Depressive symptoms and Lifestyle in a community population
Bibliographic record
Abstract
Depression plays an important role in the etiology of suicide. There are few effective screening strategy for depression with less dependence on psychological specialists, though a systematic reduction of the incidence of suicide will first require finding potentially depressive persons. We evaluated whether depressive people diagnosed by SDS questionnaire may be detected by lifestyle factors. Five hundred-one people (male/female=247/254, age 32-78 years) were asked validated questions on depression, regular diet, alcohol consumption, current smoking status, regular physical activity, and medical history. Depression was defined based on the total score from the Self-rating Depression Scale (SDS) and score of ≥40 points was considered to indicate depression. Sixty-three people (male/female=29/34, 12.6%) were defined depression. The multivariate-adjusted OR of depression was 2.70 (95%CI: 1.26-5.82) for "current smoker" and 0.48 (95%CI: 0.26-0.87) for "getting enough sleep". Persons with depression may have more risk behaviors such as smoking, poor diet, or lack of exercise than persons without depression, though it has been argued that the relationship between depression and risky lifestyle is bi-directional or high co-morbidity.
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 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 | 0.003 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".