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Using a mobile app to improve pre- and post-natal health in Myanmar

Human capital is a key factor for sustained economic growth (López-Casasnovas, 2007). Pre-natal and early-life health are particularly crucial pillars to economic development as they provide a foundation for the accumulation of cognitive and non-cognitive skills.  They have also shown to be one of the highest-return socio-economic interventions available (Heckman, 2014 and Campbell, 2014). In light of this, the MayMay app is being studied in Myanmar, to determine use and engagement with this cost-effective pre- and post-natal health technology. Whether the app has an impact on the knowledge, behavior, cultural beliefs, and ultimately, the health outcomes of users is yet to be determined.

The case of Myanmar

Pre- and post-natal health

Myanmar has some of the lowest maternal and child outcomes in the Association of Southeast Asian Nations (ASEAN) region (WHO and World Bank).  Expanding health care infrastructure (including access to personnel), especially to rural and remote regions, will be an ongoing development challenge for Myanmar in the medium to long term, as in many developing countries. In the meantime, there is a significant gap in the capacity of the state to disseminate vital pre- and post-natal health information to citizens, especially pregnant women.

Mobile health technologies

Considering the recent expansion of mobile network coverage in Myanmar, from a low base of less than 10% coverage, mobile health technologies are a promising part of the solution to expand service delivery and improve healthcare outcomes. The relatively late mobile network rollout means that most users are leaping straight from no phone coverage at all, to smartphones with colour screens that provide a powerful interface to disseminate health information.

Cellphone coverage

As of August 2016, there were 45 million active cellphone subscriptions in a national population of 54 million, with 60-80% of these subscriptions for smart phones (Forbes Asia). This is from a base of less than 3 million cellphone holders as recently as 2014. These technologies carry the promise of providing a means to overcome gaps in state capacity to disseminate health information and services in the short-to-medium term. But what are the most effective ways to do so?

The MayMay app

One promising initiative is the MayMay smartphone application, developed through joint efforts of the Myanmar social enterprise, Koe Koe Tech Ltd, and the international NGO, Population Services International, with support from the Connected Women programme of GSMA, USAID, Echoing Green, and others.

New users of MayMay provide their week of pregnancy to get regular, targeted reminders that encourage optimal pre-natal health behaviours. The app also provides access to a wealth of research-validated health information. Given that the marginal cost of the app is near-zero (in practice, it seems to be more effective to have a personal installation of the app, which implies a small setup cost), and pre-natal health improvements have high returns, if the app is at all impactful it would imply a very high return on investment.

Findings

Use

Analysis of the Key Performance Indicators (KPIs) provides some initial lessons learned, and raises additional questions. As of March 2017, MayMay has been downloaded over 300,000 times (Koe Koe Tech download data). As of March 2017, it had about 60,000 active users, who open the app at least once a month (Ibid). This is a relatively high proportion of active usage to app downloads.

Engagement

Users’ interaction with the application has been tracked in further detail. While engaging users with weekly reminder messages generates active usage, users appear to be even more responsive to interactive media to stay engaged with the app. In particular, MayMay provides “gamified” lessons and quizzes, which encourages users to build their knowledge while competing for points in the app. From August 2016 data, when MayMay had only 30,000 active users, quiz point results showed that 28% of 37,700 users (10,878 users) participated in quizzes.

Quizzes have five questions each; the average quiz participant has about 48 correct quiz responses accumulated, with the 95th percentile of 174 correct quiz responses. On average, 10.7 lessons are completed, with the 95th percentile of users having completed 38 lessons, as of August 2016. Thus, the gamified version of the app seems to be effective in developing a significant, high-commitment user base.

Pilot evaluation

Installation

Our research team has generated further insights from direct data collection piloting an evaluation of the app. In the pilot, users received the app at a health facility through direct installation by an assistant. We find that pilot users are more actively engaged with the app than the broader user population, which may suggest that app distribution through personal installation may enhance uptake.

Engagement

We also find that pilot users who did not have a recent pregnancy (within the last 5 years) were more likely to engage with the gamified quiz content (82.1 percent), than those who had had a more recent pregnancy (57.1 percent). Perhaps relatedly, younger users are also more likely to engage with the quizzes. New mothers are more likely to be engaged with the app than mothers with a previous birth history.

These findings suggest that younger users are more likely to engage with the app, though it is not clear if this is more related to technological savvy, or less experienced mothers seeing a greater need for the content. A further insight is that the month of pregnancy does not correspond to quiz participation or results. There is also no significant difference in quiz points or take up depending on the number of ante-natal care visits of the users.

Unanswered questions

While initial findings show some promise, there are several open questions that are difficult to assess with observational data, including:

  1. Knowledge: What are the impacts of the app on health knowledge? Are the apparent knowledge gains from quiz participation translating into sustained pre-natal health knowledge gains?
  2. Behaviour: What are the impacts of the app on health behavior? While engagement with the app is promising, the goal is to improve health behavior, to improve health outcomes.
  3. Cultural beliefs: It seems plausible that many pre-natal health beliefs and practices are deeply rooted in culture and social norms, making them hard to change. Hence it may be difficult to achieve meaningful impacts on outcomes through app dissemination strategies that target individual women. Could we see greater impacts of the app if disseminated to closely-connected women in the same social network, through a kind of multiplier effect as they collectively switch beliefs and resulting behaviour?

Further investigation

To more rigorously address these issues, a full randomized controlled trial (RCT) is being piloted and planned. The study is designed to determine the full impacts of the MayMay app on the health knowledge, behaviours and outcomes of pregnant women in Yangon, and to measure spillovers and social interaction multipliers. The study focuses mainly on respondents of lower socio-economic status in peri-urban townships of Yangon.

References

Campbell, F., Conti, G., Heckman, J., Moon, S. H., Pinto, R., Pungello, E., Pan, Y. (2014), “Early Childhood Investments Substantially Boost Adult Health”, American Association for the Advancement of Science, 343: 1478-85.

Heckman, J. and Mosso, S. (2014), “The Economics of Human Development and Social Mobility”, Annual Reviews of Economics, 6: 689-733.

López-Casasnovas, G., Rivera, B. and Currais, L. (2007), “Health and Economic Growth: Findings and Policy Implications”, MIT Press.

WHO, UNICEF, UNFPA, World Bank Group, and United Nations Population Division, and the Maternal Mortality Estimation Inter-Agency Group. Maternal Mortality in 1990-2015 Myanmar. Accessible: http://www.who.int/gho/maternal_health/countries/mmr.pdf

World Bank. Infant Mortality rate (per 1000 live births). Accessible: http://data.worldbank.org/indicator/SP.DYN.IMRT.IN

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