Iodine and pregnancy – a qualitative study focusing on dietary guidance and information

Iodine is essential for thyroid hormones synthesis and normal neurodevelopment; however, ~60% of pregnant women do not meet the WHO (World Health Organization) recommended intake. Using a qualitative design, we explored the perceptions, awareness, and experiences of pregnancy nutrition, focusing on iodine. Women in the perinatal period (n = 48) were interviewed and filled in a food frequency questionnaire for iodine. Almost all participants achieved the recommended 150 μg/day intake for non-pregnant adults (99%), but only 81% met the increased demands of pregnancy (250 μg/day). Most were unaware of the importance, sources of iodine, and recommendations for iodine intake. Attitudes toward dairy products consumption were positive (e.g., helps with heartburn; easy to increase). Increased fish consumption was considered less achievable, with barriers around taste, smell, heartburn, and morning sickness. Community midwives were the main recognised provider of dietary advice. The dietary advice received focused most often on multivitamin supplements rather than food sources. Analysis highlighted a clear theme of commitment to change behaviour, motivated by pregnancy, with a desired focus on user-friendly documentation and continued involvement of the health services. The study highlights the importance of redirecting advice on dietary requirements in pregnancy and offers practical suggestions from women in the perinatal period as the main stakeholder group

Effects of an mHealth intervention for community health workers on maternal and child nutrition and health service delivery in India: protocol for a quasi-experimental mixed-methods evaluation.

INTRODUCTION:Millions of children in India still suffer from poor health and under-nutrition, despite substantial improvement over decades of public health programmes. The Anganwadi centres under the Integrated Child Development Scheme (ICDS) provide a range of health and nutrition services to pregnant women, children <6 years and their mothers. However, major gaps exist in ICDS service delivery. The government is currently strengthening ICDS through an mHealth intervention called Common Application Software (ICDS-CAS) installed on smart phones, with accompanying multilevel data dashboards. This system is intended to be a job aid for frontline workers, supervisors and managers, aims to ensure better service delivery and supervision, and enable real-time monitoring and data-based decision-making. However, there is little to no evidence on the effectiveness of such large-scale mHealth interventions integrated with public health programmes in resource-constrained settings on the service delivery and subsequent health and nutrition outcomes. METHODS AND ANALYSIS:This study uses a village-matched controlled design with repeated cross-sectional surveys to evaluate whether ICDS-CAS can enable more timely and appropriate services to pregnant women, children <12 months and their mothers, compared with the standard ICDS programme. The study will recruit approximately 1500 Anganwadi workers and 6000+ mother-child dyads from 400+ matched-pair villages in Bihar and Madhya Pradesh. The primary outcomes are the proportion of beneficiaries receiving (a) adequate number of home visits and (b) appropriate level of counselling by the Anganwadi workers. Secondary outcomes are related to improvements in other ICDS services, and knowledge and practices of the Anganwadi workers and beneficiaries. ETHICS AND DISSEMINATION:Ethical oversight is provided by the Committee for the Protection of Human Subjects at the University of California at Berkeley, and the Suraksha Independent Ethics Committee in India. The results will be published in peer-reviewed journals and analysis data will be made public. TRIAL REGISTRATION NUMBER:ISRCTN83902145

Integrating Antenatal and Postnatal Pregnancy Services to Hospital Management System

Antenatal and postnatal processes and services is a component of Hospital Management Systems that has been given very little attention. Most healthcare institution carries out the antenatal and postnatal processes manually and keeps records of the whole processes on paper. In most cases in most hospital, records kept on paper and files get missing or misplaced leading to the loss of important records of clients which would have been very helpful for future pregnancies and clinical diagnosis. Report generation and statistical figures are difficult to generate with the manual based system. Data errors, security, and privacy are another problems associated with the manual system. In this paper, the antenatal and postnatal services were incorporated into the Hospital Management System of Usmanu Danfodiyo University, Sokoto with a view to reducing the issues and inconsistencies encountered with the manual procedure. Dreamweaver, PHP, CSS, JavaScript, Ajax, HTML and MySQL are the technological tools used to automate the incorporated antenatal and postnatal services in the system. The usefulness of the proposed system was evaluated using the System Usability Scale (SUS) questionnaire and some clinical users. The experimental evaluation shows that the developed system is beneficial to the clinic and the general public based on the result obtained in this study. The results also demonstrated that the developed system can fit into the antenatal and postnatal routine of many hospitals with little or no modification

Intervention planning and modification of the BUMP intervention: a digital intervention for the early detection of raised blood pressure in pregnancy

Background: Hypertensive disorders in pregnancy, particularly pre-eclampsia, pose a substantial health risk for both maternal and foetal outcomes. The BUMP (Blood Pressure Self-Monitoring in Pregnancy) interventions are being tested in a trial. They aim to facilitate the early detection of raised blood pressure through self-monitoring. This article outlines how the self-monitoring interventions in the BUMP trial were developed and modified using the person-based approach to promote engagement and adherence. Methods: Key behavioural challenges associated with blood pressure self-monitoring in pregnancy were identified through synthesising qualitative pilot data and existing evidence, which informed guiding principles for the development process. Social cognitive theory was identified as an appropriate theoretical framework. A testable logic model was developed to illustrate the hypothesised processes of change associated with the intervention. Iterative qualitative feedback from women and staff informed modifications to the participant materials. Results: The evidence synthesis suggested women face challenges integrating self-monitoring into their lives and that adherence is challenging at certain time points in pregnancy (for example, starting maternity leave). Intervention modification included strategies to address adherence but also focussed on modifying outcome expectancies, by providing messages explaining pre-eclampsia and outlining the potential benefits of self-monitoring. Conclusions: With an in-depth understanding of the target population, several methods and approaches to plan and develop interventions specifically relevant to pregnant women were successfully integrated, to address barriers to behaviour change while ensuring they are easy to engage with, persuasive and acceptable

The effectiveness of mHealth interventions for maternal, newborn and child health in low- and middle-income countries:Protocol for a systematic review and meta-analysis

Rates of maternal, newborn and child (MNCH) mortality and morbidity are vastly greater in low– than in high–income countries and represent a major source of global health inequity. A host of systemic, economic, geopolitical and sociocultural factors have been implicated. Mobile information and communication technologies hold potential to ameliorate several of these challenges by supporting coordinated and evidence–based care, facilitating community based health services and enabling citizens to access health information and support. mHealth has attracted considerable attention as a means of supporting maternal, newborn and child health in developing countries and research to assess the impacts of mHealth interventions is increasing. While a number of expert reviews have attempted to summarise this literature, there remains a need for a fully systematic review employing gold standard methods of evidence capture, critical appraisal and meta–analysis, in order to comprehensively map, quality assess and synthesise this body of knowledge

Smartphone-Based Prenatal Education for Parents with Preterm Birth Risk Factors

Objective To develop an educational mobile application (app) for expectant parents diagnosed with risk factors for premature birth. Methods Parent and medical advisory panels delineated the vision for the app. The app helps prepare for preterm birth. For pilot testing, obstetricians offered the app between 18–22 weeks gestational age to English speaking parents with risk factors for preterm birth. After 4 weeks of use, each participant completed a questionnaire. The software tracked topics accessed and duration of use. Results For pilot testing, 31 participants were recruited and 28 completed the questionnaire. After app utilization, participants reported heightened awareness of preterm birth (93%), more discussion of pregnancy or prematurity issues with partner (86%), increased questions at clinic visits (43%), and increased anxiety (21%). Participants reported receiving more prematurity information from the app than from their healthcare providers. The 15 participants for whom tracking data was available accessed the app for an average of 8 h. Conclusion Parents with increased risk for preterm birth may benefit from this mobile app educational program. Practice implications If the pregnancy results in preterm birth hospitalization, parents would have built a foundation of knowledge to make informed medical care choices

Word Adjacency Graph Modeling: Separating Signal From Noise in Big Data

There is a need to develop methods to analyze Big Data to inform patient-centered interventions for better health outcomes. The purpose of this study was to develop and test a method to explore Big Data to describe salient health concerns of people with epilepsy. Specifically, we used Word Adjacency Graph modeling to explore a data set containing 1.9 billion anonymous text queries submitted to the ChaCha question and answer service to (a) detect clusters of epilepsy-related topics, and (b) visualize the range of epilepsy-related topics and their mutual proximity to uncover the breadth and depth of particular topics and groups of users. Applied to a large, complex data set, this method successfully identified clusters of epilepsy-related topics while allowing for separation of potentially non-relevant topics. The method can be used to identify patient-driven research questions from large social media data sets and results can inform the development of patient-centered interventions

Mobile Health Care over 3G Networks: the MobiHealth Pilot System and Service

Health care is one of the most prominent areas for the application of wireless technologies. New services and applications are today under research and development targeting different areas of health care, from high risk and chronic patients’ remote monitoring to mobility tools for the medical personnel. In this direction the MobiHealth project developed and trailed a system and a service that is using UMTS for the continuous monitoring and transmission of vital signals, like Pulse Oximeter sensor , temperature, Marker, Respiratory band, motion/activity detector etc., to the hospital. The system, based on the concept of the Body Area Network, is highly customisable, allowing sensors to be seamlessly connected and transmit the monitored vital signal measurements. The system and service was trialed in 4 European countries and it is presently under market validation