1086 Non-Linear Associations Between Depression and Sleep Duration in an International Sample of 16,997 Respondents
Bibliographic record
Abstract
Abstract Introduction Abnormal sleep duration is common in people with depression and can be both a risk-factor and a symptom of depression. Here we determine the prevalence of depression likelihood and assess associations between long and short sleep duration in an international convenience sample. Methods N=16,997 respondents (age range: 8-98y, mean age 39.7y ±13.1 SD; 43% female) completed the 10-item Harvard Department of Psychiatry National Depression Screening Day Scale (HANDS) online from October 7 to October 13, 2019. Higher total scores on the HANDS indicate higher likelihood of major depressive episode with scores >8 indicate the presence of a major depressive disorder is likely. Additional questions were added to the survey including the question “During the past two weeks, how many hours of actual sleep did you average at night?” Answer choices ranged from “less than 5 hours” to “more than 10h” in half-hour increments. Results Respondents came from 115 different countries with the majority of respondents from Canada (48%) and the United States (38%). Sixty-four percent of the sample were recommended for further evaluation for depression. Of those recommended, 66% reported <7h of sleep per night and 3% reported >9h. Those who reported 7-9h of sleep per night had the lowest depression scores (9.2 points) compared to those who reported <7h (11.8 points) and >9h (13.7 points), F(2,15366)=434.81, p<0.001. The amount of sleep associated with the lowest depression scores was 7.5h (8.6 points) with <5h associated with the highest depression scores (15.5 points). Conclusion We found a high prevalence of depression likelihood in 64% of an international convenience sample, with 69% of those not meeting the recommended 7-9h of sleep per night. Both short and long sleep were associated with higher levels of depression with 7.5h of sleep associated with the lowest depression scores. Future research on depression should focus on sleep interventions aimed at improving both short and long sleep duration. Support N/A.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".