Can health information through mobile phones close the divide in health behaviours among the marginalised? An equity analysis of Kilkari in Madhya Pradesh, India.
Diwakar MohanKerry ScottNeha ShahJean Juste Harrisson BashingwaArpita ChakrabortyOsama UmmerAnna GodfreyPriyanka DuttSara ChamberlainAmnesty Elizabeth LeFevrePublished in: BMJ global health (2021)
Kilkari is one of the largest maternal mobile messaging programmes in the world. It makes weekly prerecorded calls to new and expectant mothers and their families from the fourth month of pregnancy until 1-year post partum. The programme delivers reproductive, maternal, neonatal and child health information directly to subscribers' phones. However, little is known about the reach of Kilkari among different subgroups in the population, or the differentiated benefits of the programme among these subgroups. In this analysis, we assess differentials in eligibility, enrolment, reach, exposure and impact across well-known proxies of socioeconomic position-that is, education, caste and wealth. Data are drawn from a randomised controlled trial (RCT) in Madhya Pradesh, India, including call data records from Kilkari subscribers in the RCT intervention arm, and the National Family Health Survey-4, 2015. The analysis identifies that disparities in household phone ownership and women's access to phones create inequities in the population eligible to receive Kilkari, and that among enrolled Kilkari subscribers, marginalised caste groups and those without education are under-represented. An analysis of who is left behind by such interventions and how to reach those groups through alternative communication channels and platforms should be undertaken at the intervention design phase to set reasonable expectations of impact. Results suggest that exposure to Kilkari has improved levels of some health behaviours across marginalised groups but has not completely closed pre-existing gaps in indicators such as wealth and education.
Keyphrases
- health information
- healthcare
- social media
- pregnancy outcomes
- quality improvement
- randomized controlled trial
- public health
- mental health
- birth weight
- big data
- genome wide
- polycystic ovary syndrome
- adipose tissue
- dna methylation
- machine learning
- smoking cessation
- type diabetes
- preterm birth
- weight gain
- skeletal muscle
- human health
- clinical trial
- gestational age
- double blind