EXamining the knowledge, Attitudes and experiences of Canadian seniors Towards influenza (the EXACT survey)
Bibliographic record
Abstract
BACKGROUND: Older adults are at high risk for influenza-related complications including worsening frailty and function. We surveyed older Canadians to explore the impact of influenza and determine how influenza knowledge influences vaccination decision-making. METHODS: We disseminated an online survey through a national polling panel. The survey included questions about the respondents' influenza vaccination practices and knowledge about influenza. Using validated measures, they reported their frailty and functional status prior to the 2016/17 influenza season, during illness (if applicable), and following the season. Regression analyses were used to examine predictors of poor functional outcomes. RESULTS: Five thousand and fourteen adults aged 65 and older completed the survey; mean age was 71.3 ± 5.17 years, 42.6% had one or more chronic conditions, 7.8% were vulnerable and 1.8% were frail. 67.9% reported receiving last season's influenza vaccine. Those who rarely/never receive the influenza vaccine were significantly less likely to correctly answer questions about influenza's impact than those who receive the vaccine more consistently. Of the 1035 (21.5%) who reported experiencing influenza or influenza-like illness last season, 40% indicated a recovery longer than 2 weeks, and one-fifth had health and function declines during this time. Additionally, 3.1% of those afflicted "never fully recovered". Older age, significant trouble with memory and having influenza/ILI were among the independent predictors of persistent declines in health and function. CONCLUSIONS: Given that frailty and function are important considerations for older adults' well-being and independence, healthcare decision-makers must understand the potential for significant temporary and long-term impacts of influenza to make informed vaccine-related policies and recommendations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".