Development of a Phone Survey Tool to Measure Respectful Maternity Care During Pregnancy and Childbirth in India: Study Protocol.

BACKGROUND

Respectful maternity care (RMC) is a key barometer of the underlying quality of care women receive during pregnancy and childbirth. Efforts to measure RMC have largely been qualitative, although validated quantitative tools are emerging. Available tools have been limited to the measurement of RMC during childbirth and confined to observational and face-to-face survey modes. Phone surveys are less invasive, low cost, and rapid alternatives to traditional face-to-face methods, yet little is known about their validity and reliability.

OBJECTIVE

The primary objective of this study was to develop validated face-to-face and phone survey tools for measuring RMC during pregnancy and childbirth for use in India and other low resource settings. The secondary objective was to optimize strategies for improving the delivery of phone surveys for use in measuring RMC.

METHODS

To develop face-to-face and phone surveys for measuring RMC, we describe procedures for assessing content, criterion, and construct validity as well as reliability analyses. To optimize the delivery of phone surveys, we outline plans for substudies, which aim to assess the effect of survey modality, and content on survey response, completion, and attrition rates.

RESULTS

Data collection will be carried out in 4 districts of Madhya Pradesh, India, from July 2018 to March 2019.

CONCLUSIONS

To our knowledge, this is the first RMC phone survey tool developed for India, which may provide an opportunity for the rapid, routine collection of data essential for improving the quality of care during pregnancy and childbirth. Elsewhere, phone survey tools are emerging; however, efforts to develop these surveys are often not inclusive of rigorous pretesting activities essential for ensuring quality data, including cognitive, reliability, and validity testing. In the absence of these activities, emerging data could overestimate or underestimate the burden of disease and health care practices under assessment. In the context of RMC, poor quality data could have adverse consequences including the naming and shaming of providers. By outlining a blueprint of the minimum activities required to generate reliable and valid survey tools, we hope to improve efforts to develop and deploy face-to-face and phone surveys in the health sector.

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