The struggle for digital inclusion: Phones, healthcare, and marginalisation in rural India
•This study relates to the social implications of (mobile) technology diffusion.•I hypothesise that phone diffusion undermines non-adopters’ healthcare access.•I use a panel of 12,003 sick households across rural India in 2005 and 2012.•Poor non-adopters’ access to private healthcare worsens during...
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description | •This study relates to the social implications of (mobile) technology diffusion.•I hypothesise that phone diffusion undermines non-adopters’ healthcare access.•I use a panel of 12,003 sick households across rural India in 2005 and 2012.•Poor non-adopters’ access to private healthcare worsens during fast diffusion.•Wealthier households and public healthcare access are insulated from this trend.
The gains from digital technology diffusion are deemed essential for international development, but they are also distributed unevenly. Does the uneven distribution mean that not everyone benefits from new technologies to the same extent, or do some people experience an absolute disadvantage during this process? I explore this question through the case study of curative healthcare access in the context of rapid mobile phone uptake in rural India, contributing thus to an important yet surprisingly under-researched aspect of the social implications of (mobile) technology diffusion.
Inspired by a previous analysis of cross-sectional data from rural India, I hypothesise that health systems increasingly adapt to mobile phone users where phones have diffused widely. This adaptation will leave poor non-adopters worse off than before and increases healthcare inequities. I use a panel of 12,003 rural households with an illness in 2005 and 2012 from the Indian Human Development Survey to test this hypothesis. Based on village-cluster robust fixed-effects linear probability models, I find that (a) mobile phone diffusion is significantly and negatively linked to various forms of rural healthcare access, suggesting that health systems increasingly adapt to phone use and discriminate against non-users; that (b) poor rural households without mobile phones experience more adverse effects compared to more affluent households, which indicates a struggle and competition for healthcare access among marginalised groups; and that (c) no effects emerge for access to public doctors, which implies that some healthcare providers are less responsive to mobile phone use than others.
Overall, my findings indicate that the rural Indian healthcare system gradually adapts to increasing mobile phone use at the expense of non-users. I conclude that rapid mobile phone diffusion creates an opportunity to improve people’s access to healthcare in rural India, but it also creates new forms of marginalisation among poor rural households. |
doi_str_mv | 10.1016/j.worlddev.2017.12.023 |
format | Article |
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The gains from digital technology diffusion are deemed essential for international development, but they are also distributed unevenly. Does the uneven distribution mean that not everyone benefits from new technologies to the same extent, or do some people experience an absolute disadvantage during this process? I explore this question through the case study of curative healthcare access in the context of rapid mobile phone uptake in rural India, contributing thus to an important yet surprisingly under-researched aspect of the social implications of (mobile) technology diffusion.
Inspired by a previous analysis of cross-sectional data from rural India, I hypothesise that health systems increasingly adapt to mobile phone users where phones have diffused widely. This adaptation will leave poor non-adopters worse off than before and increases healthcare inequities. I use a panel of 12,003 rural households with an illness in 2005 and 2012 from the Indian Human Development Survey to test this hypothesis. Based on village-cluster robust fixed-effects linear probability models, I find that (a) mobile phone diffusion is significantly and negatively linked to various forms of rural healthcare access, suggesting that health systems increasingly adapt to phone use and discriminate against non-users; that (b) poor rural households without mobile phones experience more adverse effects compared to more affluent households, which indicates a struggle and competition for healthcare access among marginalised groups; and that (c) no effects emerge for access to public doctors, which implies that some healthcare providers are less responsive to mobile phone use than others.
Overall, my findings indicate that the rural Indian healthcare system gradually adapts to increasing mobile phone use at the expense of non-users. I conclude that rapid mobile phone diffusion creates an opportunity to improve people’s access to healthcare in rural India, but it also creates new forms of marginalisation among poor rural households.</description><identifier>ISSN: 0305-750X</identifier><identifier>EISSN: 1873-5991</identifier><identifier>DOI: 10.1016/j.worlddev.2017.12.023</identifier><language>eng</language><publisher>Oxford: Elsevier Ltd</publisher><subject>Adoption of innovations ; Asia ; Case studies ; Cell phones ; Cellular telephones ; Competition ; Data processing ; Diffusion ; Digital inclusion ; Disadvantaged ; Health care ; Health care access ; Health care industry ; Health care policy ; Health disparities ; Health services ; Healthcare ; Household panel data ; Households ; Human development ; Illnesses ; India ; Inequality ; Marginality ; Medical technology ; Mobile phones ; New technology ; Physicians ; Rural areas ; Rural communities ; Rural poverty ; Side effects ; Social exclusion ; Technology ; Telephone communications ; Telephones ; Uptake</subject><ispartof>World development, 2018-04, Vol.104, p.358-374</ispartof><rights>2017 Elsevier Ltd</rights><rights>Copyright Pergamon Press Inc. Apr 2018</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c453t-a93cffba05f232534ddf3329920e9b1a6a43271c5ed46983fa7e4d2212708e3</citedby><cites>FETCH-LOGICAL-c453t-a93cffba05f232534ddf3329920e9b1a6a43271c5ed46983fa7e4d2212708e3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.worlddev.2017.12.023$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27866,27924,27925,33774,45995</link.rule.ids></links><search><creatorcontrib>Haenssgen, Marco J.</creatorcontrib><title>The struggle for digital inclusion: Phones, healthcare, and marginalisation in rural India</title><title>World development</title><description>•This study relates to the social implications of (mobile) technology diffusion.•I hypothesise that phone diffusion undermines non-adopters’ healthcare access.•I use a panel of 12,003 sick households across rural India in 2005 and 2012.•Poor non-adopters’ access to private healthcare worsens during fast diffusion.•Wealthier households and public healthcare access are insulated from this trend.
The gains from digital technology diffusion are deemed essential for international development, but they are also distributed unevenly. Does the uneven distribution mean that not everyone benefits from new technologies to the same extent, or do some people experience an absolute disadvantage during this process? I explore this question through the case study of curative healthcare access in the context of rapid mobile phone uptake in rural India, contributing thus to an important yet surprisingly under-researched aspect of the social implications of (mobile) technology diffusion.
Inspired by a previous analysis of cross-sectional data from rural India, I hypothesise that health systems increasingly adapt to mobile phone users where phones have diffused widely. This adaptation will leave poor non-adopters worse off than before and increases healthcare inequities. I use a panel of 12,003 rural households with an illness in 2005 and 2012 from the Indian Human Development Survey to test this hypothesis. Based on village-cluster robust fixed-effects linear probability models, I find that (a) mobile phone diffusion is significantly and negatively linked to various forms of rural healthcare access, suggesting that health systems increasingly adapt to phone use and discriminate against non-users; that (b) poor rural households without mobile phones experience more adverse effects compared to more affluent households, which indicates a struggle and competition for healthcare access among marginalised groups; and that (c) no effects emerge for access to public doctors, which implies that some healthcare providers are less responsive to mobile phone use than others.
Overall, my findings indicate that the rural Indian healthcare system gradually adapts to increasing mobile phone use at the expense of non-users. I conclude that rapid mobile phone diffusion creates an opportunity to improve people’s access to healthcare in rural India, but it also creates new forms of marginalisation among poor rural households.</description><subject>Adoption of innovations</subject><subject>Asia</subject><subject>Case studies</subject><subject>Cell phones</subject><subject>Cellular telephones</subject><subject>Competition</subject><subject>Data processing</subject><subject>Diffusion</subject><subject>Digital inclusion</subject><subject>Disadvantaged</subject><subject>Health care</subject><subject>Health care access</subject><subject>Health care industry</subject><subject>Health care policy</subject><subject>Health disparities</subject><subject>Health services</subject><subject>Healthcare</subject><subject>Household panel data</subject><subject>Households</subject><subject>Human development</subject><subject>Illnesses</subject><subject>India</subject><subject>Inequality</subject><subject>Marginality</subject><subject>Medical technology</subject><subject>Mobile phones</subject><subject>New technology</subject><subject>Physicians</subject><subject>Rural areas</subject><subject>Rural communities</subject><subject>Rural poverty</subject><subject>Side effects</subject><subject>Social exclusion</subject><subject>Technology</subject><subject>Telephone 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inclusion</topic><topic>Disadvantaged</topic><topic>Health care</topic><topic>Health care access</topic><topic>Health care industry</topic><topic>Health care policy</topic><topic>Health disparities</topic><topic>Health services</topic><topic>Healthcare</topic><topic>Household panel data</topic><topic>Households</topic><topic>Human development</topic><topic>Illnesses</topic><topic>India</topic><topic>Inequality</topic><topic>Marginality</topic><topic>Medical technology</topic><topic>Mobile phones</topic><topic>New technology</topic><topic>Physicians</topic><topic>Rural areas</topic><topic>Rural communities</topic><topic>Rural poverty</topic><topic>Side effects</topic><topic>Social exclusion</topic><topic>Technology</topic><topic>Telephone communications</topic><topic>Telephones</topic><topic>Uptake</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Haenssgen, Marco J.</creatorcontrib><collection>CrossRef</collection><collection>Environment 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inclusion: Phones, healthcare, and marginalisation in rural India</atitle><jtitle>World development</jtitle><date>2018-04-01</date><risdate>2018</risdate><volume>104</volume><spage>358</spage><epage>374</epage><pages>358-374</pages><issn>0305-750X</issn><eissn>1873-5991</eissn><abstract>•This study relates to the social implications of (mobile) technology diffusion.•I hypothesise that phone diffusion undermines non-adopters’ healthcare access.•I use a panel of 12,003 sick households across rural India in 2005 and 2012.•Poor non-adopters’ access to private healthcare worsens during fast diffusion.•Wealthier households and public healthcare access are insulated from this trend.
The gains from digital technology diffusion are deemed essential for international development, but they are also distributed unevenly. Does the uneven distribution mean that not everyone benefits from new technologies to the same extent, or do some people experience an absolute disadvantage during this process? I explore this question through the case study of curative healthcare access in the context of rapid mobile phone uptake in rural India, contributing thus to an important yet surprisingly under-researched aspect of the social implications of (mobile) technology diffusion.
Inspired by a previous analysis of cross-sectional data from rural India, I hypothesise that health systems increasingly adapt to mobile phone users where phones have diffused widely. This adaptation will leave poor non-adopters worse off than before and increases healthcare inequities. I use a panel of 12,003 rural households with an illness in 2005 and 2012 from the Indian Human Development Survey to test this hypothesis. Based on village-cluster robust fixed-effects linear probability models, I find that (a) mobile phone diffusion is significantly and negatively linked to various forms of rural healthcare access, suggesting that health systems increasingly adapt to phone use and discriminate against non-users; that (b) poor rural households without mobile phones experience more adverse effects compared to more affluent households, which indicates a struggle and competition for healthcare access among marginalised groups; and that (c) no effects emerge for access to public doctors, which implies that some healthcare providers are less responsive to mobile phone use than others.
Overall, my findings indicate that the rural Indian healthcare system gradually adapts to increasing mobile phone use at the expense of non-users. I conclude that rapid mobile phone diffusion creates an opportunity to improve people’s access to healthcare in rural India, but it also creates new forms of marginalisation among poor rural households.</abstract><cop>Oxford</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.worlddev.2017.12.023</doi><tpages>17</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Adoption of innovations Asia Case studies Cell phones Cellular telephones Competition Data processing Diffusion Digital inclusion Disadvantaged Health care Health care access Health care industry Health care policy Health disparities Health services Healthcare Household panel data Households Human development Illnesses India Inequality Marginality Medical technology Mobile phones New technology Physicians Rural areas Rural communities Rural poverty Side effects Social exclusion Technology Telephone communications Telephones Uptake |
title | The struggle for digital inclusion: Phones, healthcare, and marginalisation in rural India |
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