Seasonality, negative life events and social support in a community sample
Bibliographic record
Abstract
BACKGROUND: Seasonal affective disorder (SAD) is now a well-described form of depressive disorder. However, relatively little research has focused upon psychosocial factors and SAD. AIMS: To determine the association between demographic/psychosocial factors and increased reported seasonal patterns of mood disorder (seasonality) and SAD in a community sample in the UK. METHOD: A total of 1250 people, aged between 18 and 64 years, randomly selected from a primary care database were screened for SAD. Those above cut-off underwent diagnostic interview and completed several self-report questionnaires. Multivariate analysis was conducted to determine which variables were significantly associated with increased seasonality. RESULTS: Four factors (having experienced more numerous negative life events, having low levels of social support, being a woman and being non-native) were predictive of higher seasonality. Being a woman was predictive of being diagnosed as a case of SAD. CONCLUSIONS: A new association has been identified between increased seasonality, negative life events and social support. Future research should assess the psychosocial causes or consequences of SAD while continuing to examine the biology of the condition.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".