Motivators and deterrents for seeking eye care in a Canadian region
Bibliographic record
Abstract
BACKGROUND: Motivators and deterrents for seeking eye care in a Canadian setting were sought using a qualitative study. Provincial deregulation of eyewear dispensing in 2010 allows consumers to order eyewear without an optical prescription, thus eliminating a potential motivator for obtaining an eye examination. METHODS: Convenience sampling was used to obtain 25 members of the public who contributed to one of seven focus groups that were facilitated, audiotaped, anonymised and transcribed. Participants completed a demographic questionnaire. Focus group data analysis employed grounded theory and theme saturation determined the number of focus groups. RESULTS: Nine men and 16 women participated, ranging in age from 18 to 71 years (mean 41.5; median 40.0). Three main themes were identified as influencers for seeking eye care: priority; advice; and capacity. Priority served as a motivator ('lived experience', 'symptoms', and 'habit') and deterrent ('test distress', 'asymptomatic', 'don't know' and 'other priorities'). Advice was a motivator ('professional' and 'family/friends'), while capacity was a motivator ('insurance') and deterrent ('cost'). CONCLUSION: The motivators and deterrents of seeking eye care in these focus groups were framed by three themes. Key findings not reported previously included the motivators of 'habit', 'advice' and 'insurance' and the potential deterrent of 'test distress'. These factors should be added to other previously reported motivators and deterrents in further exploration of Canadian eye-care seeking behaviours. Such knowledge is needed to develop strategies for improving eye-care literacy in Canada. This is particularly important because eyewear deregulation and/or online eye examinations may encourage members of the public to bypass comprehensive eye care without fully understanding the implications of this decision for their health and wellness.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.016 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".