Dataset Information

Modeling and testing maternal and newborn care mHealth interventions: a pilot impact evaluation and follow-up qualitative study in Guatemala.

ABSTRACT: Objective:To develop a descriptive model of structural characteristics of mHealth in the context of newborn nutrition, and to assess the effects of illustrative interventions through a mixed-methods study consisting of an impact evaluation and a qualitative assessment. Materials and Methods:We conducted a 23-week intervention with 100 mothers in rural Guatemala in 2013 and 2014. In group 1 ( n ?=?24), participants received health-promoting text messages. In group 2 ( n ?=?32), peer-to-peer groups were formed. In group 3 ( n ?=?30), peer-to-peer groups were formed, a health professional participated in the discussions, and participants received health-promoting messages. In the control group ( n ?=?14), participants were simply given a mobile phone. We measured changes in knowledge and self-reported behavior. Four focus groups in 2015 showed the perceptions of 44 additional women and the potential of the previously tested interventions in other marginalized areas. Results:Significant relationships were found between group membership and changes in knowledge ( P ?

SUBMITTER: Prieto JT

PROVIDER: S-EPMC5391724 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Modeling and testing maternal and newborn care mHealth interventions: a pilot impact evaluation and follow-up qualitative study in Guatemala.

Prieto José Tomás JT Zuleta Clara C Rodríguez Jorge Tulio JT

Journal of the American Medical Informatics Association : JAMIA 20170301 2

<h4>Objective</h4>To develop a descriptive model of structural characteristics of mHealth in the context of newborn nutrition, and to assess the effects of illustrative interventions through a mixed-methods study consisting of an impact evaluation and a qualitative assessment.<h4>Materials and methods</h4>We conducted a 23-week intervention with 100 mothers in rural Guatemala in 2013 and 2014. In group 1 ( n = 24), participants received health-promoting text messages. In group 2 ( n = 32), pee ...[more]

PMID: 27474102

Similar Datasets

Project description:BACKGROUND:In low-resource settings, there are numerous socioeconomic challenges such as poverty, inadequate facilities, shortage of skilled health workers, illiteracy and cultural barriers that contribute to high maternal and newborn deaths. To address these challenges, there are several mHealth projects particularly in Sub-Sahara Africa seeking to exploit opportunities provided by over 90% rate of mobile penetration. However, most of these interventions have failed to justify their value proposition to inspire utilization in low-resource settings. METHODS:This study proposes a theoretical model named Technology, Individual, Process-Fit (TIPFit) suitable for user-centred evaluation of intervention designs to predict utilization of mHealth products in low-resource settings. To investigate the predictive power of TIPFit model, we operationalized its latent constructs into variables used to predict utilization of an mHealth prototype called mamacare. The study employed single-group repeated measures quasi-experiment in which a random sample of 79 antenatal and postnatal patients were recruited from a rural hospital. During the study conducted between May and October 2014, the treatment involved sending and receiving SMS alerts on vital signs, appointments, safe delivery, danger signs, nutrition, preventive care and adherence to medication. RESULTS:Measurements taken during the study were cleaned and coded for analysis using statistical models like Partial Least Squares (PLS), Repeated Measures Analysis of Variance (RM-ANOVA), and Bonferroni tests. After analyzing 73 pretest responses, the model predicted 80.2% fit, and 63.9% likelihood of utilization. However, results obtained from initial post-test taken after three months demonstrated 69.1% fit, and utilization of 50.5%. The variation between prediction and the actual outcome necessitated improvement of mamacare based on feedback obtained from users. Three months later, we conducted the second post-test that recorded further drop in fit from 69.1 to 60.3% but utilization marginally improved from 50.5 to 53.7%. CONCLUSIONS:Despite variations between the pretest and post-test outcomes, the study demonstrates that predictive approach to user-centred design offers greater flexibility in aligning design attributes of an mHealth intervention to fulfill user needs and expectations. These findings provide a unique contribution for decision makers because it is possible to prioritize investments among competing digital health projects.

Project description:ObjectiveTo assess the effectiveness of mHealth interventions for maternal, newborn and child health (MNCH) in low- and middle-income countries (LMIC).Methods16 online international databases were searched to identify studies evaluating the impact of mHealth interventions on MNCH outcomes in LMIC, between January 1990 and May 2014. Comparable studies were included in a random-effects meta-analysis.FindingsOf 8593 unique references screened after de-duplication, 15 research articles and two conference abstracts met inclusion criteria, including 12 intervention and three observational studies. Only two studies were graded at low risk of bias. Only one study demonstrated an improvement in morbidity or mortality, specifically decreased risk of perinatal death in children of mothers who received SMS support during pregnancy, compared with routine prenatal care. Meta-analysis of three studies on infant feeding showed that prenatal interventions using SMS/cell phone (vs routine care) improved rates of breastfeeding (BF) within one hour after birth (odds ratio (OR) 2.01, 95% confidence interval (CI) 1.27-2.75, I(2) = 80.9%) and exclusive BF for three/four months (OR 1.88, 95% CI 1.26-2.50, I(2) = 52.8%) and for six months (OR 2.57, 95% CI 1.46-3.68, I(2) = 0.0%). Included studies encompassed interventions designed for health information delivery (n = 6); reminders (n = 3); communication (n = 2); data collection (n = 2); test result turnaround (n = 2); peer group support (n = 2) and psychological intervention (n = 1).ConclusionsMost studies of mHealth for MNCH in LMIC are of poor methodological quality and few have evaluated impacts on patient outcomes. Improvements in intermediate outcomes have nevertheless been reported in many studies and there is modest evidence that interventions delivered via SMS messaging can improve infant feeding. Ambiguous descriptions of interventions and their mechanisms of impact present difficulties for interpretation and replication. Rigorous studies with potential to offer clearer evidence are underway.

Project description:Aim and objectivesThis review analysed the implementation and integration into healthcare systems of maternal and newborn healthcare interventions in Africa that include community health workers to reduce maternal and newborn deaths.BackgroundMost neonatal deaths (99%) occur in low- and middle-income countries, with approximately half happening at home. In resource-constrained settings, community-based maternal and newborn care is regarded as a sound programme for improving newborn survival. Health workers can play an important role in supporting families to adopt sound health practices, encourage delivery in healthcare facilities and ensure timeous referral. Maternal and newborn mortality is a major public health problem, particularly in sub-Saharan Africa, where the Millennium Development Goals 4, 5 and 6 were not achieved at the end of 2015.MethodsThe review includes quantitative, qualitative and mixed-method studies, with a data-based convergent synthesis design being used, and the results grouped into categories and trends. The review took into account the participants, interventions, context and outcome frameworks (PICO), and followed the adapted PRISMA format for reporting systematic reviews of the qualitative and quantitative evidence guide checklist.ResultsThe results from the 17 included studies focused on three themes: antenatal, delivery and postnatal care interventions as a continuum. The main components of the interventions were inadequate, highlighting the need for improved planning before each stage of implementation. A conceptual framework of planning and implementation was elaborated to improve maternal and newborn health.ConclusionThe systematic review highlight the importance of thoroughly planning before any programme implementation, and ensuring that measures are in place to enable continuity of services.Relevant to the clinical practiceConceptual framework of planning and implementation of maternal and newborn healthcare interventions by maternal community health workers.

Dataset Information

Modeling and testing maternal and newborn care mHealth interventions: a pilot impact evaluation and follow-up qualitative study in Guatemala.

Publications

Modeling and testing maternal and newborn care mHealth interventions: a pilot impact evaluation and follow-up qualitative study in Guatemala.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets