Time spent following the Russian-Ukranian war (RUW) and psychological distress: The role of sleep problems
Bibliographic record
Abstract
Background: The Russian-Ukranian war (RUW) broke in 2022. Finland is a neighboring country of Russia. People in Finland could be assumed to be especially vulnerable to war-related stress. We examined the relationship between time spent following the RUW from media, sleep problems and psychological distress in university students. Methods: The participants were university students who responded anonymously to a questionnaire. They reported their age, gender, time spent following RUW, anxiety, depressive symptoms, and sleep problems. Statistical analyses were conducted using SPSS and Mplus for structural equation modeling. Results: The time spent following RUW from media was associated with greater psychological distress, and more sleep disturbances. Sleep disturbances accounted for more than 12% of the association between time spent following RUW and psychological distress. Conclusions: Present findings suggest that sleep problems should be taken into account when supporting students. Support programs should emphasize the importance of sleep in psychological well-being.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".