Sleep in adults from the UK during the first few months of the coronavirus outbreak
Bibliographic record
Abstract
The coronavirus disease 2019 (COVID-19) outbreak emerged at the end of 2019 and quickly spread around the world. Measures to counter COVID-19, including social distancing and lockdowns, created an unusual situation that had the potential to impact a variety of behaviours, including sleep, which is crucial for health and well-being. Data were obtained through an online survey. The total sample comprised 19,482 participants from the UK. Participants were asked several questions regarding sleep quality and quantity. Each participant completed the questionnaires once during a data collection period spanning January 20 to March 31, 2020. Data provided by different participants during different weeks (spanning time-periods just before COVID-19 was identified in the UK and during the early weeks following its arrival) were compared using analysis of variance tests and regressions. Regression analyses controlling for age, sex and ethnicity revealed significant associations of small magnitude between date of survey completion and sleep quality, sleep latency, number of awakenings and composite score of poor sleep quality. These analyses also indicated small increases in eveningness tendency as the study progressed. There was no change in sleep duration or time spent awake at night. The COVID-19 outbreak did not appear to impact negatively sleep in a substantial manner during the early stages in the UK. The small increases in sleep quality variables (except for time spent awake at night and sleep duration) and eveningness are nonetheless of interest. Further research is needed to understand how best to provide support to those most in need of a good night's sleep during this unprecedented time.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 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".