January 16, 2019

Against the myth of ubiquity: Reflections on five years of mobile phone diffusion research

Writing about web page https://www.qeh.ox.ac.uk/blog/against-myth-ubiquity-reflections-five-years-mobile-phone-diffusion-research

This post is a reproduction of an earlier blog produced for the Debating Development blog from the Oxford Department of International Development, 17 April 2018


If you follow tech news and research in the field of ‘information and communication technologies for development’ (ICT4D), you will sooner or later come across the idea that mobile phones are ubiquitous. The last time I checked on Google (while preparing a recently published paper), variations of the phrase ‘mobile phones have become ubiquitous’ produced around 133,000 search results.


Mobile phone user in India

Mobile phone user in India (photo credit: Marco J Haenssgen)


This viewpoint is not surprising, considering that we witnessed a trend where, within the span of just ten years, global mobile phone ‘teledensity’ rose by 50 percentage points to more than 100% in 2016 (based on recent data from the International Telecommunication Union). And with several million smartphone apps, how can we not assume that everyone can and should use these technologies?


This excitement around mobile technology has spread into international development practice, where mobile phones have become an increasingly attractive vehicle for interventions and service delivery. To give you a sense of the scale: on my last count in March 2016, the industry group Groupe Speciale Mobile Association(GSMA) recorded worldwide 131 ongoing and planned mobile phone projects in the area of agriculture, 372 in finance, and 1,141 in health. Hopes about the transformative potential of this technology are also expressed in the opening lines of Tim Unwin’s popular book ICT4D: Information and Communication Technology for Development (at currently 432 citations according to Google Scholar), which state that, ‘This book is about how information and communication technologies (ICTs) can be used to help poor and marginalised people and communities make a difference to their lives’.


Perhaps the technological excitement is justified, but the anthropological and sociological literature suggests that the claim about mobile phone ubiquity is flawed. Other researchers have, for example, argued that access to and use of mobile phones in low- and middle-income countries reproduces existing social divisionsand creates new frictions, and – perhaps most importantly for the ‘ubiquity narrative’ – the way in which people access mobile technology goes beyond “having” and “not having” mobile phones.


Sunset in China

Sunset in China (photo credit: Marco J Haenssgen)


Yet, the notion of ubiquity persists, which may stem from an enthusiastic imagination of technology use that resembles our own urban lifestyles and aspirations, but which may also be rooted in how we conceptualise the process of technology adoption (on the individual level) and diffusion (on the population level). Implicit in the idea of ubiquity is often a binary notion of adoption (see eg Everett Rogers’ book Diffusion of Innovations). Romantic images of developing country ‘communities’ can further add to the view that sharing is widespreadand undisputed, which can suppress questions about non-adoption and exclusion.


My latest research articlecontributes to the literature that challenges this position. I drew on data that I collected as part of my DPhil in International Development, which included interviews and surveys in rural parts of India and China. My research showed that mobile phones were common in my rural field sites and that indirect forms of access could extend nominal access to mobile phones beyond the owners (the ‘adopters’). This would resonate with the ‘ubiquity’ narrative, and indeed both areas feature in publications about the potential for mobile-phone-based development interventions. Yet, these patterns of mobile phone access did not mean that phone use was actually ubiquitous.
The degree of utilisation was very diverse, with many phone owners using hardly any functions on their phones, and only a few people coming close to what could be considered ‘full use’ of a mobile phone (eg daily use of the mobile internet). It appeared that some factors commonly influenced this degree of ‘utilisation’, like education and age, while other determinants like gender seemed to depend more on the specific socio-cultural context (e.g. in rural India). Subtle frictions in sharing complicated the picture yet further. For example, people would not easily ‘share’ mobile phones with others; older and technologically less confident people would often limit themselves to basic uses or depend on other people to operate the phone for them; and to ask somebody to ‘borrow’ a mobile phone would often require a good reason and entail social obligations to reciprocate the favour.


Overall, it rather seemed that people who were at the social and economic margins of rural ‘communities’ were also more likely to be excluded from utilising mobile phones. Such a regressive pattern can be problematic, as I showed in a recent articlethat highlighted how mobile phone users gradually crowd out poor non-users from health services. At the same time, we should also not quietly assume that digital inclusion is automatically beneficial. Another articlebased on my work on healthcare indicated that mobile technologies can complicate people’s behaviour with potentially adverse consequences for health service access. For example, people in rural India and rural China shifted to private (out-of-pocket) health services and waited longer to access medical treatment if they used a mobile phone during an illness. We can also arguethat the systematic exclusion of groups with specific social and economic constraints can bias increasingly popular ‘big data’ analyses of ‘user-generated data’ towards more affluent male parts of the population with less constrained lifestyles.


This does not mean that we need to be cynical about mobile phones (it’s not an ‘if-you-aren’t-for-me- you’re-against-me’ situation). For example, if our objective was to deliver some services and information more efficiently to a wider population, then mobile phones could help achieve this objective (although we should be conservative about our expectations). Yet, if our objective is to ensure and promote equity, then we should consider the potentially regressive nature of the mobile phone platform. Savings generated by more efficient service delivery for a mobile-phone-using part of the population could for instance be used to expand service access to more marginalised groups, who are costlier to reach. However, if we continue to believe in mobile phone ubiquity, then the persistent reproduction of this myth in the global technology and development discourse will not only render it meaningless. It can also obscure potentially harmful development practices.


References

  • Bell, G. (2006). The age of the thumb: a cultural reading of mobile technologies from Asia. Knowledge, Technology, & Policy, 19(2), 41-57.
  • Fernández-Ardèvol, M. (2012). Exploring the use of mobile communications in a sample of older people: preliminary results of a case study in Los Angeles [IN3 Working Paper no. WP12-001]. Barcelona: Internet Interdisciplinary Institute.
  • Hahn, H. P., & Kibora, L. (2008). The domestication of the mobile phone: oral society and new ICT in Burkina Faso. The Journal of Modern African Studies, 46(1), 87-109. doi: doi:10.1017/S0022278X07003084
  • Ling, R., & Xiao, J. (2012). mhealth in China: designing a winning business model. New York, NY: PricewaterhouseCoopers.
  • Qiang, C. Z., Yamamichi, M., Hausman, V., Miller, R., & Altman, D. (2012). Mobile applications for the health sector. Washington, DC: World Bank.
  • Reisdorf, B. C., Axelsson, A.-S., & Söderholm, H. M. (2012). Living offline: a qualitative study of Internet non-use in Great Britain and Sweden. Paper presented at the Association of Internet Researchers Conference, 18-21 October 2012, Salford, UK.
  • Rogers, E. M. (2003). Diffusion of innovations (5th ed.). New York: Free Press.
  • Tenhunen, S. (2008). Mobile technology in the village: ICTs, culture, and social logistics in India. Journal of the Royal Anthropological Institute, 14(3), 515-534. doi: 10.1111/j.1467-9655.2008.00515.x
  • Unwin, P. T. H. (2009). ICT4D: information and communication technology for development. Cambridge: Cambridge University Press.
  • Walsham, G. (2010). ICTs for the broader development of India: an analysis of the literature. Electronic Journal of Information Systems in Developing Countries, 41(4), 1-20. ​

The complete portfolio of publications related to this research project include:

Peer-Reviewed Publications

Haenssgen, MJ (2018). Manifestations, drivers, and frictions of mobile phone use in low- and middle-income settings: a mixed methods analysis of rural India and China [epub ahead of print]. Journal of Development Studies. doi: 10.1080/00220388.2018.1453605​
Haenssgen, MJ (2018). The struggle for digital inclusion: phones, healthcare, and sharp elbows in rural India. World Development, 104, 358-374. doi: 10.1016/j.worlddev.2017.12.023
Haenssgen, MJ & Ariana, P (2018). The place of technology in the capability approach. Oxford Development Studies, 46(1), 98-112. doi: 10.1080/13600818.2017.1325456
Haenssgen, MJ & 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, MJ & Ariana, P (2017). Healthcare access: a sequence-sensitive approach. Social Science & Medicine – Population Health, 3, 37-47. doi: 10.1016/j.ssmph.2016.11.008
Haenssgen, MJ (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
Haenssgen, MJ (2015). Satellite-aided survey sampling and implementation in low- and middle-income contexts: a low-cost/low-tech alternative. Emerging Themes in Epidemiology, 12(20). doi: 10.1186/s12982-015-0041-8

Comments, Reviews, and Practitioner-Oriented Publications

Haenssgen, MJ (2017). A rich man’s world: biases of big data in a development context. Asia-Pacific Tech Monitor, 34(4), 24-29.
Haenssgen, MJ (2017). After Access: Inclusion, Development, and a More Mobile Internet. Journal of Human Development and Capabilities, 18(1), 137-139. doi: 10.1080/19452829.2017.1284950


January 09, 2019

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.


Health-related mobile phone use becomes more common. Photo credit: Nutcha Charoenboon.


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.


December 15, 2018

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.


Image


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.

Image


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

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