and Nigeria’s list were updated up to July 2018 while Kenya was updated in February 2018. A requisite sample of facilities in each country was determined using a formula for known populations and known proportion estimates by: ∆ = z√ ((p (1-p))/n). To solve for n we made it the subject: n=zΔ2p1-p, and assumed a confidence interval of 95%, with z as 1.96, and ∆ as 0.05. In all cases, the known estimate p represented the proportion of facilities capable of providing PAC contraceptive counseling, which was the lowest measure for quality of PAC in Kenya (19.4%) and Nigeria (16%) [22, 35]. Because we did not find any recent estimate in Burkina Faso, we used the 50% proxy in order to generate the maximum sample size possible. These calculations yielded the number of facilities required for each country, and upon accounting for a response rate of approximately 93%, the estimated sample size of facilities was determined as follows: 414 in Burkina Faso, 259 in Kenya, and 223 in Nigeria. The total sample size of health facilities was allocated to each of the seven sub-national units in each country depending on the population of eligible facilities in a specific region/county or state. Therefore, health facilities were randomly selected within each sub-national level with all tertiary health facilities included and a sample of primary and secondary health facilities. Eligible facilities were those that could provide normal delivery services, were publicly owned (government owned) and operational at the time of survey. As such, we excluded some specialized facilities including mental and spinal hospitals as well as military and prison hospitals known not to offer services to the public. Our focus on public health facilities is because government investments in health services primarily go to these facilities. During the survey, some facilities were dropped and replaced with similar facilities within the same locality, due to insecurity and travel inaccessibility. In addition, sampled facilities that declined to participate in the study were replaced with similar facilities from the sampling frame, which had been identified a priori. Trained field workers visited each eligible facility and administered the signal functions questionnaire which had been adopted from previous versions [36, 37]. The questionnaire was further refined to the contexts following extensive discussions with experienced obstetricians and gynecologists in each country. The questionnaires captured details on availability of key equipment, supplies and commodities, staffing and staff training, facility operation hours and ability to perform various sexual and reproductive health services (Supplementary file 1). Uniform tools were used across all countries. However, some aspects were adapted to fit in national standards (e.g. facilities categorizations). We asked the providers whether they were currently providing the listed services (Table 1). Whenever the provider indicated that a particular service was currently unavailable, the next sets of questions probed for the reasons why the service is not available. In response, the providers listed all possible reasons why the service was unavailable at that time. The tools were pre-tested to enhance conceptual clarity and logical flow. At large referral hospitals, respondents were the head of the obstetrics and gynecology department, or a key obstetrician gynecologist working in the facility. However, at lower level facilities, a nurse, a midwife or another health worker who was knowledgeable on PAC services provided in the facility was interviewed. The quantitative data were collected using tablets and hosted on the SurveyCTO platform. Completed and verified data were uploaded unto the APHRC cloud server for safe storage. Spot-checks were performed on 5% of the sample by the lead for each country. Description of signal functions for basic and comprehensive PAC services Source: Owolabi et al., (2019) [23] aHealth facilities reported whether they were providing the service bHealth facilities indicated availability of drugs or equipment, and also indicated the validity or functionality of the given item cThis was premised on availability of staff capable of conducting caesarean sections (would also capable of doing normal deliveries) Using the Ministry of Health master list of health facilities in Burkina Faso, Kenya and Nigeria, and the sampling frame of public facilities, we constructed facility-levels weights accounting for the sample design and adjusting for stratification by regions/counties/states, and facility non-response, as well as applying a finite population correction. The statistical analysis was conducted in Stata version 15.0 [38]. We therefore use weighted data to describe the capacity of health facilities to deliver PAC services. We drew from the Owolabi et al. (2019) approach and constructed composite or aggregate indicators of signal functions to provide basic and comprehensive PAC using a signal functions approach [23]. By calculating the availability of specific health interventions that are key to PAC—i.e., the signal functions—we measure the capacity for, and quality of, PAC from a health systems perspective. We do this by summating or combining sets of indicators that constitute the two delineated levels of care – basic and comprehensive PAC, that roughly correspond to care that should be provided at both the primary level and at the referral level hospitals respectively (Table (Table1).1). A key departure from the Owolabi approach is that under basic PAC indicators, we excluded the ability to communicate with referral facilities. This was mainly because this variable was not captured in our data collection tool and was proxied with having an established referral pathway between different health facilities. We also explored another level of analysis, again adopted from the Owolabi paper [23], which included developing case scenarios by excluding some PAC signal functions to have a less restrictive criterion at various stages. At first, we analyzed all PAC signal functions for each facility levels. Secondly, we excluded the availability of staff capable of conducting normal deliveries, thirdly, we excluded – staff with delivery capabilities; having a referral capacity; availability of short and long-acting, or permanent family planning methods. At the fourth stage, we examined PAC capability by excluding the ability of a facility to conduct referrals (through having a vehicle fueled). “Capacity” or “preparedness” was conceptualized as the ability of health facilities to deliver services based on signal function indicators [37]. Proportions of facilities capable of delivering basic and comprehensive PAC were generated.

Materials

https://efashare.b-cdn.net/materials/6a925fe0e9f7f908fee0b6b0c25de8a8603f4226cb72ff2e222a86e5e58ce82f/12913_2022_7873_MOESM1_ESM.pdf

Innovations

Based on the provided information, here are some potential innovations that could improve access to maternal health:

1. Telemedicine: Implementing telemedicine services can provide remote access to healthcare professionals, allowing pregnant women to receive medical advice, consultations, and follow-up care without having to travel long distances.

2. Mobile health (mHealth) applications: Developing mobile applications that provide educational resources, appointment reminders, and personalized health information can empower pregnant women to take control of their own health and access important maternal health services.

3. Community health workers: Training and deploying community health workers who can provide basic maternal health services, education, and support in remote or underserved areas can help bridge the gap in access to healthcare for pregnant women.

4. Transportation solutions: Improving transportation infrastructure and implementing innovative transportation solutions, such as mobile clinics or ambulance services, can ensure that pregnant women can reach healthcare facilities in a timely manner, especially in rural or hard-to-reach areas.

5. Task-shifting and training: Expanding the roles and responsibilities of healthcare workers, such as nurses and midwives, through task-shifting and providing them with additional training can increase the availability of skilled healthcare providers for maternal health services.

6. Supply chain management: Implementing efficient supply chain management systems to ensure the availability of essential medicines, equipment, and supplies for maternal health services can help prevent stockouts and ensure that healthcare facilities are adequately equipped to provide quality care.

7. Public-private partnerships: Collaborating with private sector organizations, such as pharmaceutical companies or technology companies, can leverage their resources, expertise, and innovation to improve access to maternal health services.

8. Health financing mechanisms: Developing innovative health financing mechanisms, such as health insurance schemes or conditional cash transfer programs, can help reduce financial barriers and increase access to maternal health services for vulnerable populations.

9. Quality improvement initiatives: Implementing quality improvement initiatives, such as clinical guidelines, training programs, and accreditation systems, can enhance the quality of maternal health services and improve patient outcomes.

10. Data-driven decision making: Utilizing data and technology to collect, analyze, and disseminate information on maternal health outcomes and service utilization can help identify gaps in access and guide evidence-based decision making to improve maternal health services.

It is important to note that the specific context and needs of each country or region should be considered when implementing these innovations to ensure their effectiveness and sustainability.

AI Innovations Description

The study mentioned in the description assessed the preparedness of public health facilities in Burkina Faso, Kenya, and Nigeria to provide post-abortion care (PAC) services. The study found significant gaps and weaknesses in the delivery of both basic and comprehensive PAC services in these countries. Some of the main reasons for the inability to provide specific PAC services included a lack of trained staff, absence of necessary equipment, and a shortage of PAC commodities and supplies.

Based on these findings, the study recommends increased investments by governments to strengthen the capacity of primary, secondary, and tertiary public health facilities to deliver quality PAC services. This would involve improving the availability of trained staff, ensuring the necessary equipment and supplies are in place, and addressing the lack of PAC commodities and supplies. Additionally, there is a need to strengthen the referral system for acute PAC cases to higher-level facilities.

By implementing these recommendations, access to PAC services can be improved, leading to a reduction in unsafe abortions and preventable maternal mortalities.

AI Innovations Methodology

Based on the provided description, here are some potential recommendations to improve access to maternal health:

1. Strengthening Health Facility Capacities: Increase investments by governments to enhance the capacity of primary, secondary, and tertiary public health facilities to deliver quality post-abortion care (PAC) services. This includes ensuring the availability of trained staff, necessary equipment, and PAC commodities and supplies.

2. Improving Referral Systems: Address the weakness in the provision of post-abortion care services by strengthening the capacity of health facilities to refer acute PAC cases to higher-level facilities. This can be done by establishing efficient referral pathways and ensuring access to transportation for timely transfers.

3. Policy and Legal Reforms: Advocate for policy and legal reforms to expand access to safe and legal abortion services. This can help reduce the incidence of unsafe abortions and the resulting complications, leading to improved maternal health outcomes.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could be developed as follows:

1. Define Key Indicators: Identify key indicators that reflect access to maternal health, such as the proportion of health facilities capable of delivering basic and comprehensive PAC services, the availability of trained staff, necessary equipment, and PAC commodities and supplies, and the effectiveness of referral systems.

2. Data Collection: Collect data on the identified indicators before implementing the recommendations. This can be done through surveys, interviews, and record reviews in the selected countries.

3. Implement Recommendations: Implement the recommended interventions, such as increasing investments in health facilities, strengthening referral systems, and advocating for policy and legal reforms.

4. Data Collection: After a suitable period of time, collect data again on the same indicators to assess the impact of the implemented recommendations. This can be done using the same data collection methods as in the initial phase.

5. Data Analysis: Analyze the collected data to compare the indicators before and after the implementation of the recommendations. This analysis can include calculating proportions, conducting statistical tests, and comparing trends over time.

6. Interpretation of Results: Interpret the findings to determine the impact of the recommendations on improving access to maternal health. This can involve identifying any changes in the proportion of facilities capable of delivering PAC services, improvements in the availability of trained staff and necessary resources, and enhancements in the effectiveness of referral systems.

7. Policy Recommendations: Based on the results, provide policy recommendations to further improve access to maternal health. These recommendations can be targeted towards governments, healthcare providers, and other stakeholders involved in maternal health services.

By following this methodology, it will be possible to simulate the impact of the recommendations on improving access to maternal health and provide evidence-based insights for decision-making and policy development.

Author

Dima Health

Statistics:

Citations: 1

Identifiers:

DOI: 10.1186/s12913-022-07873-y

Research Areas:

Community Interventions, Health System and Policy, Maternal and Child Health, Quality of Care, Sexual and Reproductive Health, Workforce

Study Countries:

Burkina Faso, Kenya, Multi-Countries, Nigeria

Study Design:

Cohort Study, Cross Sectional Study, Grounded Theory

Study Approach:

Quantitative