The relationship between sleep habits, anxiety, and depression in the elderly
Bibliographic record
Abstract
PURPOSE: The objective of this study is to determine which sleep-related behaviors are most often used by the elderly according to the presence or absence of anxiety and mood disorders. In particular, we are attempting to determine whether these behaviors are associated with the probability of suffering from a mental disorder. The behaviors being examined in the present study are taking naps, television watching or reading at bedtime, physical exercise at bedtime, relaxing activities at bedtime, and caffeine consumption in the evening. METHODS: The sample in this study consists of 2,759 participants aged 65 and over, with a mean age of 73.8. They were recruited through a method of random generation of telephone numbers according to a sampling strategy based on geographic location. After the goal of the study was explained to them, the participants agreed to have health professionals visit their home and to answer questions in an hour-and-a-half-long structured interview (after signing a consent form). RESULTS: Taking naps is the activity most often practiced by the elderly. Watching television and reading at bedtime are also frequent practices among them. The probabilities of suffering from anxiety are greater if the person never or rarely consumes caffeine after 6 pm, if the individual takes naps during the day, or if the person practices relaxation before bedtime. Television watching, reading, and physical exercise before bedtime are activities that are not associated with the probability of suffering from a mental disorder. CONCLUSION: It would be beneficial for research to be conducted to support the findings on behavioral differences between depressive and anxious seniors so that these behaviors can become further indicators of the presence of mental disorders.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".