Interventions relating to fetal movements for improving pregnancy outcomes

Objectives

This is a protocol for a Cochrane Review (intervention). The objectives are as follows:

To assess the effect of interventions to improve awareness and detection of fetal movements and interventions to address the clinical management of decreased fetal movements on maternal, perinatal and childhood outcomes.

Background

Description of the condition

Stillbirth is a devastating, yet often preventable tragedy which has profound and long‐lasting impact on women, families and communities (Heazell 2016). Globally, there are over 2.6 million stillbirths annually, the majority of which occur in low‐ and middle‐income countries (Lawn 2016). However, even in high‐resource settings, many stillbirths are potentially preventable (Flenady 2016). When compared to maternal and neonatal mortality, progress with reducing stillbirth rates has been slow (Lawn 2016). A key challenge in stillbirth prevention is the timely identification of a baby at risk and the choice of any subsequent intervention.

Maternal perception of decreased or altered fetal movements) (e.g. where fetal movements are felt to be more vigorous than normal or less frequent or less strong) (DFM) may help to identify a baby at risk of demise. DFM is a common reason women present to their healthcare provider. Fetal movements may be described as anything from a flutter or a kick, to a swish or a roll. They are usually first felt by the mother between 16 and 24 weeks of pregnancy, and are consistently felt from around 28 to 32 weeks' gestation until the end of pregnancy; they are also felt during labour. As pregnancy progresses in the third trimester, fetal movements often adopt a diurnal pattern and the mother may feel increased strength and episodes of movement and hiccups in the evening (Bradford 2019c).

Perception of DFM is considered a marker of an at‐risk pregnancy (Froen 2004; Heazell 2008; Bradford 2019a; Bradford 2019b; Heazell 2017; Stacey 2011; Warland 2015) . Women who experience DFM have four times the risk of stillbirth in high‐income settings (Froen 2004; Heazell 2008; McCarthy 2016), and double the risk of fetal growth restriction (FGR) (Saastad 2008; Saastad 2011). A recent scoping review in low‐ and middle‐income countries identified that the odds of stillbirth was 14 times greater when there were absent or reduced fetal movements (the study did not look at altered fetal movements) (Hayes 2019). Women who have experienced a stillbirth report altered fetal activity, such as "light or quiet" fetal movements in the evening, four times more frequently than those who do not (Bradford 2019a). DFM has also been associated with a number of other adverse outcomes, including fetal growth restriction, infection, feto‐maternal haemorrhage, placental insufficiency, umbilical cord complication, abnormal placental development and neurodevelopmental disability (Heazell 2008; Pagani 2014; Warrander 2007; Warrender 2012; Winje 2012). DFM is thought to be an adaptive response to acute or chronic placental dysfunction where the fetus reduces gross movement to conserve blood flow for the vital organs (Heazell 2016). Almost one in five women who have a stillbirth experienced three or more episodes of DFM (Heazell 2018). Awareness of the importance and monitoring of fetal movements, combined with clinical investigations and appropriately timed interventions, are therefore a potential strategy to reduce the risk of stillbirth and improve pregnancy outcomes.

Description of the intervention

Interventions relating to DFM can be broadly classified as interventions to improve awareness and detection of DFM, or interventions relating to appropriate clinical management of DFM. These interventions may be used alone or in combination, and may be assessed independently or as part of a package of interventions.

Improving awareness and detection of fetal movements

Several interventions to improve awareness and detection of fetal movements have been suggested and may involve both educational resources for women and strategies to monitor movements. This includes the provision of leaflets (Akselsson 2020; Norman 2018), directing women to websites (Akselsson 2020), public awareness campaigns (Stillbirth CRE; Tommy's 2018) or mobile phone applications (Flenady 2019) that provide information about the importance of DFM, how to monitor movements and what to do if they experience DFM. Fetal movement monitoring approaches include assessing the character, strength and frequency of movements (Akselsson 2020), or formal kick counting such as the "count‐to‐10' approach (Froen 2005). Both approaches require women to lie down on their side and subjectively monitor their babies' movements over a defined period of time. Fetal movement monitoring devices are an emerging field and aim to monitor the movements of the baby using wearable technology that alerts the woman or her healthcare providers when movements appear to be reduced (Smith 2017).

Clinical management of decreased fetal movements

Several interventions also address clinical management of DFM. These interventions include clinician education and management plans for women who present with DFM (Flenady 2019; Norman 2018). Management plans for women who present with DFM include recommendations regarding both investigations and suggested interventions incorporated into clinical practice guidelines (Daly 2018; RCOG 2011). Investigations include detailed clinical history, the use of cardiotocography (CTG) to assess fetal heart rate and ultrasound to determine amniotic fluid liquor volume, growth indices including estimated fetal weight and abdominal circumference, and the use of umbilical artery Dopplers if available (Flenady 2019; Norman 2018). Measurement of placental biomarkers in maternal blood — such as placental growth factor (PlGF) and soluble fms‐Like tyrosine kinase‐1 (sFlt‐1) — may also improve the detection of an at‐risk baby following presentation to hospital for reduced fetal movements, but they are not yet part of routine clinical practice (Higgins 2018). Interventions may include planned early delivery of the baby (e.g. by induction or labour or planned caesarean birth) or expectant management (e.g. waiting for labour to start naturally) with increased surveillance (Skornick‐Rapaport 2010). The timing of birth may be informed by algorithms that combine the gestation of presentation, maternal risk factors, number of presentations for DFM with threshold values from CTG and ultrasound assessments (Norman 2018).

How the intervention might work

Deficiencies relating to both the detection and management of DFM have been identified in perinatal mortality review audits (CCOPMM 2016; MMBRACE UK 2015; QMPQC 2019). Many women report not being provided with information about DFM or what to do if any they have concerns from their healthcare providers (Heazell 2017; McCardle 2013). There is also a common misconception that fetal movements decrease towards the end of pregnancy (Berndl 2013). Many stillbirths are preceded by perceived DFM for a number of days (Heazell 2008; Stacey 2011), and a delay in attending hospital for DFM increases the risk of stillbirth (Tviet 2010.) Even when women do report DFM there are variations in clinical practice due to uncertainties regarding definition (Flenady 2009) and appropriate clinical management (Daly 2018) of DFM.

Maternal education and fetal movement monitoring approaches aim to ensure early identification of a baby at risk of stillbirth and timely reporting of DFM to healthcare providers. Improved clinician education, combined with appropriate clinical management strategies and algorithms, aim to ensure the appropriate investigations and interventions are offered and variation in practice is reduced. Fetal surveillance approaches aim to better identify a deteriorating baby to guide decisions around early planned birth or expectant management, thus ensuring that timing of birth is optimised in women with DFM to both reduce the risk of stillbirth while minimising the potential harms associated with earlier birth.

Why it is important to do this review

Reducing the rates of stillbirth is a global health priority (Flenady 2016; Lawn 2016). Accurate identification and timely birthing of a baby at risk is one of the key strategies for preventing stillbirth. It is unclear how best to clinically identify a baby that is at risk. While awareness of the importance, and monitoring, of fetal movements may help to prevent stillbirth, many women who detect and report DFM go on to give birth to a healthy baby.The benefits of planned birth also need to be carefully weighed against the risks of intervention at any given gestation. Avoiding stillbirth is an aim of ending pregnancy early, but there is also growing concern about the short‐ and long‐term adverse effects of medically driven early term births. Being born at 37 to 39 weeks of gestation, as opposed to after 40 weeks, is associated with a higher rate of immediate perinatal morbidity, hospitalisation in the first five years of life, childhood diabetes, and impaired primary school performance (Bentley 2016; Ibiebele 2019).

Two other Cochrane Reviews currently address decreased fetal movements. Hofmeyr 2012 aimed to assess various management strategies for decreased fetal movements but did not identify any relevant randomised controlled trials. Mangesi 2015 assessed fetal movement counting (routine or selective) and also compared different methods of fetal movement counting. Mangesi 2015 also concluded there was insufficient evidence to demonstrate that fetal movement counting reduces the risk of stillbirth. Both of these Cochrane Reviews are now out of date. Our review will supersede Hofmeyr 2012 and Mangesi 2015, and the scope will be broader in order to encompass all eligible trials assessing interventions aimed at increasing awareness and management of reduced fetal movements.

Given that awareness and management of fetal movements is a key component of international stillbirth prevention strategies, it is imperative that all the current evidence is brought together and evaluated.

Objectives

To assess the effect of interventions to improve awareness and detection of fetal movements and interventions to address the clinical management of decreased fetal movements on maternal, perinatal and childhood outcomes.

Methods

Criteria for considering studies for this review

Types of studies

Eligible study types are randomised controlled trials (RCTs) and cluster‐RCTs. We will include studies published in abstract form only as well as eligible unpublished data obtained directly from trial investigators. We will exclude trials of cross‐over study design and quasi‐randomised trials.

Types of participants

All eligible trials in pregnant women will be included. No exclusions will be applied.

Types of interventions

Some of the interventions will be complex, including a number of components that interact or are targeted at multiple groups (Craig 2008). We plan to include trials that assess:

1. methods of raising awareness or education (or both), including phone applications, leaflets, media campaigns and education for women and clinicians;

2. methods of fetal movement monitoring and fetal monitoring devices;

3. clinical management of DFM, including monitoring management guidelines and algorithms, types of monitoring (e.g. cardiotocography; ultrasound assessment including Doppler studies; clinical and cardiotocography fetal arousal tests; and various combinations of tests), early birth versus expectant management and clinical education/e‐learning.

Comparisons will include standard care, one intervention compared with another intervention or one ‘regimen’ of an intervention compared with another 'regimen’ of the same intervention. Combinations (i.e. two or all three) of the types of interventions will also be compared, where relevant.

Types of outcome measures

Primary outcomes

1. Stillbirth

2. Perinatal death (stillbirth or neonatal death)

Secondary outcomes

1. Stillbirth at 28 weeks' gestation or more

2. Stillbirth (antepartum, intrapartum)

3. Hypoxic‐ischaemic encephalopathy, defined as mild/moderate/severe

4. Neonatal seizures

5. Meconium aspiration syndrome

6. Respiratory distress syndrome

7. Gestation at birth (weeks)

8. Preterm birth (less than 37 weeks' gestation)

9. Preterm birth (less than 34 weeks' gestation)

10. Birthweight (grams (g))

11. Small‐for‐gestational age (below the 10th centile or birthweight less than 2500 g at term gestation; below the third centile at birth)

12. Apgar score less than seven at five minutes

13. Umbilical artery pH less than 7.0

14. Baby required positive pressure ventilation

15. Baby required intubation and ventilation

16. Neonatal death (death of a live born infant regardless of gestation or birthweight)

17. Admitted to the neonatal unit (neonatal intensive care unit (NICU) or special care nursery (SCN)) (and admitted for more than 48 hours)

18. Neonatal length of stay (days)

19. Induction of labour (and induction at less than 39 weeks' gestation)

20. Vaginal birth (all and spontaneous)

21. Caesarean section

22. Maternal death or serious morbidity, as defined by trial authors’

23. Maternal sepsis, as defined by trial authors’

24. Postpartum haemorrhage; according to trial definition or greater than 500 mL

25. Maternal admission to intensive care

26. Maternal length of hospital stay (days)

27. Presentations with DFM at more than 28 weeks’ gestation

28. Two or more presentations for DFM

29. Maternal reporting of DFM delayed by more than 24 hours

30. Women’s knowledge of fetal movements (FM), as defined by trial authors’

31. Clinicians’ knowledge of FM, as defined by trial authors’

32. Adherence to clinical management protocol, as defined by trial authors’

33. Maternal‐newborn attachment, defined using validated tools

34. Maternal stress or anxiety, defined using validated tools

35. Edinburgh Postnatal Depression Scale score

36. Neurodevelopmental delay or disability in childhood, defined using validated tool

37. Caregiver satisfaction with the intervention, as defined by trial authors’

38. Maternal satisfaction with the intervention, as defined by trial authors’

39. Cost‐effectiveness

Search methods for identification of studies

Electronic searches

We will search Cochrane Pregnancy and Childbirth’s Trials Register by contacting their Information Specialist.

The Register is a database containing over 25,000 reports of controlled trials in the field of pregnancy and childbirth. It represents over 30 years of searching. For full current search methods used to populate Pregnancy and Childbirth’s Trials Register, including the detailed search strategies for CENTRAL, MEDLINE, Embase and CINAHL; the list of handsearched journals and conference proceedings, and the list of journals reviewed via the current awareness service, please follow this link.

Briefly, Cochrane Pregnancy and Childbirth’s Trials Register is maintained by their Information Specialist and contains trials identified from:

1. monthly searches of the Cochrane Central Register of Controlled Trials (CENTRAL);

2. weekly searches of MEDLINE (Ovid);

3. weekly searches of Embase (Ovid);

4. monthly searches of CINAHL (EBSCO);

5. handsearches of 30 journals and the proceedings of major conferences;

6. weekly current awareness alerts for a further 44 journals plus monthly BioMed Central email alerts.

Search results are screened by two people and the full text of all relevant trial reports identified through the searching activities described above is reviewed. Based on the intervention described, each trial report is assigned a number that corresponds to a specific Pregnancy and Childbirth review topic (or topics), and is then added to the Register. The Information Specialist searches the Register for each review using this topic number rather than keywords. This results in a more specific search set that will be fully accounted for in the relevant review sections (Included, Excluded, Awaiting Classification or Ongoing).

In addition, we will search ClinicalTrials.gov and the WHO International Clinical Trials Registry Platform (ICTRP) for unpublished, planned and ongoing trial reports using the draft search methods detailed in Appendix 1.

Searching other resources

We will search the reference lists of retrieved studies.

We will not apply any language or date restrictions.

Data collection and analysis

Selection of studies

M Davies‐Tuck (MD‐T) and P Middleton (PM) will independently assess for inclusion all the potential studies identified as a result of the search strategy. MD‐T will retrieve the full articles and eligibility will be determined by MD‐T and PM using the above criteria. Studies that are excluded, and the reasons why, will be documented. We will resolve any disagreement through discussion or, if required, we will consult V Flenady (VF). In the event of conflicts (such as assessment of trials on which review authors are involved), another review author will be asked to assess such trials.

Data extraction and management

Two review authors (MD‐T and M Weller (MW)) will extract data using a pre‐designed data extraction form. The extracted data will be independently checked and verified with discrepancies resolved by discussion. Data that will be extracted include study characteristics, trial design, number of participants, interventions, outcomes and 'Risk of bias' details. For cluster‐RCTs, we will also extract the average cluster size and the intra‐cluster correlation coefficient and whether trials correctly adjusted the analyses for clustering. Data will be entered into Review Manager 5 software (Review Manager 2020) and checked for accuracy. Trial authors will be contacted for additional information, if necessary. The authors MD‐T, VS and S Walker (SW) have not been involved in any of the studies of DFM. In the event of conflicts (such as data extraction and risk of bias assessment for trials on which review authors are involved), another review author will be asked to conduct data extraction and 'Risk of bias' assessment. VF, SW, AG and PM will not be involved in any decisions relating to their own trial.

Assessment of risk of bias in included studies

Two review authors (MD‐T and MW) will independently assess risk of bias for each study using version 2 of the Cochrane 'Risk of bias' tool for randomized trials (RoB 2), outlined in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2020). We will resolve any disagreement by discussion or by involving PM or other review authors in case of conflict. This review will assess the effect of assignment. We will use the RoB 2 Excel tool to manage the assessment of bias. In response to a series of signalling questions, and facilitated by the RoB 2 algorithm, we will make a judgement about risk of bias for domains 1 to 5 listed below, classified as:

• low risk of bias;

• some concerns; or

• high risk of bias.

The overall risk of bias for the study will be determined as:

• low risk of bias (the trial is judged to be at low risk of bias for all domains);

• some concerns (the trial is judged to raise some concerns in at least one domain, but not to be at high risk of bias for any domain); or

• high risk of bias (the trial is judged to be at high risk of bias in at least one domain, or the trial is judged to have some concerns for multiple domains in a way that substantially lowers confidence in the result).

1) Bias arising from the randomisation process

We will describe for each included study whether:

• the allocation sequence was random;

• the allocation sequence was adequately concealed;

• baseline differences between intervention groups suggest a problem with the randomisation process.

2) Bias due to deviations from intended interventions

We will describe for each included study whether:

• participants were aware of their assigned intervention during the trial;

• carers and people delivering the interventions were aware of participants’ assigned intervention during the trial;

• deviations from the intended intervention arose because of the experimental context (i.e. do not reflect usual practice), and, if so, whether they were unbalanced between groups and likely to have affected the outcome;

• an appropriate analysis was used to estimate the effect of assignment to intervention, and, if not, whether there was potential for a substantial impact on the result.

3) Bias due to missing outcome data

We will describe for each included study whether:

• data for this outcome were available for all, or nearly all, participants randomised;

• there was evidence that the result was not biased by missing outcome data;

• missingness in the outcome was likely to depend on its true value (e.g. the proportions of missing outcome data, or reasons for missing outcome data, differ between intervention groups).

4) Bias in measurement of the outcome

We will describe for each included study whether:

• the method of measuring the outcome was inappropriate;

• measurement or ascertainment of the outcome could have differed between intervention groups;

• outcome assessors were aware of the intervention received by study participants;

• assessment of the outcome was likely to have been influenced by knowledge of the intervention received.

5) Bias in selection of the reported result

We will describe for each included study whether:

• the trial was analysed in accordance with a pre‐specified plan that was finalised before unblinded outcome data were available for analysis;

• the numerical result being assessed is likely to have been selected, on the basis of the results, from multiple outcome measurements within the outcome domain;

• the numerical result being assessed is likely to have been selected, on the basis of the results, from multiple analyses of the data.

Measures of treatment effect

Dichotomous data

For dichotomous data, we will present results as summary risk ratio with 95% confidence intervals.

Continuous data

For continuous data, we will use the mean difference if outcomes were measured in the same way between trials. We will use the standardised mean difference to combine trials that measured the same outcome, but used different methods.

Unit of analysis issues

Cluster‐randomised trials

Cluster‐randomised trials are eligible for inclusion in the analyses along with individually‐randomised trials. The adapted RoB 2 tool for cluster‐randomised trials will be used. We will adjust their standard errors using the methods described in the Cochrane Handbook (Higgins 2011), using an estimate of the intracluster correlation coefficient (ICC) derived from the trial (if possible), from a similar trial or from a study of a similar population. If we use ICCs from other sources, we will report this and conduct sensitivity analyses to investigate the effect of variation in the ICC. If we identify both cluster‐randomised trials and individually‐randomised trials, we plan to synthesise the relevant information. We will consider it reasonable to combine the results from both if there is little heterogeneity between the study designs and the interaction between the effect of intervention and the choice of randomisation unit is considered to be unlikely. We will also acknowledge heterogeneity in the randomisation unit and perform a sensitivity analysis to investigate the effects of the randomisation unit.

Cross‐over trials

Cross‐over trials are not eligible for inclusion.

Other unit of analysis issues

Trials in pregnancy and childbirth may include outcomes for multiple pregnancies. If we identify trials with more than two treatment groups, we will only report on the arms relevant to this review. Where there are multiple arms that are relevant to the review we will combine groups to create a single pair‐wise comparison. This will be noted in the 'Characteristics of included studies' table.

Dealing with missing data

For included studies, we will note levels of attrition. We will explore the impact of including studies with high levels of missing data in the overall assessment of treatment effect by using sensitivity analysis.

For all outcomes, we will carry out analyses, as far as possible, on an intention‐to‐treat basis (i.e. we will attempt to include all participants randomised to each group in the analyses, and all participants will be analysed in the group to which they were allocated, regardless of whether or not they received the allocated intervention). The denominator for each outcome in each trial will be the number randomised minus any participants whose outcomes are known to be missing.

Data from trials or outcomes that are at high risk of bias, e.g. those with high levels of missing data or a large number of participants analysed in the wrong group, will be excluded from the meta‐analysis.

Assessment of heterogeneity

We will assess statistical heterogeneity in each meta‐analysis using the Tau², I² and Chi² statistics. We will regard heterogeneity as substantial if I² is greater than 30% and either Tau² is greater than zero, or there is a low P value (less than 0.10) in the Chi² test for heterogeneity. In the case of substantial heterogeneity we will explore this by performing relevant subgroup analyses.

Assessment of reporting biases

If there are 10 or more studies in the meta‐analysis we will investigate reporting biases (such as publication bias) using funnel plots. We will assess funnel plot asymmetry visually. If asymmetry is suggested by a visual assessment, we will perform exploratory analyses to investigate it.

Data synthesis

We will carry out statistical analysis using the Review Manager software (Review Manager 2020). The primary analysis will be undertaken only for studies of low risk of bias. We will use fixed‐effect meta‐analysis for combining data where it is reasonable to assume that studies are estimating the same underlying treatment effect, i.e. where trials are examining the same intervention, and the trials’ populations and methods are judged to be sufficiently similar. If there is clinical heterogeneity sufficient to expect that the underlying treatment effects differ between trials, or if substantial statistical heterogeneity is detected, we will use random‐effects meta‐analysis to produce an overall summary if an average treatment effect across trials is considered clinically meaningful. The random‐effects summary will be treated as the average of the range of possible treatment effects and we will discuss the clinical implications of treatment effects differing between trials. If the average treatment effect is not clinically meaningful we will not combine trials. If we use random‐effects analyses, the results will be presented as the average treatment effect with 95% confidence intervals, and the estimates of Tau² and I². For studies that report on multiple pregnancies, we will follow the methods outlined by Yelland 2018.

Subgroup analysis and investigation of heterogeneity

If we identify substantial heterogeneity, we will investigate it using subgroup analyses and sensitivity analyses. We will consider whether an overall summary is meaningful, and if it is, use random‐effects analysis to produce it.

We plan to carry out the following subgroup analyses:

1. risk status of women: low‐risk versus high‐risk women, as defined by individual trials (e.g. including but not limited to suspected FGR and social disadvantage);

2. parity: nulliparous versus parous women.

The following outcomes will be used in subgroup analysis:

1. stillbirth;

2. perinatal death (stillbirth and neonatal death).

We will assess subgroup differences by interaction tests available within Review Manager (Review Manager 2020). We will report the results of subgroup analyses quoting the Chi² statistic and P value, and the interaction test I² value.

Sensitivity analysis

We will undertake sensitivity analyses to explore the effects of fixed‐effect versus random‐effects analyses for outcomes with statistical heterogeneity, as well as the effects of exclusion of studies with a determined overall higher risk of bias (high risk of bias in at least one domain for this result, or some concerns for multiple domains in a way that substantially lowers confidence in the result) and the effects of varying assumptions regarding the ICC of cluster‐randomised trials.

The following outcomes will be subject to sensitivity analyses:

1. stillbirth;

2. perinatal death (stillbirth and neonatal death).

Summary of findings and assessment of the certainty of the evidence

The quality of the evidence will be assessed using the GRADE approach, as outlined in the GRADE handbook, in order to assess the quality of the body of evidence relating to the following outcomes:

1. stillbirth;

2. perinatal death (stillbirth and neonatal death).

We will import data from Review Manager to the GRADEpro Guideline Development Tool in order to create 'Summary of findings’ tables. A summary of the intervention effect and a measure of certainty for each of the above outcomes will be produced using the GRADE approach. The GRADE approach uses five considerations (study limitations, consistency of effect, imprecision, indirectness, publication bias and overall risk of bias) to assess the certainty of the body of evidence for each outcome. The evidence can be downgraded from 'high certainty' by one level for serious (or by two levels for very serious) limitations, depending on assessments for risk of bias, indirectness of evidence, serious inconsistency, imprecision of effect estimates or potential publication bias.

Appendices

Appendix 1. Search methods for trial registries

These are draft search strings; we will report the final searches in the full review.

ClinicalTrials.gov

Advanced search

Interventional Studies | fetal activity

fetal movement perception | Interventional Studies

mindfulness | Interventional Studies | pregnancy

kick count | Interventional Studies

WHO ICTRP

fetal movement*

foetal movement*

fetal activit*

foetal activit*

baby AND movement* AND pregnancy

Contributions of authors

PM is the guarantor of the review. VF and PM conceived the review. All authors designed the review. MD‐T and PM will undertake the searches and screening of results for inclusion in the review. MD‐T, MW and PM will retrieve the included studies, extract relevant data and perform the 'Risk of  bias' assessments. MD‐T and PM will write to study authors for additional information, if necessary. MD‐T will enter all data into Review Manager 5 software and undertake the meta‐analysis. All authors will be involved in the interpretation of the findings and will contribute to the writing of the review.

Sources of support

Internal sources

• No sources of support provided

External sources

• No sources of support provided

Declarations of interest

MDT is employed by Hudson Institute of Medical research, Australia as a post‐doctoral scientist. She currently receives salary support from an NHMRC CRE Stillbirth Fellowship (2020‐2021) and was previously funded by an NHMRC Early Career Fellowship (2014‐2018). She currently also holds a project grant from the NHMRC for a randomised controlled trial in induction of labour.

PM is an investigator on the My Baby’s Movements trial.

AG is an investigator on the My Baby’s Movements trial and has published opinions in medical journals, public press, broadcast, social media relevant to the interventions in the work.  AG is Chief Investigator, Stillbirth Centre of Research Excellence – and has grants to support the National Safer baby bundle initiative which includes awareness of fetal movements and management pathway.

MW has no conflicts of interest to disclose.

VS has no conflicts of interest to disclose.

SW is an investigator on the My Baby’s Movements trial.

VF receive funding, administered through the Mater Research Institute‐ University of Queensland, from the National Health and Medical Research Council (NHMRC) for my salary ( as a research fellowship), as lead investigator for the Stillbirth Centre of Research Excellence. I am the lead investigator of a cluster randomised trial ( My Baby's Movements) on fetal movement awareness to reduce stillbirths which is also funded by NHMRC.

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