Salam, S.S., Ali, N.B., Rahman, A.E. et al. (6 more authors) (2018) Study protocol of a 4- parallel arm, superiority, community based cluster randomized controlled trial comparing paper and e-platform based interventions to improve accuracy of recall of last menstrual period (LMP) dates in rural Bangladesh. BMC Public Health, 18 (1). 1359. ISSN 1471-2458
Abstract
Background
Gestational age (GA) is a key determinant of newborn survival and long-term impairment. Accurate estimation of GA facilitates timely provision of essential interventions to improve maternal and newborn outcomes. Menstrual based dating, ultrasound based dating, and neonatal estimates are the primarily used methods for assessing GA; all of which have some strength and weaknesses that require critical consideration. Last menstrual period (LMP) is simple, low-cost self-reported information, recommended by the World Health Organization for estimating GA but has issues of recall mainly among poorer, less educated women and women with irregular menstruation, undiagnosed abortion, and spotting during early pregnancy. Several studies have noted that about 20–50% of women cannot accurately recall the date of LMP. The goal of this study is therefore to improve recall and reporting of LMP and by doing so increase the accuracy of LMP based GA assessment in a rural population of Bangladesh where antenatal care-seeking, availability and utilization of USG is low.
Method
We propose to conduct a 4- parallel arm, superiority, community based cluster randomized controlled trial comparing three interventions to improve recall of GA with a no intervention arm. The interventions include (i) counselling and a paper based calendar (ii) counselling and a cell phone based SMS alert system (iii) counselling and smart-phone application. The trial is being conducted among 3360 adolescent girls and recently married women in Mirzapur sub-district of Bangladesh.
Discussion
Enrolment of study participants continued from January 24, 2017 to March 29, 2017. Data collection and intervention implementation is ongoing and will end by February, 2019. Data analysis will measure efficacy of interventions in improving the recall of LMP date among enrolled participants. Results will be reported following CONSORT guideline.
The innovative conventional & e-platform based interventions, if successful, can provide substantial evidence to scale-up in a low resource setting where m-Health initiatives are proliferating with active support from all sectors in policy and implementation.
Trial registration
ClinicalTrials.gov NCT02944747. The trial has been registered before starting enrolment on 24 October 2016.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Author(s). 2018. Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
Keywords: | Bangladesh; Gestational age; LMP; M-health; Mobile phone; Preterm birth; Recall; Adolescent; Adult; Bangladesh; Calendars as Topic; Cluster Analysis; Community Health Services; Counseling; Data Collection; Female; Humans; Menstrual Cycle; Mental Recall; Mobile Applications; Paper; Reproducibility of Results; Research Design; Rural Population; Smartphone; Text Messaging; Young Adult |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > School of Health and Related Research (Sheffield) > ScHARR - Sheffield Centre for Health and Related Research The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > The Medical School (Sheffield) > Division of Genomic Medicine (Sheffield) > Department of Oncology and Metabolism (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 03 Apr 2024 13:21 |
Last Modified: | 03 Apr 2024 13:21 |
Status: | Published |
Publisher: | Springer Science and Business Media LLC |
Refereed: | Yes |
Identification Number: | 10.1186/s12889-018-6258-z |
Related URLs: | |
Sustainable Development Goals: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:211045 |