Barriers and Determinants of Referral Adherence in AI-Enabled Diabetic Retinopathy Screening for Older Adults in Northern India During the COVID-19 Pandemic: Mixed Methods Pilot Study
Abstract BackgroundDiabetic retinopathy (DR) is a leading cause of blindness globally. DR has increasingly affected both individuals and health care systems as the population ages. ObjectiveThis study aims to explore factors and identify barriers associated with no...
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JMIR Publications
2025-03-01
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| Series: | JMIR Formative Research |
| Online Access: | https://formative.jmir.org/2025/1/e67047 |
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| author | Anshul Chauhan Anju Goyal Ritika Masih Gagandeep Kaur Lakshay Kumar Neha Harsh Rastogi Sonam Kumar Bidhi Lord Singh Preeti Syal Vishali Gupta Luke Vale Mona Duggal |
| author_facet | Anshul Chauhan Anju Goyal Ritika Masih Gagandeep Kaur Lakshay Kumar Neha Harsh Rastogi Sonam Kumar Bidhi Lord Singh Preeti Syal Vishali Gupta Luke Vale Mona Duggal |
| author_sort | Anshul Chauhan |
| collection | DOAJ |
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Abstract
BackgroundDiabetic retinopathy (DR) is a leading cause of blindness globally. DR has increasingly affected both individuals and health care systems as the population ages.
ObjectiveThis study aims to explore factors and identify barriers associated with nonadherence to referral recommendations among older adult participants after DR screening (DRS) during the COVID-19 pandemic.
MethodThis paper presents findings from a pilot study on artificial intelligence–enabled DRS conducted in two districts in Punjab, India (Moga and Mohali) during the COVID-19 pandemic. The screenings were conducted from March to June 2022 at community health center Badhani Kalan in Moga and from March to June 2021 in community settings (homes) in Block Boothgarh, Mohali. Participants were referred to the district hospital for an ophthalmological review based on artificial intelligence–enabled screening. After 1 month, the participants were contacted by telephone to assess adherence to the referral recommendations. Participants who did not adhere to the referral were then interviewed alongside health care providers to understand the barriers explaining their nonadherence.
ResultsWe aimed to recruit 346 and 600 older adult participants from 2 sites but enrolled 390. Key challenges included health facility closures due to COVID-19, low motivation among health personnel for recruitment, incomplete nonparticipation data, and high participant workloads. Approximately 45% of the participants were male and 55% female. Most participants (62.6%) were between 60 and 69 years old, while 37.4% were 70 or older, with a mean age of 67.2 (SD 6.2) years. In total, 159 participants (40.8%) were referred, while 231 participants (59.2%) were not. Only 23 (14.5%) of those referred followed through and visited a health facility for ophthalmological review, while 136 (85.5%) did not pursue further evaluation. Our analysis revealed no significant differences in the characteristics between adherent and nonadherent participants, suggesting that demographic and health factors alone do not predict adherence behavior in patients with DR. Interviews identified limited knowledge about DR, logistical challenges, financial constraints, and attitudinal barriers as the primary challenges.
ConclusionsThis study, conducted during the COVID-19 pandemic, showed suboptimal adherence to referral recommendations among older adult patients due to knowledge gaps, logistical challenges, and health system issues. Quantifying and understanding adherence factors are crucial for targeted interventions addressing barriers to referral recommendations after DRS. Integrating teleophthalmology into and strengthening infrastructure for artificial intelligence–enabled diabetic retinopathy screening to enhance access and outcomes. |
| format | Article |
| id | doaj-art-23f1d74cceda48e1b65eb494c1478713 |
| institution | OA Journals |
| issn | 2561-326X |
| language | English |
| publishDate | 2025-03-01 |
| publisher | JMIR Publications |
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| series | JMIR Formative Research |
| spelling | doaj-art-23f1d74cceda48e1b65eb494c14787132025-08-20T02:26:06ZengJMIR PublicationsJMIR Formative Research2561-326X2025-03-019e67047e6704710.2196/67047Barriers and Determinants of Referral Adherence in AI-Enabled Diabetic Retinopathy Screening for Older Adults in Northern India During the COVID-19 Pandemic: Mixed Methods Pilot StudyAnshul Chauhanhttp://orcid.org/0000-0002-2434-935XAnju Goyalhttp://orcid.org/0000-0002-0171-3163Ritika Masihhttp://orcid.org/0009-0007-5162-6475Gagandeep Kaurhttp://orcid.org/0009-0003-0403-8997Lakshay Kumarhttp://orcid.org/0009-0007-4026-9935 Nehahttp://orcid.org/0009-0004-5913-1029Harsh Rastogihttp://orcid.org/0009-0002-1568-4321Sonam Kumarhttp://orcid.org/0009-0008-7257-9644Bidhi Lord Singhhttp://orcid.org/0000-0001-6598-9743Preeti Syalhttp://orcid.org/0009-0003-8461-8528Vishali Guptahttp://orcid.org/0000-0001-8216-4620Luke Valehttp://orcid.org/0000-0001-8574-8429Mona Duggalhttp://orcid.org/0000-0002-9404-2871 Abstract BackgroundDiabetic retinopathy (DR) is a leading cause of blindness globally. DR has increasingly affected both individuals and health care systems as the population ages. ObjectiveThis study aims to explore factors and identify barriers associated with nonadherence to referral recommendations among older adult participants after DR screening (DRS) during the COVID-19 pandemic. MethodThis paper presents findings from a pilot study on artificial intelligence–enabled DRS conducted in two districts in Punjab, India (Moga and Mohali) during the COVID-19 pandemic. The screenings were conducted from March to June 2022 at community health center Badhani Kalan in Moga and from March to June 2021 in community settings (homes) in Block Boothgarh, Mohali. Participants were referred to the district hospital for an ophthalmological review based on artificial intelligence–enabled screening. After 1 month, the participants were contacted by telephone to assess adherence to the referral recommendations. Participants who did not adhere to the referral were then interviewed alongside health care providers to understand the barriers explaining their nonadherence. ResultsWe aimed to recruit 346 and 600 older adult participants from 2 sites but enrolled 390. Key challenges included health facility closures due to COVID-19, low motivation among health personnel for recruitment, incomplete nonparticipation data, and high participant workloads. Approximately 45% of the participants were male and 55% female. Most participants (62.6%) were between 60 and 69 years old, while 37.4% were 70 or older, with a mean age of 67.2 (SD 6.2) years. In total, 159 participants (40.8%) were referred, while 231 participants (59.2%) were not. Only 23 (14.5%) of those referred followed through and visited a health facility for ophthalmological review, while 136 (85.5%) did not pursue further evaluation. Our analysis revealed no significant differences in the characteristics between adherent and nonadherent participants, suggesting that demographic and health factors alone do not predict adherence behavior in patients with DR. Interviews identified limited knowledge about DR, logistical challenges, financial constraints, and attitudinal barriers as the primary challenges. ConclusionsThis study, conducted during the COVID-19 pandemic, showed suboptimal adherence to referral recommendations among older adult patients due to knowledge gaps, logistical challenges, and health system issues. Quantifying and understanding adherence factors are crucial for targeted interventions addressing barriers to referral recommendations after DRS. Integrating teleophthalmology into and strengthening infrastructure for artificial intelligence–enabled diabetic retinopathy screening to enhance access and outcomes.https://formative.jmir.org/2025/1/e67047 |
| spellingShingle | Anshul Chauhan Anju Goyal Ritika Masih Gagandeep Kaur Lakshay Kumar Neha Harsh Rastogi Sonam Kumar Bidhi Lord Singh Preeti Syal Vishali Gupta Luke Vale Mona Duggal Barriers and Determinants of Referral Adherence in AI-Enabled Diabetic Retinopathy Screening for Older Adults in Northern India During the COVID-19 Pandemic: Mixed Methods Pilot Study JMIR Formative Research |
| title | Barriers and Determinants of Referral Adherence in AI-Enabled Diabetic Retinopathy Screening for Older Adults in Northern India During the COVID-19 Pandemic: Mixed Methods Pilot Study |
| title_full | Barriers and Determinants of Referral Adherence in AI-Enabled Diabetic Retinopathy Screening for Older Adults in Northern India During the COVID-19 Pandemic: Mixed Methods Pilot Study |
| title_fullStr | Barriers and Determinants of Referral Adherence in AI-Enabled Diabetic Retinopathy Screening for Older Adults in Northern India During the COVID-19 Pandemic: Mixed Methods Pilot Study |
| title_full_unstemmed | Barriers and Determinants of Referral Adherence in AI-Enabled Diabetic Retinopathy Screening for Older Adults in Northern India During the COVID-19 Pandemic: Mixed Methods Pilot Study |
| title_short | Barriers and Determinants of Referral Adherence in AI-Enabled Diabetic Retinopathy Screening for Older Adults in Northern India During the COVID-19 Pandemic: Mixed Methods Pilot Study |
| title_sort | barriers and determinants of referral adherence in ai enabled diabetic retinopathy screening for older adults in northern india during the covid 19 pandemic mixed methods pilot study |
| url | https://formative.jmir.org/2025/1/e67047 |
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