scholarly journals Paradoxes in Eye Health Care in Low-Income Countries and Design Strategies for Mobile Health Technology to Overcome them

Author(s):  
Esmael Nida ◽  
Luc Geurts ◽  
Vero Abeele
2018 ◽  
Vol 22 (10) ◽  
pp. 3373-3383 ◽  
Author(s):  
Rebecca Schnall ◽  
Hwayoung Cho ◽  
Alexander Mangone ◽  
Adrienne Pichon ◽  
Haomiao Jia

2020 ◽  
Vol 222 (1) ◽  
pp. S203-S204
Author(s):  
Karolina Leziak ◽  
Angelina Strohbach ◽  
Jenise Jackson ◽  
Charlotte M. Niznik ◽  
Lynn M. Yee

2018 ◽  
Vol 6 (4) ◽  
pp. e109 ◽  
Author(s):  
Sanne B Overdijkink ◽  
Adeline V Velu ◽  
Ageeth N Rosman ◽  
Monique DM van Beukering ◽  
Marjolein Kok ◽  
...  

2018 ◽  
Vol 9 (3) ◽  
Author(s):  
Velibanti Nhlanhla Sukati ◽  
Vannesa Raquel Moodley ◽  
Khathutshelo Percy Mashige

Compared to other African countries, Swaziland performs the worst in terms of providing eye health care services. A priority goal of the World Health Organization (WHO) is to alleviate childhood blindness, particularly in low-income countries such as Swaziland, where many people live in poverty, which is a contributor to poor health outcomes. A mixed method approach that entailed a document review, key informant interviews and clinical facility assessment questionnaires was used. Hospitals and mission clinics offering ophthalmic services were identified through the website of the Ministry of Health and verified during key informant interviews. A saturated sampling procedure was applied due to the few facilities that offer eye care services. Six framework components from the WHO for analysing health systems were utilised in an eye health care service context: leadership and governance, eye health services, eye health workforce, eye health financing systems, eye health medical supplies and technologies, and eye health information systems. Poor management, lack of accountability, poor monitoring and evaluation mechanisms, weak coordination and ineffective private-public sector regulations were identified as factors that lead to poor eye care in the country. The optometrists indicated that refractive services are the most rendered ophthalmic services. The exodus of healthcare practitioners has contributed to the downfall of the public health sector in the country. Five government eye care facilities, 3 government hospitals, 1 non-governmental organization (NGO) and a church mission clinic were included in this analysis. The eye services distribution favors the more affluent areas, particularly the more urban Hhohho Region, which is also where most of the eye health professionals are located. No campaigns have been conducted to prevent childhood blinding diseases or create awareness about getting children’s eyes tested for refractive correction. The burden of eye diseases among children in Swaziland remains unknown. More eye health care personnel and equipped facilities are needed throughout the country, and the eye health care program needs to be adopted.


2017 ◽  
Author(s):  
Kelly Bosak ◽  
Shin Hye Park

BACKGROUND Mobile health technology is rapidly evolving with the potential to transform health care. Self-management of health facilitated by mobile technology can maximize long-term health trajectories of adults. Little is known about the characteristics of adults seeking Web-based support from health care providers facilitated by mobile technology. OBJECTIVE This study aimed to examine the following: (1) the characteristics of adults who seek human support from health care providers for health concerns using mobile technology rather than from family members and friends or others with similar health conditions and (2) the use of mobile health technology among adults with chronic health conditions. Findings of this study were interpreted in the context of the Efficiency Model of Support. METHODS We first described characteristics of adults seeking Web-based support from health care providers. Using chi-square tests for categorical variables and t test for the continuous variable of age, we compared adults seeking Web-based and conventional support by demographics. The primary aim was analyzed using multivariate logistic regression to examine whether chronic health conditions and demographic factors (eg, sex, income, employment status, race, ethnicity, education, and age) were associated with seeking Web-based support from health care providers. RESULTS The sample included adults (N=1453), the majority of whom were female 57.60% (837/1453), white 75.02% (1090/1453), and non-Hispanic 89.13% (1295/1453). The age of the participants ranged from 18 to 92 years (mean 48.6, standard deviation [SD] 16.8). The majority 76.05% (1105/1453) of participants reported college or higher level of education. A disparity was found in access to health care providers via mobile technology based on socioeconomic status. Adults with annual income of US $30,000 to US $100,000 were 1.72 times more likely to use Web-based methods to contact a health care provider, and adults with an annual income above US $100,000 were 2.41 to 2.46 times more likely to access health care provider support on the Web, compared with those with an annual income below US $30,000. After adjusting for other demographic covariates and chronic conditions, age was not a significant factor in Web-based support seeking. CONCLUSIONS In this study, the likelihood of seeking Web-based support increased when adults had any or multiple chronic health conditions. A higher level of income and education than the general population was found to be related to the use of mobile health technology among adults in this survey. Future study is needed to better understand the disparity in Web-based support seeking for health issues and the clinicians’ role in promoting access to and use of mobile health technology.


Author(s):  
Karola V. Kreitmair ◽  
Mildred K. Cho

Wearable and mobile health technology is becoming increasingly pervasive, both in professional healthcare settings and with individual consumers. This chapter delineates the various functionalities of this technology and identifies its different purposes. It then addresses the ethical challenges that this pervasiveness poses in the areas of accuracy and reliability of the technology, privacy and confidentiality of data, consent, and the democratization of healthcare. It also looks at mobile mental health apps as a case study to elucidate the discussion of ethical issues. Finally, the chapter turns to the question of how this technology and the associated “quantification of the self” affect traditional modes of epistemic access to and phenomenological conceptions of the self.


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