Back

Interrogating a framework for diabetic retinopathy screening adherence: qualitative interviews of a severe disease and unengaged population

Fu, J.; Andoh, J.; Fairless, E.; Weiss, J.; Norcott, A.; Nwanyanwu, K.

2025-05-31 ophthalmology
10.1101/2025.05.29.25328601 medRxiv
Show abstract

BackgroundTo interrogate a framework of diabetic retinopathy (DR) screening adherence by conducting qualitative interviews with individuals with severe DR and those unengaged in eye care. MethodsFrom March 2021 to February 2022, we conducted eight remote semi-structured interviews with participants diagnosed with diabetes divided into two cohorts: those with severe DR who had undergone procedures (n=4) and those unengaged in eye care for >1 year (n=4). We recruited participants from an academic faculty practice, community referrals, and word of mouth. During the interviews, we collected demographic data and presented participants with a DR screening utilization framework previously developed by our group. We transcribed all interviews and conducted analyses using grounded theory and the constant comparative method to identify recurring themes. ResultsIn the unengaged cohort, seven recurring themes emerged: vision status, emotional context, competing concerns, resource availability, cues to action, knowledge-creating experiences, and in-clinic experiences. These themes also emerged in the severe disease cohort, with the addition of the patient-doctor relationship. At the individual level, participants with stable vision often perceived no need for screening. At the interpersonal level, participants identified powerful patient-doctor relationships that empowered them to seek care. At the institutional and structural level, participants identified lack of insurance and transportation as significant barriers. ConclusionsImproving education about DR, increasing resource accessibility, and strengthening the patient-doctor relationship may mitigate barriers to DR screening in populations at highest-risk for vision loss. To do so, we must implement innovative strategies, such as co-designed educational videos and digital health tools.

Matching journals

The top 2 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.