Determinants of men’s involvement in maternity care in dodoma region, central Tanzania

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Study Justification:
– Men’s involvement in maternity care is important for improving maternal health and reducing maternal mortality.
– This study aimed to investigate the factors that determine men’s involvement in maternity care in Dodoma Region, Central Tanzania.
– Understanding these factors can help inform strategies to increase men’s involvement and improve maternal health outcomes.
Highlights:
– Only 1 in 5 men were found to be involved in maternity care of their partners.
– Factors that determined men’s involvement included having more than 4 children, urban area of residence, long waiting time at healthcare facilities, limited access to information, and limited spousal communication.
– Long waiting times and limited access to information were associated with lower men’s involvement in maternity care.
– Male-friendly maternity care should prioritize timely access to services and provide relevant information to men about their roles in maternity care.
– Spousal communication is important, and mothers should be empowered with information to communicate with their male partners about fertility preferences and maternity care.
Recommendations:
– Improve access to and availability of maternity care services to reduce waiting times.
– Develop and implement male-friendly maternity care programs that address men’s preferences for timely access to services and provide them with relevant information.
– Promote spousal communication about fertility preferences and maternity care through educational campaigns and support programs.
Key Role Players:
– Healthcare providers: They play a crucial role in providing male-friendly maternity care and ensuring timely access to services.
– Community leaders and influencers: They can help promote the importance of men’s involvement in maternity care and encourage spousal communication.
– Non-governmental organizations (NGOs): They can support the implementation of male-friendly maternity care programs and provide resources for education and awareness campaigns.
– Policy makers: They can create policies and allocate resources to support initiatives that promote men’s involvement in maternity care.
Cost Items for Planning Recommendations:
– Training and capacity building for healthcare providers on male-friendly maternity care: This includes workshops, materials, and resources.
– Development and dissemination of educational materials for men: This includes brochures, posters, and videos.
– Awareness campaigns: This includes media advertisements, community events, and outreach programs.
– Monitoring and evaluation: This includes data collection, analysis, and reporting to assess the impact of interventions.
– Collaboration and coordination: This includes meetings, workshops, and networking activities to bring together key stakeholders and ensure effective implementation of recommendations.

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is rated 7 because it provides a clear description of the study methodology and findings. However, it lacks information on the representativeness of the sample and the generalizability of the results. To improve the evidence, the authors could include details on the sampling method used and the demographic characteristics of the participants. Additionally, they could discuss the limitations of the study and suggest areas for further research.

Background. Men’s involvement in maternity care is recognized as a key strategy in improving maternal health and accelerating reduction of maternal mortality. This study investigated the factors determining men’s involvement in maternity care in Dodoma Region, Central Tanzania. Methods. This cross-sectional survey used multistage sampling in four districts of Dodoma Region to select 966 married men participants aged 18 years and above. Data were collected using a structured questionnaire. Multivariate logistic regression analysis was carried out in SPSS version 21.0 to measure the determinants of men’s involvement in maternity care. Results. The study found that only 1 in 5 men were involved in maternity care of their partners. Factors found to determine men’s involvement in maternity care were having >4 children (AOR=1.658, 95%CI=1.134 to 2.422), urban area of residence (AOR=0.510, 95%CI=0.354 to 0.735), waiting time >1 hour at the health care facility (AOR=0.685, 95%CI=0.479 to 0.978), limited access to information (AOR=0.491, 95%CI=0.322 to 0.747), and limited spousal communication (AOR=0.3, 95%CI=0.155 to 0.327). Conclusions. Long waiting time to receive the service and limited access to information regarding men’s involvement are associated with low men’s involvement in maternity care. Male friendly maternity care should recognize men’s preferences on timely access to services and provide them with relevant information on their roles in maternity care. Spousal communication is important; mothers must be empowered with relevant information to communicate to their male partners regarding fertility preferences and maternity care in general.

The study was conducted in Dodoma Region. The area was selected because it is the capital of the country and a fast growing region with a cultural diversity befitting the examination of male involvement in maternity care. Therefore, it was assumed that studying the determinants of men’s involvement in maternity care in Dodoma Region would provide a broad picture of the study findings from different cultures in Tanzania. Dodoma Region has seven districts; four districts were randomly selected to be involved in the study namely: Kondoa, Kongwa, Chamwino, and Dodoma Municipality. Dodoma Region is located in central part of Tanzania, with a population of 2,083,588 people and population density of 50 people per square kilometers. It covers an area of 41,310 square kilometers [26]. Male population accounts for 48.7% of the total population. The annual population growth rate is 2.1% with a sex ratio of 95 males to 100 females [26]. The region’s health care service structure is made up of seven hospitals, 32 health centers, and 269 dispensaries, most of which provide reproductive and child health services [26]. This study employed a descriptive cross-sectional survey using quantitative research approach. It involved married men aged 18 years and above, who resided with their spouses together in the same household, whose partner had a child aged two years or below, and whose partners had second pregnancy and above at the time of data collection and was willing to participate in the study. The study was conducted between November 2016 and June 2017. Sample size was estimated using the Kish Leslie’s formula based on the following assumptions: 95% confidence level, 39.2% estimated prevalence (findings from a previous study [8]), a 5% margin of error and a design effect assumed to be 2.5 to cater for intracluster variability; the sample was further increased by 20% to account for nonresponse or recording error [27]. Therefore, the estimated total sample size was 1,099 respondents. A three-stage cluster sampling strategy was used to select a representative sample from the four districts. First, all wards in the four districts were listed and then two wards in each district were randomly selected using the ballot method, which made a total of eight wards. In the second stage, all streets and villages in the selected wards were listed and then two streets in Dodoma Municipality and two villages in each three districts (Kondoa, Kongwa, and Chamwino) were randomly selected. In stage three, list of houses was obtained and then proportionate samples were drawn from each district. A systematic sampling technique with the starting point obtained using a table of random numbers was used to select the houses. In cases where more than one household was found in a house, one household was selected by using a single one-time ballot. In the households if a man had more than one partner with a child born within the past two years, the interview was conducted based on the information from the youngest child. Eligible men in the sampled household were approached to participate in the study. A structured, interviewer-administered questionnaire containing open and close-ended questions was used to collect data. This data collection tool was adapted from the previous works [6, 28]. The adaptation of the questionnaire was based on the aim and objectives of our study, literature review and relevant local factors related to the research question. The questionnaire was divided into three parts. The first part captured information on household social demographic variables. The second part assessed the level of men’s involvement in maternity care during antenatal, natal, and postnatal periods. The third part assessed the determinants of men’s involvement in maternity care. Prior to data collection, the questionnaire was pretested in Bahi district, which has similar characteristics as the districts selected for study. The questionnaire was modified accordingly before being used in the study. It was administered by eight male research assistants who had recently graduated from medical school and were trained by principal investigator for 3 days before the start of data collection. The interviews were conducted in Swahili language. Prior to actual analysis of the data, the data were cleaned, validated, and analyzed using SPSS version 21.0. The dependent variable (men’s involvement in maternity care) was constructed as a single variable to obtain the involvement index using twelve dichotomized (yes/no) variables. The study assessed four activities and each activity had three variables as follows: (1) accompanies partner to antenatal, natal, and postnatal care, (2) provides physical and emotional support to his partner during antenatal, natal, and postnatal periods, (3) is involved in joint planning for antenatal care, place of delivery, and postnatal care, and (4) discusses maternal health issues with her health care providers during antenatal, natal, and postnatal periods. Factor analysis was performed to obtain male involvement index. The purpose was to measure how much each variable contributes to the outcome variable (male involvement). All twelve variables were subjected in the principal component analysis. In the first analysis four components with eigenvalues (variance) greater than one were extracted. According to “Kaiser’s rule” only those components with eigenvalues greater than one should be retained [29]. Based on Kaiser’s rule the study decided to retain the first component because it had greater eigenvalue (variance) than other components. In the first component the variables that had correlation coefficients score of less than 0.3 were excluded in the second analysis. Correlation coefficient (r) must be 0.30 or greater since anything lower would suggest a really weak relationship between the variables [30]. In this study six variables were found to have a correlation coefficient less than 0.3 which indicated a weak relationship with the outcome variable. The variables that had weak relationship were provides physical support during postnatal period, provides physical support during natal period, is involved in joint planning for place of delivery, is involved in joint planning for postnatal care, provides physical support during antenatal period, and accompanies partner to delivery of the child. These variables were excluded in the second factor analysis. The second factor analysis was performed with the remaining six variables. Two components with eigenvalues greater than one were extracted. Based on the same rule “Kaiser’s rule” the first component was retained because it had greater eigenvalue than the second component and this first component was the one used to obtain men’s involvement index score. After obtaining the scores of each respondent, the median, minimum, and maximum values of the scores were calculated as follows: mean was 0.7137965, median was 0.3460358, minimum score was -1.94712, and maximum score was 1.15192. To obtain the scores in percent the percentile was set as 0-50 low involvement and 51-100 as high involvement. Based on the median, mean, and maximum values the percentile was calculated and categorized as -1.94712 to less than 0.7137965 as low involvement and above 0.7137966 to 1.15192 as high involvement. Lastly the categories were coded as “0” for low involvement “1” for high involvement and the frequency of overall involvement score was obtained. Preventive cultural norms/taboo was measured by asking the respondents if there are any cultural norms or taboos which prevent them from accompanying their partners to the health care services and they were required to respond if it is yes/no. The variable attitude was measured by asking the respondents the following question: how do you find the attitude of health workers towards men who accompany their partners to hospital to seek care? The question had two options: (1) they attend to us very well and friendly and (2) they are unfriendly. Those who answered option one had a positive attitude and number two were regarded as negative attitude. Access to information was measured by asking the following question: have you ever heard or been told that men are supposed to attend at antenatal care services with their partners? (yes/no). Time spent while waiting for ANC service was measured by asking the following question: how long on average do you spend in the health facility when you accompany your partner for ANC service? The responses obtained were summarized into two categories (less than or equal to one hour/ more than one hour). Spousal communication was measured by asking the respondents the following question: do you discuss or ask your partner any issues related to her pregnancy and delivery? Respondents were required to answer if it is yes/no. The data was entered, cleaned, validated, and analyzed using Statistical Package for Social Sciences (SPSS Version 21.0). Variables were tabulated using frequencies and percentages. The Chi-square test was used for testing the significance of association between categorical variables. A bivariate analysis was carried out and crude odds ratios (ORs) for each variable were calculated. All variables that were significantly associated with men’s involvement in maternity care were included in a multivariate logistic regression analysis in order to determine their independent effects in maternity care. The Adjusted ORs and their corresponding 95% Confidence Interval (CI) were obtained. The level of significance was set at P < 0.05.

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

1. Reduce waiting time: Implement strategies to decrease the waiting time at healthcare facilities for both women and men accompanying their partners. This could include streamlining processes, improving appointment scheduling systems, and increasing the number of healthcare providers.

2. Increase access to information: Develop and implement targeted educational campaigns to raise awareness among men about the importance of their involvement in maternity care. This could involve distributing informational materials, conducting community workshops, and utilizing digital platforms to disseminate information.

3. Male-friendly maternity care: Create a supportive and welcoming environment for men in healthcare facilities by training healthcare providers to be more inclusive and sensitive to the needs of men. This could involve providing training on effective communication, cultural competency, and gender sensitivity.

4. Enhance spousal communication: Develop interventions that promote open and effective communication between partners regarding fertility preferences and maternity care. This could include couple counseling sessions, support groups, and educational programs that encourage dialogue and shared decision-making.

5. Address cultural norms and taboos: Work with community leaders, religious institutions, and other influential stakeholders to challenge and change cultural norms and taboos that prevent men from accompanying their partners to healthcare services. This could involve community engagement initiatives, awareness campaigns, and advocacy efforts.

It is important to note that these recommendations are based on the specific findings and context of the study conducted in Dodoma Region, Central Tanzania. The implementation of these innovations should be tailored to the local context and involve collaboration with relevant stakeholders, including healthcare providers, policymakers, and community members.
AI Innovations Description
The study titled “Determinants of men’s involvement in maternity care in Dodoma Region, Central Tanzania” aimed to investigate the factors influencing men’s involvement in maternity care in order to improve maternal health and reduce maternal mortality. The study was conducted in Dodoma Region, which was selected due to its cultural diversity and representation of different cultures in Tanzania.

The study used a cross-sectional survey design and involved 966 married men aged 18 years and above. The participants were selected using a multistage sampling technique in four districts of Dodoma Region: Kondoa, Kongwa, Chamwino, and Dodoma Municipality. Data were collected using a structured questionnaire administered by trained research assistants.

The study found that only 1 in 5 men were involved in maternity care of their partners. Several factors were identified as determinants of men’s involvement in maternity care. These factors included having more than 4 children, residing in an urban area, experiencing a waiting time of more than 1 hour at the healthcare facility, limited access to information, and limited spousal communication.

Based on the study findings, the researchers recommended the implementation of male-friendly maternity care services. This would involve recognizing men’s preferences for timely access to services and providing them with relevant information on their roles in maternity care. It was also emphasized that spousal communication is crucial, and mothers should be empowered with relevant information to communicate with their male partners regarding fertility preferences and maternity care in general.

In summary, the study highlighted the importance of men’s involvement in maternity care for improving maternal health outcomes. The recommendations focused on addressing the identified determinants of men’s involvement to enhance access to maternal health services and promote effective communication between couples.
AI Innovations Methodology
Based on the information provided, here are some potential recommendations to improve access to maternal health:

1. Reduce waiting time: Long waiting times at healthcare facilities were found to be a barrier to men’s involvement in maternity care. Implementing strategies to reduce waiting times, such as improving appointment scheduling systems, increasing healthcare staff, and streamlining processes, can help improve access to maternal health for both men and women.

2. Increase access to information: Limited access to information regarding men’s involvement in maternity care was identified as a factor affecting men’s participation. Developing and implementing targeted communication campaigns that provide information on the importance of men’s involvement in maternity care, their roles and responsibilities, and the benefits for both the mother and child can help increase awareness and encourage men to participate.

3. Improve spousal communication: Limited spousal communication was found to be associated with low men’s involvement in maternity care. Promoting open and supportive communication between partners regarding fertility preferences, pregnancy, and maternity care can help increase men’s involvement. Providing couples with communication tools and resources, such as counseling services or educational materials, can facilitate these conversations.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could include the following steps:

1. Define the indicators: Determine the specific indicators that will be used to measure access to maternal health, such as the percentage of men accompanying their partners to antenatal care, the percentage of men involved in joint planning for maternity care, or the percentage of men discussing maternal health issues with healthcare providers.

2. Baseline data collection: Collect baseline data on the selected indicators before implementing the recommendations. This can be done through surveys, interviews, or data from healthcare facilities.

3. Implement the recommendations: Implement the recommended strategies, such as reducing waiting times, increasing access to information, and promoting spousal communication.

4. Post-implementation data collection: After a sufficient period of time, collect data on the selected indicators again to measure the impact of the recommendations. This can be done using the same methods as the baseline data collection.

5. Data analysis: Analyze the data collected before and after implementing the recommendations to determine the changes in the selected indicators. This can be done using statistical analysis techniques, such as chi-square tests or logistic regression analysis, to assess the significance of the changes.

6. Interpretation and reporting: Interpret the findings of the data analysis and report on the impact of the recommendations on improving access to maternal health. This can include presenting the changes in the selected indicators, identifying any barriers or challenges encountered during implementation, and providing recommendations for further improvement.

By following this methodology, it will be possible to simulate the impact of the recommendations on improving access to maternal health and assess their effectiveness in increasing men’s involvement in maternity care.

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