A model for predicting utilization of mHealth interventions in low-resource settings: case of maternal and newborn care in Kenya

BMC Medical Informatics and Decision Making
Stephen Mburu, Robert Oboko

Abstract

In low-resource settings, there are numerous socioeconomic challenges such as poverty, inadequate facilities, shortage of skilled health workers, illiteracy and cultural barriers that contribute to high maternal and newborn deaths. To address these challenges, there are several mHealth projects particularly in Sub-Sahara Africa seeking to exploit opportunities provided by over 90% rate of mobile penetration. However, most of these interventions have failed to justify their value proposition to inspire utilization in low-resource settings. This study proposes a theoretical model named Technology, Individual, Process-Fit (TIPFit) suitable for user-centred evaluation of intervention designs to predict utilization of mHealth products in low-resource settings. To investigate the predictive power of TIPFit model, we operationalized its latent constructs into variables used to predict utilization of an mHealth prototype called mamacare. The study employed single-group repeated measures quasi-experiment in which a random sample of 79 antenatal and postnatal patients were recruited from a rural hospital. During the study conducted between May and October 2014, the treatment involved sending and receiving SMS alerts on vital signs, appoi...Continue Reading

References

Jan 25, 2002·The British Journal of Social Psychology·C J Armitage, M Conner
Oct 30, 2007·International Journal of Medical Informatics·Maryati Mohd YusofLampros K Stergioulas
Mar 20, 2010·Social Work in Public Health·Gerald-Mark Breen, Jonathan Matusitz
Nov 19, 2013·BMC Medical Informatics and Decision Making·Hsiu-Ling HuangChia-Jung Chuang

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