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

Abstract:
Background
Attendance rates for eye clinics are low across low- and middle-income countries (LMICs) and exhibit marked sociodemographic inequalities. We aimed to quantify the association between a range of sociodemographic domains and attendance rates from vision screening in programmes launching in Botswana, India, Kenya and Nepal.

Methods
We performed a literature review of international guidance on sociodemographic data collection. Once we had identified 13 core candidate domains (age, gender, place of residence, language, ethnicity/tribe/caste, religion, marital status, parent/guardian status, place of birth, education, occupation, income, wealth) we held workshops with researchers, academics, programme implementers, and programme designers in each country to tailor the domains and response options to the national context, basing our survey development on the USAID Demographic and Health Survey model questionnaire and the RAAB7 eye health survey methodology. The draft surveys were reviewed by health economists and piloted with laypeople before being finalised, translated, and back-translated for use in Botswana, Kenya, India, and Nepal. These surveys will be used to assess the distribution of eye disease among different sociodemographic groups, and to track attendance rates between groups in four major eye screening programmes. We gather data from 3,850 people in each country and use logistic regression to identify the groups that experience the worst access to community-based eye care services in each setting. We will use a secure, password protected android-based app to gather sociodemographic information. These data will be stored using state-of-the art security measures, complying with each country’s data management legislation and UK law.

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.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.12688/wellcomeopenres.17768.2

Authors

More by this author
Institution:
University of Oxford
Division:
MSD
Department:
Primary Care Health Sciences
Oxford college:
Kellogg College
Role:
Author
ORCID:
0000-0003-2750-3575
More by this author
Role:
Author
ORCID:
0000-0002-2040-4059


More from this funder
Funder identifier:
https://ror.org/029chgv08
Grant:
215633
More from this funder
Funder identifier:
https://ror.org/015ah0c92
Grant:
215633/Z/19/Z


Publisher:
F1000Research
Journal:
Wellcome Open Research More from this journal
Volume:
7
Article number:
144
Place of publication:
England
Publication date:
2022-05-04
Acceptance date:
2023-12-08
DOI:
EISSN:
2398-502X
ISSN:
2398-502X
Pmid:
37485295


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