Lost Time, Absence Costs, and Reduced Productivity Output for Employees With Bipolar Disorder
Bibliographic record
Abstract
OBJECTIVE: We sought to evaluate the incremental health-related lost work time and at-work productivity loss for employees with bipolar disorder (BPD). METHODS: Health-related absence and real productivity output of employees with BPD were compared with that of non-BPD and other employee cohorts from a large employer database using multivariate regression to control for cohort differences. RESULTS: After adjusting for confounding factors, employees with BPD had significantly higher absence costs (1,219 dollars) and 11.5 additional lost days (P<0.05) per year than those without BPD. Adjusted annual productivity output was 20% lower for the BPD group (P<0.05). CONCLUSIONS: Employees with BPD are less likely to be present for work. When present, their productivity level is similar to that of other employees, but over the course of a year, their absence rates result in significant productivity losses.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".