Health profile of deaf Canadians: analysis of the Canada Community Health Survey.
Bibliographic record
Abstract
OBJECTIVE: To profile the health of deaf and hard-of-hearing Canadians in relation to the population as a whole. DESIGN: Using data from the Canada Community Health Survey 1.1, across-sectional survey conducted by Statistics Canada with a total of 131,535 respondents, a series of logistic regression models was fitted to estimate the odds, compared with the general population, of respondents classified as having hearing problems reporting the presence of various chronic health outcomes; of their utilizing the health care system; of their engaging in certain health promotion activities; and of their reporting certain perceptions about their overall health. For each odds ratio, 95% confidence intervals are provided. All analyses were adjusted for age and sex with some analyses being restricted to appropriate age ranges or having further adjustments made, depending on the outcomes. MAIN OUTCOME MEASURES: In addition to indications of deafness or hearing loss, this study examined health care utilization, several commonly accepted health outcomes, engagement in health promotion activities, and perceptions of overall health. RESULTS: Approximately 4% of respondents in the cross-sectional survey were considered to have hearing problems. The prevalence of hearing problems increased with age, with males having a slightly higher prevalence of hearing problems compared with females (4.52% versus 3.53%). Respondents classified as having hearing problems, whether hearing loss or deafness, were more likely to report adverse health conditions and low levels of physical activity, and to experience higher rates of depression. Respondents classified as having hearing problems were not more likely to smoke or to drink excessively. CONCLUSION: Communication is essential to both health promotion and health care delivery. Deafness-both the disability and the culture-creates barriers to communication. Individual practitioners can and should consider the communication needs of individual patients with hearing loss or deafness to avoid barriers to optimal health.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".