Quality of life as an outcome indicator in patients with seasonal affective disorder: results from the Can-SAD study
Bibliographic record
Abstract
BACKGROUND: Although a host of studies have now examined the relationship between quality of life (QoL) and non-seasonal depression, few have measured QoL in seasonal affective disorder (SAD). We report here on results from the Can-SAD trial, which assessed the impact of treatment with either antidepressant medication or light therapy upon QoL in patients diagnosed with SAD. METHOD: This Canadian double-blind, multicentre, randomized controlled trial included 96 patients who met strict diagnostic criteria for SAD. Eligible patients were randomized to 8 weeks of treatment with either: (1) 10000 lux light treatment and a placebo capsule or (2) 100 lux light treatment (placebo light) and 20 mg fluoxetine. QoL was measured with the Quality of Life Enjoyment and Satisfaction Questionnaire (Q-LES-Q) and the Medical Outcomes Study (MOS) Short-Form General Health Survey (SF-20) at baseline and 8 weeks. RESULTS: Both intervention groups showed significant improvement in QoL over time with no significant differences being detected by treatment condition. Q-LES-Q scores increased significantly in seven of eight domains, with the average scores rising from 48 x 0 (S.D.=10 x 7) at baseline to 69 x 1 (S.D.=15 x 6) at week 8. Treatment-related improvement in QoL was strongly associated with improvement in depression symptoms. DISCUSSION: Patients with SAD report markedly impaired QoL during the winter months. Treatment with light therapy or antidepressant medication is associated with equivalent marked improvement in perceived QoL. Studies of treatment interventions for SAD should routinely include broader indices of patient outcome, such as the assessment of psychosocial functioning or life quality.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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 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".