Evidence map›Paper›PMID 33087391›Full record

ArticleBMJ global health2020

Not just money: what mothers value in conditional cash transfer programs in India.

Krishna D Rao, Shivani Kachwaha, Avril Kaplan, David Bishai

Abstract read
In one paragraph

Article in BMJ global health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Krishna D RaoDepartment of International Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA kdrao@jhu.edu.
Shivani KachwahaPoverty, Health and Nutrition Division, International Food Policy Research Institute, New Delhi, India.
Avril KaplanInternational Health, Johns Hopkins University, Baltimore, Maryland, USA.
David BishaiFamily and Population Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionConditional cash transfers (CCTs) have become an important policy tool for increasing demand for key maternal and child health services in low/middle-income countries. Yet, these programs have had variable success in increasing service use. Understanding beneficiary preferences for design features of CCTs can increase program effectiveness.

methodsWe conducted a Discrete choice experiment in two districts of Uttar Pradesh, India in 2018 with 405 mothers with young children (<3 years). Respondents were asked to choose between hypothetical CCT programme profiles described in terms of five attribute levels (cash, antenatal care visits, growth-monitoring and immunisation visits, visit duration and health benefit received) and responses were analysed using mixed logit regression.

resultsMothers most valued the cash transfer amount, followed by the health benefit received from services. Mothers did not have a strong preference for conditionalities related to the number of health centre visits or for time spent seeking care; however, service delivery points were in close proximity to households. Mothers were willing to accept lower cash rewards for better perceived health benefits-they were willing to accept 2854 Indian rupees ($41) less for a programme that produced good health, which is about half the amount currently offered by India's Maternal Benefits Program. Mothers who had low utilisation of health services, and those from poor households, valued the cash transfer and the health benefit significantly more than others.

conclusionBoth cash transfers and the perceived health benefit from services are highly valued, particularly by infrequent service users. In CCTs, this highlights the importance of communicating value of services to beneficiaries by informing about health benefits of services and providing quality care. Conditionalities requiring frequent health centre visits or time taken for seeking care may not have large negative effects on CCT participation in contexts of good service coverage.

Indexed as

Child Health ServicesMothersChildChild, PreschoolFamily CharacteristicsFemaleHumansIndiaPovertyPregnancyhealth economicshealth policyhealth systems

Identifiers

PMID33087391
PMCPMC7580051

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.