The co-development of a linguistic and culturally tailored tele-retinopathy screening intervention for immigrants living with diabetes from China and African-Caribbean countries in Ottawa, Canada
Bibliographic record
Abstract
Abstract Background Diabetic retinopathy is a sight-threatening ocular complication of diabetes. Screening is an effective way to reduce severe complications, but screening attendance rates are often low, particularly for newcomers and immigrants to Canada and people from cultural and linguistic minority groups. Building on previous work, in partnership with patient and health system stakeholders, we co-developed a linguistically and culturally tailored tele-retinopathy screening intervention for people living with diabetes who recently immigrated to Canada from either China or African-Caribbean countries. Methods Following an environmental scan of diabetes eye care pathways in Ottawa, we conducted co-development workshops using a nominal group technique to create and prioritize personas of individuals requiring screening and identify barriers to screening that each persona may face. Next, we used the Theoretical Domains Framework to categorize the barriers/enablers and then mapped these categories to potential evidence-informed behaviour change techniques. Finally with these techniques in mind, participants prioritized strategies and channels of delivery, developed intervention content, and clarified actions required by different actors to overcome anticipated intervention delivery barriers. Results We carried out iterative co-development workshops with Mandarin and French-speaking individuals living with diabetes (i.e., patients in the community) who immigrated to Canada from China and African-Caribbean countries (n = 13), patient partners (n = 7), and health system partners (n = 6) recruited from community health centres in Ottawa. Patients in the community co-development workshops were conducted in Mandarin or French. Together, we prioritized five barriers to attending diabetic retinopathy screening: language (TDF Domains: skills, social influences), retinopathy familiarity (knowledge, beliefs about consequences), physician barriers regarding communication for screening (social influences), lack of publicity about screening (knowledge, environmental context and resources), and fitting screening around other activities (environmental context and resources). The resulting intervention included the following behaviour change techniques to address prioritized local barriers: information about health consequence, providing instructions on how to attend screening, prompts/cues, adding objects to the environment, social support, and restructuring the social environment. Operationalized delivery channels incorporated language support, pre-booking screening and sending reminders, social support via social media and community champions, and providing using flyers and videos as delivery channels. Conclusion Working with intervention users and stakeholders, we co-developed a culturally and linguistically relevant tele-retinopathy intervention to address barriers to attending diabetic retinopathy screening and increase uptake among two under-served groups.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".