All 2 entries tagged Mhealth

The Tyranny of Digital Inclusion

Writing about web page https://dig.oii.ox.ac.uk/2017/12/31/the-tyranny-of-digital-inclusion/

This post is a reproduction of an earlier blog produced for the Digital Inequality Group at the Oxford Internet Institute, 31 December 2017.

In a previous blog post, I argued that mobile phone use can have negative consequences for people’s behaviour. If we assume for the sake of the argument that people would be better off if everyone used digital technology (e.g. by gaining better access to government services or markets), then the intuitive conclusion would be to provide more widespread access and more opportunities to use information and communication technology, for example mobile phones or the Internet.

But what if the very process of digital inclusion – that is, the expansion of technology access and use – has negative effects on people’s lives? Imagine the following scenario: You live in a place where people just started using mobile phones. As people use these phones increasingly to communicate with each other and solve daily tasks like business, banking, or medical care, society will gradually come to expectpeople to use mobile phones – they will become “taken for granted” (Ling, 2012).

With regard to health in low- and middle-income countries (my subject area), a wide range of health-related uses will emerge in the process of mobile phone diffusion, for example making appointments with hospitals doctors or calling a private doctor to your home. Over time, health systems will adapt to this mobile phone use, making it necessaryto make appointments with doctors in order to receive treatment. Elsewhere, doctors might only be “on call,” or they may be out of station because they cater to patients who called them to their homes. Such a process of adaptation will be problematic for people who cannot use mobile phones (e.g. because they cannot afford mobile phones, they have nobody to explain how to use them, or bad eyesight and hearing prevent them from using the devices), making it harder for them to get treatment and consultation from doctors whose services become biased towards phone users.

This is a hypothesis which I test in a recent article. Using data from more than 12,000 households in rural India between 2005 and 2012, I studied whether the rapid spread of mobile phones (from 3% in 2005 to 75% in 2012) undermines the healthcare access for digitally excluded households. My findings suggest that the fast pace of mobile phone diffusion makes it harder for poor people without phones to access essential health services. In other words, non-adopters are increasingly excluded from health services if everyone around them starts using mobile phones, leaving them worse offthan before. In contrast, poor phone users can maintain their healthcare access. The spread of mobile phones can therefore create new divisions between poor parts of the population, and make it necessary to adopt new technology in order to secure existing access to services. Where this is not possible, poor people will fall further behind.

My study uses only crude measures of healthcare access and mobile phone use, so this certainly is not the end of the story. But the findings add to a consistent picture of mobile phone use and healthcare access that has emerged over the past five years of research. While there is no reason to demonise mobile phones, we see again and again that their spread comes with problems as well as opportunities. We should therefore not conclude that now everyone really needs a mobile just to maintain their basic access to services – that would be tyranny.

This post is based on my recent publication in World Development:

Haenssgen, M. J. (2018). The struggle for digital inclusion: phones, healthcare, and marginalisation in rural India. World Development, 104, 358-374. doi: 10.1016/j.worlddev.2017.12.023(free access until 18 February 2018 via https://authors.elsevier.com/a/1WJ8v,6yxD2w1Z)

Related research:

Haenssgen, M. J., & Ariana, P. (2017). The social implications of technology diffusion: uncovering the unintended consequences of people’s health-related mobile phone use in rural India and China.World Development, 94, 286-304. doi: http://doi.org/10.1016/j.worlddev.2017.01.014

References:

Ling, R. S. (2012). Taken for grantedness: the embedding of mobile communication into society. Cambridge, MA: MIT Press.

Marco Haenssgen : 09 Jan 2019 16:51 |  Tags: Developing Countries Digital Divide Digital Technologies Health Ict4D Mhealth Mobile Phones |  Comments (0) |  Close comments |  Report a problem

Mobiles and healthcare: Road blocks or digital fast lanes?

Writing about web page https://dig.oii.ox.ac.uk/2016/04/25/1591/

This post is a reproduction of an earlier blog produced for the Digital Inequality Group at the Oxford Internet Institute, 25 April 2016, following a presentation at the 13th Global Health & Innovation Conference, 16-17 April 2016, Yale University

Let’s try an experiment: Think of an object with global outreach. Nearly everybody around the world has access and in fact a billion people use it daily, especially in low- and middle-income countries. Picture not just an ordinary object, but one that is also a vehicle for social interaction and recreation. Everybody knows it, and even if people don’t use it themselves, they most certainly know somebody who does – it’s ubiquitous. In light of the glaring health problems persisting in developing countries, why don’t we take advantage of its global spread in order to deliver public health interventions, for example with messages to maintain a healthy diet and regular exercise (the absence of which is a major global health risk according to the World Health Organization, WHO, 2009:16-17). There is limitless potential ready to be harnessed because the solution is already at people’s fingertips.

What came to your mind – Computers? The Internet? Mobile phones? Plausible, indeed, but the narrative as it stands applies equally well to a somewhat less fashionable object – cigarettes (Ng et al., 2014:186). Yet it would be silly to even propose small fruit and exercise pictographs on the objects to serve as reminders of healthy lifestyles that can be communicated and explained during social smoking, where even people who do not smoke probably know someone who does and thereby benefit indirectly from the health information. We know that cigarette use is harmful.

Let us turn to mobile technology, where the same global outreach narrative has been repeatedly used to argue for more efficient, effective, and equitable health services and information delivery. In light of the alleged healthcare “potential” of mobile phones, 1,141 projects worldwide now use phones as a platform for health service delivery or health system improvements (my count on March 25th 2016; these are called “mHealth” projects), and, on January 5th 2016, I counted 101,672 apps in Apple’s App Store in the categories “Health and Fitness” and “Medical” (Apple Inc., 2016; GSMA, 2016).

Mobile phones are of course different from cigarettes because their use is not detrimental to people’s health. Or is it? Alongside the technology optimists are also voices declaring that “the more [mobile] technology is used, the less advantageous it is for one’s health, particularly as it pertains to sleep patterns, BMI [body-mass index], and healthy eating” (Melton et al., 2014:516). If it were indeed the case that the global spread of mobile phones had negative effects on people’s health and health behaviour, would that not make phones as attractive a medium for health service delivery as cigarettes?

My point here is not that mobile phones are as bad as cigarettes, or that phone-based interventions are mindless. Technologies like mobile phones are neither evil nor a godsend, and a number of reviews has attested modestly positive effects of some phone-based health interventions (Free et al., 2013a; Free et al., 2013b). The point is rather that, if mobile phones had a harmful impact on people’s behaviour, we would probably want to know this because it would affect how we think about mHealth and other phone-based services. The problem, however, is that we have no idea. Some research has examined the direct health consequences of mobile phones, for example exploding batteries and sleep deprivation (Ben et al., 2009; Brady et al., 2011; Karabagli et al., 2006; Patrick et al., 2008:178; Wilson & Stimpson, 2010); a few quantitative and qualitative studies have suggested that people also use phones in the context of illness and healthcare (Ahmed et al., 2014; Burrell, 2010; Hampshire et al., 2015; Horst & Miller, 2006; Mechael, 2008); but no research has tried to understand whether and how any such phone use affects health behaviour.

This isn’t an easy thing to find out. Already the notion of mobile phone adoption (or use) is more complicated than it seems at the first glance. What distinguishes a “user” from a “non-user,” and is such a binary distinction even useful? In practice, researchers often rely on information on whether someone owns a mobile phone, which tells us little about their actual use. The distinction between phone user and non-user is not necessarily helpful either: Should a “user” who takes one call per week fall in the same category as a “user” who spends six hours a day online, writing blog posts and emailing on a smartphone? Data analysis from rural India and China showed that moving away from simplistic ownership indicators towards more faithful (and “multidimensional”) representations of mobile phone use enables us to predict better when a patient will make use of a mobile phone in the process of getting medical treatment (Haenssgen, 2015).

But we should not be led to believe that technology will necessarily lead people to do what we want them to do. My research in India and China suggests that health-related mobile phone use amplifies people’s healthcare-seeking behaviours, including their biases. This means that phone users are more likely to utilise the healthcare system, even for health conditions (common cold, unspecified pain) that might not necessarily require medical attention in the resource-scarce health systems of rural India and rural China. Alas, not everyone can make use of mobile phones during an illness, for example because of impaired eyesight or because they never learned how to make a phone call. These groups remain systematically excluded from health-related mobile phone use and face potentially higher barriers to medical care because phone users are gradually absorbing the existing healthcare resources. Incidentally, higher household wealth produces the same patterns as mobile phone use, suggesting that a new mobile middle class exercises its “sharp elbows” when accessing healthcare (Seddon, 2007:88).

Related Papers

Haenssgen, M. J., & Ariana, P. (2017). The social implications of technology diffusion: uncovering the unintended consequences of people’s health-related mobile phone use in rural India and China. World Development, 94, 286-304. doi: 10.1016/j.worlddev.2017.01.014
Haenssgen, M. J. (2015). Exploring the mismatch between mobile phone adoption and use through survey data from rural India and China. Proceedings of the 2015 IEEE International Symposium on Technology and Society (ISTAS), 1-15. doi: 10.1109/ISTAS.2015.7439402

References

• Ahmed, T., Bloom, G., Iqbal, M., Lucas, H., Rasheed, S., Waldman, L., et al. (2014). E-health and M-health in Bangladesh: opportunities and challenges [IDS Evidence Report no. 60]. Brighton: Institute of Development Studies.
• Apple Inc. (2016). iTunes preview: App Store. Retrieved 05 January 2015, from https://itunes.apple.com/gb/genre/ios/id36?mt=8
• Ben, D., Ma, B., Liu, L., Xia, Z., Zhang, W., & Liu, F. (2009). Unusual burns with combined injuries caused by mobile phone explosion: Watch out for the “mini-bomb”! Journal of Burn Care & Research, 30(6). doi: 10.1097/BCR.0b013e3181bfb8c0
• Brady, R. R., Hunt, A. C., Visvanathan, A., Rodrigues, M. A., Graham, C., Rae, C., et al. (2011). Mobile phone technology and hospitalized patients: a cross-sectional surveillance study of bacterial colonization, and patient opinions and behaviours. Clinical Microbiology and Infection, 17(6), 830-835. doi: 10.1111/j.1469-0691.2011.03493.x
• Burrell, J. (2010). Evaluating shared access: social equality and the circulation of mobile phones in rural Uganda. Journal of Computer-Mediated Communication, 15(2), 230-250. doi: 10.1111/j.1083-6101.2010.01518.x
• Free, C., Phillips, G., Galli, L., Watson, L., Felix, L., Edwards, P., et al. (2013a). The effectiveness of mobile-health technology-based health behaviour change or disease management interventions for health care consumers: a systematic review. PLoS Medicine, 10(1), e1001362. doi: 10.1371/journal.pmed.1001362
• Free, C., Phillips, G., Watson, L., Galli, L., Felix, L., Edwards, P., et al. (2013b). The effectiveness of mobile-health technologies to improve health care service delivery processes: a systematic review and meta-analysis. PLoS Medicine, 10(1), e1001363. doi: 10.1371/journal.pmed.1001363
• GSMA. (2016). GSMA mHealth tracker. Retrieved 25 March 2016, from http://www.gsma.com/mobilefordevelopment/programmes/mhealth/mhealth-deployment-tracker
• Haenssgen, M. J. (2015). Exploring the mismatch between mobile phone adoption and use through survey data from rural India and China. Proceedings of the 2015 IEEE International Symposium on Technology and Society (ISTAS), 1-15. doi: 10.1109/ISTAS.2015.7439402
• Hampshire, K., Porter, G., Owusu, S. A., Mariwah, S., Abane, A., Robson, E., et al. (2015). Informal m-health: How are young people using mobile phones to bridge healthcare gaps in Sub-Saharan Africa? Social Science & Medicine, 142, 90-99. doi: http://dx.doi.org/10.1016/j.socscimed.2015.07.033
• Horst, H. A., & Miller, D. (2006). The cell phone: an anthropology of communication. Oxford: Berg.
• Karabagli, Y., Köse, A. A., & Çetin, C. (2006). Partial thickness burns caused by a spontaneously exploding mobile phone. Burns, 32(7), 922-924. doi: http://dx.doi.org/10.1016/j.burns.2006.03.009
• Mechael, P. (2008). Health services and mobiles: a case from Egypt. In J. E. Katz (Ed.), Handbook of mobile communication studies (pp. 91-103). Cambridge, MA: MIT Press.
• Melton, B. F., Bigham, L. E., Bland, H. W., Bird, M., & Fairman, C. (2014). Health-related behaviors and technology usage among college students. American Journal of Health Behavior, 38(4), 510-518. doi: 10.5993/ajhb.38.4.4
• Ng, M., Freeman, M. K., Fleming, T. D., Robinson, M., Dwyer-Lindgren, L., Thomson, B., et al. (2014). Smoking prevalence and cigarette consumption in 187 countries, 1980-2012. JAMA, 311(2), 183-192. doi: 10.1001/jama.2013.284692
• Patrick, K., Griswold, W. G., Raab, F., & Intille, S. S. (2008). Health and the mobile phone. American Journal of Preventive Medicine, 35(2), 177-181. doi: 10.1016/j.amepre.2008.05.001
• Seddon, N. (2007). Quite like heaven? Options for the NHS in a consumer age. Bury St Edmunds: St Edmundsbury Press.
• WHO. (2009). Global health risks: mortality and burden of disease attributable to major risks. Geneva: World Health Organization.
• Wilson, F. A., & Stimpson, J. P. (2010). Trends in fatalities from distracted driving in the United States, 1999 to 2008. American Journal of Public Health, 100(11), 2213-2219. doi: 10.2105/ajph.2009.187179

Marco Haenssgen : 15 Dec 2018 09:43 |  Tags: Developing Countries Digital Technologies Health Ict4D Mhealth |  Comments (0) |  Close comments |  Report a problem