The Clinical and Occupational Correlates of Work Productivity Loss Among Employed Patients With Depression
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Employers who are developing strategies to reduce health-related productivity loss may benefit from aiming their interventions at the employees who need them most. We determined whether depression's negative productivity impact varied with the type of work employees performed. Subjects (246 with depression and 143 controls) answered the Work Limitations Questionnaire and additional work questions. Occupational requirements were measured objectively. In multiple regression analyses, productivity was most influenced by depression severity (P < 0.01 in 5/5 models). However, certain occupations also significantly increased employee vulnerability to productivity loss. Losses increased when employees had occupations requiring proficiency in decision-making and communication and/or frequent customer contact (P < 0.05 in 3/5 models). The Work Limitations Questionnaire can help employers to reduce productivity loss by identifying health and productivity improvement priorities.
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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 | 0.001 | 0.001 |
| 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 it