0992 Follow-up of Insomnia, Depression and Anxiety Over 12 Months
Bibliographic record
Abstract
It is well known that insomnia is related to both depression and anxiety. However, no research has followed the course of these conditions monthly for a year. This study aimed to monitor individuals with insomnia, depression and anxiety, as well as individuals with none of these conditions in the first month, monthly, over a 12-month period. Four hundred and fifty-one participants (ages 18–82; mean = 27.9; 21.3% male) took part in this study. They were recruited in classes at the Université du Québec à Trois-Rivières and through an article published in a local newspaper. Each participant filled in online questionnaires, namely the Insomnia Severity Index (ISI), the Beck Depression Inventory-II (BDI-II) and the Beck Anxiety Inventory (BAI). Each questionnaire was to be completed monthly for a year. The progression of insomnia, depression and anxiety in the first month was observed in insomniac participants, depressed and anxious participants, and participants with none of these conditions. Among insomniacs in month one, 73% were still insomniacs in month two and 48% in month three. Stabilization then occurs between month 4 and month 11, and at month 12 only 40% were still insomniacs. The results show that among insomniacs in month one of the study, insomnia, depression and anxiety oscillate more each month than among non-insomniacs. In addition, a greater percentage of insomniacs have moderate-severe and severe anxiety, and severe depression, according to the BAI and BDI-II. Our results corroborate the previous findings that insomnia is associated with anxiety and depression. Further, the temporal stability of insomnia, depression and anxiety over 12 months is very low. 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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 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".