Abstract
After three decades of mobile phone diffusion, thousands of mobile-phone-based health projects worldwide (“mHealth”), and hundreds of thousands of smartphone health applications, fundamental questions about the effect of phone diffusion on people’s healthcare behavior continue to remain unanswered. This study investigated whether, in the absence of specific mHealth interventions, people make different healthcare decisions if they use mobile phones during an illness. Following mainstream narratives, we hypothesized that phone use during an illness (a) increases and (b) accelerates healthcare access. Our study was based on original survey data from 800 respondents in rural Rajasthan (India) and Gansu (China), sampled from the general adult population in 2014 in a three-stage stratified cluster random sampling design. We analyzed single- and multi-level logistic, Poisson, and negative binomial regression models with cluster-robust standard errors. Contrary to other research at the intersection of mobile phones and healthcare, we captured actual health-related mobile phone use during people’s illnesses irrespective of whether they own a phone. Our analysis produced the first quantitative micro-evidence that patients’ personal mobile phone use is correlated with their healthcare decisions. Despite a positive association between phone use and healthcare access, health-related phone use was also linked to delayed access to public doctors and nurses. We considered theoretical explanations for the observed patterns by augmenting transaction cost and information deficit arguments with the prevailing health system configuration and with notions of heuristic decision-making during the healthcare-seeking process. Our study was a first step toward understanding the implications of mobile technology diffusion on health behavior in low- and middle-income countries in the absence of specific mHealth interventions. Future research will have to explore the causal relationships underlying these statistical associations. Such a link could potentially mean that development interventions aimed at improving access to healthcare continue to require conventional solutions to sustain healthcare equity.
Highlights
The world has undergone a rapid mobile connectivity transition during the past decade: Up to 630 million new subscriptions per year were added in low- and middle-income countries (LMICs; 40% of this growth was occurred in India and China), and these countries account for three in four mobile phone subscriptions worldwide (ITU, 2015a, 2015b)
We carried out an exploratory study using a novel, cross-sectional data set of healthcare behavior among the general adult population in rural Rajasthan (India) and Gansu (China)—irrespective of whether the respondent owned a phone
To the best of our knowledge, this is the first study that identified a statistical association between mobile phone use and healthcare access behavior among the rural adult population in LMICs in the absence of a specific phone-based healthcare intervention
Summary
The world has undergone a rapid mobile connectivity transition during the past decade: Up to 630 million new subscriptions per year were added in low- and middle-income countries (LMICs; 40% of this growth was occurred in India and China), and these countries account for three in four mobile phone subscriptions worldwide (ITU, 2015a, 2015b). A better understanding of positive as well as negative consequences of mobile phone use on people’s health-seeking behavior is important for the branch of mHealth that delivers interventions through this platform to patients. As part of the broader study of the social implications of technology diffusion, this paper investigated the effect of mobile phones on people’s healthcare-seeking behavior in two rural low- and middle-income contexts. The overarching research question for this paper was, ‘‘In the absence of specific mHealth interventions, do people make different healthcare decisions if they use a mobile phone during an illness?” To answer this question, we tested two hypotheses on the implications of phone-aided healthcare-seeking behavior, using novel survey data from rural Rajasthan (India) and rural Gansu (China): H1. An implication of our study is that future patient-focused mHealth projects potentially compete with people’s existing (non-mHealth) mobile-phonebased solutions, and mHealth interventions may have to combat adverse behaviors created by the mobile phone platform itself
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