Affective Vulnerability to Short Sleep Predicts 10-Year Changes in Chronic Health Conditions
Bibliographic record
Abstract
Abstract We examined daily affective vulnerability to short sleep (i.e., individual differences in the extent that sleeping ≤6h predicts next-day affect) as a risk factor for developing chronic conditions 10 years later. Participants (N=1945, ages 35-85, 57% women) from the National Study of Daily Experiences reported sleep duration and affect in daily diary telephone interviews. Chronic conditions were assessed with a 39-item checklist (e.g., arthritis, hypertension, diabetes). Multilevel structural equation models revealed that individuals with heightened negative affect following short sleep had an increased number of chronic conditions after 10 years (Est.=1.20, SE=.48, p<.01). Positive affective vulnerability (i.e., greater declines in positive affect following shorter sleep vs. longer sleep) was marginally associated with 10-year chronic conditions (Est.=-.72, SE=.40, p=.07). Adding to the well-established connections between sleep duration and well-being across adulthood, these findings suggest that affective vulnerability to short sleep represents a unique risk factor for long-term health as people age.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| 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 | 0.001 |
| 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".