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Sociodemographic characteristics of community eye screening participants: protocol for cross-sectional equity analyses in Botswana, Kenya, and Nepal.

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Title: Sociodemographic characteristics of community eye screening participants: protocol for cross-sectional equity analyses in Botswana, Kenya, and Nepal.
Authors: Allen, Luke N.1 luke.allen@lshtm.ac.uk, Nkomazana, Oathokwa2, Mishra, Sailesh Kumar3, Ratshaa, Bakgaki2, Ho-Foster, Ari2, Rono, Hillary4,5, Roshan, Abhiskek3,6, Macleod, David7, Kim, Min7, Marques, Ana Patricia7, Bolster, Nigel4,7, Burton, Matthew7, Gichangi, Michael8, Karanja, Sarah9, Bastawrous, Andrew4,7
Source: Wellcome Open Research. 2022, Vol. 7, p1-37. 37p.
Subject Terms: Eye examination, Sociodemographic factors, Socioeconomic status
Geographic Terms: Botswana, Kenya, Nepal
Abstract: Background: Attendance rates for eye clinics are low across low- and middle-income countries (LMICs) and exhibit marked sociodemographic (SD) inequalities. We aimed to quantify the association between a range of SD domains and attendance rates from vision screening in programmes launching in Botswana, Kenya and Nepal. Methods: We will develop a set of sociodemographic questions and introduce them into routine community-based eye screening programmes in Kenya, Botswana and Nepal, targeting children aged 5-18 years and adults. Our study design is a rolling survey, embedded within the Peek screening programme. The sociodemographic questions will be asked of 10% of all those presenting to be screened, and 100% of those identified with an eye problem. We will also collect data on whether people referred to ophthalmic clinic for treatment or further assessment attended, and we will use logistic regression to report odds ratios for this outcome attendance) for each socioeconomic domain in each country. We hypothesise that attendance rates will be lowest among marginalised sociodemographic groups such as older, less educated, less wealthy women. To identify the most appropriate sociodemographic items we will perform a literature review, and then hold workshops with researchers, academics, programme implementers, and programme designers in each country to tailor the domains and response options to the national context. We will report outcome data at 6 and 12 months, identifying the groups facing the highest barriers to access. Discussion: This low-risk, embedded, pragmatic, observational data collection will enable eye screening programme managers to accurately identify which sociodemographic groups are facing the highest systematic barriers to accessing care at any point in time. This information will be used to inform the development of service improvements to improve equity. [ABSTRACT FROM AUTHOR]
Copyright of Wellcome Open Research is the property of Wellcome Trust and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Sociodemographic characteristics of community eye screening participants: protocol for cross-sectional equity analyses in Botswana, Kenya, and Nepal.
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  Data: <searchLink fieldCode="AR" term="%22Allen%2C+Luke+N%2E%22">Allen, Luke N.</searchLink><relatesTo>1</relatesTo><i> luke.allen@lshtm.ac.uk</i><br /><searchLink fieldCode="AR" term="%22Nkomazana%2C+Oathokwa%22">Nkomazana, Oathokwa</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Mishra%2C+Sailesh+Kumar%22">Mishra, Sailesh Kumar</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22Ratshaa%2C+Bakgaki%22">Ratshaa, Bakgaki</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Ho-Foster%2C+Ari%22">Ho-Foster, Ari</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Rono%2C+Hillary%22">Rono, Hillary</searchLink><relatesTo>4,5</relatesTo><br /><searchLink fieldCode="AR" term="%22Roshan%2C+Abhiskek%22">Roshan, Abhiskek</searchLink><relatesTo>3,6</relatesTo><br /><searchLink fieldCode="AR" term="%22Macleod%2C+David%22">Macleod, David</searchLink><relatesTo>7</relatesTo><br /><searchLink fieldCode="AR" term="%22Kim%2C+Min%22">Kim, Min</searchLink><relatesTo>7</relatesTo><br /><searchLink fieldCode="AR" term="%22Marques%2C+Ana+Patricia%22">Marques, Ana Patricia</searchLink><relatesTo>7</relatesTo><br /><searchLink fieldCode="AR" term="%22Bolster%2C+Nigel%22">Bolster, Nigel</searchLink><relatesTo>4,7</relatesTo><br /><searchLink fieldCode="AR" term="%22Burton%2C+Matthew%22">Burton, Matthew</searchLink><relatesTo>7</relatesTo><br /><searchLink fieldCode="AR" term="%22Gichangi%2C+Michael%22">Gichangi, Michael</searchLink><relatesTo>8</relatesTo><br /><searchLink fieldCode="AR" term="%22Karanja%2C+Sarah%22">Karanja, Sarah</searchLink><relatesTo>9</relatesTo><br /><searchLink fieldCode="AR" term="%22Bastawrous%2C+Andrew%22">Bastawrous, Andrew</searchLink><relatesTo>4,7</relatesTo>
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  Data: <searchLink fieldCode="JN" term="%22Wellcome+Open+Research%22">Wellcome Open Research</searchLink>. 2022, Vol. 7, p1-37. 37p.
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  Data: Background: Attendance rates for eye clinics are low across low- and middle-income countries (LMICs) and exhibit marked sociodemographic (SD) inequalities. We aimed to quantify the association between a range of SD domains and attendance rates from vision screening in programmes launching in Botswana, Kenya and Nepal. Methods: We will develop a set of sociodemographic questions and introduce them into routine community-based eye screening programmes in Kenya, Botswana and Nepal, targeting children aged 5-18 years and adults. Our study design is a rolling survey, embedded within the Peek screening programme. The sociodemographic questions will be asked of 10% of all those presenting to be screened, and 100% of those identified with an eye problem. We will also collect data on whether people referred to ophthalmic clinic for treatment or further assessment attended, and we will use logistic regression to report odds ratios for this outcome attendance) for each socioeconomic domain in each country. We hypothesise that attendance rates will be lowest among marginalised sociodemographic groups such as older, less educated, less wealthy women. To identify the most appropriate sociodemographic items we will perform a literature review, and then hold workshops with researchers, academics, programme implementers, and programme designers in each country to tailor the domains and response options to the national context. We will report outcome data at 6 and 12 months, identifying the groups facing the highest barriers to access. Discussion: This low-risk, embedded, pragmatic, observational data collection will enable eye screening programme managers to accurately identify which sociodemographic groups are facing the highest systematic barriers to accessing care at any point in time. This information will be used to inform the development of service improvements to improve equity. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Wellcome Open Research is the property of Wellcome Trust and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – SubjectFull: Botswana
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      – SubjectFull: Kenya
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