Title |
The impact of digital technology on health of populations affected by humanitarian crises: Recent innovations and current gaps
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Published in |
Journal of Public Health Policy, November 2016
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DOI | 10.1057/s41271-016-0040-1 |
Pubmed ID | |
Authors |
Sandra Mesmar, Reem Talhouk, Chaza Akik, Patrick Olivier, Imad H. Elhajj, Shady Elbassuoni, Sarah Armoush, Joumana Kalot, Madeline Balaam, Aline Germani, Hala Ghattas |
Abstract |
Digital technology is increasingly used in humanitarian action and promises to improve the health and social well-being of populations affected by both acute and protracted crises. We set out to (1) review the current landscape of digital technologies used by humanitarian actors and affected populations, (2) examine their impact on health and well-being of affected populations, and (3) consider the opportunities for and challenges faced by users of these technologies. Through a systematic search of academic databases and reports, we identified 50 digital technologies used by humanitarian actors, and/or populations affected by crises. We organized them according to the stage of the humanitarian cycle that they were used in, and the health outcomes or determinants of health they affected. Digital technologies were found to facilitate communication, coordination, and collection and analysis of data, enabling timely responses in humanitarian contexts. A lack of evaluation of these technologies, a paternalistic approach to their development, and issues of privacy and equity constituted major challenges. We highlight the need to create a space for dialogue between technology designers and populations affected by humanitarian crises. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 2 | 29% |
Unknown | 5 | 71% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 3 | 43% |
Scientists | 3 | 43% |
Practitioners (doctors, other healthcare professionals) | 1 | 14% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 179 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 43 | 24% |
Researcher | 21 | 12% |
Student > Ph. D. Student | 20 | 11% |
Student > Bachelor | 16 | 9% |
Other | 9 | 5% |
Other | 32 | 18% |
Unknown | 38 | 21% |
Readers by discipline | Count | As % |
---|---|---|
Social Sciences | 35 | 20% |
Nursing and Health Professions | 16 | 9% |
Business, Management and Accounting | 15 | 8% |
Medicine and Dentistry | 15 | 8% |
Engineering | 12 | 7% |
Other | 40 | 22% |
Unknown | 46 | 26% |