Skip to main content
NCBI home page
Bulletin of the World Health Organization logoLink to Bulletin of the World Health Organization
. 2025 Feb 13;103(4):255–265. doi: 10.2471/BLT.24.292145

A mobile messaging service for families on postnatal knowledge and practices: a cluster randomized trial, India

Service de messagerie mobile pour familles sur les connaissances et les pratiques postnatales: essai randomisé en cluster, Inde

Un servicio de mensajería móvil para familias sobre los conocimientos y las prácticas posnatales; un ensayo aleatorizado por grupos en la India

خدمة الرسائل عبر الهاتف المحمول للأسر حول المعرفة والممارسات بعد الولادة؛ تجربة عشوائية مجمعة، الهند

为家庭提供产后知识和护理实践的移动信息服务，在印度进行的一项随机试验

Мобильный сервис обмена сообщениями для семей по вопросам знаний и практики в послеродовой период; кластерное рандомизированное исследование, Индия

Jamie Sewan Johnston a,✉, Pooja Suri b, Shirley Yan c, Adithi Chandrasekar d, Saumya Singla a, Victoria C Ward e, Seema Murthy f
PMCID: PMC11978415  PMID: 40207245

Abstract

Objective

To evaluate the impact of a mobile messaging service that delivers World Health Organization recommendations on postnatal care to families from birth through six weeks postpartum via a messaging platform.

Methods

We randomized tertiary hospitals in four Indian states into two groups. In the treatment group, 15 hospitals promoted the messaging service to families in maternity wards before discharge following a recent birth. Nine control hospitals provided standard in-hospital information. From mid-March 2021 to mid-January 2022, we recruited mothers to participate in the study. Consenting mothers completed a face-to-face baseline survey before hospital discharge after birth and a follow-up phone survey roughly 6 weeks postpartum. Using logistic regression controlling for state-fixed effects and baseline covariates, we examine intent-to-treat estimates and report risk differences.

Findings

A total of 21 937 participants met the inclusion criteria. We observed significant positive impacts in 7 out of 11 neonatal and maternal care practices examined (P-values < 0.05). Breastfeeding increased by 3.1 percentage points, recommended cord care practices by 4.1 percentage points, skin-to-skin care with mothers by 9.2 percentage points, and skin-to-skin care by fathers by 2.2 percentage points. For recommended maternal dietary practices, we observed significant increases in adherence to guidelines advising no reduction of food intake (7.1 percentage points), no reduction of water intake (7.9 percentage points) and no restrictions on food items (10.8 percentage point; P-values < 0.01).

Conclusion

This study demonstrates that concise yet comprehensive digital messaging delivered to families during the postpartum period can effectively encourage recommended postnatal care practices.

Introduction

Reducing maternal and neonatal mortality is a global health priority, particularly in countries like India, where the burden is high.1–3 For the last decade, Indian national and state policy initiatives have focused on decreasing preventable maternal and infant deaths.4 However, despite recent progress, maternal and neonatal mortality remain high, particularly among the country’s poorest households.1,5,6

To save lives and improve infant and mother well-being, experts have highlighted the importance of health education interventions that improve postnatal care practices.7–10 The provision of predischarge information and postnatal health education to new parents in the critical time period following childbirth has been shown to improve their knowledge and care practices.11

Several health education interventions aim to improve the knowledge,12 including the care companion programme designed by the non-profit organization Noora Health in partnership with governments in Bangladesh, India and Indonesia. This in-hospital education programme addresses gaps in postnatal education in hospitals,13,14 by offering interactive group sessions run by health educators in postpartum maternity wards, designated to teach mothers and their family caregivers essential care practices following World Health Organization (WHO) guidelines.15,16 The sessions, typically 20–30 minutes in length, involve the use of flipcharts, visuals aids and videos where televisions are available.14

The care companion programme model is based on evidence supporting the importance of family members in postnatal care.17,18 In India, family members, particularly grandmothers of new infants, not only support new mothers with caregiving but are also primary household decision-makers for maternal and infant care.19,20 Research indicates that new mothers are more likely to adopt WHO-recommended best practices when they have strong family support.21,22

While the model has shown improved health outcomes,12,13,23 anecdotal evidence suggests gaps in the care companion programme, notably in follow-up care after discharge. Many mothers do not attend postnatal doctor appointments and miss out on essential information and support. This issue is especially common among the poorest families and those residing in rural regions, because of their limited literacy and fewer opportunities to access health centres and critical health information.24,25 Furthermore, health workers face challenges related to the time and resources required to deliver quality in-person postnatal education.26

Digital technologies present a promising opportunity to overcome these challenges. In India, smartphone penetration has greatly increased in the last decade, with social media and messaging platforms like WhatsApp (Meta, Menlo Park, United States of America) widely used across populations, including those with lower socioeconomic status.27 Research suggests that parents seek out infant care advice via mobile devices,28,29 and numerous studies have demonstrated the effectiveness of perinatal education delivered through mobile phones.30–47 Digital messaging interventions have the potential to bridge gaps in in-person information delivery, promoting attendance in antenatal and postnatal care visits,30–36 increasing breastfeeding and safe infant feeding and care,36–38 and improving immunization coverage.32,33,38–42 However, more studies are needed to establish key strategies to improve the effectiveness of mobile messaging interventions, particularly in low- and middle-income countries.32–34

Recognizing this opportunity accompanying the widespread adoption of smartphones in India, the Noora Health’s care companion programme includes a mobile extension of the programme, the mobile care companion programme. This extension aims to continue providing key health information directly to households through messaging platforms in the critical months following the discharge of new mothers from the hospital. In this study, we evaluate the impact of the mobile care companion programme delivered through WhatsApp on maternal and newborn care practices through a cluster randomized trial in four Indian states.

Methods

Intervention

The mobile care companion programme delivers continued care advice to families via a free mobile messaging service on WhatsApp. At the end of every in-person care companion training session, health educators encourage mothers and family caregivers (typically fathers and grandmothers of newborns) to enrol in the mobile programme and provide a phone number to sign up for the service.

The programme delivers 25 messages, including seven videos, over 50 days (available in the online repository).48 The messages align with the content of the in-person programme and promote WHO-recommended postnatal practices, including early and exclusive breastfeeding, hygienic cord care, skin-to-skin care, vaccination, maternal nutrition recommendations and recognizing warning signs of critical illness in mothers and babies.15,16 The messages have been reviewed by a team of medical experts and state health departments, who also piloted the messages among target learners. The service is available in seven languages: English, Hindi, Kannada, Marathi, Punjabi, Tamil and Telugu. Like the in-person programme, the mobile messages direct advice to entire families rather than exclusively to new mothers. Upon introduction to the mobile care companion programme, the programme health educators encourage family members to engage with the service alongside new mothers.

In addition to receiving care advice through the mobile messages, recipients can also ask questions on WhatsApp. A team of trained support staff monitors and responds to questions; however, they do not provide medical consultation or advice on medications, rather they direct recipients to health providers for such queries.

Study design

To evaluate the effectiveness of the mobile care companion programme, we conducted a cluster-randomized controlled trial, with hospitals as the unit of randomization. We registered the trial on Open Science Framework.48 The Consolidated Standards of Reporting Trials (CONSORT)checklist is available in the online repository.48

Based on programmatic feasibility and resources, Noora Health determined the number of hospitals to be included in the study. To achieve a representative sample of hospitals, we first stratified districts in each state by India’s health management information health index quartiles, and randomly selected a set of high- and low-delivery load hospitals where the care companion programme had been implemented for at least two years. We selected 26 tertiary hospitals in four states (Karnataka, Madhya Pradesh, Maharashtra and Punjab) for inclusion in the study.

We excluded two hospitals from the study. One hospital was excluded before randomization because the facility shifted focus to coronavirus disease 2019 (COVID-19) treatment and redirected births to alternative facilities. The second hospital was excluded after randomization when the state government requested the hospital, originally assigned to the standard-of-care control group, begin implementing the mobile care companion programme intervention three months into the study. The hospitals were stratified by state, and 15 were randomly assigned via a random number generator to the treatment group where the mobile extension of the programme would be promoted. The remaining nine hospitals served as a control and provided only the in-person programme.

Noora Health decided to recruit and enrol participants during a 10-month period. From mid-March 2021 to mid-January 2022, data collection field teams recruited new mothers in maternity wards across the 24 hospitals during their hospital stays, following birth and before discharge. Birthing women who had not experienced a stillbirth and were present at the time of data collection were invited to participate. Inclusion criteria required completing a demographic survey at recruitment and household ownership of a smartphone. Families in which newborns or mothers died before discharge were excluded. In treatment hospitals, out of 14 018 mothers recruited, 11 611 (82.8%) consented and met inclusion criteria. In control hospitals, 10 326 (87.4%) out of 11 806 recruited consented and met inclusion criteria.

Measures

Data collection teams conducted face-to-face demographic surveys with all consenting mothers during recruitment. If new mothers were unable to respond, family members designated by the mother responded on their behalf. We constructed a socioeconomic status index using the same method as the Indian National Family Health Survey 4, assigning pre-determined weights to each socioeconomic indicator. We then summed and standardized these weights around the control group's index mean. All consenting mothers self-identified themselves as female in the demographic survey.

About eight weeks (55 days on average) after participants consented, data collection teams attempted to contact all participants for a follow-up phone survey (online repository).48

Primary outcomes included self-reported post-discharge behaviours in three categories: (i) newborn care practices, including exclusive breastfeeding, any breastfeeding, recommended umbilical cord care, skin-to-skin care and six-week immunization; (ii) maternal dietary practices, including adherence to recommendations not to reduce or restrict food and water, and consumption of iron, folic acid and calcium supplements; and (iii) newborn and maternal complications, including post-discharge hospital readmissions. Secondary outcomes included knowledge of newborn care practices regarding infant feeding, skin-to-skin care and cord care. Because of the programmatic limitations in the number of clusters (hospitals) and overall sample size of the study, the study had insufficient power to examine impact on maternal and infant mortality as primary outcomes.

We controlled for baseline characteristics, obtained from the demographic survey, and imputed missing values for covariates using the median of the non-missing values conditioned on the state. The final set of covariates included in the model was determined using post-double selection,45 with a complete list of high-dimensional controls provided in the online repository.48

Statistical analysis

To estimate the impact of the mobile care companion programme intervention, we calculated intent-to-treat estimates, which capture the effect of offering mobile messages, regardless of take-up, using the following logistic regression equation:

log (Pih) = α + β1 Th + γ Xih + θs + εih (1)

where the dependent variable Pih represents the probability of an outcome for a mother i recruited in hospital h. The treatment variable Th is a binary variable, which is 0 if a hospital is assigned the standard of care, and 1 if it is assigned the intervention. Our main estimate of interest is β1 which provides the intent-to-treat estimate of the impact of the mobile intervention as compared to the in-person care companion programme. The vector Xih consists of mother- and hospital-level covariates, selected using post-double selection to improve precision.45 The intercept α represents the baseline log-odds of the outcome in the control group, accounting for covariates and fixed effects. We included state-fixed effects (θs) and εih is the error term clustered at the hospital level. We used a logistic regression model to estimate the results as outcomes are binary and report risk differences using the Stata margins command. To correct for multiple hypothesis testing, we calculated sharpened false discovery rate adjusted q-values.46 Analyses were conducted in Stata version 16 (StataCorp LLC, College Station, United States of America (USA)).

Ethics review

This study received approval from the ACE Ethics Committee (DCGI Reg. No. ECR/141/Indt/KA/2013/RR-19) based in Bangalore, India and the Institutional Review Boards at Stanford University, Stanford, USA (IRB-65931) and the University of California, Berkeley, USA (2024–04–17420). All participants consented in their local language.

Results

Sample

Of the 25 824 participants recruited for the in-hospital demographic survey, 25 417 (98.4%) consented and 25 401 (98.4%) completed the survey (Fig. 1). Of the participants who completed survey, 11 611 in the intervention group and 10 326 in the standard-of-care group met the inclusion criteria. The excluded participants had a lower socioeconomic status (−0.573: standard deviation, SD: 1.153) than participants in the control group (0.0; SD: 1.0) and the intervention group (−0.01; SD: 1.01; Table 1 and online repository).48

Fig. 1.

Participant flowchart for a cluster randomized trial of a postnatal mobile messaging service for families, India, 2021–2022

COVID-19: coronavirus disease 2019.

Notes: Participant inclusion criteria includes completion of baseline survey at the time of recruitment in hospitals and household ownership of a smartphone through which WhatsApp can be accessed. Households with mothers or babies who died before hospital discharge were also excluded.

Fig. 1

Open in a new tab

Table 1. Baseline characteristics of participants in the randomized controlled trial on mobile messaging service for postnatal care practices, India, 2021–2022.

Characteristic No. (%)a
Control group (n = 6650) Intervention group (n = 6841)
Average mother's age in years (SD) 24.27 (3.77)  24.39 (3.66)
Average no. of live births (SD) 1.29 (0.99) 1.16 (0.95)
Newborn is male 3476 (52.3) 3586 (52.4)
Mother as primary respondent 6560 (98.6) 6651 (97.2)
Vaginal delivery 3765 (56.6) 3431 (50.2)
First-time mother 1451 (21.8) 1815 (26.5)
Social category
General 936 (14.1) 816 (11.9)
Scheduled caste or scheduled tribe 5467 (82.2) 5667 (82.8)
Other 247 (3.7) 358 (5.2)
Ownership of a below poverty line card 3810 (57.3) 4158 (60.8)
Socioeconomic status indexb 0.00 (1.00) −0.01 (1.01)
Ownership of household item
Pressure cooker 5202 (78.2) 5328 (77.9)
Colour television 4976 (74.8) 4934 (72.1)
Refrigerator 2621 (39.4) 2670 (39.0)
Table 1602 (24.1) 2752 (40.2)
Washing machine 623 (9.4) 1155 (16.9)
Sewing machine 1580 (23.8) 1412 (20.6)
Air conditioner or cooler 2243 (33.7) 1821 (26.6)
Mattress 3778 (56.8) 4308 (63.0)
Motorcycle or scooter 4003 (60.2) 4063 (59.4)
None of these 337 (5.1) 431 (6.3)
Household characteristic
Concrete roof 4149 (62.4) 4540 (66.4)
Uses liquefied petroleum gas mostly for cooking 5496 (82.6) 6054 (88.5)
Uses open toilet 1802 (27.1) 890 (13.0)
Highest level of education
No formal schooling 824 (12.4) 365 (5.3)
Primary school 408 (6.1) 292 (4.3)
Secondary school 3091 (46.5) 3310 (48.4)
Higher than secondary school 2324 (34.9) 2865 (41.9)
Occupation
Unemployed 27 (0.4) 201 (2.9)
Homemaker 5364 (80.7) 5946 (87.0)
Self-employed 241 (3.6) 255 (3.7)
Daily wage worker 862 (13.0) 246 (3.6)
Private sector employee 100 (1.5) 152 (2.2)
Public sector employee 53 (0.8) 32 (0.5)
Open in a new tab

NA: not applicable.

a Value represents no. (%) unless otherwise stated.

b The socioeconomic status index is calculated using the method from the Indian National Family Health Survey 4 and standardized around the control group.

Notes: Inconsistencies arise in some values due to rounding. The data represents the final analytic sample after loss-to-follow-up.

The overall loss-to-follow-up was 37.1% (Fig. 1), similar to previous postnatal follow-up phone surveys conducted by Noora Health.13 We observed no significant differences in attrition between the control and treatment groups (online repository).48 Attrition was more common among participants with the following characteristics: someone other than the mother completed the demographic survey; newborn readmission to the hospital after delivery; belonging to other minority social categories; and fewer household assets (online repository).48

Examining the pre-intervention characteristics of the 13 491 mothers who completed the follow-up survey showed that the intervention and control groups were well balanced (Table 1). We observed similar balance between the two randomized groups in the baseline survey (online repository).48 Significant, but small differences in the proportion of first-time mothers and number of previous births existed between the groups (Table 1).

The average age of all mothers was 24.33 years (SD: 3.72). Vaginal delivery accounted for just over half of the births, and mothers had an average of 1.23 previous births (SD: 0.97). Of the 13 491 mothers, most (11 134; 82.5%) belong to a scheduled caste or tribe indicating lower socioeconomic status, and most (7968; 59.1%) possessed a below poverty line card. Additionally, most mothers are homemakers (11 310; 83.8%) and completed secondary education (11 590; 85.9%).

Participation in the intervention

Of the 6841 mothers responding to the follow-up survey, 4224 (61.7%) could recall who enrolled the household in the mobile care companion programme. Of these, 70.1% (2963) reported themselves as the household member that initiated enrolment, 22.2% (937) reported the spouses and 7.7% (324) reported other relatives as initiators of enrolment. Only 3015 (44.1%) mothers recalled viewing the mobile messages. However, of these, nearly all (2909; 96.5%) reported understanding the messages; 1131 (37.5%) recalled viewing any videos; 477 (15.8%) recalled asking questions on the platform; and 846 (28.1%) shared information or videos with other family members. Of the 1261 mothers whose family members enrolled, 848 (67.2%) recalled family members sharing information or videos with them (Table 2). The uptake of practice and knowledge reported in the follow-up survey is presented in Table 3.

Table 2. Mother-reported uptake and engagement in a postnatal mobile messaging service for families, India, 2021–2022.

Variable No. (%)
(n = 6841)
Recalled which family member enrolled in programme 4224 (61.7)
Mother (self) 2963 (70.1)
Spouse 937 (22.2)
Other family member 324 (7.7)
Could not recall if anyone enrolled in programme 2617 (38.3)
Engagement with programme
Mother recalled viewing messages on WhatsApp 3015 (44.1)
    Understood messages received 2909 (96.5)
    Viewed any linked videos 1131 (37.5)
    Asked questions on the platform 477 (15.8)
    Shared information or videos with family members 846 (28.1)
Family members shared information or videos with the mothera 848 (67.2)
Open in a new tab

a Whether a family member shared the message with the mother was only asked of 1261 mothers who recalled family members enrolling in the programme.

Table 3. Uptake of postnatal care practices and knowledge reported in the follow-up survey of a cluster randomized trial of a postnatal mobile messaging service for families, India, 2021–2022.

Outcome No. of participants reporting an outcome (%)
Control group
(n = 6650)		 Intervention group
(n = 6841)
Practice
Newborn care practice
  Exclusive breastfeeding 3316 (49.9) 3310 (48.4)
  Fed any breastmilk 6259 (94.1) 6737 (98.5)
  Practiced recommended cord care 3255 (48.9) 4155 (60.7)
  Mother practiced skin-to-skin with newborn 622 (9.4) 1209 (17.7)
  Father practiced skin-to-skin with newborn 69 (1.0) 219 (3.2)
  Completed six-week vaccinations 3387 (50.9) 3942 (57.6)
Maternal dietary practice
  No reduction of food intake 4635 (69.7) 5243 (76.6)
  No reduction of water intake 4996 (75.1) 5380 (78.6)
  No restriction of food items 2530 (38.0) 3486 (51.0)
  Consumed iron and folic acid supplements 822 (12.4) 1425 (20.8)
  Consumed calcium supplements 770 (11.6) 1467 (21.4)
Newborn and maternal complication
  Newborn admitted to hospital after discharge 453 (6.8) 407 (5.9)
  Newborn experienced complications after discharge 1961 (29.5) 2041 (29.8)
  Mother admitted to hospital after discharge 78 (1.2) 107 (1.6)
  Mother experienced complications after discharge 745 (11.2) 859 (12.6)
  Experienced issues with cord care 369 (5.5) 379 (5.5)
Knowledge
Know to breastfeed when mother has a fever 2674 (40.2) 3230 (47.2)
Know to breastfeed jaundiced newborn 3560 (53.5) 4074 (59.6)
Know age to start complementary feeding 4540 (68.3) 4790 (70.0)
Know recommended cord care 2526 (38.0) 3353 (49.0)
Know about skin-to-skin care 1233 (18.5) 2191 (32.0)
Open in a new tab

Effect on postnatal care practices

The mobile care companion programme intervention significantly improved four of the six newborn care practices measured. Mothers receiving mobile messages experienced increases of 3.1 percentage points (95% confidence interval, CI: 1.5–4.74) in feeding any breastmilk; 4.1 percentage points (95% CI: 0.4–7.8) in practicing recommended cord care; 9.2 percentage points (95% CI: 6.2–12.2) in skin-to-skin care by the mother; and 2.2 percentage points (95% CI: 0.7–3.8) in skin-to-skin care by the father. We observed no significant impact on exclusive breastfeeding or six-week vaccinations (Table 4).

Table 4. Effect of a postnatal mobile messaging service for families on newborn care, maternal diet, complications and knowledge, India, 2021–2022.

Outcome Mean % of participants in control groupa Risk difference, percentage points (95% CI) q b
Practice
Newborn care practice
  Exclusive breastfeeding 49.9 1.8 (−6.0 to 9.6) 0.563
  Fed any breastmilk 94.1 3.1 (1.5 to 4.7) 0.001
  Practiced recommended cord care 48.9 4.1 (0.4 to 7.8) 0.056
  Mother practiced skin-to-skin with newborn 9.4 9.2 (6.2 to 12.2) 0.001
  Father practiced skin-to-skin with newborn 1.0 2.2 (0.7 to 3.8) 0.012
  Completed six-week vaccinations 50.9 4.2 (−1.5 to 9.9) 0.259
Maternal dietary practice
  No reduction of food intake 69.7 7.1 (5.0 to 9.2) 0.001
  No reduction of water intake 75.1 7.9 (3.6 to 12.1) 0.001
  No restriction of food items 38.0 10.8 (7.1 to 14.5) 0.001
  Consumed iron and folic acid supplements 12.4 6.0 (−3.2 to 15.3) 0.267
  Consumed calcium supplements 11.6 6.5 (−1.6 to 14.6) 0.214
Newborn and maternal complication
  Newborn admitted to hospital after discharge 6.8 0.3 (−1.7 to 2.3) 0.697
  Newborn experienced complications after discharge 29.5 2.2 (−0.8 to 5.1) 0.259
  Mother admitted to hospital after discharge 1.2 0.2 (−0.4 to 0.8) 0.504
  Mother experienced complications after discharge 11.2 2.1 (0.7 to 3.5) 0.010
  Experienced issues with cord care 5.5 −0.3 (−1.5 to 0.9) 0.563
Knowledge
Know to breastfeed when mother has a fever 40.2 8.7 (4.1 to 13.3) 0.001
Know to breastfeed jaundiced newborn 53.5 4.9 (−2.4 to 12.1) 0.267
Know age to start complementary feeding 68.3 −4.5 (−10.9 to 1.9) 0.265
Know recommended cord care 38.0 2.1 (−3.6 to 7.9) 0.504
Know about skin-to-skin care 18.5 14.9 (10.5 to 19.4) 0.001
Open in a new tab

CI: confidence interval.

a Mean percentages of the intervention group are presented in Table 3.

b q denotes adjusted false discovery rate to correct for multiple hypothesis testing.41

Notes: We ran a logistic regression of the primary outcomes on treatment for 13 491 respondents. Each row represents a separate regression. All outcome variables presented are indicators that are 0 if the behaviour was not practiced, and 1 if the behaviour was practiced. The treatment variable is an indicator that is 0 if they were assigned to the control group and 1 if they were assigned to treatment. Covariates were included in all regressions using post-double selection,40 and missing values were imputed using the median of the non-missing values conditional on the state. Standard errors (not shown here) are robust, and are clustered at the hospital level.

We observed significant improvements in three of the five maternal diet practices measured. Mothers in the intervention group were significantly more likely to adhere to recommendations advising that they do not reduce their food intake (7.1 percentage points increase; 95% CI: 5.0–9.2) or water intake (7.9 percentage points increase; 95% CI: 3.6–12.1) or restrict specific food items (10.8 percentage points increase; 95% CI: 7.1–14.5). We did not observe any significant impact on supplement consumption (Table 4).

We observed no differences in newborn complications at follow-up. Mothers in the intervention group were significantly more likely to report experiencing complications after discharge (2.1 percentage points; 95% CI: 0.7–3.5).

Across all care practices, we examined heterogeneity in differences for first-time mothers and young mothers (aged 18–24 years) and did not observe substantive differences in outcomes (online repository).48

Effect on postnatal care knowledge

We observed a significant impact on two of the five knowledge outcomes measured. Mothers in the intervention group were significantly more likely to know that breastfeeding is recommended even when the mother has a fever (8.7 percentage points; 95% CI: 4.1–13.3) and to know about skin-to-skin care (14.9 percentage points; 95% CI: 10.5–19.4; Table 4).

Calculations of q-values included all outcomes reported in Table 4 and confirmed that the findings were consistent with P-values. The unadjusted results of the primary outcomes on treatment are robust to adjusted specifications (online repository).48

Discussion

The study contributes to the mobile health messaging literature in several ways. First, it provides causal evidence on the effectiveness of a replicable model of mobile messaging in driving behaviour change and improving uptake of key recommended care practices among low socioeconomic status populations. Second, while most postnatal education interventions focus on a narrow set of practices, such as breastfeeding or immunization alone,11 the mobile care companion programme offers concise yet comprehensive messaging across a broad set of postnatal care practices. Third, unlike many postnatal interventions, the mobile care companion programme actively engages households by inviting all family members involved in caregiving to participate alongside new mothers. The intervention design recognizes the role of family members in postnatal care and decision-making and accommodates shared mobile phone use, which is often controlled by male heads of households.43,44

Our study findings add to a growing body of evidence showing that mobile dissemination of postnatal care education can improve care practices.30–42 By delivering concise, spaced messages over six weeks, the mobile extension of the companion care programme positively influenced the uptake of WHO-recommended postnatal care practices. While the mobile extension covered the same general topics as the in-person education provided to the control group, the addition of spaced mobile-delivered messages led to improvements in most neonatal practices measured. These findings suggest the added value of mobile messaging as a complementary tool, allowing families to access information at their convenience and retain it for future reference.

This study further highlights the importance of delivering health education to family members involved in postnatal care. Although our study relied on self-reported survey data due to the inability to link WhatsApp platform analytics with participants, our findings show that family members initiated enrolment in nearly one third of households. In these households, two thirds of mothers reported receiving information from their family members. Similarly, nearly one third of mothers who recalled using the programme shared messages with family members. However, less than half of mothers recalled viewing the programme’s messages, likely reflecting limited smartphone access among women. Addressing shared phone ownership dynamics and increasing smartphone access for mothers could increase the effectiveness of mobile education while also challenging traditional gender norms around caregiving. Prior studies have shown that mobile messaging interventions can increase men’s involvement in caregiving, suggesting potential for broader impact.36,40

This study demonstrates the feasibility of achieving impact among low socioeconomic populations. The proliferation of smartphones in India, even among marginalized groups, highlights the potential of digital interventions to overcome barriers to quality in-person care. In our study, only one in eight participants were excluded due to lack of a smartphone, showing that digital tools can reach low-income mothers delivering in tertiary hospitals.

This study has some limitations. First, we only included mothers who had delivered in a tertiary hospital, possibly excluding the poorest in communities. Nonetheless, mothers participating in the study predominantly belonged to low socioeconomic status populations. Second, although the mobile care companion programme was designed as a two-way communication service, it was largely used as a one-way information delivery system, with only one in seven mothers (among mothers who recalled viewing messages) reporting that they asked questions on the platform. Because of the small number of mothers using the interactive component of the service, we were unable to assess its impact. Third, we were unable to observe how information was consumed within households. This drawback underscores the need to develop effective strategies for directing educational content to new mothers and family members. Finally, some messages were likely mistimed, arriving too late to influence caregiving practices. Tailoring messages to specific patient needs and improving the timing of delivery could increase the programme’s impact. We recommend that future studies explore how interactive messaging services can identify patient needs and provide tailored information. Future advancements in technology, such as artificial intelligence, could help improve personalization and timing of mobile messages to better meet individual needs

In conclusion, this study suggests that even simple information delivery through smartphones can positively impact care, consistent with evidence that one-way postnatal messaging can be cost-effective in saving lives.47 The impact observed for relatively simple messaging underscores opportunities to improve mobile interventions to improve postnatal care and ultimately save lives.

Acknowledgements

We thank the Noora Health and Yosaid research and implementation teams including Sahana S D, Veena J C, Pooja, Abel Desai, Pradeep K, Babita Sharma, Nisha Gupta, Vinayaka A M, Huma Sulaiman, Bhanu Pratap Yadav, Sareen Kak, Tanmay Singh Pathani, Abhimanyu Kotwal, Mahesh A M, Shanthi, Nagesha M, Manikanta N, Anant Pawar, Juhi Jain, Parag Soni, Divya Mishra, Atul Gautam, Sapna Rai, Shailendra Tomar, Victoria G, Preeti Raju, Nishighanda Ankolekar, Sreeram NR; Archana Mishra and the National Health Missions of Karnataka, Madhya Pradesh, Maharashtra and Punjab; the Stanford Center for Health Education Digital Medic team including Charles Prober and Aarti Porwal; advisor, William Dow; and, most importantly, the families who participated in the study.

Funding:

Stanford University researchers were funded by the Stanford Center for Health Education and by a grant from Noora Health for this work. Noora Health is supported by private philanthropic donors, foundations, and corporate giving. Noora Health PLC is an Indian subsidiary of Noora Health, and YosAID Innovation Foundation is an implementing partner in India.

Competing interests:

None declared.

References

  • 1.Liu L, Chu Y, Oza S, Hogan D, Perin J, Bassani DG, et al. National, regional, and state-level all-cause and cause-specific under-5 mortality in India in 2000–15: a systematic analysis with implications for the sustainable development goals. Lancet Glob Health. 2019. Jun;7(6):e721–34. 10.1016/S2214-109X(19)30080-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Neonatal mortality [data set]. New York: United Nations Children’s Fund; 2024. Available from: https://data.unicef.org/topic/child-survival/neonatal-mortality/ [cited 2024 May 11].
  • 3.Mortality rate, neonatal (per 1,000 live births) – India [internet]. Washington, DC: World Bank; 2024. Available from: https://data.worldbank.org/indicator/SH.DYN.NMRT?locations=IN [cited 2024 May 11].
  • 4.Datta V, Ghosh S, Aquino LD. Progressing towards SDG 2030 goals with system changes: the India newborn action plan. BMJ Open Qual. 2022. May;11 Suppl 1:e001971. 10.1136/bmjoq-2022-001971 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Meh C, Sharma A, Ram U, Fadel S, Correa N, Snelgrove JW, et al. Trends in maternal mortality in India over two decades in nationally representative surveys. BJOG. 2022. Mar;129(4):550–61. 10.1111/1471-0528.16888 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Tripathy JP, Mishra S. Causes and predictors of neonatal, post-neonatal and maternal deaths in India: analysis of a nationwide district-level household survey-4 (DLHS-4), 2012-13. J Trop Pediatr. 2017. Dec 1;63(6):431–9. 10.1093/tropej/fmx009 [DOI] [PubMed] [Google Scholar]
  • 7.Bhutta ZA, Das JK, Bahl R, Lawn JE, Salam RA, Paul VK, et al. Lancet Newborn Interventions Review Group; Lancet Every Newborn Study Group. Can available interventions end preventable deaths in mothers, newborn babies, and stillbirths, and at what cost? Lancet. 2014. Jul 26;384(9940):347–70. 10.1016/S0140-6736(14)60792-3 [DOI] [PubMed] [Google Scholar]
  • 8.Darmstadt GL, Walker N, Lawn JE, Bhutta ZA, Haws RA, Cousens S. Saving newborn lives in Asia and Africa: cost and impact of phased scale-up of interventions within the continuum of care. Health Policy Plan. 2008. Mar;23(2):101–17. 10.1093/heapol/czn001 [DOI] [PubMed] [Google Scholar]
  • 9.Darmstadt GL, Bhutta ZA, Cousens S, Adam T, Walker N, de Bernis L; Lancet Neonatal Survival Steering Team. Evidence-based, cost-effective interventions: how many newborn babies can we save? Lancet. 2005. Mar 12-18;365(9463):977–88. 10.1016/S0140-6736(05)71088-6 [DOI] [PubMed] [Google Scholar]
  • 10.Knippenberg R, Lawn JE, Darmstadt GL, Begkoyian G, Fogstad H, Walelign N, et al. ; Lancet Neonatal Survival Steering Team. Systematic scaling up of neonatal care in countries. Lancet. 2005. Mar 19-25;365(9464):1087–98. 10.1016/S0140-6736(05)71145-4 [DOI] [PubMed] [Google Scholar]
  • 11.Dol J, Campbell-Yeo M, Tomblin Murphy G, Aston M, McMillan D, Gahagan J, et al. Parent-targeted postnatal educational interventions in low- and middle-income countries: a scoping review and critical analysis. Int J Nurs Stud. 2019. Jun;94:60–73. 10.1016/j.ijnurstu.2019.03.011 [DOI] [PubMed] [Google Scholar]
  • 12.Subramanian L, Murthy S, Bogam P, Yan SD, Marx Delaney M, Goodwin CDG, et al. Just-in-time postnatal education programmes to improve newborn care practices: needs and opportunities in low-resource settings. BMJ Glob Health. 2020. Jul;5(7):e002660. 10.1136/bmjgh-2020-002660 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Murthy S, Yan SD, Alam S, Kumar A, Rangarajan A, Sawant M, et al. Improving neonatal health with family-centered, early postnatal care: a quasi-experimental study in India. PLOS Glob Public Health. 2023. May 25;3(5):e0001240. 10.1371/journal.pgph.0001240 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Yan SD, S D S, Desai M, Delaney MM, Bobanski L, Rajkumar N, et al. Qualitative assessment of family caregiver-centered neonatal education program in Karnataka, India. PLOS Glob Public Health. 2023. Feb 14;3(2):e0000524. 10.1371/journal.pgph.0000524 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.WHO recommendations on postnatal care of the mother and newborn. Geneva: World Health Organization; 2013. Available from: https://www.who.int/publications/i/item/9789241506649 [cited 2024 May 11].
  • 16.Essential newborn care course. 2nd ed. Geneva: World Health Organization; 2022. Available from: https://www.who.int/tools/essential-newborn-care-course [cited 2024 Sep 18].
  • 17.Martin SL, McCann JK, Gascoigne E, Allotey D, Fundira D, Dickin KL. Engaging family members in maternal, infant and young child nutrition activities in low- and middle-income countries: a systematic scoping review. Matern Child Nutr. 2021. Jul;17(Suppl 1) Suppl 1:e13158. 10.1111/mcn.13158 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Martin SL, McCann JK, Gascoigne E, Allotey D, Fundira D, Dickin KL. Mixed-methods systematic review of behavioral interventions in low- and middle-income countries to increase family support for maternal, infant, and young child nutrition during the first 1000 days. Curr Dev Nutr. 2020. May 21;4(6):nzaa085. 10.1093/cdn/nzaa085 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Withers M, Kharazmi N, Lim E. Traditional beliefs and practices in pregnancy, childbirth and postpartum: a review of the evidence from Asian countries. Midwifery. 2018. Jan;56:158–70. 10.1016/j.midw.2017.10.019 [DOI] [PubMed] [Google Scholar]
  • 20.Choudhry UK. Traditional practices of women from India: pregnancy, childbirth, and newborn care. J Obstet Gynecol Neonatal Nurs. 1997. Sep-Oct;26(5):533–9. 10.1111/j.1552-6909.1997.tb02156.x [DOI] [PubMed] [Google Scholar]
  • 21.Nguyen PH, Kachwaha S, Avula R, Young M, Tran LM, Ghosh S, et al. Maternal nutrition practices in Uttar Pradesh, India: role of key influential demand and supply factors. Matern Child Nutr. 2019. Oct;15(4):e12839. 10.1111/mcn.12839 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Allendorf K. The quality of family relationships and use of maternal health-care services in India. Stud Fam Plann. 2010. Dec;41(4):263–76. 10.1111/j.1728-4465.2010.00252.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Kashyap S, Spielman AF, Ramnarayan N, Sd S, Pant R, Kaur B, et al. Impact of family-centred postnatal training on maternal and neonatal health and care practices in district hospitals in two states in India: a pre-post study. BMJ Open Qual. 2022. May;11 Suppl 1:e001462. 10.1136/bmjoq-2021-001462 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Balarajan Y, Selvaraj S, Subramanian SV. Health care and equity in India. Lancet. 2011. Feb 5;377(9764):505–15. 10.1016/S0140-6736(10)61894-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Subramanian SV, Ackerson LK, Subramanyam MA, Sivaramakrishnan K. Health inequalities in India: the axes of stratification. Brown J World Aff. 2008. Spring/Summer;14(2):27–38. [Google Scholar]
  • 26.Gilmer C, Buchan JL, Letourneau N, Bennett CT, Shanker SG, Fenwick A, et al. Parent education interventions designed to support the transition to parenthood: a realist review. Int J Nurs Stud. 2016. Jul;59:118–33. 10.1016/j.ijnurstu.2016.03.015 [DOI] [PubMed] [Google Scholar]
  • 27.Balkrishan D, Joshi A, Rajendran C, Nizam N, Parab C, Devkar S. Making and breaking the user-usage model: WhatsApp adoption amongst emergent users in India. In: IndiaHCI '16: proceedings of the 8th Indian conference on human-computer interaction; 2016 Dec 7–9; Mumbai, India. New York: Association for Computing Machinery; 2016. pp. 52–63. 10.1145/3014362.3014367 [DOI] [Google Scholar]
  • 28.Richardson B, Dol J, Rutledge K, Monaghan J, Orovec A, Howie K, et al. Evaluation of mobile apps targeted to parents of infants in the neonatal intensive care unit: systematic app review. JMIR Mhealth Uhealth. 2019. Apr 15;7(4):e11620. 10.2196/11620 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Tang S, Ghose B, Hoque MR, Hao G, Yaya S. Women using mobile phones for health communication are more likely to use prenatal and postnatal services in Bangladesh: cross-sectional study. JMIR Mhealth Uhealth. 2019. Feb 28;7(2):e10645. 10.2196/10645 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Lund S, Nielsen BB, Hemed M, Boas IM, Said A, Said K, et al. Mobile phones improve antenatal care attendance in Zanzibar: a cluster randomized controlled trial. BMC Pregnancy Childbirth. 2014. Jan 17;14(1):29. 10.1186/1471-2393-14-29 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Dol J, Richardson B, Tomblin Murphy G, Aston M, McMillan D, Campbell-Yeo M. Impact of mobile health (mHealth) interventions during the perinatal period for mothers in low- and middle-income countries: a systematic review. JBI Database Syst Rev Implement Reports. 2019. Aug;17(8):1634–67. 10.11124/JBISRIR-2017-004022 [DOI] [PubMed] [Google Scholar]
  • 32.Bossman E, Johansen MA, Zanaboni P. mHealth interventions to reduce maternal and child mortality in Sub-Saharan Africa and Southern Asia: a systematic literature review. Front Glob Womens Health. 2022. Aug 25;3:942146. 10.3389/fgwh.2022.942146 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Watterson JL, Walsh J, Madeka I. Using mHealth to improve usage of antenatal care, postnatal care, and immunization: a systematic review of the literature. BioMed Res Int. 2015;2015:153402. 10.1155/2015/153402 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Feroz A, Perveen S, Aftab W. Role of mHealth applications for improving antenatal and postnatal care in low and middle income countries: a systematic review. BMC Health Serv Res. 2017. Nov 7;17(1):704. 10.1186/s12913-017-2664-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Free C, Phillips G, Galli L, Watson L, Felix L, Edwards P, et al. The effectiveness of mobile-health technology-based health behaviour change or disease management interventions for health care consumers: a systematic review. PLoS Med. 2013;10(1):e1001362. 10.1371/journal.pmed.1001362 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Mbuthia F, Reid M, Fichardt A. mHealth communication to strengthen postnatal care in rural areas: a systematic review. BMC Pregnancy Childbirth. 2019. Nov 6;19(1):406. 10.1186/s12884-019-2531-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Mohamad Pilus F, Ahmad N, Mohd Zulkefli NA, Mohd Shukri NH. Effect of face-to-face and WhatsApp communication of a theory-based health education intervention on breastfeeding self-efficacy (SeBF intervention): cluster randomized controlled field trial. JMIR Mhealth Uhealth. 2022. Sep 14;10(9):e31996. 10.2196/31996 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Murthy N, Chandrasekharan S, Prakash MP, Kaonga NN, Peter J, Ganju A, et al. The impact of an mHealth voice message service (mMitra) on infant care knowledge, and practices among low-income women in India: findings from a pseudo-randomized controlled trial. Matern Child Health J. 2019. Dec;23(12):1658–69. 10.1007/s10995-019-02805-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Lubis TA, Gunardi H, Herqutanto, Soedjatmiko S, Satari HI, Alatas FS, et al. Educational videos to address vaccine hesitancy in childhood immunization. Vaccine. 2022. Sep 29;40(41):5965–70. 10.1016/j.vaccine.2022.08.044 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Chakraborty A, Mohan D, Scott K, Sahore A, Shah N, Kumar N, et al. ; Kilkari Impact Evaluation Team. Does exposure to health information through mobile phones increase immunisation knowledge, completeness and timeliness in rural India? BMJ Glob Health. 2021. Jul;6 Suppl 5:e005489. 10.1136/bmjgh-2021-005489 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Gibson DG, Ochieng B, Kagucia EW, Were J, Hayford K, Moulton LH, et al. Mobile phone-delivered reminders and incentives to improve childhood immunisation coverage and timeliness in Kenya (M-SIMU): a cluster randomised controlled trial. Lancet Glob Health. 2017. Apr;5(4):e428–38. 10.1016/S2214-109X(17)30072-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.LeFevre AE, Shah N, Scott K, Chamberlain S, Ummer O, Bashingwa JJH, et al. ; Kilkari Impact Evaluation Team. The impact of a direct to beneficiary mobile communication program on reproductive and child health outcomes: a randomised controlled trial in India. BMJ Glob Health. 2022. Jul;6 Suppl 5:e008838. 10.1136/bmjgh-2022-008838 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Mohan D, Bashingwa JJH, Tiffin N, Dhar D, Mulder N, George A, et al. Does having a mobile phone matter? Linking phone access among women to health in India: an exploratory analysis of the national family health survey. PLOS ONE. 2020. Jul 20;15(7):e0236078. 10.1371/journal.pone.0236078 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Scott K, Ummer O, Shinde A, Sharma M, Yadav S, Jairath A, et al. ; Kilkari Impact Evaluation team. Another voice in the crowd: the challenge of changing family planning and child feeding practices through mHealth messaging in rural central India. BMJ Glob Health. 2021. Jul;6 Suppl 5:e005868. 10.1136/bmjgh-2021-005868 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Chernozhukov V, Chetverikov D, Demirer M, Duflo E, Hansen C, Newey W, et al. Double/debiased machine learning for treatment and structural parameters. Econom J. 2018;21(1):C1–68. 10.1111/ectj.12097 [DOI] [Google Scholar]
  • 46.Anderson ML. Multiple inference and gender differences in the effects of early intervention: a reevaluation of the abecedarian, perry preschool, and early training projects. J Am Stat Assoc. 2008;103(484):1481–95. 10.1198/016214508000000841 [DOI] [Google Scholar]
  • 47.LeFevre AE, Mendiratta J, Jo Y, Chamberlain S, Ummer O, Miller M, et al. Cost-effectiveness of a direct to beneficiary mobile communication programme in improving reproductive and child health outcomes in India. BMJ Glob Health. 2023. Mar;6 Suppl 5:e009553. 10.1136/bmjgh-2022-009553 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Johnston J, Yan S, Ward V, Murthy S. Evaluating the impact of a mobile phone messaging intervention on postnatal care: cluster randomized trial in four states in India. [online repository]. Charlottesville: Center of Open Science; 2023. 10.17605/OSF.IO/RF86P [DOI] [Google Scholar]

Articles from Bulletin of the World Health Organization are provided here courtesy of World Health Organization

RESOURCES