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Record W4281398424 · doi:10.1101/2022.05.24.22275352

Barriers and enablers to diabetic eye screening: a cross sectional survey of young adults with type 1 and type 2 diabetes in the UK

2022· preprint· en· W4281398424 on OpenAlexaff
Louise Prothero, Martin Cartwright, Fabiana Lorencatto, Jennifer Burr, John Anderson, Philip Gardner, Justin Presseau, Noah Ivers, Jeremy Grimshaw, John G Lawrenson

Bibliographic record

VenuemedRxiv · 2022
Typepreprint
Languageen
FieldMedicine
TopicRetinal Diseases and Treatments
Canadian institutionsWomen's College HospitalOttawa HospitalUniversity of Ottawa
FundersDepartment of Health and Social CareDiabetes UKNational Institute for Health and Care Research
KeywordsAttendanceContext (archaeology)Diabetic retinopathyType 2 diabetesMedicineFlexibility (engineering)PsychologyFamily medicineDiabetes mellitusGerontologyEndocrinologyGeography

Abstract

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Abstract Introduction Diabetic retinopathy screening (DRS) attendance in young adults is consistently below recommended levels. The aim of this study was to identify barriers and enablers of diabetic retinopathy screening (DRS) attendance amongst young adults (YA) in the UK living with type 1 (T1D) and type 2 (T2D) diabetes. Research design and methods YAs (18-34yrs) were invited to complete an anonymous online survey in June 2021 assessing agreement with 30 belief statements informed by the Theoretical Domains Framework of behaviour change (TDF) describing potential barriers/enablers to DRS. Results In total 102 responses were received. Most had T1D (65.7%) and were regular attenders for DRS (76.5%). The most salient TDF domains for DRS attendance w ere ‘Goals’ , with 93% agreeing that DRS was a high priority and ‘Knowledge’ , with 98% being aware that screening can detect eye problems early. Overall 67.4% indicated that they would like greater appointment flexibility [ Environmental context/resources ] and 31.3% reported difficulties getting time off work/study to attend appointments [ Environmental Context/Resources ]. This was more commonly reported by occasional non-attenders versus regular attenders (59.1% vs 23.4%, P=0.002) Most YAs were worried about diabetic retinopathy (74.3%), anxious when receiving screening results (63%) [ Emotion ] and would like more support after getting their results (66%) [ Social influences ]. Responses for T1D and T2D were broadly similar, although those with T2D were more likely have developed strategies to help them to remember their appointments (63.6% vs 37.9%, P=0.019) [ Behavioural regulation ]. Conclusions Attendance for DRS in YAs is influenced by complex interacting behavioural factors. Identifying modifiable determinants of behaviour will provide a basis for designing tailored interventions to improve DRS in YAs and prevent avoidable vision loss. Significance of this study What is already known about this subject? Younger adults (<35 years) with diabetes have been identified as having longer time intervals before attending initial diabetic retinopathy screening (DRS) and are more likely to miss successive screening appointments. Previous studies have explored modifiable influences on DRS attendance, but often do not differentiate between population groups, particularly young adults. What are the new findings? One of the main reported barriers to attending DRS was the lack of appointment flexibility and difficulty getting time off work/study to attend appointments. This was compounded by the lack of integration of DRS with other diabetes appointments. Most young adults were worried about diabetic retinopathy, anxious when receiving screening results and would like more support How might these results change the focus of research or clinical practice? A more tailored approach is needed to support young adults to attend DRS. The findings of this research provide a basis for developing tailored interventions to increase screening uptake in this age group

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score0.106

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.024
GPT teacher head0.294
Teacher spread0.271 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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