scholarly journals Texting Condolences: Adapting mHealth Programs After Unexpected Pregnancy and Infant Outcomes (Preprint)

2017 ◽  
Author(s):  
Jennifer A Unger ◽  
John Kinuthia ◽  
Grace John-Stewart

UNSTRUCTURED Mobile health (mHealth) short message system (SMS) interventions for maternal and child health (MCH) are being implemented globally. In many low- and middle-income settings in which these mHealth interventions are being rolled out, stillbirths and neonatal and infant deaths are common. It is important that mHealth solutions do not exacerbate emotional stress and pain by continuing with routine messaging for pregnancy or infant care when someone has experienced loss. In this brief viewpoint paper, we argue that SMS programs for maternal and child health need to adapt and make available messaging for miscarriage, stillbirth, and infant loss.

Author(s):  
Briana Britton ◽  
Laura Pugliese ◽  
Stan Kachnowski

The incorporation of mobile devices into the delivery of healthcare, known as mHealth, is changing the way care is delivered in the 21st century. The impact of mHealth is particularly salient in low and middle income countries (LMICs), where mHealth poses the opportunity to increase access and quality of healthcare in systems where supportive infrastructure is otherwise lacking. This approach is well-suited to target issues of maternal and child health, permitting an increase in health education, communication, monitoring, and care to what are often vulnerable and hard-to-access populations. Employing mHealth tactics that target such populations can improve the overall access and quality of maternal and child health in the developing world - a priority for the United Nations as reflected in the Millennium Development Goals (MDGs). While the field of mHealth is new and still developing, many programs and thought-leaders have already successfully applied mHealth strategies in interventions to improve maternal and child health through health education, preventive care, emergency response, biometric data collection, and training healthcare workers.


2018 ◽  
Vol 3 (3) ◽  
pp. e000466 ◽  
Author(s):  
Iryna Postolovska ◽  
Stéphane Helleringer ◽  
Margaret E Kruk ◽  
Stéphane Verguet

BackgroundMeasles supplementary immunisation activities (SIAs) are an integral component of measles elimination in low-income and middle-income countries (LMICs). Despite their success in increasing vaccination coverage, there are concerns about their negative consequences on routine services. Few studies have conducted quantitative assessments of SIA impact on utilisation of health services.MethodsWe analysed the impact of SIAs on utilisation of selected maternal and child health services using Demographic and Health Surveys and Multiple Indicator Cluster Surveys from 28 LMICs, where at least one SIA occurred over 2000–2014. Logistic regressions were conducted to investigate the association between SIAs and utilisation of the following services: facility delivery, postnatal care and outpatient sick child care (for fever, diarrhoea, cough).ResultsSIAs do not appear to significantly impact utilisation of maternal and child services. We find a reduction in care-seeking for treatment of child cough (OR 0.67; 95% CI 0.48 to 0.95); and a few significant effects at the country level, suggesting the need for further investigation of the idiosyncratic effects of SIAs in each country.ConclusionThe paper contributes to the debate on vertical versus horizontal programmes to ensure universal access to vaccination. Measles SIAs do not seem to affect care-seeking for critical conditions.


2020 ◽  
Author(s):  
Eveline Muika Kabongo ◽  
Ferdinand Mukumbang ◽  
Peter N/A Delobelle ◽  
Edward N/A Nicol

Abstract Background: Despite the growing global application of mobile health (mHealth) technology in maternal and child health, contextual factors, and mechanisms by which interventional outcomes are generated, have not been subjected to a systematic examination. In this study, we sought to uncover context, mechanisms, and outcome elements of various mHealth interventions based on implementation and evaluation studies to formulate theories or models explicating how mHealth interventions work (or not) both for health care providers and for pregnant women and mothers.Method: We undertook a realist synthesis. An electronic search of six online databases (Medline, PubMed, Google Scholar, Scopus, Academic Search Premier, and Health Systems Evidence) was performed. Using appropriate Boolean phrases terms and selection procedures, 32 articles were identified. A theory-driven approach, narrative synthesis, was applied to synthesize the data. Thematic content analysis was used to delineate elements of the intervention, including its context, actors, mechanisms, and outcomes. Abduction and retroduction were applied using a realist evaluation heuristic tool to formulate generative theories.Results: We formulated two configurational models illustrating how and why mHealth impacts the implementation and uptake of maternal and child care services. Implementation-related mechanisms include buy-in from health care providers, perceived support of health care providers’ motivation, and perceived ease of use and usefulness. These mechanisms were influenced by adaptive health system conditions including organization, resource availability, policy implementation dynamics, experience with technology, network infrastructure, and connectivity. For pregnant women and mothers, mechanisms that trigger mHealth use and consequently uptake of maternal and child health care include perceived satisfaction, motivation, and positive psychological support. Information overload was identified as a potential negative mechanism impacting the uptake of maternal and child health care. These mechanisms were influenced by health system conditions, socio-cultural characteristics, socio-economic and demographics characteristics, network infrastructure and connectivity, and awareness.Conclusion: Models developed in this study provide a detailed understanding of the implementation and uptake of mHealth interventions and how and why they impact maternal and child health care in low- and middle-income countries. These models provide a foundation for the ‘white box’ of theory-driven evaluation of mHealth interventions and can improve rollout and implementation where required.


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