Mobile phone access and willingness among mothers to receive a text-based mhealth intervention to improve prenatal care in northwest ethiopia: Cross-sectional study

  • JMIR Pediatrics and Parenting, Volume 1, No. 2, Year 2018

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Study Justification:
– Maternal mortality is a significant issue in low- and middle-income countries, often due to limited access to health services and low utilization of antenatal care.
– Effective communication and engagement with care providers are crucial for the delivery and receipt of sufficient healthcare services.
– Simple text-based interventions have shown evidence of improving prenatal care utilization, but there is a lack of context and preliminary evidence on how to implement these interventions on a larger scale.
Study Highlights:
– The study aimed to determine access to mobile phones and willingness to receive a text message-based mHealth intervention among pregnant women attending antenatal care in Northwest Ethiopia.
– A total of 416 pregnant women were included in the analysis, with a response rate of 98.6%.
– 76.7% of respondents owned a mobile phone, and 71.2% were willing to receive an SMS text message.
– Factors associated with willingness included youth age group, higher educational level, and frequency of mobile phone use.
– Among the phone owners, 90.0% could read and 86.8% could send SMS text messages.
Study Recommendations:
– The high proportion of pregnant women with mobile phones and willingness to receive SMS text message-based mHealth interventions suggests the potential for implementing such interventions on a larger scale.
– Age, educational status, and frequency of mobile phone use should be considered when designing and implementing mHealth interventions.
– Further research and pilot studies are needed to explore the effectiveness and feasibility of text-based interventions for improving prenatal care utilization in low-resource settings.
Key Role Players:
– Researchers and public health professionals: To conduct further research, pilot studies, and program evaluations related to text-based mHealth interventions for prenatal care.
– Healthcare providers: To integrate mHealth interventions into antenatal care services and provide support and guidance to pregnant women.
– Mobile network operators: To ensure reliable network coverage and accessibility to mobile phone services in remote areas.
– Policy makers and government agencies: To develop policies and allocate resources for the implementation and scale-up of mHealth interventions for prenatal care.
Cost Items for Planning Recommendations:
– Research and program evaluation costs: Including funding for research studies, pilot programs, and program evaluations to assess the effectiveness and feasibility of text-based mHealth interventions.
– Training and capacity building costs: To train healthcare providers and other key stakeholders on the implementation and management of mHealth interventions.
– Mobile network infrastructure costs: To ensure reliable network coverage and accessibility to mobile phone services in remote areas.
– Communication and outreach costs: Including the development and dissemination of educational materials and messages for pregnant women.
– Monitoring and evaluation costs: To track the progress and impact of mHealth interventions and make necessary adjustments for improvement.

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is based on a cross-sectional quantitative study conducted among 422 pregnant women attending antenatal care in Northwest Ethiopia. The study provides descriptive statistics, bivariable and multivariable logistic regression analyses, and odds ratios with 95% confidence intervals to identify factors associated with the willingness to receive a text message-based mHealth intervention. The study has a high response rate and provides specific details about the study population and methodology. However, the evidence is limited to a single study and does not include information on the generalizability of the findings or potential limitations of the study design. To improve the evidence, future research could include a larger sample size, a more diverse study population, and a longitudinal design to assess the long-term impact of text message-based mHealth interventions on prenatal care utilization.

Background: Maternal mortality remains high in many low- and middle-income countries where limited access to health services is linked to low antenatal care utilization. Effective communication and engagement with care providers are vital for the delivery and receipt of sufficient health care services. There is strong evidence that simple text-based interventions can improve the prenatal care utilization, but most mobile health (mHealth) interventions are not implemented on a larger scale owing to the lack of context and preliminary evidence on how to make the transition. Objective: The objective of this study was to determine access to mobile phones by pregnant women attending antenatal care as well as willingness to receive a text message (short message service, SMS)–based mHealth intervention for antenatal care services and identify its associated factors among pregnant women attending an antenatal care clinic in Gondar Town Administration, Northwest Ethiopia, Africa. Methods: A cross-sectional quantitative study was conducted among 422 pregnant women attending antenatal care from March 27 to April 28, 2017. Data were collected using structured questionnaires. Data entry and analysis were performed using Epi-Info version 7 and SPSS version 20, respectively. In addition, descriptive statistics and bivariable and multivariable logistic regression analyses were performed. Furthermore, odds ratio with 95% CI was used to identify factors associated with the willingness to receive a text message–based mHealth intervention. Results: A total of 416 respondents (response rate 98.6%, 416/422) were included in the analysis. About 76.7% (319/416) of respondents owned a mobile phone and 71.2% (296/416) were willing to receive an SMS text message. Among the mobile phone owners, only 37.6% (120/319) were having smartphones. Of all women with mobile phones, 89.7% (286/319) described that they are the primary holders of these phones and among them, 85.0% (271/319) reported having had the same phone number for more than a year. Among the phone owners, 90.0% (287/319) described that they could read and 86.8% (277/416) could send SMS text messages using their mobile phones in their day-to-day activities. Among pregnant women who were willing to receive SMS text messages, about 96.3% (285/296) were willing to receive information regarding activities or things to avoid during pregnancy. Factors associated with willingness were youth age group (adjusted odds ratio [AOR] 2.869, 95% CI 1.451-5.651), having attained secondary and higher educational level (AOR 4.995, 95% CI 1.489-14.773), and the frequency of mobile phone use (AOR 0.319, 95% CI 0.141-0.718). Conclusions: A high proportion of pregnant women in an antenatal care clinic in this remote setting have a mobile phone and are willing to receive an SMS text message–based mHealth intervention. Age, educational status, and the frequency of mobile phone use are significantly associated with the willingness to receive SMS text message–based mHealth interventions.

A cross-sectional quantitative study was conducted at 8 health facilities from March 27 to April 28, 2017, in the Gondar Town Administration, Northwest Ethiopia. The Gondar Town Administration is divided into 8 clusters namely Gondar, Ginbot 20, Azezo, Gebriel, Maraki, Woleka, Teda, and Belajig; the administration has a total of 24 Kebele (13 urban and 11 rural). In addition, the administration has a total of 23 public health facilities, 1 referral hospital, 8 health centers, and 14 health posts. Of the estimated population of the town, 49.5% (162,192/327,661) are females and 50.5% (165,469/327,661) are males. Among the total population, 260,183 are urban inhabitants and the rest 67,478 are rural inhabitants. In the 2016-17 budget year, the number of women in the reproductive age group was 77,262 and the estimated number of pregnancies was 11,042 (data from Gondar Town health department). In the Ethiopian context, health center means a health facility that provides primary health care and urban area implies a town that consists of at least 2000 residences. All women who were pregnant and attending ANC service at health centers during the study period were used as the study population. The sample size of this study was determined using the single population proportion formula (n=(z α/2)2pq/∂2) with the following assumptions: We could not find any studies conducted to determine the mobile phone ownership among pregnant women attending ANC in Ethiopia, although the general subscriber identity module (SIM or subscriber identification module) population in Ethiopia is 48.3% [20]. Moreover, we could not find any study conducted in Ethiopia to determine the willingness of pregnant women who are attending ANC to receive SMS text message–based mHealth interventions for ANC services. Therefore, we assumed that 50% of pregnant women are willing to receive an SMS text message–based mHealth intervention for ANC services. The maximum sample size was 384 using the proportion of pregnant women who were attending ANC and willing to be contacted by mobile phone. Considering a 10% nonresponse rate, we calculated the final sample size to be 422. Thus, a systematic random sampling technique was performed to select 422 study participants. Women exiting ANC visit were approached for interviews at each of the 8 health centers. The interviews included sociodemographic characteristics, physical accessibility to a health care facility, electricity and network availability, patterns of mobile phone use, and women’s opinion and willingness to receive health information via SMS text messages through mobile phones. Questionnaires were first developed in English, which then underwent forward and backward translation to ensure semantic consistency (English to Amharic then English), for the appropriateness and easiness in approaching study participants. Of note, a pretest of the questionnaire was conducted among pregnant women attending ANC (5% of the sample) before the study period at health centers in the Debre-tabor Town Administration, following which necessary modifications were made on the basis of pretest findings. Research personnel, including 2 health information technicians, 2 nurses with bachelor degrees acting as supervisors, and 8 clinical nurses serving as data collectors or interviewers, received a 1-day training course on implementing the evaluation, which included training on research ethics, providing informed consent, data collection procedures, data collecting tools, how to approach participants, data confidentiality, respondents’ right and all the study protocols to be followed throughout the course of the data collection period. In addition, continuous monitoring by supervisors was done throughout the data collection period to ensure that the data were collected according to the study protocol. The completed questionnaires were stored in binders in nurses’ class until collected by the principal investigator. Data were entered using Epi-Info version 7 and transferred to SPSS version 20. Descriptive statistics were performed to describe the study population. We used the binary logistic regression to analyze the association of each study variable on the outcome variable. The dependent variable was designated as “no”=0 (have no willingness) and “yes”=1 (for having willingness). Variables significantly associated with the outcome variable (P<.2) in the bivariable analysis were included in the multivariable logistic regression analysis for controlling the possible effects of confounders. In the multivariable analysis, Hosmer and Lemeshow goodness-of-fit test was performed (P=.76), and variables which were significant based on the adjusted odds ratio (AOR), with 95% CI and P<.05, were considered to be the determinant factors of willingness to receive an SMS text message–based mHealth intervention. Ethical clearance was obtained from the ethical review board of the University of Gondar. In addition, oral consent was obtained from study participants after narrating the objective of the study; they were also informed about the benefits of the study. If they felt discomfort during the interview, they were informed that they could stop at any time. Moreover, confidentiality assurance was provided to study participants on any information provided by them; the data collection procedure was anonymous, and their privacy was upheld.

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Innovation 1: Design a user-friendly text-based mHealth intervention that provides information and reminders about prenatal care, tailored to the specific needs of pregnant women in Northwest Ethiopia.

Innovation 2: Collaborate with healthcare providers in antenatal care clinics to integrate the text-based intervention into their existing services and train them on how to promote and support its use among pregnant women.

Innovation 3: Establish partnerships with mobile network operators to ensure widespread access to the text-based intervention, exploring options for providing free or low-cost access to pregnant women.

Innovation 4: Conduct pilot testing and evaluation of the text-based intervention to assess its effectiveness and feasibility, collecting feedback from pregnant women and healthcare providers to make necessary adjustments.

Innovation 5: Scale up the text-based intervention based on the results of the pilot program, collaborating with government agencies, NGOs, and other stakeholders to ensure sustainability and long-term impact.

Innovation 6: Continuously monitor and evaluate the impact of the text-based intervention on access to prenatal care and maternal health outcomes, collecting data on the number of pregnant women reached, their engagement with the intervention, and improvements in antenatal care utilization and maternal health indicators.
AI Innovations Description
The recommendation from the study is to develop a text-based mHealth intervention using mobile phones to improve access to prenatal care for pregnant women in Northwest Ethiopia. The study found that a high proportion of pregnant women attending antenatal care clinics in the region owned mobile phones and were willing to receive SMS text messages related to prenatal care. Factors associated with willingness to receive the intervention included being in the youth age group, having attained secondary and higher education, and frequency of mobile phone use.

To develop this recommendation into an innovation, the following steps can be taken:

1. Design a text-based mHealth intervention: Develop a comprehensive and user-friendly text-based intervention that provides information and reminders about prenatal care, including activities to avoid during pregnancy. The intervention should be culturally sensitive and tailored to the specific needs of pregnant women in Northwest Ethiopia.

2. Collaborate with healthcare providers: Work closely with healthcare providers in antenatal care clinics to integrate the text-based intervention into their existing services. Train healthcare providers on how to promote and support the use of the intervention among pregnant women.

3. Establish partnerships with mobile network operators: Collaborate with mobile network operators to ensure widespread access to the text-based intervention. Explore options for providing free or low-cost access to the intervention for pregnant women, considering the high proportion of mobile phone ownership among the target population.

4. Conduct pilot testing and evaluation: Implement a pilot program to test the effectiveness and feasibility of the text-based intervention. Collect feedback from pregnant women and healthcare providers to identify areas for improvement and make necessary adjustments to the intervention.

5. Scale up the intervention: Based on the results of the pilot program, scale up the text-based intervention to reach a larger number of pregnant women in Northwest Ethiopia. Collaborate with government agencies, non-governmental organizations, and other stakeholders to ensure sustainability and long-term impact.

6. Monitor and evaluate the intervention: Continuously monitor and evaluate the impact of the text-based intervention on access to prenatal care and maternal health outcomes. Collect data on the number of pregnant women reached, their engagement with the intervention, and any improvements in antenatal care utilization and maternal health indicators.

By implementing this recommendation and developing a text-based mHealth intervention, access to maternal health can be improved in Northwest Ethiopia, leading to better health outcomes for pregnant women and their babies.
AI Innovations Methodology
To simulate the impact of the main recommendations on improving access to maternal health, the following methodology can be used:

1. Define the target population: Identify the specific population of pregnant women in Northwest Ethiopia who would benefit from the text-based mHealth intervention. This could include pregnant women attending antenatal care clinics in the region.

2. Develop a simulation model: Create a simulation model that represents the target population and the healthcare system in Northwest Ethiopia. The model should include variables such as the number of pregnant women, their mobile phone ownership, willingness to receive SMS text messages, and factors associated with willingness (e.g., age, education level, frequency of mobile phone use).

3. Input data: Collect and input data into the simulation model based on the findings of the study. This includes the proportion of pregnant women who own mobile phones, the proportion willing to receive SMS text messages, and the factors associated with willingness.

4. Simulate the intervention: Implement the text-based mHealth intervention in the simulation model. This could involve sending SMS text messages to pregnant women based on their willingness and other factors. The model should simulate the impact of the intervention on access to prenatal care, such as increased utilization of antenatal care services and improved maternal health outcomes.

5. Analyze results: Analyze the results of the simulation to determine the impact of the intervention on improving access to maternal health. This could include measuring changes in antenatal care utilization rates, maternal health indicators, and other relevant outcomes.

6. Sensitivity analysis: Conduct sensitivity analysis to assess the robustness of the results. This involves varying the input parameters within a plausible range to see how sensitive the outcomes are to changes in those parameters.

7. Interpret and communicate findings: Interpret the findings of the simulation and communicate them to relevant stakeholders, such as healthcare providers, policymakers, and funding agencies. Highlight the potential benefits of the text-based mHealth intervention in improving access to maternal health and the factors that contribute to its effectiveness.

By using this methodology, researchers and policymakers can gain insights into the potential impact of implementing the text-based mHealth intervention and make informed decisions on its implementation and scalability.

Statistics:
Citations: 8
Authors: 6
Identifiers:
DOI: 10.2196/pediatrics.9618
Research Areas:
Community Interventions, Health System and Policy, Maternal Access, Maternal and Child Health, Quality of Care, Sexual and Reproductive Health, Social Determinants, Technology and Innovations
Study Countries:
Ethiopia
Study Design:
Case-Control Study, Cross Sectional Study, Grounded Theory, randomised-control-trial
Study Approach:
Quantitative
Participants Gender:
Female
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