Clinical Trial Details
— Status: Active, not recruiting
Administrative data
| NCT number |
NCT02944747 |
| Other study ID # |
PR-16031 |
| Secondary ID |
OPP1142797 |
| Status |
Active, not recruiting |
| Phase |
N/A
|
| First received |
|
| Last updated |
|
| Start date |
January 24, 2017 |
| Est. completion date |
October 2022 |
Study information
| Verified date |
January 2022 |
| Source |
International Centre for Diarrhoeal Disease Research, Bangladesh |
| Contact |
n/a |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Interventional
|
Clinical Trial Summary
Background (brief):
1. Burden: Bangladesh has a high maternal (194 per 100,000 live births) and newborn
mortality (28 per 1000 live births). In 2010, prematurity represented ~14% of all births
and directly and indirectly contributed to 45% of all neonatal deaths. 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.
2. Knowledge gap: Last menstrual period (LMP) is a simple, low-cost self reported
information, recommended by the World Health Organization for estimating gestational age
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.
3. Relevance: The goal of this study is to improve maternal and newborn outcomes by
increasing the accuracy of gestational age estimation, using menstrual based dating,
that is vital for providing timely and necessary obstetric and newborn care
interventions. The study will determine the efficacy of three community based
interventions using e-platform targeted to improve the recall and reporting of the date
of last menstrual period in a rural resource poor setting. The innovative e-platform
based interventions, if successful, can provide substantial evidence to scale-up in a
low resource setting where e-Health and m-Health initiatives are proliferating with
active support from all sectors in policy and implementation.
Hypothesis :
1. Implementation of conventional and e-platform based interventions will lead to a 30%
improvement in recall of the date of the LMP in adolescent girls and married women in
rural Bangladesh.
2. Intervention triggered improvement in LMP date recall among pregnant women in rural
Bangladesh will improve the accuracy in GA estimation.
Objectives: The main objectives of the study are to:
1. Determine whether a set of conventional and e-platform based interventions improve
recall of the date of the LMP in adolescent girls and married women in rural Bangladesh.
2. Determine whether intervention triggered improvement in LMP date recall in rural
Bangladesh improves the accuracy in GA estimation or not
Methods: A 4- parallel arm, superiority, community based cluster randomized controlled trial
comparing three conventional and e-platform based interventions is proposed to improve recall
of GA with a control arm. The trial will be conducted among adolescent girls and recently
married women (within past two years) with no children or a single child in Mirzapur
sub-district of Bangladesh.The interventions include (i) education and calendar for recording
date of LMP (ii) education and SMS based system for recording dates of LMP and reminders
using mobile phone (normal) (iii) education and smart-phone based application for recording
dates of LMP with an inbuilt reminder system.
Outcome measures/variables: The trial has two primary outcomes, (i) improvement in the recall
of LMP date among enrolled participants in the three different intervention compared to
control arm and (ii) increased accuracy of LMP-based gestational age measurement, as compared
to USG, following the intervention.
Description:
Background:
Bangladesh has a high maternal (194 per 100,000 live births) and newborn mortality (28 per
1000 live births)(1-3). In 2010, prematurity represented ~14% of all births and directly and
indirectly contributed to 45% of all neonatal deaths(4, 5). Accurate estimation of
gestational age (GA) is a critical for providing optimal clinical care during the prenatal,
delivery and postnatal period and for public health interventions(6). Knowing GA to the week
is essential for determining the adequacy of fetal growth, correct diagnosis of preterm or
post-term labor and also for the correct use of many interventions (e.g., antenatal
corticosteroids therapy, tocolytics, continuous positive airway pressure) targeted to improve
maternal and newborn outcomes(7).
Three methods of GA estimation are primarily used - menstrual based dating (LMP),
ultrasonography (USG) and neonatal assessment, all of which have some strengths and
weaknesses(8). USG, based on biometric measurements of the fetus, is considered to be the
gold standard when done before 20 weeks of gestation i.e., when biologic variations in fetal
size and the effects of growth restriction are low(9). However, the accuracy of USG decreases
when done in the latter trimesters, particularly in settings with high intrauterine growth
restriction, as in Bangladesh(10). However, USG is often unavailable in low-resource
countries, especially in rural areas. Even if it is available, the equipment can be of poor
quality and operated by personnel with minimal expertise(10). In addition, pregnancies are
often not identified until the 2nd or 3rd trimesters and women often seek antenatal care late
in their pregnancies, which further limits the use of USG to assess GA(10-12).
Alternate methods of assessing GA are therefore preferred in such settings. One approach is
to use neonatal assessments that are based on standardized scoring systems of physical and
neuromuscular maturity. These are, however, less precise then obstetric estimates and also
require skilled personnel which is frequently not practical(13). Dating based on the LMP is
another alternative. It is a simple, low-cost method recommended by the World Health
Organization(14). However, several studies have shown that that approximately 15-45% of
pregnant women are unable to recall their LMP accurately resulting in an unreliable estimate
and digit preference(15-17). Recall period is crucial determinant influencing accuracy of
LMP. Literature suggests that LMP recall is more precise with shorter recall period.(15)
Accuracy in recall of LMP is also limited due to irregularity or individual variations in the
length of the menstrual cycle, short birth spacing, preconception amenorrhea and implantation
bleeding(18, 19). This is further complicated by late presentation for first antenatal care
consultation and providers with minimal skills in probing for an accurate LMP date. Reliance
on LMP alone has shown a tendency to overestimate GA at the extremes of gestation which is
more common in women with no or low education and those living in poverty(15, 20). Despite
the limitations, studies conducted in Bangladesh and Guatemala has suggested LMP to be the
preferred method for determining GA in low-resource settings(10, 21).
The study therefore aim to determine the efficacy of three interventions targeted to improve
the recall and reporting of the LMP among women in rural Bangladesh. The interventions
include both conventional LMP dating calendar as well as an innovative e-platform - mobile
phones and smart phone applications.
Although calendar, or menstrual dairies has already been tried in clinical settings for
recording menstrual dates, public health implication of using these tools for recording LMP
is yet to be explored(15, 22). Moreover, use of m health for providing health education has
already shown impact on improving coverage of maternal health services.(23) Additionally,
providing educational and health promotion messages, tele-consultation, prescription and
referral through mobile phones are becoming increasingly popular in Bangladesh due to the
nationwide coverage of mobile network, availability of cheap hand sets, increasing use of
smart phones and cheap call rates. The growing investment of the public and private sector in
Information and Communications Techonology (ICT) has seen a substantial access and acceptance
of technology among the general public, especially the poor. In 2013, there were 105 million
active mobile phone subscribers with 75% of household in rural areas owning a mobile phone(3,
24). The current Government's mandate to build Digital Bangladesh also includes provision of
Quality Healthcare to all citizens through innovative application of ICT. A recent WHO report
indicated that health education was delivered by the health ministry to 98% of its target
population through SMS. All these initiatives support the potential financial viability for
eHealth and mHealth in Bangladesh and raises clear opportunities in terms of healthcare
provision and its scale-up(24).
Hypothesis :
1. Implementation of conventional and e-platform based interventions will lead to a 30%
improvement in recall of the date of the LMP in adolescent girls and married women in
rural Bangladesh.
2. Intervention triggered improvement in LMP date recall among pregnant women in rural
Bangladesh will improve the accuracy in GA estimation by 15%.
Specific Objectives:
The specific objectives are to:
1. Determine whether a set of conventional and e-platform based interventions improve
recall of the date of the LMP in adolescent girls and married women in rural Bangladesh.
2. Determine whether intervention triggered improvement in LMP date recall and reporting in
rural Bangladesh improves the accuracy in GA estimation or not.
Study Design:
In order to achieve the objectives, a 4- parallel arm, superiority, community based cluster
randomized controlled trial comparing conventional and e-platform based interventions is
proposed to improve recall of GA with a no intervention or control group. The trial will be
conducted among two groups of participants- adolescent girls and recently married women
(within past two years) with no children or a single child in a rural community in
Bangladesh. The four arms are:
Arm 1: Control arm. Arm 2: Education on the importance of remembering the date of LMP and a
paper based calendar to help remember and record the date of LMP in each month.
Arm 3: Education and a cell-phone based SMS alert system where participants will be asked to
text their LMP dates every month, free of cost. In situations, where the participants fail to
text, she will be provided SMS reminders.
Arm 4: Education and smart-phone based application for recording menstrual dates every month.
Setting:
The study will be carried out in Mirzapur sub-district of Tangail district located at the
northwest of Dhaka city, the capital of Bangladesh. Administratively Mirzapur has 13 unions
(the lowest administrative body), with 219 villages covering a area of 375 sq. km and a
population of 3,37,496. icddr,b has an existing demographic surveillance system (DSS) in
Mirzapur that covers 288,395 population from 10 unions, data in which is collected by 17
surveillance workers in a four monthly round. The trial will be implemented in the existing
surveillance area for ease of identification and enrollment of study participants. Table 1
also provides estimates on the number of adolescents in 2014 and married women with no or
single child at the start of 2014.
Participants:
Adolescent girls (15-17 years) and recently married women (within past two years) with no
children or a single child residing in the selected villages, willing to participate in this
study will be recruited.
Randomization, invitation, recruitment and consent:
The trial administrator for this study will be responsible for randomizing clusters in the
study arms. The DSS area consists of 1360 blocks, each with a population of 212 and is
assigned to 17 surveillance workers. For the purpose of this trial 136 clusters will be
formed each with 10 blocks i.e., each cluster will have a population of 2120. The trial
administrator will randomize the clusters to four arms (each with 34 clusters) using a
computer generated randomization schedule. To ensure that clusters of each DSS data collector
have a chance of receiving any of the interventions, randomization will be stratified by the
surveillance workers' area.
This design will control for potential confounding factors (observed and unobserved) as well
as selection bias especially by random assignment of the interventions and controls at
cluster level. We will try to ensure that there will be minimal chance of spill over as
participants from the same community or blocks will receive the same intervention and we will
try to keep geographical buffers between the clusters.
Following randomization of clusters, the required sample of adolescents and married women per
cluster will be selected from a list of eligible participants generated from the DSS
database. Those who agree to further contact will be recruited in the study after written
informed consent. Later LMP date of the recruited participants will be collected fortnightly
for 3 months in all the arms followed by baseline assessment. Interventions will be rolled
out after the baseline assessment and the person conducting or participating in the survey
will not be aware of the intervention group. The sample size calculations have been
elaborated in the section on Sample size .
Intervention activities:
(i) Intervention package and duration
Three interventions will be tested in this study. These are described below:
Intervention 1: This intervention will entail education and documentation of menstrual
bleeding on a paper based calendar. The participants will be counselled on importance of
remembering LMP. In addition, a free calendar will be provided to the participant who will be
asked to record menstrual bleeding and spotting dates in each month. The women will be asked
to record "no bleeding" if she did not bleed for any particular month. Likewise, if anybody
forgets to record, she will asked to keep a record of it in the subsequent month. Female
counselors from the study team will conduct the group or individual education sessions.
Intervention 2: Participants of this intervention will receive education and a cell-phone
based recording and SMS alert system. Cell-phones will be provided free of cost to
participants who will be asked to text the bleeding dates of their menstruation and spotting
every month within 3 days of the start of the bleeding. Study team will collaborate with a
mobile phone company and the charge of SMS for reporting LMP dates will be free for the user.
In situations, where the participant fails to text, she will be provided with several SMS
reminders after the due date.
Intervention 3: Participants of this intervention arm will receive education and a free
smart-phone with an application for recording menstruation dates and an inbuilt reminder
system. Experienced programmer from icddr,b will be involved in developing the application.
Again, participants will be asked to record bleeding dates each month and will upload the
data in the central server via internet. If participants fail to record the dates and upload
the data, an automatic reminders will be sent.
(ii) Enrolment in the intervention The study participants (adolescent girls & recently
married women) will be selected using DSS database and will be recruited in the LMP
surveillance after getting written informed consent. Thereafter, they would be offered either
of three interventions: menstrual tracking calendar, SMS or smart phone based LMP recording
system (as per intervention design). Following enrolment in the study, group or individual
counseling session will be conducted by female counselor to educate the participants on
importance of remembering LMP dates and on use of the tools for recording of LMP in each
month. The roll out of interventions will be cluster specific and will follow the same
sequence in which the baseline survey will be done.
(iii) Delivering the interventions Education will be provided by female counselors in
individual or group sessions immediately after baseline survey. The topics of education will
include importance of remembering and recording menstrual bleeding patterns and dates.
Calendar, mobile phones and smart phones will be given to the recruited participants at free
of cost and the study will bear the cost of SMS and internet for uploading data. The
counselors will also teach the participants how to record dates using the different tools.
The intervention will be reinforced intensively every month during the first 3 months and
later intensity of reinforcement will be adjusted depending on the compliance of the use of
tools.
Methods of data collection:
1. Data collection will employ the following techniques: 2. Household surveys in all arms 3.
LMP surveillance in all arms 4. Data extraction from the intervention tools. 5. Pregnancy
surveillance in intervention arms
(i) Household surveys: Household surveys will be conducted with eligible adolescents and
recently married women in all arms at two points of time: baseline- before the start of the
intervention and at end of project, after 12 months in the intervention arms. Any household
with no participants/guardian present at the time of the survey will be visited a second and
third time. If these additional visits are unsuccessful then the participants will be
excluded. Face-to face interviews will be conducted by trained data collectors using a
structured questionnaire (annex X) to elicit the required information.
Outcome variables:
Recalled and reported dates of LMP for the past 3 months prior to the survey and their level
of certainty in reporting the dates
Explanatory variables:
1. Demographic characteristics of participants including age, sex, education and occupation
2. Household socio-economic profile including housing status, assets, monthly income,
ownership of mobile phone & accessibility to mobile phone etc.
3. Birth history and use of contraceptives of married women
4. Information on menstrual irregularity, gynaecological problems
5. Acceptability, challenges and adherence to the tools (where applicable)
(ii) LMP surveillence in all the arms: LMP dates of the recruited participants will be
collected actively every two weeks so that the actual date of LMP is recorded in all arms for
3 months before baseline and endline survey. No other information will be elicited from the
participants.
(iii) Data extraction from the intervention tools: Data will be extracted from calendar
records, SMS and smart-phones. The data from mobile SMS will be obtained every month from the
mobile company whereas users of the smart-phone will be asked to upload their data via the
internet connected to the cell-phone. For participants using the calendar, data collectors
will collect the information from the enrolled household every two months.
(iv) Pregnancy surveillance in intervention arms: Pregnancy surveillance will be continued
throughout the intervention period among recently married women enrolled in the intervention
arms. In case of missed period reporting on calendar or failure of SMS or smart phone based
LMP reporting, a surveillance worker will visit the enrolled recently married women's house.
Surveillance worker will be complete each round every 8 weeks. Any women having missed period
within one year of recruitment will have the pregnancies confirmed through testing and their
recalled LMP date collected. They will be followed until 20 weeks into their pregnancy with
USG assessments being done between 10-13 weeks of gestation. The study will bear the cost of
USG and associated travel.
Study team:
(i) Central The study will be conducted by central team of investigators and field research
team. The Central team will be composed of one principle investigator, one MNCS expert as an
external co-principle investigator and 2 research investigators (1 full time equivalent). The
Central team will be responsible for overall study design, seeking ethical approval, tools
development, field implementation and quality assurance.
(ii) Intervention implementation team The intervention implementation team will be comprised
of female counselors, immediate supervisors and a manager. It was estimated that 15
counselors (5 per intervention arm) will be required to train/educate the participants (2400;
see sample size section for details) in the intervention arms in a period 1-2 months. As
mentioned earlier, female counselors will conduct education sessions twice during project
implementation period; at the beginning and six month after intervention. There will be one
immediate supervisor for the counselors in each arm and over all intervention activity will
be monitored by a field manager.
(ii) Data collection team The study will require approximately 3200 participants to estimate
the required effect size (detailed in the section on sample size calculation). Based on these
assumptions, it was estimated that the study will require fifteen data collectors to carry
out the surveys in two months in the study area. Additionally, 10 data collectors will be
deployed to collect regular LMP data from all the arms for 3 months before baseline and
enline survey and 5 data collectors for pregnancy surveillance throughout the project period.
The project will employ 2 immediate supervisors of data collectors and a manager to monitor
the activities of the data collection team.
Sample size:
Sample size has been calculated to observe expected changes in the primary outcome measure
using the formula for comparison of two proportions in the presence of clustering. The
investigators expect that any of the intervention arms will have a minimum 30% relative
improvement in accuracy of LMP recall in comparison to control arm and our intention is not
to compare between interventions due to resource constraints. Assuming that in the rural
context of Bangladesh approximately 55% of women can accurately recall LMP, to measure a 30%
expected change in recall after the implementation of the interventions, we will require 238
participants from 34 clusters per arm assuming 5% level of significance and 90% power.
Accounting for 15% refusal and 20% loss to follow-up we will require approximately 400
adolescents and 400 recently married women (within past 2 years) with no children or one
child in each arm. Hence, 1600 adolescents and 1600 recently married women will be required
in four arms. .
The second outcome aims to assess the accuracy of LMP based GA assessment in the intervention
arms compared to USG based GA. As mentioned a subset of the recently married women, who
become pregnant within a year of enrollment will recruited for this study. The study
conducted at Shishu Hospital in Bangladesh (10), have shown that the intra class correlation
coefficient of LMP based GA measurement versus USG based GA measurement was 0.84. Considering
a change of 15% from the above estimates due to the intervention, a sample of 120 pregnancies
will be required assuming 80% power, 5% level of significance and 20% refusal or loss to
follow-up. Women who become pregnant from the pool of 1200 married women from the three
intervention arms will be followed up until 16 weeks of gestation and will be asked to
undertake USG for GA measurement between 10-13 weeks. Surveillance data from Mirzapur shows
that approximately 11% of recently married women will become pregnant within the next year.
Hence, The investigators assume to get approximately 120 pregnant women out of 1200 married
women in the intervention groups.
Data analysis:
Data analysis will be done following intention to treat analysis under the guidance of an
experienced statistician. Analyses will be conducted at the individual level, and will be
adjusted for cluster randomization.
For the primary outcome we will first validate the tools by comparing the distribution of
recorded LMP dates between the intervention arms at different points in time (baseline and
endpoint) with actual LMP dates collected during LMP surveillance. We will examine the
proportion of women exactly reporting the accurate LMP dates. Differences in differences
method will be used to ascertain the change in proportion of women accurately reporting LMP
dates and their level of certainty on reporting LMP dates. Accuracy of LMP dates will be
ascertained if survey and surveillance dates matches within +/- 1 day variation for an
individual. Level of certainty of reporting LMP dates will be assessed using Likart scale.
The analysis will be adjusted for confounders such as education, socio-economic status and
length in recall time. Additionally, we will explore the change in mean and standard
deviation in reported LMP compared to the actual LMP by recall periods.
For the second outcome we will compare GA calculated by LMP and USG (gold standard) using the
mean (students t-test) and distribution. Convergent validity will also be assessed between
the estimates of GA by LMP and USG using intra-class correlation coefficients, Lin's
concordance coefficient and Bland-altman analysis for exact comparison of continuous values.
Stata® software version 13 will be used for all analyses.
Data safety & Monitoring:
We anticipate no risk of interventions. Validity and integrity of the data will be ensured by
appropriate research design, use of pretested and validated tools for data collection and by
quality assurance. In order to protect the safety of participants, all trial related
information will be kept confidential and stored securely at the central office in icddr,b.
Coded identification will be used to anonymyse and depersonalize the data. The linking code,
electronic data files and paper forms will be stored in a separate locations under password
protections or lock and key. Access to the data will be to the small number of individuals
including the investigators, statisticians, quality control and audit. The trial results will
be communicated and published irrespective of the outcome of the trial.
Ethical Approval:
Ethical approval for the trial has been obtained from the Institutional review Board of
icddr,b. The trial will be conducted following the ethical principles in the Declaration of
Helsinki and good practice guidelines on the proper conduct of research.
Informed consent process:
Participants will be informed about the objective of the study along with associated
risk/benefits and will be asked to participate voluntarily. Informed written consent will be
taken from the participants. For illiterate participants thumb print will be taken. If the
participant agrees to participate, they will be recruited for the study. Questionnaires will
be administered in the local language for data collection.
Perceived risks and benefits:
There are no risks to participation in this study. The topics addressed do not relate to
illegal, sensitive or stigmatized behavior.
Safeguards to protect any recognized vulnerability of the study:
The risk to invasion of privacy will be addressed by the use of study identification numbers
and the secure storage of study records in locked cabinet at study headquarters.
Confidentiality of the data will be assured at all steps of the study including data
collection, data management, access to data and use of the information. The survey data will
be retained according to the Orgnization's policy. Only the de-identified version of the data
will be accessible for analysis.
Reimbursement or compensation to study participants:
No direct monetary compensation will be provided to the participants in this study. However,
the intervention is expected to increase the knowledge of the participants regarding
importance of LMP date recording.
Responsiveness of the project to community needs and priorities:
This study is expected to provide critical evidence to understand the efficacy of three
different interventions for LMP date recording and thereby improving the accuracy of
gestational age measurement. As such the project not only aims to benefit the community but
also will generate evidence to support further scale-up at national level.
