Bibliographic record
Abstract
OBJECTIVES: To estimate the number and cost of asthma-related productivity loss days due to absenteeism and presenteeism (at work but not fully functioning) in Alberta in 2005. METHODS: Using data from the 2005 Canadian Community Health Survey, this study focused on people of working age (18-64 years), who reported having an asthma diagnosis. Total asthma-related disability days, including in-bed days and activity-restricted days, were estimated by multiplying the difference in the means of total disability days between asthmatics and nonasthmatics adjusted for sociodemographic characteristics and other health conditions by a multiple linear regression, with the number of asthmatics in the population. Number of productivity loss days was a sum between the number of in-bed days (absenteeism) and the number of activity-restricted days multiplied by a reduction in functional level (presenteeism), adjusted for five working days per week. Other data from Alberta or Canadian published literature, such as a reduction in functional level of 20%-30%, a labor participation rate of 73%, and an average wage of $158 per day in 2005, were also used for analyses. RESULTS: The prevalence of asthma was estimated at 8.5% among approximately 2.1 million people of working age in Alberta in 2005. The difference in the means of total disability days between asthmatics and nonasthmatics was 0.487 (95% CI: 0.286-0.688) in a period of two weeks or 12.7 (7.5-17.9) in one year. With the reduction in functional level of 20%-30%, the number of asthma-related productivity loss days was estimated from 442 (259-624) to 533 (313-753) thousand, respectively. The corresponding cost was from $70 ($41-$99) to $84 ($49-$119) million. Of these, the presenteeism accounted for 42% to 52%. CONCLUSIONS: The results suggest that an improvement in the controlling of asthma could have a significant economic impact in Alberta and that presenteeism plays an important role in asthma-related productivity losses and therefore employers should not only pay attention to absenteeism, but also to presenteeism to minimize productivity loss.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".