The Associations between Insomnia Severity and Health Outcomes in the United States
Bibliographic record
Abstract
Little is known about the associations between insomnia severity, insomnia symptoms, and key health outcomes. Using 2020 United States National Health and Wellness Survey (NHWS) data, we conducted a retrospective, cross-sectional analysis to determine the associations between insomnia severity and a number of health outcomes germane to patients (health-related quality of life (HRQoL), employers and government (workplace productivity), and healthcare payers (healthcare resource utilization (HCRU)). The Insomnia Severity Index (ISI) questionnaire was used to evaluate overall insomnia severity. HRQoL was assessed using the physical and mental component summary scores of the Short Form-36v2 (SF-36v2) questionnaire, and health utility status was measured using the Short Form-6D (SF-6D) and EuroQoL-5D (EQ-5D) questionnaires. Workplace productivity was measured using the Work Productivity and Activity Impairment (WPAI) questionnaire. After adjusting for confounders, greater insomnia severity was significantly associated with worsened quality of life, decreased productivity, and increased HCRU in an apparent linear fashion. These findings have important implications for future research, including the need for specific assessment of insomnia symptoms and their impact on key health outcomes.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.001 | 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".