The effect of bipolar I disorder and major depressive disorder on workforce function
Bibliographic record
Abstract
This investigation was undertaken to explore and compare the effect of bipolar I disorder (BD) and major depressive disorder (MDD) on workforce function. The data for this analysis were procured from the Canadian Community Health Survey (CCHS 1.2). The sample consisted of 20,747 individuals (>or=18 years or older and currently working); the proportions screening positive for lifetime BD and MDD were 2.4% and 11.2%, respectively. Individuals with BD or MDD had a significantly lower mean annual income, compared to people without these disorders. Individuals with BD had a significantly lower annual income when compared to MDD (p < 0.05). Results from a multiple logistic regression also indicate that employed individuals with BD had greater odds of reporting one or more mental health disability days in the past two weeks, compared with those with MDD (OR = 1.6; 95% CI = 1.0 to 2.6). Currently employed individuals with BD had lower odds of "good job security" relative to those with MDD (OR = 0.6 95% CI = 0.5 to 0.9). The data herein underscore the pernicious effect of BD on workforce function, and suggest that opportunistic screening for BD in all individuals utilizing employment assistance programs for depression might be warranted.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".